Skip to main content Accessibility help
×
Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-24T18:16:56.015Z Has data issue: false hasContentIssue false

Part I - The Political, Economic, and Institutional Features of Tanzania’s Development

Published online by Cambridge University Press:  09 November 2023

Samuel Mwita Wangwe
Affiliation:
Daima Associates
François Bourguignon
Affiliation:
École d'économie de Paris and École des Hautes Études en Sciences Sociales, Paris

Summary

Type
Chapter
Information
State and Business in Tanzania's Development
The Institutional Diagnostic Project
, pp. 1 - 92
Publisher: Cambridge University Press
Print publication year: 2023
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY-NC-SA 4.0 https://creativecommons.org/cclicenses/

This first part of the volume reviews the economic, social, political, and institutional development of Tanzania. The first chapter focuses on the political history of the country since independence, whereas the second evaluates its economic development achievements and, most importantly, the challenges ahead. The third chapter focuses on the possible obstacles to development arising from weak or failing institutions, as perceived by various types of decision-makers, top policymakers, and experts.

1 Tanzania in a Geographic, Demographic, and Historical Perspective

François Bourguignon and Samuel Mwita Wangwe

Embarking on a study of a country’s economic development requires having clearly in mind its main geographic and cultural aspects as well as a precise vision of its history and the main features of its current political context. Such is the objective of this first chapter.

I The Natural and Human Context of Development in Tanzania

With almost a million square kilometres, Tanzania is by far the biggest country in East Africa and even in Southern Africa, excluding South Africa. It borders the Indian Ocean over 1,400 kilometres and extends some 750 kilometres west inland at its larger width. It shares borders with eight countries: Kenya and Uganda to the north; Rwanda, Burundi, and Zaire to the west; and Zambia, Malawi, and Mozambique to the south. Today’s United Republic of Tanzania also includes several islands off its Indian Ocean shore, including the island of Zanzibar.

Just a few degrees below the equator, Tanzania’s climate is essentially tropical, although it is temperate in the highlands. Much of the country outside the coastal area is above 900 metres. It consists of extensive rolling plains interrupted by the Great Rift Valley, which cuts the east of the African continent from north to south. The Rift crosses the western part of Tanzania, where it is interspersed by Africa’s three great lakes: Victoria, Tanganyika, and Malawi (or Nyasa), whose shores are shared with neighbouring countries. The country offers a wide variety of landscapes: from coastal swamps to rain forests, and from savannahs to plateaus and mountains. Four major ecological regions are usually distinguished because of highly differentiated climates. The mountain lands in the north and south-west receive generous amounts of rain, and the same is true of the lakeshore regions, especially Lake Victoria’s; high plateaus that fill the centre of the country are semi-arid, whereas the coastal area is both hot and humid.

Overall, however, the country enjoys high agricultural potential, which presently is under-exploited. It is estimated that land suitable for cultivation amounts to 44 Mha, of which only 30 per cent is presently cultivated, most often under harsh conditions, and is rainfed with irregular precipitations and using traditional techniques. Numerous rivers and lakes represent a huge potential for irrigated agriculture, however. As much as 7 Mha are considered to have medium or high irrigation potential, out of which only 5 Mha are actually under irrigation.

Tanzania’s subsoil is rich in minerals and fuel resources. Minerals include gold, iron ore, nickel, and uranium, whereas fuels include coal and natural gas, mostly offshore. Gemstones are another important resource, most notable diamonds and a local stone called tanzanite. Altogether, mineral and fuel exports represent 45 per cent of exports.

The beauty of its mountainous, sea, and savannah landscapes along with its world-famous reserves of wild animals is another of Tanzania’s resources. Year-round, tourists flock to the numerous reserve game parks at the foot of Mount Kilimanjaro and to the resorts on the Indian Ocean coast in Zanzibar and neighbouring islands. Tourism revenues represent more than 25 per cent of exports of goods and services, even though they contracted sharply in 2020 owing to the COVID-19 pandemic.

Moving on to population characteristics, Tanzania shelters some 60 million people. Given its size, however, it is relatively sparsely populated. Its population density is the lowest in East Africa. However, as in most African countries, its population grows very quickly, presently at an annual rate of around 2.8 per cent, and density increases at the same pace. It more than doubled over the last twenty-five years. Even though urbanisation progressed during that period, it had only a small impact on the rise in population density in rural areas. This densification of the country would look even more impressive if the comparison were to be made with that seen in the mid-twentieth century at the time of independence. Population density then was only eleven inhabitants per square kilometre, a figure that is found today in desertic countries such as Libya, Mauritania, and Australia. In the opposite direction, the present size of the population and its rate of growth is sometimes worrying when one thinks about the future. By 2040, the Tanzanian population will reach more than 100 million, which may raise serious issues of employment, individual livelihood, and pressure on the provision of public goods and services.

This low population density is a reminder of the conditions of the early peopling of the geographical area that became Tanzania and the human landscape found by the colonisers in the late nineteenth century that then shaped the context of early development after independence. It can be summarised in two words: ethnic diversity.

It is estimated that there were 120 different ethnic groups in Tanzania, most with their own language, customs, and political systems, and kingdoms or chieftaincies at the time of independence. This state of affairs raises two important issues: (1) Why did no single groups or coalitions impose or at least repeatedly try to impose its rule over the others, as was seen in various other instances in Africa, in particular among neighbouring countries such as Kenya or Uganda? (2) To what extent was this conspicuous ethnic diversity a decisive factor in the development path that Tanzania followed after independence and is still following today?

There may not be a decisive answer to these questions. But it is tempting to imagine that the extension of the area that would later become Tanzania and the diversity of its habitats are the cause of the relative fragmentation of ethnic groups since the early days of the peopling of the country. In his chapter on the history of Tanzania, J. Sutton insists that until the fifteenth century, the peopling of Tanzania by successive arrivals of new tribes proceeded more by assimilation than by the conquest, extinction, and acculturation of existing tribal groups by others.Footnote 1 Even though conflicts and struggles erupted afterwards, with some groups trying to appropriate the land of others, as explained by Kimambo in another chapter of the same volume,Footnote 2 no big kingdom was ever formed that would be able to conquer a significant portion of the territory. Also, it took a long time before tight links were established between the coastal area and the interior of the country, and they were more commercial – in particular, through caravan trade – than bellicose. Today, the largest ethnic group, the Sukuma, represents only 13 per cent of the population, whereas the second largest group, the Nyamwezi, is four times smaller. This contrasts with other East African countries, where the largest groups are of comparable size or where there are essentially two groups of unequal size that are strongly rivalrous.

The lack of rivalry among ethnic groups and the rather common front opposed to the German colonisers at the time of the Maji-Maji uprising (1905-1907), which some consider to be a founding event of the Tanzanian nation, explain the lack of a strong power struggle at the time of independence, which was doubtlessly gave Tanzania a decisive advantage over other countries where internal fights for the control of power have wasted time and resources that could be put towards development. It is also argued that Swahili developed rather early as a kind of lingua franca for communication among groups and played the role of a unifying factor.

Another kind of human differentiation with some importance in Tanzania’s history is the racial discrimination explicitly introduced by the colonial powers on the basis of the origin of the population. Strong differences were thus made between Europeans, Arabs, Asians, and Africans. Even though Africans were over-dominant from a demographic point of view, economic power was in the hands of the others. Europeans lost importance when most left the country at independence. But Arabs and Asians, mostly Indians, remained powerful. The former owed their economic power to the conquest of Zanzibar by the Oman Sultanate in the late seventeenth century and the Arab domination over trade along the East African coast and between the coast and the interior. Even though they were a tiny minority, they were able to maintain their influence throughout the colonial period and after Zanzibar united with the mainland after independence. Indian merchants had always been part of the trading network along the African shores of the Indian Ocean. Some Indians were also hired as civil servants by the Oman Sultanate in Zanzibar. In colonial times, a sizeable number were brought in by the British to build railroads in the region. Many of them decided to stay. As they could not access land cultivated by Africans, they specialised in retail and wholesale trade in the interior of the country and later in light manufacturing. Both groups failed to integrate with the African population. They remain small minorities today, but their early business specialisation in the pre-colonial and colonial economy gave them an economic power that was not in proportion to their demographic weight. Their social distance from Tanzanian Africans is still quite detectable.

A last source of human differentiation to be stressed concerns religion. Christianity was introduced in the sixteenth and seventeenth centuries in the coastal area and progressively spread to the interior of the country through numerous missions. Today some 60 per cent of the population is Christian, half of it Roman Catholic and the other protestants of various denominations. Being 30 per cent of the population, Muslims are far from being a minority. They are mostly Sunni, but Shia are also present. Given the strong historical influence of Arabs in Zanzibar and along the coast, Muslims tend to be concentrated in those areas. A rather tiny minority of Tanzanians are animists or without religion. Traditionally, religion was not a source of friction in Tanzanian society. On the contrary, tolerance on both the Christian and the Muslim sides has been the norm. Lately, however, following the rise in Islamist activism in the world, some tension has occasionally appeared.

Such is, in a few words, the natural and human context in which Tanzania’s history unfolded throughout colonial times and after independence, and which has influenced and continues to influence its economic development today.

II A Short Account of the Political History of Tanzania

Two features are apparent in the short history of Tanzania since independence.Footnote 3 The first is the extent to which it is intertwined with the economy. The course followed by Tanzania was strongly influenced by economic events, most noticeably the serious balance of payment crisis of the early 1980s, but the country’s course also had a huge impact on the economy itself, in particular the early choice of a socialist development strategy. The second feature is its clear periodicity. Unlike many African countries, politics in Tanzania have been fairly peaceful and respectful of the constitution. History since independence divides itself logically into four periods, each corresponding to a different personality in the presidential seat – hence the organisation of the brief summary that follows, after a short reminder of the colonisation period.

The African Association, which became the Tanganyika African Association (TAA) after splitting from Zanzibar, initially had weak political ambition. Yet a land dispute between settlers and natives in two Meru villages in the 1950s led the local TAA secretary, Kyrilo Japhet, to launch a vigorous anti-government campaign and to seek support from the Trusteeship Council, which was responsible for the supervision of territories under mandate in the United Nations. This triggered the politicising of the TAA.

Julius Nyerere, who had studied in the United Kingdom and was one of the early Africans in Tanganyika to get a university degree, accelerated this process when he became the president of TAA in 1953. He transformed it into a real political party with local bases throughout the territory and links with trade unions, cooperative societies, and tribal unions. The explicit goal of this newly labelled Tanganyika African National Union (TANU) was independence.

A Independence

Independence was obtained in a peaceful way after TANU won practically all the seats of the Legislative Council that were open to election in 1958, and then again when all the seats in the Council were open to election in 1960. The British colonial secretary then acceded to African demand for a ‘responsible government’. One year later, independence was declared, with TANU as the party of government and Nyerere as prime minister.

Three years later, the new Republic of Tanganyika united with Zanzibar, where a violent revolution against the Arab minority that was ruling the islands had just brought to power an African-dominated party. Together the two countries formed the United Republic of Tanzania, with Julius Nyerere as president and Abeid Amani Karume from Zanzibar as vice-president. Tanzania is one state and a sovereign united republic. Nevertheless, the new country was a union, with two governments, the Union Government (United Republic of Tanzania) and the Revolutionary Government of Zanzibar as an autonomous government. The size imbalance between the two members of the union was the main reason for this structure of governance. The population of Zanzibar never represented more than 3 per cent of the whole population of the united republic.

B Forging a Nation: The Nyerere Socialist Era

Although Nyerere had been at the helm since 1961, it was not until 1967 that his strategy for the development of Tanzania was made explicit. A first five-year development plan with emphasis on private sector development, poverty reduction, and agricultural development proved disappointing. The resulting frustration, as well as the views about development that Nyerere developed during the time TANU was preparing for independence and that he shared with some other African leaders, led him to elaborate a new strategy. It was very much inspired by the experiences of socialist countries such as the Soviet Union and China, which were to be adapted to fit the African context. The full strategy was exposed in the Arusha Declaration, which is still very vividly recalled today not so much because of its economic aspects but because it was in some sense foundational for Tanzania as an independent nation.Footnote 4

The Arusha Declaration announced a socialist-oriented development programme adapted to the African context under the label of ‘Ujamaa’, or ‘family-hood’, in Swahili. It comprised three dominant strategies: first, emphasising the agricultural sector and the urgent need to improve its productivity, most importantly through regrouping dispersed subsistence farms; second, ensuring state control of the means of production and exchange, and thus nationalisation of part of the non-agricultural sector; and third, addressing social demands in terms of education, health, equality, and participation in public decision making.

The implementation of the programme sketched in the Arusha Declaration was quick in terms of nationalisation of banks, import–export companies, and several major industries. It was slower in agriculture, where the gains in productivity as well as generalised access to social services, including education and health, were supposed to go through ‘villagisation’ and, in part, collective farming. The Ujamaa villages undoubtedly represented the most original part of the whole development strategy put forward by the Nyerere government. Yet some resistance grew against the villagisation process in various parts of the country, and in several cases it became necessary to move people by force.

The results of the strategy spelled out in the Arusha Declaration were far from spectacular. In a rather candid evaluation ten years later, Nyerere himself gave a lukewarm account of it, acknowledging that growth had slowed since the new development strategy had been put in place, and results in the agricultural sector were particularly disappointing (Nyerere, Reference Niba1977).

Nationalisations did not hold on to the Arusha promises. In fact, they led to disastrous results a few years later, very much because of mismanagement by bureaucrats, interference from politicians, weaknesses in technology management, slow human resource development, limited commercialisation, and corruption at the head of nationalised companies. Even the most obvious economic strengths of Tanzania, like sisal exports, progressively weakened, a drop that was aggravated by falling world prices and that led the economy to the edge of bankruptcy.

Results were especially bad in the agricultural sector. The villagisation programme seems to have badly disrupted production processes. The outcome of villagisation as a basis for harnessing economies of scale proved disappointing, as collective farms were not as productive as envisaged – for example, productivity on farms under the villagisation programme was lower than that seen on private peasant farms in the 1970s.Footnote 5 If overall productivity gains had been obtained in the extensive cultivation of some export cash crops such as tea and tobacco, this had been at the expense of food crops. In a few years, Tanzania had gone from being a net exporter to a net importer of food, the progress in export crops being insufficient to cover the cost of imports. Without the aid of the World Bank and the International Monetary Fund (IMF), the country would have been bankrupt and doomed to famine. While some scholars such as Edwards (Reference Dixit2014) interpret this failure as the result of Nyerere’s socialist policies, other scholars argue that it does not necessarily reflect the failure of this strategy but rather the failure to involve people in the whole Ujamaa initiative.Footnote 6 Key social groups such as mass organisations had either been weakened or co-opted into the single party system or into the ruling bureaucracy and were not truly representing and acting for the people.Footnote 7

After slowing down, gross domestic product (GDP) per capita started to fall after 1976, at the same time as severe balance of payment problems developed. Nyerere refused the conditions imposed by international financial institutions for helping the country out of its foreign payment difficulties. A National Economic Survival Programme (NESP) and then a home-grown Structural Adjustment Programme (SAP) were launched in the early 1980s. However, they came too late and failed to get the economy out of the crisis. After having expelled an IMF mission in 1981, Nyerere was finally forced to accept a stand-by agreement with that institution in 1985. This agreement was a preliminary step towards an SAP to be signed with the World Bank, the aim of which was to move the economy back to a market-led economic system and, as a matter of fact, to undo much of Nyerere’s effort to build a socialist economy. He left power in 1985, leaving to his successor the task of managing this change in economic regime.

If the economic achievements of the Nyerere era were disappointing, the same cannot be said of the non-economic sphere. A key success, and a consequence of the villagisation process, has been to promote participation in development activities and decision making. The nation-building project Nyerere embarked on – which included disbanding chiefdoms and promoting the Swahili language – brought national unity and cohesion. This was reinforced by investments in education, the schooling system, literacy, and health programmes. In comparison with many other African countries, Tanzania is exceptional in the political stability it has shown since independence, under the influence of Nyerere’s probity and respect of constitutional rules. Both legacies are closely linked, for political stability would have been difficult to achieve in the presence of tribal rivalry.

Another aspect of Nyerere’s actions that made him a major political figure in Africa was his pan-Africanism and his view that African states were most often too small to develop in an autonomous way. Here, too, however, he was unsuccessful, at the level of both the continent and the region. As far as the latter is concerned, he was a strong promoter of the East Africa Community (EAC) that would federate Kenya, Tanzania, and Uganda. Yet, after some years, Western-oriented Kenya’s leadership sought to isolate itself from the socialist regime in Tanzania, whereas Uganda, under Amin Dada, aggressively invaded the northern region of Tanzania in 1978. Nyerere chased the invaders and then entered Uganda, where he was able to oust Amin Dada after a long war, the cost of which was sizeable for Tanzania and was aggravated by the consequences of the breakup of the East African Community. Rising oil prices also contributed to an economic situation that was already difficult. These circumstances ultimately led to the end of Tanzania’s socialist era.

C The Difficult Transition to the Market: 1980–1995 (Nyerere-Mwinyi)

Ali Hassan Mwinyi, who was the vice-president of Tanzania and also the president of Zanzibar, was elected president in 1985 with the explicit support of Nyerere, who was still in control of the Chama Cha Mapinduzi (CCM) party that was borne from the merger of TANU of Tanzania Mainland and Afro Shirazi Party of Zanzibar in 1977 and that is constitutionally the single political party in Tanzania. His objective was quite explicitly to re-establish the primacy of market mechanisms and to put the Tanzanian economy back on a positive growth path. This was done in a somewhat disordered way over his two presidential mandates under the strong influence of bilateral donors and the Bretton Woods institutions, though there was some domestic resistance.

The first set of reforms consisted of trying to align prices to supply–demand conditions so that they would give the right incentives to economic agents. Agricultural marketing, including the supply of agricultural inputs, was liberalised, prices and wages were deregulated, the currency was massively devalued, and import tariffs were rationalised. Initially, growth reacted positively to the reforms, mostly because of the release of aid resources that had been withheld by donors because of friction with the Tanzanian government in the last years of the Nyerere era and because the agricultural sector recovered some dynamism after years of paralysis. However, growth then stagnated, as it was becoming obvious that several institutional factors were preventing it from really taking off.

Another set of structural reforms was launched during the second mandate of Mwinyi from 1990 onwards, the most important one being dismantling and privatising the numerous state-owned companies that ran the economy during the socialist era and were still operating. Other reforms included opening the financial sector to private domestic and foreign actors, concentrating tax collection within a single Tanzanian Revenue Authority,Footnote 8 dismantling monopolies in the agricultural output trade, and reforming the civil service with the aim of reducing the number of civil servants and making them more effective.

Other reforms were undertaken in the political sphere. Constitutional changes had been passed in 1985 that defined more precisely the prerogatives of the president and limited his mandate to two five-year terms. Most importantly, a multi-party system was established in 1992, formally ending the legal monopoly of the CCM party, the so-called party of the revolution. Consequently, the political scene became much more active, and the Tanzanian people’s political unity began to weaken as the 1995 general election approached.

The end of Mwinyi’s second term was marked by various corruption scandals, the most notorious of which was revealed by the World Bank in November 1994. The embezzlement, amounting to some 3 per cent of annual GDP, involved senior officials in the Ministry of Finance and caused donors to temporarily stop all disbursements.Footnote 9

This event was the culmination of a rampant crisis between the executive branch and the donors that ran throughout practically the whole Mwinyi presidency. Its root lay in the fundamental opposition of a large part of the Tanzanian elite, including in some instances cabinet ministers, to moving away from the socialist regime. Some held such a view for ideological reasons, but others clearly tried to protect the rents they were able to create during the socialist era. As a result, the reforms imposed by the international financial institutions slowed down and had little impact on the economy. Corruption was rising, whereas growth would not take off. The crisis that culminated in donors withdrawing a significant part of their aid in 1995 was finally overcome thanks to the work of a consultative group, which was able to pacify the donor–recipient relationship.Footnote 10

It is hardly surprising that such a transition from socialism to a market economy was so difficult and conflictive, both with donors and within Tanzania. It is not surprising either that corruption practices spread in such a period of disruptive reforms, especially starting from a regime where corruption was already widespread among the elite. Some time was necessary for the economy and society to stabilise and growth to pick up. Quite revelatory in this respect is the ‘Mzee Rukhsa’ or ‘Everything goes’ nickname given by Tanzanians to the Mwinyi era. Although this occurred some twenty-five years ago, it will be seen that this period left durable marks on society and the economy.

The economy and society started to settle down and growth started to pick up under the presidency of Benjamin Mkapa, the first president elected in multi-party elections.

D The Marker Era: 1995–2015 (Mkapa-Kikwete)

The evolution of Tanzania over since the early 2000s under the successive presidencies of Benjamin Mkapa and Jakaya Kikwete may be described as the actual implementation and deepening of the reforms passed under the presidency of Mwinyi. Despite the underlying tension mentioned earlier, this took place with remarkable political stability, at least on the mainland, owing in part to the single party (CCM) that had ruled the country since independence remaining the dominant party after the move to a multi-party system. In fact, it took some time for the opposition to strengthen and it is only recently that it has started to represent a possible threat to the CCM, at least on the mainland.

The same cannot be said of Zanzibar, where the confrontation between the CCM and the local opposition party (Civic United Front, CUF) and later ACT has been extremely conflictive, with several upsurges of violence. Rigged elections, a partisan electoral commission, harsh repression of protests, and reneging on union government commitments created a climate of mutual distrust that proved difficult to calm down. A constitutional reform of the relationship between the two members of the United Republic of Tanzania that could reduce the intensity of the confrontation has been considered for some time, but it is presently at a stalemate.

Another prominent feature of the last two decades is the frequency of major corruption scandals, which suggests that corruption is indeed rooted in society and the economy. Several cases came to light under both Mkapa and Kikwete, which every time led to ministers and high-ranked officials being dismissed and led to donors temporarily suspending aid disbursements. Since those days, Tanzania has found itself systematically rated very low in the corruption rankings published by Transparency International and comparable organisations. Donors repeatedly conditioned their aid on efforts being made to curb corruption, and successive governments have committed to act in this area. Their impact has been limited, though. Inherited from the socialist era and the disordered period of transition towards a market economy, corruption is a plague that now seems extremely difficult to eradicate.Footnote 11

Some other noteworthy political developments are worth stressing. One is the inflow of refugees owing to conflicts in the neighbouring Democratic Republic of Congo (DRC), Rwanda, and Burundi since the mid-1990s. At some stage, there were around 700,000 refugees hosted in Tanzanian camps who were supported by international organisations and the Tanzanian government. Another development was the re-launch in 2000, twenty-three years after its collapse in 1977, of the East African Community. Initially revived with its three founding members (Tanzania, Kenya, and Uganda), the EAC was enlarged to include Rwanda and Burundi in July 2009.Footnote 12

On the economic side, the progress towards an all-market economy proved to be slower than anticipated. The number of parastatals or state-owned enterprises (SOEs) still active in 1995 was considerable – that is, more than 300. It took time to privatise them, to merge them in joint ventures with the private sector, or simply to dismantle them. There was concern that the privatisation programme did not give adequate opportunity for local private entrepreneurs to participate. One factor that contributed to this outcome was the failure to operationalise the Privatisation Trust Fund established by the Privatisation Trust Act of 1996. It also took time for the public mindset to change with respect to the role of the private sector in development. It was only during the second term of Kikwete’s mandate that policies aimed at creating a favourable climate for the private sector were explicitly adopted.

Still on the economic side, the last twenty years have seen significant progress towards macroeconomic stability but relatively little towards the ‘self-reliance’ goal pursued since the Nyerere era. Since independence, donors have generously supported the development of Tanzania. They have sometimes suspended their aid after corruption scandals or in times of disagreement about the policies to be implemented, but they have always been present when their help was crucially needed. It cannot be denied that, at least over the last twenty to twenty-five years, Tanzania has been an ‘aid darling’.

In any case, the recent period has been rather favourable on the economic growth front. Considerable acceleration took place during the second term of the Mkapa presidency. With an average GDP growth rate of 6 per cent between 2002 and 2015, Tanzania is among the African champions. As in other countries, however, it is difficult to say how much of this is thanks to domestic reforms and how much to a favourable international context.

E The Fifth Phase: November 2015–March 2021

On 5 November 2015, the fifth president of Tanzania was elected. John Pombe Magufuli’s nomination within the dominant CCM party was the result of a difficult process, as he was a kind of outsider with respect to influential groups within the party. He won the nomination, and then the election, very much on his anti-corruption platform and his well-recognised personal probity, a quality he had shown as the minister of Public Works in the previous administration. For the first time since the advent of multi-partyism, however, the opposition showed real strength, getting a little more than 40 per cent of the votes in the run-off ballot.

One of the factors that contributed to his rise to power in spite of his limited record as a player in the ruling party is the manner in which the credibility of the dominant party, CCM, had been eroded by a series of corruption scandals and a general perception that corruption had been on the rise in the country.Footnote 13 In this regard, the main opposition party, Chadema, made considerable political gains in society by launching an anti-corruption campaign that contributed to eroding the credibility of CCM. This may have been one of the factors that led to dropping Edward Lowasa from the CCM candidacy, even though he was rated as highly popular among the candidates within CCM. The decision to drop his name is likely to have been influenced by the fact that he had been mentioned in a recent major scandal and had then been attacked by Chadema in their anti-corruption campaign. The ruling party, CCM, and its leaders had been so maligned and marred by allegations of corruption that it is likely this situation enhanced the chances of nominating for the presidency a candidate who was not identifiable with the party and its heavyweights – that is, a relatively clean person. Ironically, when Lowasa was dropped by CCM, he was nominated by Chadema as their presidential candidate. It had ben hoped that this candidate, perceived to be popular in CCM, would move to Chadema with a substantial group of CCM members. In any case, he moved with a handful of CCM members. The nomination of Lowasa as Chadema presidential candidate had a major paradoxical effect on the choice of campaign agenda on both sides. Chadema dropped the anti-corruption agenda, presumably because earlier they had tainted Lowasa as a corrupt person, and the CCM candidate picked the anti-corruption agenda and campaigned on that ticket, often putting CCM on the back burner. This change of roles in the agenda put forward, and shifting agenda so easily, may be an indication of the ideological shortcomings of both parties. Magufuli won with 58 per cent of the vote, mainly on his anti-corruption platform.

It may be too early to evaluate the full consequences of Magufuli’s actions, as the outcomes were still unfolding in terms of institutional diagnostics when he died in March 2021, after just more than five years in office. Yet it will be useful for the analysis in this volume to mention their main original features.

President Magufuli entered office as a popular leader largely on account of the promises he made about fighting corruption, cutting down on unnecessary public expenditures, checking the waste of public resources, identifying as a man of action (he was nicknamed the ‘bulldozer’), and caring for the downtrodden (wanyonge). These promises were appealing because they came at a time when corruption scandals had been rampant, poverty and unemployment were still major concerns, and the ideological direction of CCM was being questioned because of what Shivji calls the consequence of CCM having been disarmed ideologically and organisationally over a generation.Footnote 14 His popularity was enhanced by the perception that he was a leader who could get things done. This was appealing because the Kikwete administration had increasingly gained a laissez-faire reputation and because of the perception that ‘law and order’ had been eroded while transparency – which he promoted – was perceived as not being accompanied by accountability. This perception planted seeds of what was later to manifest as high-handed actions to return the country to order and get things done, even if it meant taking shortcuts involving autocratic means. Indeed, he did get things done, confirming his nickname ‘bulldozer’, but, as some have said, he was more of a supervisor than a political leader.Footnote 15

President Magufuli identified the concept of development with accomplishing major infrastructure undertakings. Huge projects were thus launched, including the hydroelectric dam across Stigler’s Gorge (Nyerere Hydroelectric project), the Standard Gauge Railway from Dar es Salaam to Kigoma and further west, and many miles of tarmac roads across the country. These projects will yield development returns in the future, possibly helping industrialisation, another of Magufuli’s priorities (Tanzania ya viwanda). However, he did not really define the kind of industrialisation he stood for, nor the way it could trickle down to agriculture, the sector where the majority of the poor (wanyonge) are found. The industrialisation drive remained unplanned and confused, and the youth still have not seen the level of job creation that they had hoped for. The animosity that often tinted the relationship between the president and big business did not help to carry forward the industrialisation agenda.

Under President Magufuli, efforts were also made to get the most out of Tanzania’s natural resources to benefit the people of Tanzania. He effected a piece of legislation called the Natural Wealth and Resources (Permanent Sovereignty) Act that was passed in 2017 and that asserted the Tanzanian people’s sovereign ownership and control over natural resources. He took on Barrick, the multinational gold company, and stopped containers full of mineral sand from being exported while he formed a local team of experts to check the mineral content of the sand. He also worked on other forms of revenue generation from minerals. However, these efforts fell short in two areas. First, building the human and institutional capacity for managing natural resources along the long-run lines was not accorded priority, contrary to recommendations that had been made by civil society organisations such as Haki Rasilimali – the Tanzanian branch of the ‘Publish What You Pay’ international non-governmental organisation (NGO) – about extractive industry governance. Second, the regime did not effectively engage in formulating and strengthening policy frameworks for managing natural resources.

On other fronts, the president boldly moved against grand corruption in both the political and business spheres. For what this kind of study is worth given the difficulty of evaluating corruption, a 2020 report by the Tanzanian anti-corruption agency, the Prevention and Combating Corruption Bureau (PCCB), revealed that corruption had declined during his administration. In education, he abolished primary and secondary school fees, and accelerated the building of classrooms and the provision of desks. On health, investments in new facilities and equipment were enhanced, and health insurance coverage was extended at a cheap premium to almost one-third of the population. He was also in favour of less informality in the economy but did not have a clear strategy for formalisation besides issuing street vendors and kiosk-owners with identity cards at 20 shillings that would free them from further tax payments and harassment by law enforcement personnel.

Magufuli wanted to see results fast. His strategy fits the saying ‘If you want to go fast, go alone; but it you want to go far, go together’. He chose to go fast and obtained some results. But, breaking very much from his predecessors, he ruled in a rather authoritarian and personalised way.

If Tanzania continued to be a relatively stable and peaceful polity during his mandate, this stability was superficial, and continuity was illusory (Shivji, Reference Rodrik2021). To some extent stability and peace were induced by fear and the narrowing of civic space. Political rallies were banned, and opposition leaders were openly harassed by the police and implicated in numerous court cases. Space for civil society organisations and NGOs was severely restricted. Many organisations and civil society actors were subjected to all kinds of intimidating demands from state authorities, but print and electronic media bore the brunt of the repression. Some journalists and opposition leaders were taken to jail or even assaulted. Ironically, while the mainstream media was undergoing censure, a small pro-Magufuli media house emerged, introducing itself as an independent advocate that supported him. Its newspapers and TV defamed prominent people, including former secretary generals of the ruling party who were perceived to have fallen out of favour. The media house abused Magufuli’s critics and pursued opponents and foes without hindrance. Of course, no disciplinary action was taken against it by either regulatory bodies or media watchdogs. After Magufuli died, however, the organisation was taken to court and convicted for defamation. This story illustrates the fear inspired by Magufuli’s authoritarianism in the whole state apparatus, including the closest circle around him, as well as many private actors (Shivji, Reference Rodrik2021).

This state of affairs made people unhappy and frustrated as they were not able to hold their government accountable. Instead, ‘people were expected to be accountable to the government’.Footnote 16 Magufuli’s domestic popularity started very high as measured by the annual TWAWEZA poll. His posture as a ‘man of integrity’, determined to go against the status quo, and able to sometimes take spectacular measures initially pleased public opinion. Over time his popularity started to fall, however, to such an extent that the 2018 TWAWEZA poll showed a rate of approval only moderately above 50 per cent. TWAWEZA got into trouble with the Magufuli government, and no more poll results have been published since then.

In two elections (local government elections in 2019 and the general election in October 2020) when people could have openly expressed their views, there were rampant claims of unfair treatment of the opposition. In the local government elections of 2019, the opposition felt so mistreated that they opted out of the elections, which led Magufuli to observe that opting out was a democratic decision too. In the general election of October 2020, Chadema presidential candidate Tundu Lissu drew such large crowds during the campaign that the winner of the election appeared increasingly uncertain. However, Magufuli, the CCM presidential candidate, and CCM parliamentary candidates won with such a large margin that opposition cried foul, accusing CCM of malpractice supported by the police. Indeed, Magufuli won with 84 per cent of the vote, and CCM won all parliamentary seats except a couple. However, for the first time since the beginning of general elections in 1965, no election petitions were filed. By itself, this was not only a telling critical comment on the 2020 general elections under President Magufuli’s watch but above all a veiled pointer to the loss of people’s trust in the impartiality of the judiciary. In the Journal of Democracy in July 2021, Dan Paget argued that with brutal resolve, the ruling party sought not merely to win an election, but to annihilate the opposition. According to other observers,Footnote 17 the flawed 2020 Tanzanian elections are blamed on an authoritarian turn instigated by Magufuli, although focusing exclusively on Magufuli obscures the authoritarian foundations of CCM rule and the strategies used by CCM to maintain political control, albeit in a more subtle way.

The stand Magufuli took on COVID-19 is another sign of his distrust of others’ opinion as well as a mind that could at times be seen as both obsessive and self-contradictory. He denied the existence of the pandemic while sometimes acknowledging its reality. He thus publicly claimed that Tanzania had eradicated COVID-19 through three days of prayer, but is also reported to have played down the pandemic and denounced vaccines as a Western conspiracy against Africans. Under his administration Tanzania suspended updating its COVID-19 cases and deaths to the World Health Organization and communication on the pandemic was prohibited, even though there were clear indications that the number of admissions at hospitals of patients exhibiting respiratory symptoms consistent with COVID-19 was increasing. Although still unofficial, he may have been one of them when he died in March 2021, a few weeks after starting his second presidential mandate. Despite, or possibly because of, his persistent denial of the virus, the US State Department diplomatically remarked after his passing that the United States remained committed to continuing to support Tanzanians ‘as they work to combat the COVID-19 pandemic’.

The history of President Magufuli’s administration underlines the risks of viewing leaders through rose-tinted glasses. Charismatic individuals can claim the reformer’s mantle, but giving them too much credence before structural reforms are implemented sells democracy short and increases the risk of authoritarian relapse.

F The Beginning of the Sixth Phase

President Samia Suluhu Hassan was sworn in as the new president of the sixth-phase government on 19 March 2021 following the death of Magufuli. Several new developments and notable changes in policies on several fronts have already been observed.

Freedom of the media and of speech has been one immediate change from the Magufuli regime. Social media immediately became vibrant in the first week of the sixth phase. Print and electronic media are operating freely, and some of those that had been closed have been restarted. There is freedom of the opposition parties, and President Samia has openly spoken in favour of bringing unity and peace between CCM and the opposition parties. There are clear signs of departure from authoritarianism.

President Samia has demonstrated that observance of the rule of law is being restored. Several businesspeople who had been arrested and stayed in custody without being charged and those who had been charged falsely for money laundering have been released. Those who had been close to Magufuli and broke the law with impunity have been taken to court and charged.

There are encouraging indications of an improved business climate. The relationship with the business sector has improved, as indicated by frequent meetings with sections of the business community and resumption of dialogue between government and the private sector in the Tanzania National Business Council. President Samia has been accompanied by business representatives in her state visits to other countries (Uganda, Kenya, Rwanda, Burundi, and the United States), an indication that she is determined to improve relations with the private sector. President Samia has liberalised several policies politically and economically and in terms of economic diplomacy, as indicated by mended relations with several foreign governments and international financial institutions, notably the World Bank and the IMF. The policies and procedures related to issuing permits to investors have eased, and permits for foreign experts have been made more liberal and efficient. Investors are facilitated more efficiently in terms of the time it takes.

G Final Remarks on Political History

Numerous major events have occurred over the last fifty years or so that have oriented Tanzania in various, sometimes opposing, directions. In the first stage, post-independence Tanzania continued colonial trends, with essentially an outward market orientation. Then came the turn to socialism and the attempt at creating a self-reliant African socialist society. This second period lasted seventeen years, during which huge and sometimes violent reforms took place at the same time as mindsets were deeply modified. Then a new period came that started to reverse the previous order, trying to instil in society the seeds of a market economy and a multi-party democracy. Ten years later, this new regime is more or less in place, but the old order has not completely disappeared in the minds of civil servants and the employees and managers of SOEs. Also, such a succession of reforms and the difficulty of monitoring them in a rigorous way has generated specific mindsets, especially regarding corruption, that will take time to be modified.

Most importantly for the present study, it is difficult to imagine that such a contrasting evolution in such a short time span has had no impact on the institutional context in which present and future development must take place. It is the purpose of this study to identify precisely which institutions are the most likely to be obstacles to that development. Before focusing on institutional issues, however, it is necessary to review the main features of the development process in Tanzania.

2 Features and Challenges of Economic Development

François Bourguignon

Tanzania graduated in 2020 from low-income to lower middle-income status in the country classification used by international organisations. This means that its national income per inhabitant is now just above USD 1,025 at the current official exchange rate. This was celebrated as an important achievement, even though such a nominal concept that does not take into account the purchasing power of the population is of dubious significance. After correcting for this factor, it turns out that the average Tanzanian citizen lives on USD 2,700 at the present purchasing power of advanced countries. Although higher in absolute terms, this figure is still less than a sixth of the world average and ranks Tanzania only slightly above the bottom 10 per cent threshold in a world ranking of countries. Despite graduation, Tanzania is still a poor country where economic development is as urgent today as it has been since independence.

As noted in Chapter 1, the country has gone through difficult times with the severe crisis that ended Nyerere’s socialist experiment and the painful transition to a modern market economy under the control of donors and international financial organisations. It is only since the end of the 1990s, that is almost forty years after independence, that the country has seen steady growth. Progress since then has been impressive. Yet, with still almost half of its population below the international poverty line of USD 2.15 a day at international prices, there is still a very long way to go before it will have completely eradicated poverty, fast population growth making this even more challenging.

This chapter analyses the economic development obstacles that Tanzania faces today and is likely to face in the future on its way to full poverty eradication. It starts with a review of the evolution of key economic indicators and its main causes with a focus on the most recent period and the factors that may presently be constraining further or faster progress. The spotlight then moves to social issues, where results appear significantly less remarkable than could be expected given the economic achievements. The chapter ends with a summary of the main economic and social development challenges faced by Tanzania in the early 2020s. More detailed aspects of the economic as well as institutional context of Tanzanian development are considered in subsequent chapters.

I The Main Features of Tanzania’s Economic Development

The short economic history of Tanzania has been chaotic. It is only during the last twenty-five years or so that economic development has proceeded at a steady pace, and this is the period the following review will mostly focus upon. Yet it is also important to sometimes refer to the preceding period, that is the socialist development era and the difficult transition to a full market economy, to put the recent period in perspective.

The following review of economic development in Tanzania is organised around four major sets of issues that, directly or indirectly, have all to do with the determinants of the pace and structure of economic growth. The first set is concerned with the gross domestic product (GDP) growth rate and the way it can be explained by changes in the sectoral structure of the economy and/or productivity gains within sectors. The second set of issues has to do with capital accumulation as an essential factor of growth, and more generally the division of national income into investment and consumption expenditures. The third set involves the role of external trade, a major factor in all contemporaneous development histories. The last set is about the financing of the economy and especially foreign finance flows, including official development assistance (ODA).

A Pace and Sources of Aggregate Growth

Growth has closely followed the changes in political and economic regimes that have characterised Tanzania since the end of the Nyerere era. Growth was fast following independence but slowed down a bit after the implementation of the socialist Ujamaa strategy, and then fully collapsed when the destabilisation caused by the latter combined with adverse external conditions to produce a severe economic crisis in the mid-1980s. A long period of stagnation followed as the transition back to a market economy took place under strict macroeconomic and structural adjustment constraints imposed by the International Monetary Fund (IMF) and the World Bank. It was only in the late 1990s that GDP per capita started to grow vigorously again, after almost twenty years of stagnation. Since then, progress has been dynamic, to such an extent that Tanzania’s development has often been called a ‘success story’ – masking earlier difficulties. GDP per capita has grown on average by 3 per cent and total GDP by around 6 per cent a year over the last twenty years or so. As can be seen in Figure 2.1, GDP per capita has practically doubled over that period, a rather impressive performance in comparison with earlier decades and with the whole of the sub-Saharan region.

Figure 2.1 Tanzania’s GDP per capita (absolute and relative to sub-Saharan Africa) and growth rate, 1960–2020

Source: Penn World Tables 9.1 1960–2009; WDI 2019–20

That overall evolution of growth since independence in Tanzania is far from unique to the region. Most sub-Saharan countries have gone through the same sequence of booms and busts, although with different intensity: fast growth after independence, recession and severe balance of payment crises in the early or mid-1980s partly because of unfavourable external contexts, structural adjustment programmes (SAPs) forced upon them by the IMF and the World Bank, and exit from this long stagnation in the mid- or late 1990s. Compared with the whole of sub-Saharan Africa – excluding South Africa – Tanzania did better in the post-independence years, then worse in the early 1970s, at the time of Ujamaa. It then performed on a par with the region, recovered earlier from the long stagnation of the 1980s and early 1990s, and then performed significantly better over the last two decades. Over the last sixty years, Tanzania’s growth of GDP per capita has outperformed the average sub-Saharan country by 50 per cent.

The comparison is less favourable with other developing countries. In the early 1980s, countries such as Bangladesh, Cambodia, India, Laos, and Vietnam had a GDP per capita lower than Tanzania in international purchasing power parity. Today, it is 30 per cent higher in Bangladesh and Cambodia and more than twice in the other countries.

1 The Sources of Growth: Structural Change More Than Productivity Gains

Analysis of changes in the structure of the economy and productivity growth since independence is made difficult because of a lack of homogeneous series over the whole period. The Groningen Growth Development Centre (GGDC) provides data on sectoral components of GDP and employment that result from a careful analysis of all existing sources of data – especially on employment – and reasonable inter- or extrapolation when data are missing. The problem is that the GGDC changed definitions and price corrections in its most recent release for the 1990–2018 period, thus making it not directly comparable with the previous release, which covered 1960–2011. Rather than trying to build artificially homogeneous series covering the whole economic history since independence, we use the two sources as follows: the initial series for the 1960–97 period, that is the independence period followed by the long recession that ended in the late 1990s, and the most recent dataset since 1997.

Tables 2.1a and 2.1b describe respectively the evolution of the structure of the economy over these two periods. Figures for 1997, which appear in both tables, thus refer to two different sources that differ on the one hand in the definition of sectors and on the other hand in the base year for constant price GDP series. Differences are noticeable. Reassuringly, however, it turns out that the two data sets are roughly consistent with each other in describing the changes in the structure of employment and GDP over periods common to the two sets, although this convergence is not explored further here.

Table 2.1a Evolution of the sectoral structure of employment and GDP, 1960–97 (GGDC Release 2014, GDP at constant 2005 prices)

(%)
Year
196019771997
GDPEmpl.R. ProdFootnote aGDPEmpl.R. ProdFootnote aGDPEmpl.R. ProdFootnote a
Agriculture45.091.70.533.088.50.439.785.30.5
Mining3.80.127.91.20.62.01.60.53.4
Manufacturing6.91.076.412.41.67.78.51.55.7
Utilities0.80.029.91.50.118.92.60.214.8
Construction7.20.242.28.70.711.97.30.611.2
Trade and hospitality17.71.018.316.23.94.215.96.12.6
Transport, storage, and communication6.30.226.99.00.811.67.00.79.6
Finance, insurance, real estate, and business services2.60.127.93.40.220.14.80.223.8
Government services9.23.52.613.82.26.211.63.13.7
Community, social, and personal services0.52.10.30.81.40.61.01.80.5
Total100100100100100100
GDP and GDP/worker (1997 = 100)27.680.160.6108.8100100

a Sectoral productivity relative to overall productivity at the bottom of the column (1997 = 100), i.e. GDP divided by Empl. column

Source: Author’s calculation from Groningen Growth Development Centre database.

Table 2.1b Evolution of the sectoral structure of employment and GDP, 1997–2018 (GGDC Release 2021, GDP at constant 2015 prices)

(%)
Year
199720072018
GDPEmpl.R. ProdFootnote aGDPEmpl.R. ProdFootnote aGDPEmpl.R. ProdFootnote a
Agriculture39.784.40.532.275.30.427.969.70.4
Mining2.80.64.64.70.68.54.40.85.6
Manufacturing6.91.83.97.92.73.09.13.22.8
Utilities1.90.211.31.60.115.21.30.110.2
Construction6.10.87.59.41.27.914.71.97.9
Trade and hospitality13.16.42.011.710.41.111.414.20.8
Transport, storage, and communication8.20.711.07.91.65.18.32.14.0
Finance, insurance, real estate, and business services10.60.424.612.70.816.712.21.111.1
Government services8.53.32.610.23.23.29.33.72.5
Community, social, and personal services2.31.41.71.74.20.41.43.20.4
Total100100100100100100
GDP and GDP/worker (1997 = 100)100100180132.5356198.6

a Sectoral productivity relative to overall productivity at the bottom of the column (1997 = 100), i.e. GDP divided by Empl. column

Source: Author’s calculation from Groningen Growth Development Centre database.

The story told by Table 2.1a on the earlier period fits the growth account presented earlier. It breaks down into a rather dynamic time from independence to the mid-1970s and then a long regression until the late 1990s. Structural changes are noticeable – from 1977 to 1997 – with the GDP-share of agriculture falling rapidly in favour of manufacturing, utilities, and government services. Changes on the employment side are more limited,Footnote 1 the dominant feature being the loss of agriculture mostly to the benefit of trade and hospitality, with a pronounced drop in both sectors in relative productivity, that is the ratio of sectoral productivity to overall (GDP) productivity. On the GDP side, the second subperiod – from 1977 to 1997 – witnesses structural changes that go in the opposite direction, with agriculture regaining weight at the expense of manufacturing and other sectors, whereas labour movement from agriculture to the rest of the economy continues at the same slow pace.

Structural changes shown in Table 2.1b for the last two decades resemble the post-independence period in the preceding table, with fast and accelerating progress of aggregate productivity and a quick decline in the GDP share for agriculture. Sizeable relative gains are observed in construction, whose share more than doubled, mining, and, to a lesser extent, manufacturing. It is interesting that these changes look to be continuous throughout the whole timespan, the structure of GDP in 2007 being intermediate between those observed at the beginning and end of the period. For employment, the same migration phenomenon as before is present, although much enhanced, between agriculture and the trade sector. Employment movement towards the latter sector is so strong that its productivity relative to that of the whole economy is more than halved over the whole period – which implies a slight decline in absolute terms.

Focusing on the periods of fast growth, it is tempting to conclude from these tables that Tanzania’s engines of economic growth stood in those sectors whose GDP share benefited most from the decreasing importance of agriculture. They comprise manufacturing, transport, and government services in the post-independence years, and essentially construction, mining, and manufacturing in the last twenty years. Such a reading of the preceding tables would be misleading, however. First, engines of growth in a small open economy such as Tanzania are almost necessarily located in sectors that produce tradable goods. Growth in other sectors reflects the dynamism of the demand side of the economy or its consequences rather than being the cause of overall growth. Thus, mining and manufacturing are sectors that might possibly qualify as growth engines, but not construction, which essentially responds to the demand arising from growing public infrastructure investments. Second, true engines of growth are unlikely to be sectors whose labour productivity lags behind that of the whole economy while their employment share rises, as has been the case for the trade and hospitality sector in Tanzania. Either those sectors are sheltering surplus labour or their development concentrates in sub-sectors with lower productivity, an unlikely trend.

The case of the manufacturing sector is of particular interest owing to the emphasis presently put by the Tanzanian government on the need for the economy to industrialise. It can be seen in Table 2.1b that the manufacturing sector has grown somewhat faster than total GDP over the last twenty years, without its share in GDP ever reaching the level achieved by 1977 before the long recession. Assuming that part of that growth was a response to the increase in demand originating in the rest of the economy, the other part can be seen as truly autonomous and directed towards exports – or substituting for imports. It is indeed the case that manufacturing exports grew quite substantially during the 2000s, as emphasised for instance in MacMillan et al. (2017, pp. 155–60),Footnote 2 suggesting that this sector has the potential to grow independently of the rest of the economy, a feature that is expected from a genuine growth driver. Yet the contribution of the manufacturing sector to the overall growth of the economy is presently limited by its size. It is easily calculated that the 2 per cent GDP-share increase in Table 2.1b is responsible for only 10 per cent of overall growth over the last two decades.

An unexpected feature of the evolution of the manufacturing sector over that period is the drop in its productivity relative to that of the whole economy – see Table 2.1b – which seems to contradict the capacity of this sector to play the role of a growth engine, even as a side influence rather than the main driving factor. The point is that this concept of relative productivity may be misleading, and the comparison with the growth of overall productivity may hide the true contribution to overall growth of the productivity gain arising within a sector.

The reason for this ambiguity lies in the key role of structural change, that is the reallocation of labour across sectors, in overall labour productivity gains. When workers leave agriculture, they move away from a sector where labour productivity is among the lowest – as can be seen in Tables 2.1a and 2.1b – and move to sectors where the productivity is higher. By itself, this restructuring of employment thus raises the overall labour productivity in the economy. This would be the case even if no productivity gain were taking place within sectors. When comparing the change in the productivity within a specific sector to overall productivity, it must thus be taken into account that the latter includes this structural change effect. Productivity may well increase in the sector under consideration, but may be less than the overall productivity gains due to structural change.

The decomposition of the change in overall productivity into its structural change and its within-sector components shown in Table 2.2 for the two pre- and post-1997 periods is quite instructive. The striking feature is the importance of the structural change component. Until 1997, gains in overall labour productivity – and roughly speaking in GDP per capita since employment may be assumed to be approximately proportional to the population – were essentially due to structural change, whereas the within-sector productivity gain was negative. Roughly speaking, this can be interpreted as the result of workers moving from agriculture to sectors with a higher productivity but contributing at the same time to lowering productivity within the latter. This is exactly the way the increasing employment share and decreasing GDP share of the trade sector, the main destination of the net flow of workers out of agriculture, can be interpreted in Tables 2.1a and 2.1b.

Table 2.2 Decomposition of the change in overall labour productivity into structural change and within-sector productivity effect, 1960–2018

(Percentage points)Structural changeWithin-sector productivityTotal
(GGDG Release 2014, GDP at 2005 prices)
1960–7768.7−32.835.9
1977–977.9−14.7−6.8
1960–9785.2−42.742.5
(GGDG Release 2021, GDP at 2015 prices)
1997–200725.76.832.5
2007–1822.327.549.9
1997–201853.736.289.9
Source: Calculation in Appendix

Things change drastically after 1997, however. First, the structural change effect tends to weaken, mostly because the productivity gap between agriculture and the trade and hospitality sector shrinks. Second, the average within-sector productivity increases, especially after 2007.Footnote 3 Over the most recent sub-period, the within-sector productivity component is even slightly bigger than the structural change effect. It thus looks as if some deep change had taken place in the Tanzanian economy. Coming back to the issue of the contribution of the manufacturing sector to growth, it can be seen in the Appendix that its contribution to the growth of overall productivity is definitely more through its autonomous increase in productivity than its participation in structural change through faster employment creation than in the rest of the economy.

What should be concluded from this review of the changes in the structure of the Tanzanian economy and in sectoral productivities in terms of sources of growth? A first conclusion is the importance of the sectoral reallocation of labour as the main source of growth from independence until today,Footnote 4 except, of course, during the long recession of the 1980s and 1990s, a period of more than fifteen years over which both overall growth of labour productivity and its structural change component have been close to zero. A second conclusion is the negative overall contribution of changes in within-sector productivity from independence to the mid-2000s. It is only over the recent past that productivity gains acquired a dynamic role in Tanzanian growth. Interestingly, it will be seen later that this coincides with a sustained high level of capital accumulation, as not experienced in Tanzania since the socialist era. Causality is not granted, though, especially because much of the gross capital formation seems to have taken place in infrastructure, as may be guessed from the surge of the construction sector, which produces a type of capital whose impact on productivity generally takes some time to become visible.

The rather satisfactory rate of growth that Tanzania has enjoyed over the last twenty years or so is good news. That it cannot be attributed to the autonomous growth of a specific sector progressing on international markets or competing with imports is more worrying. The reallocation of labour from low-productivity agriculture to a slightly less low-productivity trade sector cannot be considered as a sustainable engine of growth. At some stage, employment in higher productivity sectors, especially in tradable goods and services, will have to expand. It is not clear this is about to happen. Even though more dynamic lately, the manufacturing sector is presently not big enough to be more than a side engine of growth. As noted in Chapter 1, the agricultural sector is home to the natural comparative advantages of the Tanzanian economy. Until now, however, these have not been exploited and agriculture lies largely behind the growth of the rest of the economy. Mining is the last tradable sector that could be an autonomous source of growth, but this would be more through favourable international prices, and therefore its positive impact on the demand side of the economy, than through enhanced production on the supply side, unless of course a flow of new resources were to be discovered in the coming decades.Footnote 5

II Investment and the Structure of Aggregate Spending

Even though the growth performance of the Tanzanian economy has been reasonably high over the last twenty years, and especially the last decade, it is not to be ignored that it was largely demand-driven rather than the produce of a clearly identified autonomous growth engine in tradable sectors. This would be the case, for instance, if a significant improvement in the terms of trade or important foreign resources grants had fed private and public domestic demand, fostering activity and possibly investment. It will be seen later that such an improvement in terms of trade occurred at around the turn of the millennium. In the future, however, a way has to be found to maintain and enhance the progress observed lately in the productivity, and therefore competitiveness, of key tradable sectors, manufacturing in the first place, but possibly also agriculture and the agroindustry. This requires keeping investment at a high level and making it more effective.

The evolution of the domestic expenditure counterpart of GDP is shown in Figure 2.2 from 1985 to 2017. Earlier data are not available or are not comparable, whereas data after 2017 are still provisional and likely to be affected by measurement errors. The dark curve that describes the evolution of the GDP-share of gross capital formation exhibits an interesting shape. It surged in 1990 and reached a level close to 40 per cent for a few years. It then fell sharply until 2000, before progressively getting back to its previous maximum over the last ten years or so. Such an evolution raises two sets of questions. First, what explains such fluctuations and what made, and is making possible today, such a high rate of investment in a country that has just graduated from low-income status? Second, are the rate of growth of the economy and its productivity gains consistent with its investment efforts?

Figure 2.2 Absorption and expenditures on GDP, 1985–2018 (percentage of GDP)

Note: Because of a shift in the base of Tanzanian national accounts in 2015, the IMF today reports only data after 2012. Figures for the period before 2012 are taken from previous 2005-based national account series after adjusting them proportionally so that they coincide with the new definition in 2012

Source: IMF, International Financial Statistics

The evolution of investment in the first half of the period shown in Figure 2.2 closely follows the economic history of Tanzania. After Nyerere’s resignation in 1985 and the concomitant shift to a market economic system under the pressure of donors, and in front of the dismal situation of the economy, ODA flows surged while new ambitious development programmes were launched. These included huge investment efforts that were essentially financed externally; hence the high level of absorption – that is, total domestic expenditures including investment – observed in around 1990, a period during which domestic spending overcame GDP in some years by as much as 35 per cent. But donors did not want to keep Tanzania permanently on a drip and started reducing aid. After a short rebound in the early 1990s, growth slowed down, and so did investment. As the share of private consumption in GDP kept constant, it turned out that the brunt of the drop in absorption caused by the decline in aid was borne by investment and government recurrent expenditures.

The recent, more progressive surge of investment is a different story. First, growth accelerated in the 2000s, partly because of foreign financing and partly because of improving terms of trade. This triggered a rebound in investment. Second, the share of private consumption in GDP started to decline, thus providing space for additional investment expenditures. The economy then gradually settled into a new rather favourable kind of equilibrium, with an investment rate a little below 35 per cent of GDP and private consumption around 60 per cent, but also with a need for foreign financing to fund a level of absorption still above GDP.

There are several explanations for the decline of the average household propensity to consume that permitted the sharp increase in investment. The first is the change in the share of agriculture in total income. The propensity to consume is known to be higher from agricultural income, if only through subsistence farmers consuming most of their own produce. As seen earlier, the share of agriculture in GDP fell drastically at the turn of the millennium, thus bringing about a drop in the average propensity to consume in the economy.Footnote 6 In addition, the propensity to consume has likely decreased owing to various other causes, including an increase in taxation in the early 2000s, a slower inflation of consumption prices relative to the GDP deflator, and rising income inequality, as will be discussed later.

In view of the decomposition of changes in labour productivity in the preceding section, one may ask whether the evolution of the investment share in GDP is consistent with it, and thus check the role of capital accumulation as a key determinant of Tanzanian growth. Interestingly, the profile of the investment ratio over time explains why growth has long been driven essentially by structural change while within-sector productivity was falling, a feature that changed only during the last decade. Indeed, the slow pace of capital accumulation observed before the late 2000s was barely enough to cover more than the capital needs arising from depreciation, demographic growth, and the extra capital required to equip the net flow of agricultural workers moving to higher productivity and therefore more capital-intensive sectors. This explains why no gain was recorded in within-sector productivity in earlier periods. As the investment rate rose, a threshold was then passed such that the investment rate is able not only to cover all these needs but also to increase the capita–labour ratio, and therefore productivity within sectors of production. Apparently, the threshold was passed in the late 2000s, before the investment rate reached a plateau at around 35 per cent of GDP. Growth proved to be the result of both structural change and within-sector productivity gains.Footnote 7

This rather favourable evolution nevertheless leaves open the question of whether these productivity gains are efficient or whether the pace of capital formation would allow for faster gains. Answering this would require a detailed analysis of the conditions of production sector by sector, even though the World Bank enterprise surveys suggest several common factors that limit productivity, such as insufficient and irregular power supply or the lack of skilled manpower. A rough calculation shows that the observed average productivity gain across sectors in the 2007–18 period could probably have been substantially higher in view of existing estimates of the productivity of capital.Footnote 8

Not only the volume but also the composition of investment matters for growth. In this respect, the low level of the stock of infrastructure in Tanzania needs to be emphasised. In most enterprise surveys, managers report the low volume and quality of infrastructure as one of the factors that most constrain production and competitiveness. This is particularly true in the field of electricity, Tanzania being among the countries where the consumption of electricity is the lowest in the world. But this is also true of port facilities and the road network. Efforts are being made, as can be seen from the surge of the construction sector over the last two decades, but needs are huge.

If it proves possible to maintain such a high volume of investment as the present one, the prospects of the Tanzanian economy would seem promising. Two downsides must be mentioned, however. First, this requires that external funding remains available. It can be seen in Figure 2.2 that, even though lower than in the early 1990s, the absorption rate is still above 100, which means that the economy relies on foreign financing to cover part of its expenditure. This need was on average around 8 per cent of GDP over the last ten years. Second, outlets for production from new private investments must be available, which raises again the issue of the nature of the growth engine. This is not granted if growth is mostly demand-driven, as suggested earlier for the last two decades, unless the source of growing income behind demand has some permanence. If this is not the case, the high level of investment and growth can only be maintained through an expansion of tradable sectors and progress being achieved in terms of international competitiveness. This is the issue we now turn to while focusing on external trade.

A External Trade

The evolution of trade between Tanzania and the rest of the world has been extremely variable over time. Data series for foreign trade since independence do not seem very reliable, nor do they always fit national accounts. What seems certain is that the share of exports in GDP was around 30 per cent at the time of independence and had practically collapsed by the time of the dramatic balance of payment crisis that triggered the SAP in the mid-1980s. It was then as low as 5 per cent to a large part because of a dramatic drop in the production of export crops. It had recovered a little by 1990, and then exports surged for a short while before falling sharply again, in both instances mostly for climatic reasons and fluctuations in international prices.Footnote 9 They have gradually regained lost ground since the turn of the millennium and seem to have now stabilised at around 20 per cent or so over the last years. Yet their composition was drastically modified, with traditional exports crops losing weight in favour of mining and, to a lesser extent, manufacturing products.

Notwithstanding these fluctuations, and taking the late 1990s as a point of departure, exports have been extremely dynamic over the last twenty years, to such an extent that they may have been a significant contributor to the overall growth of the economy during that period. If their volume has grown on average only slightly faster than GDP, their unit value has significantly increased both with respect to imports – as can be seen from the terms of trade graph in Figure 2.3 – and domestic goods. As exported and domestically consumed goods and services can rarely be substituted for each other, exports have directly contributed to the growth of overall production roughly in the same proportion as their share in GDP, that is around 13 per cent over the last two decades. However, because of very favourable terms of trade – a 40 per cent increase since 2000 according to Figure 2.3 – they raised the purchasing power of the economy and exerted positive pressure on growth through the domestic demand side of the domestic economy. These effects are part of the implicit demand-driven component of recent growth mentioned earlier in this chapter when reviewing growth performances and their determinants.

Figure 2.3 Foreign trade and terms of trade, 1990–2019 (shares of GDP or 2010 based indices)

Note: The real effective exchange rate is defined as the ratio of the price of domestic over foreign goods. It is obtained by dividing the consumer price index in Tanzania by the product of the exchange rate (in Tanzanian Shillings per dollar) and the mean GDP deflator of partner countries. Trade partners were identified by the mean share of merchandise exports and imports across the two sub-periods 1997–9 and 2013–15. Only partners with shares above 2 per cent were considered. The resulting list of countries is, in order of importance, India, South Africa, China, Kenya, Japan, UK, Saudi Arabia, Germany, UAE, Switzerland, Netherlands, USA, and Belgium

Source: Author’s calculation from World Development Indicators (see figure note)

The overall growth of exports hides a substantial diversification of exported products. Figure 2.4 shows that merchandise exports were essentially agricultural products in the mid-1990s and, as such, subject to fluctuations in climatic conditions as well as price variations in international markets. In a few years in the early 2000s, mineral exports and especially gold and precious stones became dominant, with a share of total exports slightly above half. Agricultural products now represent less than 20 per cent, less than manufacturing products. For both groups of products, it should be noted that present trends may be stronger than it appears in the chart. In 2018, gold exports have been negatively affected by a ban agreed by the government of Tanzania, which was accusing foreign mining companies of cheating on the gold content of exported auriferous sand, whereas agricultural exports suffered from a row between the government and foreign buyers of cashew nuts whose price was found too low. The 2019 figures may not be completely back to normal.

Figure 2.4 Composition of merchandise exports, 1995–2019 (shares of total)

Source: Calculation from Bank of Tanzania annual reports (1995–2019)

The manufacturing sector has also been a driver of export growth. Its share in merchandise exports doubled in the last fifteen years and now represents a fifth of total exports. It was mentioned that the growth of the manufacturing sector being faster than of GDP could mean that an increasing share of its output was directed towards foreign markets or was substituting imports. Figure 2.4 confirms this view on the export side. It is also quite striking that the surge in manufacturing exports coincided with a steady and strong real depreciation of the currency – see the real exchange rate chart in Figure 2.3.Footnote 10 After a big depreciation in the early 1990s followed by an equally rapid re-appreciation, the real effective exchange rate declined continuously between 1998 and 2006, at roughly 4 per cent a year. That simultaneity between manufacturing export growth and the real exchange rate fits the view famously put forward by Rodrik (Reference Quah2008) about the favourable development impact of the undervaluation of the local currency on development.Footnote 11 Tanzania could thus be another example of the favourable consequences of currency undervaluation on industrialisation and growth, although it might be better to refer in this case to a move away from overvaluation rather than an undervaluation strategy. Note also that the argument does not apply to mineral exports, whose price is set on international markets rather than by domestic production costs.

The preceding remarks refer to merchandise exports, thus ignoring exports of services. The latter represent between 50 and 60 per cent of merchandise exports, and no noticeable change has taken place in this ratio over the last two decades or so. Service exports primarily include transports of goods between landlocked neighbour countries and domestic seaports, and, most importantly, tourism receipts. If they contributed to the dynamism of exports in the early 2000s, the latter have now stabilised and represent a little more than 4 per cent of GDP.

There is no doubt that the development of exports, particularly during the 2000s, largely contributed to the growth performances of the Tanzanian economy. The issue, however, is whether such a dynamism is sustainable in the long run. Commodity exports, mineral or agricultural, are determined by foreign demand and their price is set on international markets. Their revenue is thus uncertain, even though the relative diversification of Tanzania’s commodity exports attenuates that uncertainty. The same can be said of the transport services that depend on the trade activity of neighbouring countries – a business likely to increase within a few years with the completion of the railway link with Rwanda and Burundi. Overall, then, the manufacturing and tourism sectors represent the only truly autonomous factors of growth. They are also labour-intensive, unlike other non-agricultural exports, a key issue for the inclusiveness of growth, especially in view of the fast population increase. As seen earlier, however, they are presently too limited – roughly 6 per cent of GDP altogether – to be a real growth engine of the Tanzanian economy.

One word must be said about the huge offshore resources of natural gas discovered in Tanzania since 2011. The dependency on foreign prices is at its strongest here since projects are currently on hold in view of international liquefied natural gas (LNG) prices being much lower than the estimated cost of extraction.Footnote 12 Estimates of potential revenues vary depending on the expected overall cost of extraction. Revenues amounting to 1.2 to 1.5 per cent of GDP seem reasonable estimates.Footnote 13 Of course, this would be a real bonus for Tanzania and might be managed without too much negative spill-over of the ‘natural resource curse’ type. However, it is unlikely to drastically change the long-run economic prospects of the country either.

Another factor that may have contributed to the dynamism of Tanzanian exports that is worth emphasising is the change in the relative weight of destination countries. Exports towards China have surged over the last two decades, reflecting both the expansion of China as a trade partner of sub-Saharan Africa and the fast growth of its economy. But trade has also grown very fast with two African countries that have become major trade partners: Kenya, another member country of the East African Community, and South Africa, the dominant economic power of the region.

On the side of imports, the most noticeable fact over the preceding few decades has been their explosion in the early 1990s, when import licensing was almost completely abolished as a final step of the transition towards a market economy. They then fell against GDP partly because they were reverting to a more normal level and partly because of the real depreciation of the currency. Since the beginning of the century, the GDP share of imports has surged again under the pressure of accelerating growth, increasing investment, and a stable real exchange rate, before declining, possibly because of the real depreciation of the national currency over the last five years or so.

As far as the composition of imports is concerned, the most noticeable change is the sizeable drop that has occurred in the share of consumer goods – from 36 per cent in 2000 to around 25 per cent in 2016. It may result from two circumstances: the drop in the share of private consumption in GDP and the real depreciation of the currency. It is unlikely that the former can explain all the observed drop, so some import substitution has probably taken place,Footnote 14 which might have reinforced the impact of exports on the development of the domestic manufacturing sector.

Trade policy in Tanzania is constrained by its simultaneous membership in the East Africa Community (EAC), in the South African Development Community, and the Common Market for the Eastern and Southern Africa. The most developed agreement is with the EAC. It includes free trade among members (Burundi, Kenya, Rwanda Tanzania, and Uganda) as well as a common external tariff; yet some freedom is left to members to depart from common tariffs through ‘stays of application’ or duty remission on imported intermediate products. It turns out that the number of such exceptions has swelled over recent years in Tanzania. According to a recent report, it increased from 7 in 2011 to 100 in 2018, mostly being aimed at protecting domestic production and encouraging exports – through duty remission.Footnote 15 This may be another explanation of the slowing down of imports over the recent years. On the other hand, the rent-seeking aspect of some of these trade measures should not be ignored. For instance, such a suspicion of corruption has arisen with respect to the 100 per cent tariff on sugar imports.Footnote 16

It is fair to say that the value of imports is structurally higher than export revenues in Tanzania, which is another aspect of absorption being higher than GDP or domestic savings not covering investment expenditures. The deficit reached alarmingly high levels at the time of the liberalisation of imports at the turn of the 1990s, and when exports had not yet fully recovered from their collapse during the crisis of the 1980s. It was still high until a few years ago, averaging more than 10 per cent of GDP between 2005 and 2015. It has got close to zero over the last few years, but it is still too early to know whether this is the result of structural changes, temporary policies, or favourable trade circumstances.

B The Financing of the Economy and the Key Role of Foreign Aid

A thorough appraisal of the way Tanzanian development has been financed over time is a difficult task because of the lack of mutual consistency of the data sources to be used – that is, national accounts, balance of payments, and general government accounts – and, sometimes, the lack of time consistency within some of these sources, an example being the recent change of base in national accounting. It is only recently that it has become possible to make these various sources mutually consistent. Results appear in Table 2.3, which shows the evolution of key indicators since 2010 on a three-year average basis.Footnote 17 Inconsistencies are still apparent when comparing the ‘total’ row in the foreign financing section of the table with overall needs for funds in the domestic section. The former exceeds the latter in 2010–12, which seems odd, even though not impossible. Fortunately, the discrepancy is limited.

Table 2.3 The financing of the Tanzanian economy, 2010–18

(% of GDP, period averages) Period2010–122013–152016–18
Domestic flows
Domestic savings22.323.830.5
Central government−0.80.24.0
Private sectorFootnote b23.123.626.5
Gross fixed capital formation33.133.035.8
General government6.34.56.3
Private sectorFootnote b26.828.529.5
Need for funding10.89.25.3
Government: deficit excluding current foreign grants7.14.32.3
(Deficit including current foreign grants)4.23.01.6
Private sectorFootnote b3.74.93.0
Foreign financing
Primary and secondary income in current accountFootnote c−0.9−0.6−0.9
Official development assistance7.86.14.6
Foreign direct investment4.63.51.7
Foreign inflows accounted for11.59.05.5
Outstanding debt28.730.333.2
Of which
Public and publicly guaranteed18.321.022.9
Other10.49.310.3

a Government account indicators are defined over the fiscal year from 01/07 to 30/06; accordingly, GDP, savings and investment figures have been transformed into 2-years averages for consistency

b Including non-government public entities

c Excluding foreign grants included in Official Development Assistance

Source: Author’s calculation from IMF, Government Accounts and Balance of payments data in annual reports of the Bank of Tanzania.

The very acute need of the Tanzanian economy for foreign financing was already apparent in the absorption figures shown in Figure 2.2. By definition, the gap between this aggregate indicator and GDP is the overall need of the economy for external funding. It averaged 13 per cent of GDP in the 1990s, but this average hid a strongly declining trend that even reached zero for a short while in the early 2000s. Since then, however, the need for external funding has increased again, and was still around 10 per cent in the mid 2010s. Table 2.3 shows that it then halved thanks to a noticeable increase in the domestic saving rate, but the question arises whether this change is permanent or results from specific circumstances.

A second noticeable feature of the table is the difference between the public and the private sector. In the early years of the 2020s, as practically all the time during the one or two decades before, the main financing difficulty of the Tanzanian economy clearly arose in the government. Its current savings, that is the difference between its current revenue and recurrent expenditures, were negative or close to zero. In other words, government revenues barely covered current spending, so that all public investments, and often more, had to be financed by foreign or domestic private agents. The reason for such a state of affairs was not so much because of abnormally high recurrent expenditures, but rather the relatively low tax revenues. With an average tax/GDP ratio of around 11 per cent, Tanzania lies behind all East African countries and substantially below the average sub-Saharan country.

It is only in the last few years that the government has adopted a more rigorous fiscal policy consisting of a slight increase in revenues, not more than half a percentage point of GDP, though, and a pronounced drop in current expenditures – a little more than 2 per cent of GDP. This has allowed the government to cover a substantial share of public infrastructure investments and to significantly reduce its budget deficit. Yet the social cost of the cut that took place in recurrent spending should not be ignored. If it was not fully compensated by efficiency gains, it must have affected some services delivered to the population.

On the foreign financing side, most of the funding needs of the Tanzanian economy are covered by foreign aid. Although its volume declined substantially with respect to GDP, it remains substantial, and the sign of a high degree of dependency on foreign donors. At a little less than 5 per cent of GDP, today’s volume of aid represents a quarter of the government’s budget.

Given its importance, the ambiguity of the role of ODA in the development of the Tanzanian economy must be stressed. Tanzania may need foreign aid to provide basic public services and infrastructure, but it may also be the case that it is the availability of foreign aid that has led in the past to low savings and inefficiency in the public sector as well as to price distortions, through ‘Dutch disease’ effects,Footnote 18 as the ongoing debate on aid effectiveness emphasises.Footnote 19 It is difficult to analyse in detail the causality relationship between foreign aid and the need for external funds or the trade deficit because of very special past circumstances. These comprise the whole transitional period towards a market economy when donors provided resources the economy could not produce, or donors’ debt relief policies directed towards so-called Highly Indebted Poor Countries from the late 1990s to the mid-2000s. In Tanzania, as in most other poor countries, aid flows observed during this period include debt service moratoria and debt cancelling operations that do not bear much relationship to the actual funding needs of these countries.

If these problems have largely disappeared in the recent period, the issue arises of the meaning of the concomitance between the recent drop in trade deficit – and the need for external funds- and in ODA, as observed in Table 2.3. For some time, there have been talks among donors about progressively reducing aid flows to Tanzania, the present volume being often held up as a possible hindrance to the autonomous development of the country. In several instances, the Tanzanian government has openly concurred with such a view. There may thus have been something like a tacit agreement between donors and the Tanzanian government that aid flows need to be scaled down, with the latter correctly anticipating this trend and making policy decisions to adjust to this situation. It may also be the case that the reduction in foreign aid flows is the consequence of various crises during which donors have effectively put off disbursements or reduced their commitments because of major corruption scandals involving the government. This occurred in 2014 after the USD 180 million escrow scandal, in which an escrow account at the Central Bank was unlawfully emptied, itself the last episode of the Richmond scandal that a few years before had involved an overcharging private power provider and caused the resignation of several members of the government, including the prime minister. More recently, donors have threatened again to hold onto aid disbursements because of what they saw as violations of human rights by the government. Domestic policies behind the observed drop in external funding needs, including reining in public spending and letting the currency devalue in real terms, may be a kind of response to these repeated frictions with donors.

Several episodes of severe tensions between Tanzanian governments and donors have taken place in the past that could have led to a rupture. One took place at the end of the socialist period at the middle of an acute macroeconomic crisis when Nyerere was resisting the IMF’s conventional and potentially socially costly adjustment measures. After a few years of tension, other donors finally imposed their view that transformative reforms were needed. Another crisis developed in the mid-1990s. On one side were the donors, exasperated by various corruption affairs, the ineffectiveness of financial management, and the lack of results of the programmes they were financing. On the other side, the Tanzanian government was complaining about the cost of dealing with all the monitoring procedures imposed by donors and its lack of autonomy in deciding the use to be made of aid. A special commission appointed by the Danish aid agency wrote a report with inventive suggestions about reforming the cooperation between the Tanzanian government and donors. This largely anticipated reforms that would become current practice in the development community a few years later, including part of aid being provided as general budget support, and therefore at the full discretion of the recipient country.Footnote 20

Remembering these episodes is important because it shows how important foreign aid and donors have been in the development of Tanzania, practically since independence. By and large, aid may have been the engine of growth that seems to be missing in the domestic economy. By allowing investment to gain 5 to 10 per cent of GDP, it may have been responsible for two to four additional percentage points of annual growth. However, such a high volume of aid may also have had negative effects on other aspects of the economy, whether on savings, the efficiency of government machinery, the degree of corruption, or the democratic functioning of society – as forcefully argued by authors such as Easterly (Reference de Janvry, Gonzalez-Navarro and Sadoulet2006) and Deaton (2013).Footnote 21 The volume of aid soon recovered its pre-crisis level after both the crises just mentioned, so that, even though modalities had changed, the country somehow remained as aid-dependent as before, at least in terms of a large part of capital accumulation that was directly or indirectly financed by aid. Now that a trend has appeared that tends to lessen this dependency, the question arises whether the policies meant to address this new situation, including the drop in recurrent expenditure, is sustainable. In any case, at close to 5 per cent of GDP, foreign aid remains sizeable and a pillar of Tanzanian economic growth.

Foreign direct investment is another source of investment funding. It amounts to roughly a sixth of the overall capital formation. As a percentage of GDP, it has been roughly constant until recently. The drop observed during the last few years may only be the reaction of foreign investors to the dispute alluded to earlier between the Tanzanian government and a gold mining company, and more generally to the suspicious attitude of that government towards foreign companies. The new government seems to have a more friendly attitude towards foreign companies. It should be noted, though, that direct investments in Tanzania are heavily concentrated in mining, a sector less transparent to domestic authorities than manufacturing, which accounts for only 15 per cent of foreign investments.Footnote 22

It would be wrong to consider that Tanzania’s increasing indebtedness results from a gap between the needs for external funds on the one hand and foreign aid and direct investment on the other. As illustrated in Table 2.3 indebtedness has increased since the mid-2010s despite funding needs being almost exactly met by aid and direct investments. The point here is that foreign aid comes under the form of grants and concessional loans, with the latter contributing to increasing the level of debt. The Highly Indebted Poor Countries initiative permitted to reduce Tanzania’s debt to 22 per cent of GDP by 2006. It gone up to 33 per cent by 2018, with practically all that increase concentrated in the public and publicly guaranteed debt. It has further increased since then. Concessional loans contribute to reducing the debt burden but their share seem to be falling.

III Summarising the Determinants of and Constraints to Growth

Many other aspects of economic development in Tanzania could be analysed, including monetary policies, taxation, infrastructure capital, and social sectors. The latter will be considered explicitly in the second part of this chapter. The others will be dealt in one way or another in subsequent chapters. At this stage, however, it is useful to summarise what has been learned from the preceding review about the determinants of and constraints to economic development in Tanzania.

The main conclusion is without any doubt the uncertainty that bears upon what could be a sustainable engine of growth in the Tanzanian economy. Growth has taken place, and substantially so, but it seems to have been more demand driven than resulting from the autonomous development of a few sectors oriented towards export or import substitution. It is true that exports have been a driving force for a while in the last two decades, but this has in large part been thanks to mining, especially gold, and thus has been highly dependent on foreign demand and world prices. Manufacturing exports have also played a role, but a minor one, and the whole sector is still too small to be a true driver of development. Instead of an autonomous supply side drive, it thus seems that it is domestic demand, pulled by purchasing power increases arising from gains in terms of trade and foreign aid, that have fed growth throughout the economy, especially in sectors highly dependent on public spending and investment.

This situation raises an issue of autonomy and sustainability in Tanzanian economic development. Dependency on foreign demand for commodities, on prices on international markets, and on foreign aid is the opposite of truly autonomous development that would result mostly from efforts by domestic agents to expand production through enhanced productivity and competitiveness. The present development strategy is in some senses passive. This does not mean that domestic agents lack dynamism, only that they mostly respond to domestic demand stimuli that often originate outside national borders. This model may not be sustainable if drastic changes take place within the foreign context, such as a lasting contraction of commodity prices or a further reduction of foreign aid. In addition, the mineral natural resources exported by Tanzania will be depleted in the foreseeable future: gold reserves, for instance, represent only thirty years of current exports.

Overall, Tanzania has done well in productively exploiting favourable opportunities that have arisen in its foreign environment. It may now be time to consider a more autonomous strategy, and it is the task of subsequent chapters to reflect on the institutional factors that may influence or constrain this choice. However, the present review of Tanzania’s development achievements and challenges would be incomplete without an examination of its social aspects, in particular its inclusiveness.

IV Some Social Aspects of Tanzanian Development

This review of the main features and evolution of the Tanzanian economy has essentially been conducted at the macro-level. It is now time to see what has happened at the level of individual households and the extent to which the overall progress of the economy has been reflected in individual welfare. Three dimensions of welfare are briefly reviewed in what follows: income poverty and inequality, education, and health.

A Poverty and Inequality

Figure 2.5 presents some summary statistics on poverty, inequality, and household consumption expenditure as estimated in the five national Household Budget Surveys (HBS) taken since 1990 and compares them with relevant national account indicators. Two sets of poverty headcount estimates, both based on the HBS, are shown. The National Bureau of Statistics (NBS) uses a poverty line based on the value of the food basket consumed by the poorest half of the population deflated by the share taken by food in the budget of these households. The poverty line is updated from one survey to the next through specific food price indices – which differ substantially from the consumer price index (CPI) or the deflator of consumption expenditure in national accounts. The methodology to compute the poverty line and even to collect data on the consumption of food products seems to have been changing over time, so there is some imprecision on the estimated evolution of poverty across the five surveys. The other set of estimates is taken from the World Bank Povcalnet database. It is based on the international poverty line, set to USD 1.9 per person – at 2011 purchasing power parity – and per day, and the same household survey sources as the NBS but made comparable over time through the CPI.Footnote 23

Figure 2.5 Consumption per capita, poverty and inequality, 1991–2017

Source: HBS (since 1990), NBS data (1991–2017), World Bank Povcalnet database (1991–2017)

According to the NBS estimates, the proportion of poor people in Tanzania has regularly declined over the last thirty years or so, even though the estimated drop is anything but impressive in view of the change that took place in GDP per capita or even household consumption per capita. Indeed, the poverty headcount fell from 39 per cent in 1991 to 26 per cent in 2017, whereas GDP per capita nearly doubled, an elasticity much lower than commonly observed. The picture painted by the World Bank estimates is quite different. First, the poverty headcount is approximately double, reflecting a discrepancy between the two sources in the definition of the poverty line. Second, poverty would have surged, rather than slowly declined, between 1991 and 2001. Accordingly, the acceleration of growth in the 2000s would have caused a sizeable drop in poverty from 2001 to 2007. The drop is still sizeable between 2007 and 2011, but no significant change has occurred since then.

Clearly, the 2001 estimate by the World Bank is wrong and inconsistent with other data sources such as consumption per capita as recorded in the national accounts. It is thus better to ignore it – as is done with the dashed line in Figure 2.5. After 2001, the two sets of estimates show a roughly consistent evolution of poverty given their implicit difference in the poverty line and the resulting value of the headcount.Footnote 24 Both show an elasticity of poverty with respect to GDP per capita around unity for the 2001–11 period, an order of magnitude commonly found in sub-Saharan countries.Footnote 25 However, things seem to have changed over the recent period, since both sources show some stickiness of the poverty headcount between 2011 and 2017 despite sizeable growth of GDP per capita. It is also reported that poverty might even have slightly increased in urban areas (World Bank, 2019a, p. 7).

The main conclusion to be drawn from this discussion of poverty estimates, besides the need for more clarity in the way the poverty line is set, is that there seems to be a real challenge in Tanzania in transforming GDP growth into poverty reduction. In other words, growth has not been inclusive enough over the last twenty-five years, this being especially the case in the recent past.Footnote 26

This conclusion is reinforced by the observed change in the degree of inequality of distribution of per capita household expenditure. Figure 2.5 shows an increasing trend in the Gini coefficient, the most usual measure of inequality, since the early 1990s, although a short-lived reversal seems to have taken place between 2007 and 2011 – which, coincides with the acceleration of poverty reduction noted in Figure 2.5. Over recent years, however, inequality has reverted to its previous rising trend. Even though Tanzania’s level of inequality would probably stand below average by sub-Saharan African standards, the change that has taken place since the early 1990s is far from negligible. Economic development in Tanzania has favoured relatively more the upper part of per capita consumption scale, especially the top decile. Decile shares available in the Povcalnet database suggest that as much as two-thirds of the increase in consumption expenditures of the whole population went to the top 10 per cent. This is twice its share of total consumption. Such a situation would quickly become worrying if it were to last.

As an important footnote to the preceding discussion of inequality, it must be stressed that the inequality of consumption expenditures as recorded in household surveys is most likely underestimated. People at the very top of the distribution of living standards are unlikely to be covered in HBS, and if they were, they would most likely under-report their expenditures. Moreover, inequality of consumption expenditures is known to be substantially lower than income inequality. In the case of Tanzania, the huge discrepancy between the growth of GDP and that of consumption expenditures in the national accounts – see Figure 2.2 – suggests that the difference may be quite significant. In addition, incomes from illegal activities or corruption, judged to be substantial, escape measurement. This is where the most important source of inequality may lie, and it may have a sizeable impact on the economy overall depending on the use made of it by those to whom it accrues. Unfortunately, not much is known about it and about its evolution over time.Footnote 27

B Education

The educational level of the population has enormously progressed in Tanzania, as in the rest of the sub-Saharan African region over the last two or three decades. According to the Barro-Lee database, the mean number of years of schooling in the adult population has increased from less than four years in 1990 to six and a half today. Likewise, the proportion of the population without education and who were therefore illiterate was around 15 per cent by 2015,Footnote 28 down from 27 per cent in 2000. The mean number of years of schooling has followed the sub-Saharan average, whereas the proportion of adults without education is lower in Tanzania.

If human capital in a country were measured by the number of years of education of its whole population, then it would have grown at roughly 4.5 per cent since the beginning of the millennium, less than GDP and less than the physical capital stock, but enough to contribute to productivity gains. However, looking at the performances of the education system today leads to a more nuanced view about the efforts made in the country to improve its stock of human capital.

On this account, Tanzania does not seem to be doing that well. With respect to education, the recently developed Human Capital Index by the World Bank ranks it in the bottom 10 per cent of countries ordered by increasing ‘expected years of schooling’ and ‘learning-adjusted years of schooling’.Footnote 29 However, this does not mean that no effort is being made in the country to improve the coverage of its schooling system; quite the contrary. The difficulty would rather seem to lie in the quality of the schooling system.

As in the whole sub-Saharan region, primary school enrolment has made huge progress in Tanzania, although with pronounced fluctuations and a somewhat surprising reversal over the last few years. As can be seen in Figure 2.6, enrolment increased very rapidly after independence before receding at the time of the macroeconomic crisis and adjustments in the 1980s, and then stagnating for the next ten years. It then surged again with the launch of the ‘Education for All’ programme under the aegis of UNESCO and the UN’s Millennium Development Goals initiative in the early 2000s. This major increase in enrolment, which resulted from the international initiatives just mentioned, and also from Tanzania’s economic recovery as well as policies such as the abolishment of tuition fees, could not be sustained. After having practically become universal in the mid-2000s, enrolment had fallen back by twenty percentage points by 2015, a drop possibly underestimated according to Joshi and Gaddis (2015, p. 2). Since then, the situation has somewhat improved, but the gross enrolment rate is just below 100 per cent, whereas universal enrolment would imply a rate above that threshold: net enrolment has not recovered.Footnote 30 This trend is confirmed by the direct observation of school attendance in the national household surveys taken by the NBS.

Figure 2.6 Primary and secondary school enrolment (gross and net) in Tanzania and the sub-Saharan region, 1970–2015 (per cent)

Source: UNESCO, WDI and NBS

The progress in secondary education has been steadier, although Tanzania is lagging behind regional averages. Enrolment increased from 5 per cent in 1990 to 31 per cent in 2010. Since then, it has stagnated, after sliding a bit in 2015, as for primary. Furthermore, the gap with respect to the sub-Saharan region has become larger, although a kind of plateau seems to have been reached there too.

Pre-primary schooling has also made rapid progress, and Tanzania is ahead of other African countries. Yet high enrolment rates may hide low quality. The pupil to qualified teacher ratio at pre-primary level is reported to be as high as 169:1 in public schools (UNICEF, 2017). The consequence is that most children enter primary school in unfavourable conditions, owing either to a lack of, or poor, pre-primary facilities.

Quality is also found to be low, and deteriorating, in both primary and secondary schooling. Joshi and Gaddis (2015) report that the pass rate of the primary school leaving examination went down from close to 70 per cent in 2006 to 30 per cent in 2012. The deterioration is even worse for secondary schooling, as the pass rate for the Secondary Education Examination fell from 90 to 30 per cent over the same period (Joshi and Gaddis, 2015, Figure 1.1). The deterioration is already noticeable in the first grades. Only 10 per cent of grade three students can read a grade two story in Kiswahili, and only 30 per cent have mastered grade two numeracy. In addition, this low average performance hides a high level of disparity across geographic regions and social backgrounds.

Even though Tanzania does better than most other east and southern African countries in the educational achievement tests conducted under the Southern and Eastern Africa Consortium for Monitoring Educational Quality, the drop in performance is worrying. At primary level, a possible cause may be the overcrowding of schools, partly due to the surge in enrolment in the early 2000s. The average number of pupils per teacher in primary schools closely followed the enrolment rate. It went from 45:1 in 2004 to 58:1 in 2007. The number of students per classroom increased accordingly. It is thus no surprise that the quality of schooling worsened during that period and that parents were disincentivised to send their children to schools that they knew were overcrowded (Ponera et al., 2011). However, another cause of low and falling performances in both primary and secondary schools is teacher absenteeism. Surprise inspections suggest that one out of four teachers is not in school when supposed to be there, and more than half of teachers are not in the classroom when they should be teaching. It has been estimated that students in primary school are taught for 2.4 hours a day on average, instead of the scheduled five hours. As can be expected, all these ratios are much worse in rural than in urban areas (Wane and Gaddis, Reference Van Arkadie2015). Teacher absenteeism has apparently gone down since 2010, but it remains extremely high.Footnote 31

As diagnostics for the educational sector date back to 2015, things may have changed for the better. Yet changes are known to be slow in this area. On the other hand, some indicators may have worsened. For instance, the number of primary education teachers is reported to have reduced by 5 per cent since 2016, whereas the population of children has increased by around 10 per cent. On average, the number of pupils per teacher might have increased by 15 per cent over recent years.Footnote 32

There is most likely a direct relationship between the observed drop in primary enrolment and the deterioration in the quality of schooling, with the relationship self-reinforcing over time. Primary school overcrowding and the subsequent lowering of school quality may have disincentivised parents, as mentioned earlier, but overcrowding itself and the lack of resources in general may have disincentivised teachers, causing a further drop in quality.

A possible cause of that evolution may be the recent drop in the share of public expenditures from GDP. It was already the case that education’s share in the budget had fallen by the mid-2010s, even though it was still increasing in real terms. It is too early to say, but this might not be the case in recent years, thanks to the recent tightening of expenditure, thus aggravating existing constraints on progress in the public delivery of educational services.

C Health Care

The diagnostic of the healthcare sector in Tanzania is mixed. On the one hand, some input and outcome indicators show satisfactory results, while others have evolved less favourably. On the other hand, a recent evaluation suggests important quality issues in health care delivery. In addition, the funding of the sector strongly relies on foreign assistance, and this shows no sign of decline.

Figure 2.7 shows various indicators that illustrate the contrasting performances of the health sector. Under-five mortality has undoubtedly made considerable progress since the turn of the millennium, most likely in connection with the launch of the Millennium Development Goals. This indicator went down from 148 for 1990–5 to 67 in 2010–15.Footnote 33 Thus, Tanzania was very close to achieving Millennium Development Goal number four, which was to reduce infant mortality by two-thirds between 1990 and 2015. Present trends also seem promising in view of the third Sustainable Development Goal, which requires reducing under-five mortality below twenty-five per thousand.

Figure 2.7 Some health care indicators in Tanzania and sub-Saharan Africa, 1990–2018

Source: WDI and Tanzania Demographic and Health Survey (DHS)

It is not coincidental that the fast drop in infant mortality after 1995 took place at the same time as health care expenditure per capita was growing at an accelerated pace. What is more surprising, however, is the sudden pause in that progression and the stagnation of both public and total health care spending after a small drop in 2010,Footnote 34 a stagnation that might be related to the slowing down of progress on the child mortality front. Over the last ten years or so, the share of health expenditures in GDP has fallen, a trend that can also be observed more recently at the regional level. The gap between Tanzania and the average sub-Saharan country in real health care expenditure is striking. The fact that it essentially comes from private spending may suggest a deficit in health care infrastructure, including professionals, needed for the private provision of health care.

With essentially a flat long-run trend, the evolution of maternal mortality is less satisfactory than child mortality.Footnote 35 This seems to contradict the substantial increase documented in the Tanzanian Demographic and Health Survey in skilled delivery assistance as part of the Strategic Plan to Accelerate Reduction in Maternal, Neonatal and Child Deaths launched by the Ministry of Health and Social Security in 2008 (United Republic of Tanzania, 2016b, p. 172).

This last observation suggests that there may be some skill deficit in the provision of health care. It is not clear whether this may apply to maternal mortality, but the 2014 Health Service Delivery report by the World Bank points to such weaknesses when concluding that the ‘major challenge for Tanzania’s health sector is the shortage of skilled human resources for health’ (World Bank, 2014a, p. 9). The report also insists on possible gains in efficiency through increasing the caseloads of health personnel, currently low by international standards, and reducing absenteeism, although, at 14 per cent, it is much less pronounced than in the education sector.

On the financing side, a major cause of concern is the importance of foreign assistance. The share of expenditure financed by external sources has averaged 45 per cent since 2006, which suggests a serious problem of sustainability in the long run. If progress in health outcomes is to continue at the same pace as in previous years, funding will have to keep increasing faster than GDP, unlike what is being observed today. More funding will thus be needed domestically. This might come from the higher formalisation of the economy, leading to more people being covered by health insurance programmes paid for by employers through the National Social Security Fund, or, in the informal sector, from expanding the coverage of the Community Health Fund, a voluntary insurance programme. However, it is unlikely that with a premium of less than USD 10 per household and per year, the latter could become a significant source of funds for the health care system, especially given its complex decentralised governance. Further progress in health care will have to come from more resources being made available at central government level or through the cross-subsidising of health care in the informal sector by the health insurance system in the formal sector.

This expansion of health care funding and service provision is still more necessary given that large disparities are observed in most health indicators between geographical areas and, within areas, between households with different socio-economic characteristics. From that point of view, the cheapest progress in health care in Tanzania may come from extensive rather than intensive strategies – in other words, more people being covered rather than more risks being covered.

V Conclusion: The Main Economic Challenges of Tanzanian Development

Tanzania started its independent existence with considerable economic dynamism, until it was hit on the one hand by the consequence of an ill-prepared transition towards socialism, which made the economy increasingly inefficient, and, on the other hand, by the global development crisis of the early 1980s. There followed a long and painful period of slow growth, caused by a grim international economic environment and a difficult adjustment back to a market economy. The growth acceleration observed over the last twenty years is all the more spectacular. At the current rate of growth, GDP per capita will double in twenty years, and the country has just graduated from the low-income tier of World Bank classification to become a middle-income country.

This does not mean there is no cause for concern about the long-run sustainability of the present pace and structure of economic growth. The main challenges identified throughout this chapter are listed next, before they are compared to former diagnostics about Tanzanian development, and finally a few remarks on the likely consequences of the COVID-19 crisis that recently affected Tanzania, as the rest of the world.

A Main Causes for Concern about Tanzanian Development

The first cause for concern is the uncertainty about what could be Tanzania’s long-run engine of growth. To a large extent, growth during the last two decades has been pushed by the demand side of the economy, itself relying on increasing export revenues and foreign financing. Such a model is quite different from the industrialisation model that has been experienced over the last few decades in Asia, or in Latin America in the 1960s and 1970s. To be sure, the Tanzanian manufacturing sector has not underperformed; it has even been able to significantly expand exports and substitute some imports. The problem is that it is presently too small to pull the economy forward thanks to its sole area of development. Although manufacturing exports have done well, they remain a minor fraction of total exports, and it is the other fraction that has driven recent growth. The problem is that this component is essentially exogenous, depending on international prices and the foreign level of activity, and is therefore unable to feed a pace of growth faster than that of the global economy. More is needed for Tanzania to continue reducing its income gap with the rest of the world. On the other hand, circumstances may become less favourable than they have been since the turn of the millennium. A priori, there are fewer external constraints in manufacturing, agroindustry, or tradable services such as tourism. How to enhance their development?

A second cause for concern is how to sustain and, more importantly, to enhance the within-sector productivity gains observed in the last decade or so. Maintaining the investment rate at a 35 per cent level is a challenge in itself. At the same time, there are indications that such a high rate of capital formation may not be fully exploited. Moreover, there may be untapped efficiency gains that could improve productivity and competitiveness. Agriculture, for instance, has often been mentioned as under-performing in comparison with other countries in the region and the continent,Footnote 36 possibly because the difficulty in establishing firm land rights disincentivises innovation and investment.

The third source of concern may be the most serious one. It is the strong dependency of the Tanzanian economy upon foreign financing. It is true that, for several reasons, the gap between absorption and national revenue has been scaled down in recent years. However, it is not clear whether this is due to domestic structural factors and policymaking or to decisions made by foreign donors. In any case, even during recent years, dependency has remained high. Excluding foreign grants, the deficit of the current account was still above 4 per cent of GDP on average between 2015 and 2020. ODA itself still represented more than 5 per cent of GDP over the same period, a little more than a quarter of the government budget and practically all of the public investment in infrastructure. What would happen if, for some geopolitical reason or unexpected development, this flow was to dry up? It is most unlikely that the current growth trend could be maintained.

An important unknown for the economic development of Tanzania is what will happen with its offshore natural gas reserves. These are sizeable and could provide Tanzania with substantial additional revenues for the twenty to thirty years after a five-year investment period. This would require that the international price of gas stays at a much higher level than observed throughout the 2010s. It has been seen that extraction costs are high. At this stage, it is therefore not clear whether the discovery of these reserves truly modifies the prospects of the Tanzanian economy in the reasonably near future.

A final source of concern is on the social side. Poverty is receding slowly, certainly more slowly than if the real income or consumption expenditure of all households was growing at the same rate as GDP per capita. That growth has not trickled down more systematically to all segments of the population since its acceleration at the turn of the millennium is a problem, and a challenge for the future. The reason why growth has not been inclusive lately is unclear, but action should be taken so this situation does not persist. Increasing inequality may indeed have adverse effects on future development through the demand side of the economy, by reducing the aggregate propensity to consume, and more fundamentally by undermining the social and political climate. The same applies to the stagnation of school enrolment below universal enrolment in primary school and the low quality of the educational system in general, which may put future growth, poverty reduction, and the social equilibrium at risk. More is to be done to ensure more inclusive growth and more dynamic investment in human capital.

The preceding review of the economic development challenges faced by Tanzania was essentially factual. Little was said of policy choices or the behaviour of major economic actors. Only the consequences of their actions, rather than their decisions and their behaviour, were analysed. The way in which the economic decision makers, public or private, interact and generate specific economic outcomes, including obstacles to development, depends on the complex set of rules that govern these interactions. These rules constitute the institutional framework in which development takes place. Beyond the pure economic facts reviewed in this chapter, a deeper analysis of development challenges thus requires identification of the institutional challenges causing them. This will be the task of the rest of this volume.

B Convergence with Former Diagnostics of Tanzania’s Development

Several former attempts have been made in the last ten years to diagnose the main obstacles to faster economic growth in Tanzania, so it is worth checking whether they agree with the analysis in this chapter, even though the latter relies on more recent data.

A first diagnostic was undertaken in 2010 under the auspices of both the Government of Tanzania and the US government, the latter as part of the Partnership for Growth initiative (Partnership for Growth, 2011), following the methodology proposed by Hausman et al. (2005). It subsequently influenced the reflection about national development strategies, including the ‘Vision 2025’ report.

A similar, although more focused, exercise was undertaken two years later by the Organisation for Economic Co-operation and Development (OECD) as part of its ‘Investment Policies Reviews’ aimed at recommending measures to improve the investment climate and attract more foreign investors (OECD, Reference Nyerere2013).

Finally, a more recent study is the World Bank ‘Systematic Country Diagnostic’, entitled ‘To the next level of development’, completed in February 2017. This document comprises a review of Tanzania’s development since the mid-2000s similar to the one undertaken in this chapter. However, because it relies on data that do not go beyond 2015 and in some cases stop before then, it misses some important recent changes, especially with respect to the evolution of productivity, poverty, and income distribution.

Overall, the diagnostics brought forward by these various studies are convergent and very much overlap with the analysis in the present chapter. Yet their main objective is to identify possible economic and, in some cases, institutional bottlenecks for development rather than more structural factors that slow down or threaten future development as attempted earlier in this chapter. Institutional issues and some of the bottlenecks pinpointed in these growth diagnostic studies will be considered in more detail later in this volume. For further reference, however, the priority policy areas they single out are the following – with the agency supporting them noted in brackets:

  • infrastructure, especially power supply and spatial integration (United States–Government of Tanzania, OECD, World Bank);

  • lack of vocational, technical, and professional skills (United States–Government of Tanzania, OECD, World Bank);

  • appropriability of returns: insecurity of land rights (United States–Government of Tanzania, OECD), high and volatile tax rates (OECD);

  • lack of access to finance for small and medium-sized enterprises (SMEs) and agriculture (United States–Government of Tanzania, OECD, World Bank);

  • disorganised regulation of business (OECD);

  • low quality of civil service and delivery of public goods (World Bank);

  • weak institutional capacity to manage natural resources (World Bank);

  • mobilisation of government revenues (World Bank).

C The COVID-19 Crisis in Tanzania

Clearly, the recent past has been very much influenced by the COVID-19 crisis, and this is why the review in this chapter stopped before 2020. Because it may influence future development, a word must be said about its impact on the economy and the population.

It is difficult to get a clear idea about the health impact of COVID-19 in Tanzania because of the denial of the existence of such a pandemic by the then president, John Magufuli. As soon as May 2020, President Magufuli lifted the few restrictions initially set on public gatherings, schools, and universities, and declared the nation free of COVID-19. He eschewed lockdowns, discouraged the use of face masks, and banned the release of infection data. Information about the spread of the pandemic was tightly controlled. Talking publicly about signs of the pandemic, as for instance the rising frequency of burials, was strictly prohibited.

It is unclear why President Magufuli adopted such a posture and went as far as advising sick people to go to church to be cured. He always wanted to appear as a man who was inflexible about work and did not take sickness as an excuse. A few days before getting sick himself, he inaugurated a new road in Dar es Salaam, and congratulated the contractor and the workers for completing the work in time and for ‘no-one [having] used corona as an excuse to delay it’. His government had become more and more authoritarian over time, and he handled what he saw as essentially a distraction from work for the whole population in the same imperious way he handled other affairs that he thought could threaten the country’s development. Of course, such an attitude denotes a worrying denial of reality and a complete lack of a sense of responsibility, which indeed characterised some aspects of management throughout his mandate.

Meanwhile, hospitals were crowded and were rejecting patients, oxygen was becoming scarce, and funeral announcements were multiplied by three to four times. Several high-ranked politicians or policymakers are known to have died from COVID-19, including the author of one of the chapters in this volume. President Magufuli himself died in March 2021 officially from a heart attack, but many suspect this was COVID-19. He was replaced by the vice president, Samia Suluhu Hassan, who immediately reverted to an open and effective treatment of the pandemic.

Estimates of the impact of COVID-19 in Tanzania are still imprecise. According to (still provisional) national accounts, GDP growth receded to 2 per cent in 2019 from roughly 6 per cent in the preceding years. The order of magnitude of the economic cost of the pandemic would thus have been around 4 per cent of GDP. Such a recession meant that GDP per capita went down for the first time since the 1990s. At less than 1 per cent, the drop is limited, though. It is lower than in other sub-Saharan countries that imposed severe lockdown on their population. In Rwanda, for instance, GDP is estimated to have fallen by as much as 3.5 per cent. At the same time, the health casualties may have been lower there than in Tanzania, precisely because of the measures taken to prevent the spreading of the virus. Without reasonable estimates for Tanzania, it is difficult to say.

The 2020 slowdown in GDP was caused by a drop in traditional exports and tourism owing to the COVID-19 crisis in the rest of the world, and also because of precautionary behaviour by the population in light of the diffusion of the virus – and possibly some proportion of the population being infected and becoming temporarily sick. During June and July 2020, the World Bank ran a survey covering 1,000 SMEs to measure the impact of the pandemic. It was found that as much as 140,000 formal jobs, or roughly 5 per cent of total formal employment, were lost, whereas 2.2 non-farm informal workers, roughly one-third, suffered income losses. However, it is difficult to go from such observations at one point in time to estimates of the overall impact of the crisis upon poverty. Estimates have been circulated according to which the poverty headcount went from 26.1 per cent in 2019 to 27.2 per cent at the end of 2020.Footnote 37

As far as the future is concerned, GDP growth is forecast to be around 4 per cent in 2021, below the trend over the last ten years or so. Huge vaccination efforts are presently being made and improvements in health services are being implemented to increase the capacity of the system to deal with possible new waves of infection. Tanzania was also provided with emergency loans by the IMF and is expecting more aid from other donors to address the consequences of the COVID-19 crisis. This makes the prospects for 2022 look a bit more favourable.

3 Gathering Evidence on the Quality of Institutions

François Bourguignon and François Libois

The objective of this chapter is to collect insights from different sources and different people about institutional features that may slow down economic development in Tanzania or threaten its sustainability and inclusiveness.

It essentially follows three approaches, and these are presented in separate sections. First, by exploiting the numerous institutional indicators available in international databases, insights were collected about the quality of Tanzanian institutions in comparison with a set of relevant countries. Insights aim to identify those institutional features that may possibly differentiate Tanzania. Second, an original questionnaire survey was undertaken among various types of decision makers operating in Tanzania. The survey asked them about their own perception of how institutions worked there and how they affect development. Finally, the analysis was enriched by the summary of the main points that arose in a large set of open-ended interviews with top policymakers of the country about the same questions. The final section concludes.

I Institutional Indicators: How ‘Different’ Is Tanzania among Developing Countries?

The development community has long known that institutions matter for development, and several country-level indicators describing various aspects of institutions, especially those that have to do with governance, have developed over time. They are meant to facilitate cross-country comparisons and to correlate, in a rough way and most often on a cross-sectional basis, institutional or governance quality with growth or other development indicators. Many such international databases now exist. They either focus on a specific institutional area – democracy, corruption, ease of doing business – or cover a wide range of themes. The Worldwide Governance Indicators (WGI) provide synthetic indicators obtained from extracting from these datasets some common factors in pre-defined institutional areas.Footnote 1

Quantitative indicators reported in these cross-country datasets generally reflect expert opinion on some specific aspect of institutions in a country. They may not coincide with the way people within a country perceive them. This is the reason why this analysis of the specificity of Tanzania in the space of cross-country institutional indicators is extended to more specialised and more pragmatically oriented databases that are not included in the WGI. This is the case of the World Bank enterprise surveys that collect the opinion of firm managers or the African Barometer, which surveys the public on some more focused institutional issues.

A How Different Is Tanzania Using the Synthetic WGI?

Figure 3.1 compares Tanzania with two sets of comparator countries and according to the six synthetic indicators present in the WGI database for 2018. The six indicators refer to the following institution-related areas: ‘Control of corruption’, ‘Government effectiveness’, ‘Political stability and lack of violence’, ‘Regulatory quality’, ‘Rule of Law’, and ‘Voice and accountability’. Comparator countries are of two types:

  • Neighbour countries may share a close history, similar environmental conditions, comparative advantages, or political and economic organisations. The issue is thus whether such a common background does exist and, most importantly, whether Tanzania departs in any way from it, or on the contrary conforms with it. This group includes the East African community (Burundi, Kenya, Rwanda, Uganda), to which we add three countries on the southern border of Tanzania (Malawi, Mozambique, and Zambia).Footnote 2

  • Another natural set of comparators are those countries that were at the same level of development, as measured by gross domestic product (GDP) per capita, as Tanzania twenty or thirty years ago and have done better since. These outperforming peer countries are all in Asia: Bangladesh, Lao and Vietnam have gained between 60 and 150 per cent in GDP per capita over Tanzania since 1990, and Cambodia substantially less (30 per cent). The issue is whether these outperformers present institutional features significantly different from Tanzania, which might explain their better performance or be a consequence of faster growth.

Before discussing the charts shown in Figure 3.1, a word must be said about the WGI database and the way these indicators are measured. As mentioned, each synthetic indicator results from the combination of those individual indicators in the original datasets that belong to each institutional area being considered – corruption, regulation, rule of law, and so on. Synthetic indicators thus capture the common information in the underlying set of individual indicators; that is, how they differ across countries. They are normalised with mean zero and unit standard deviation. As their distribution across countries is not far from being normal, their value, between −2 and +2, indicates where a country ranks in the global ordering according to a particular synthetic indicator. Roughly speaking, 0 would correspond to the median and −.5, around which most countries in Figure 3.1 tend to concentrate, would roughly correspond to the third decile from the bottom. Thus, most countries in the figure are in the middle part of the lower half of the global ranking – which comprises more than 200 countries.

Figure 3.1a WGI: Tanzania and neighbour countries, 2018

Figure 3.1b WGI: Tanzania and outperforming peer countries, 2018

A striking feature of Tanzania, taken in isolation, is the relative balance that is observed among the various indicators. If it were not for ‘government effectiveness’, its radar chart would be an almost perfect regular hexagon. An obvious conclusion is thus that most institutional areas described by the WGI in Tanzania are weak by international standards – that is, at the limit of the bottom third of the global ranking – but government effectiveness is a bit weaker than the others.

The comparison of Tanzania with neighbour countries shows both convergence and divergence. On the one hand, there are clearly two outliers in the region: Burundi with uniformly extremely weak WGI scores and, at the other extreme, Rwanda with scores high enough to reach the sixtieth global percentile in all institutional dimensions but ‘voice and accountability’, a clear reflection of its rather autocratic but otherwise effective leadership regime. On the other hand, Tanzania’s institutional profile turns out to be very similar to that of the other countries in the region. In Figure 3.1, Tanzania generally lies in the middle of the range defined by its neighbours – Uganda, Kenya, Mozambique, Malawi – in all areas except the control of corruption, where it apparently does less badly. Overall, if it were not for the very peculiar institutional quality profile of Burundi and Rwanda, two countries deeply marked, in opposite directions, by what has probably been the most tragic ethnic conflict in the history of the African continent, the left-hand chart of Figure 3.1 would suggest a rather homogeneous and moderately weak institutional quality profile for Tanzania and the Eastern Africa region.

When comparing Tanzania with outperforming peer countries on the right-hand panel of Figure 3.1, four features are noticeable: (1) the superiority of Tanzania over all countries in ‘voice and accountability’ and, to a lesser degree, the ‘control of corruption’; (2) the neat dominance of Vietnam in all other dimensions; (3) the relative disadvantage of Tanzania in the area of political stability – which is a bit surprising given precisely the stability of its democracy until quite recently; and (4) the similarity between Tanzania and other better performing countries in other areas. The main point, however, is that, despite those outperforming countries having grown considerably faster than Tanzania from the late 1980s to the mid-2010s, no strong differences seem to be present in their institutional quality profile, except for the superiority of Tanzania on the democratic front and the outstanding performance of Vietnam. Therefore, with the exception of the latter, growth does not seem to have brought a significant institutional advantage to the other outperformers. It is striking that Tanzania even dominates Bangladesh in all areas.

One could object to the preceding comparison with the outperforming peers that it should be carried out not in the most recent period but in the past, when income per capita in those countries was actually overtaking Tanzania’s. Figure 3.2 is the equivalent of Figure 3.1 for 2005. On the basis of the right-hand panel, it certainly cannot be said that outperformers were institutionally dominating Tanzania; it might even have been the contrary. However, what is striking is that, when comparing 2005 with 2018, all outperformers have substantially improved the quality of their institutions whereas little has changed in Tanzania, except for a slight improvement in the control of corruption, most likely the result of President Magufuli’s anti-corruption campaign, and a more sizeable worsening of government effectiveness. Faster growth among outperformers is thus associated with institutional improvement over time rather than some initial institutional advantage, which is an interesting observation.

Figure 3.2a WGI: Tanzania and neighbour countries, 2005

Figure 3.2b WGI: Tanzania and outperforming peer countries, 2005

The same can be said of the comparison between the left-hand panel of Figures 3.1 and 3.2. It appears there that neighbour countries in general have witnessed some improvement in the quality of their institutions, whereas this is not the case of Tanzania. As a matter of fact, it is noticeable that Tanzania practically dominated Burundi, Kenya, Rwanda, and Uganda in almost all areas in 2005, whereas it only dominates Burundi in 2018. It can thus be said that, in relative terms with respect to its neighbours and outperforming peers, the quality of institutions in Tanzania has somewhat deteriorated – except in the control of corruption – even though its ranking in the international scale may not have significantly changed.

B Exploring Alternative Synthetic Indicators

The conclusions from the comparison of WGI between Tanzania and comparator countries are interesting, and should somehow contribute to the institutional diagnostic of Tanzania: relative homogeneity of institutional quality at a low-middle international level across WGI areas, convergence with neighbour countries except Burundi and Rwanda, progress in the control of corruption, which may turn out to be less of a problem than in most comparator countries, less political stability but more democracy than outperforming peer countries, and limited improvement of institutional quality over time with respect to comparator countries. Yet the issue arises whether these conclusions may depend on the specificity of WGI synthetic indicators, in particular the way they are obtained from a variety of individual indicators and the fact that they are defined across the whole range of world nations.

Because of the growing interest in the relationship between development and institutions, many databases have been put together over the last few decades that rely on expert opinion to compare the quality of institutions across countries and in many different areas, be it the Polity IV database on the functioning of political institutions, Transparency International on corruption, Reporters without Borders on freedom of speech, the World Economic Forum Competitiveness index, the Bertelsmann Foundation Transformation Index, or Varieties of Democracy, to quote a few. As mentioned earlier, the WGI provides a statistical summary of those individual indicators found in a collection of these datasets, which presumably are related to each of the six areas that are considered in the WGI database. But even though they clearly make intuitive sense, do these areas provide the best analytical structure to study the relationship between institutions and development? Why not other areas, maybe more political or sociological, or possibly sub-areas?

The other question is whether a statistical summary based on the heterogeneity observed among all countries in the world is the best instrument to study the way institutions may affect the development process among countries at an early stage of economic development. Differences in institutional quality between advanced countries and low-income countries may not be of much relevance when trying to understand how institutions may be an obstacle to reach lower-middle income status. Would the synthetic WGI in the six institutional areas defined in that database be the same if they had been built on a sample of developing countries only?

To answer these questions, the Institutional Diagnostic Project has explored a set of alternative indicators based on developing countries and endogenously defined institutional areas. These are based on the Quality of Government (QoG) database managed at the University of Goteborg, which functions as a kind of repository of all databases gathering expert opinion in institutional areas (Teorell et al., Reference Sutton and Olomi2022). They boast today more than 2,000 individual indicators covering more than seventy years and most countries of the world, even though, of course, not all indicators are available for every year and every country – very far from it. Only a subset of developing countries and indicators were selected so as to avoid missing data and to strictly focus on institutional characteristics. As a result, the size of the country sample and the set of individual indicators were severely reduced, even when working on a single year.Footnote 3

Instead of predefining categories of individual indicators related to a single theme such as the control of corruption or the rule of law in the WGI database, a statistical procedure was used to regroup individual indicators by their informational proximity, or more precisely by their capacity to rank countries in roughly comparable order, while maximising the difference in rankings produced by distinct synthetic indicators. Each group or category of individual indicators is then summarised by a single synthetic indicator, in the same way as the synthetic WGI summarise all individual indicators behind ‘regulatory quality’ or ‘government effectiveness’. A statistical pseudo-cluster analysis permits us to endogenously define an arbitrary number of such categories with a methodology that is somehow equivalent to minimising the country-variability of individual indicators within categories and maximising differences between them.Footnote 4 To get a set of categories comparable with the WGI, it was arbitrarily decided to define six categories.Footnote 5

The novelty of this procedure lies in the statistical categorising of individual indicators based on how similar their variation across countries is, while not paying attention to what they represent. With the procedure used to summarise the informational content of all individual indicators in a category, the method extracts maximum information from the overall set of individual indicators in the database through a small arbitrary number of synthetic indicators.

The drawback of this methodology, compared with the WGI, is to make the labelling of categories less intuitive. As variables are grouped in an agnostic way, as a function of their informational content but not of their labelling, it may not be obvious a priori to find a common label. The intuition, however, is that, if the informational content across countries is similar, they must be related to some common institutional area. Experience shows that commonalities among indicators belonging to the same group are sufficient to encapsulate them under a single theme.

In our comparison of Tanzania with other countries, 160 individual indicators were selected from the QoG covering forty-five developing countries with no missing information. The preceding methodology was then applied to this subset of the QoG database, and resulted into six categories of individual indicators, each one being summarised by a synthetic indicator. Table 3.1 presents these six indicators, reporting the number of variables falling in each category and the common approximate theme they seem to cover. When needed, and to differentiate these indicators from the WGI, they will be labelled ‘QoG-DGC’ synthetic indicators (DGC for developing countries) in what follows.Footnote 6

Table 3.1 The six QoG-DGC synthetic indicators

GroupNumber of indicators in the QoG databaseLabel
G115Corruption
G220Administrative and regulatory capacity
G329Conflict and violence
G414Competitiveness (World Economic Forum)
G524Democracy and accountability
G656Voice and civil society

It is interesting that this purely statistical categorisation of indicators led to a grouping that is not very different from the a priori grouping used by the WGI mentioned earlier. Yet there are noticeable and interesting differences. For instance, administrative capacity – or government effectiveness – and regulatory capacity are now a single indicator, suggesting that both are somewhat correlated across the developing countries in the database. This was not the case with the WGI. The same is observed with the control of corruption and the rule of law, which are now amalgamated as the issue of corruption. On the opposite side, voice and accountability in WGI are now separated into ‘voice and civil society’ and ‘democracy and accountability’. ‘Voice and civil society’ groups variables with a societal content. ‘Democracy and accountability’ describes more specifically the way political institutions work.

Overall, it is rather satisfactory to see that the institutional areas thought to be important play an important role in differentiating developing countries, and also that nuances need to be introduced, which are not present in the a priori categorisation used in WGI. That it is difficult to distinguish corruption and the rule of law, or that it makes sense in developing countries to distinguish between the autonomy of civil society and individuals on the one hand, and indicators describing the functioning of the parliament or the relationship between the executive and the judiciary on the other are useful warnings when embarking on an institutional diagnostic of a country.

Figure 3.3 is the replica with QoG-DGC indicators of Figure 3.1 built around the WGI. Both charts refer to 2018, and it can be seen they are convergent. The same regularity among the six axes is observed for Tanzania with some more weakness in ‘administrative and regulatory capacity’. In the comparison with neighbour countries, Tanzania still dominates Burundi but is close to other countries, except Rwanda – excluding ‘civil society and voice’ – a feature that was already present in Figure 3.1. As before, Tanzania does better than all countries but Rwanda in the control of corruption. When compared with outperforming peer countries in the right-hand chart, Tanzania appears a bit stronger than in Figure 3.1. It dominates Bangladesh – as before – but still appears weaker than other countries with respect to administrative and regulatory capacity and conflict and violence. Thus, the conclusion obtained earlier that institutional quality in outperforming peer countries was not overwhelmingly above that of Tanzania, and that Tanzania clearly dominated in terms of political institutions – that is, ‘voice and accountability’ in Figure 3.1, ‘civil society and voice’ in Figure 3.3 – is maintained. The main difference lies in the evaluation of Vietnam, which is relatively less favourable with the QoG-DGC synthetic indicators.

Figure 3.3a QoG-DGC synthetic indicators: Tanzania versus neighbour countries

Figure 3.3b QoG-DGC synthetic indicators: Tanzania versus outperforming peer countries

In sum, the alternative set of synthetic indicators derived in the present study from the QoG database and focused on developing countries does not lead us to modify the conclusions obtained with the WGI. This is clearly a test of their robustness. In particular, it is remarkable that ignoring the differences between advanced and developing countries, which are likely to strongly structure the WGI, does not really modify the relative institutional profile of Tanzania when set against those of the comparator countries considered in the present study. One could have thought that some institutions would differ across countries mostly because of the gap between advanced and developing countries but that this would matter less among the latter. Corruption may be a case in point. It clearly matters a lot when examining differences among all countries, as it is much less acute among advanced countries. It was not necessarily expected to be a differentiating feature when restricting the comparison to developing countries. It possibly reflects the importance that experts behind individual indicators put on that specific institutional feature.

C Tanzanian Institutions According to Other Indicators

Individual indicators in the databases used to build synthetic institutional indicators often originate from experts who presumably have inside knowledge about the way institutions work in a country and are able to make cross-country comparisons. Views may be different among people who are more directly exposed to the functioning of a country’s institutions, as citizens or firm managers. As a complement to the preceding analysis of synthetic expert indicators, this section compares Tanzania with the same set of countries using two surveys that are representative of users of institutions: the World Bank Enterprise Survey,Footnote 7 and the Afrobarometer (for the sub-Saharan comparator countries).

World Bank Enterprise Survey

The Work Bank Enterprise Survey is a firm-level survey based on a representative sample of private firms, which collects the opinion of entrepreneurs on their working conditions and their daily experience with the institutional fabric of the country, including the government and public agencies. Their concerns are thus as much about the functioning of some particular institutions (law, regulation) as about the availability of key inputs or infrastructure. The survey asks, among other things, whether business owners and top managers identify a given topic as a major constraint.

Unlike the situation with the synthetic indicators reviewed earlier, the Tanzanian institutional context of firms is felt to be very constraining. Figure 3.4 shows how various areas are felt as more constraining by firms in the same set of countries as earlier. Firm managers in all neighbour countries but Burundi feel much less constrained than in Tanzania. Compared with outperforming peers, the difference is even more striking. Less than 15 per cent of firms feel constrained in those countries, except in Bangladesh where, as in Tanzania, corruption and electricity shortages appear to be a major constraint for more than half of the firms.

Figure 3.4a Perceived constraints in World Bank Enterprise Surveys: Tanzania versus neighbour countries

Figure 3.4b Perceived constraints in World Bank Enterprise Surveys: Tanzania versus outperforming peer countries

The perception of Tanzanian entrepreneurs, however, appears more negative than their actual experience. If corruption is reported as a major constraint by almost half of firms in Tanzania, only a fifth effectively experience the payment of bribes, a value substantially lower than the sub-Saharan average (a quarter) and lower than Burundi (almost a third), or Kenya and Malawi (around a quarter). The dimension in which Tanzania clearly underperforms is in the share of firms that expect to give gifts to secure contracts with the government. On this specific question, two-thirds of Tanzanian firms answer positively, much more than in neighbour countries but at a level comparable with Cambodia, Laos, and Vietnam. It suggests that in some contexts corruption is institutionalised in such a way that firms fully internalise it and do not perceive it as a constraint, while they are more perceptive in other contexts where corruption looks more like rent extraction.

The relatively pessimistic perception of firms in Tanzania and the contrast with their practical experience appear again in the relationship of firms with the tax administration. Senior Tanzanian managers report that, on average, they spend 2 per cent of their time dealing with the tax administration. This is below most of the comparator countries. Still, it translates into the worst perception of the tax administration compared with all other countries. The length of procedures may explain these differences. Interaction with public officials might not be that costly in monetary terms or in actual time spent, even if things do not move forward.

An interesting conclusion that comes from this brief review of the World Bank Enterprise Surveys in connection with the deeper analysis of synthetic institutional or governance indicators made earlier is that the context in which people assess the quality of their institutional environment matters. Experts may be right that, practically, corruption and rent-seeking in Tanzania tend to be milder than in other developing countries since Tanzanian entrepreneurs altogether seem to pay fewer bribes. Yet entrepreneurs may be more sensitive to the fact that some of them make such payments. Whether facts or perception matter more for development is an open question, but perception does drive actual behaviour, at least partially.

Afrobarometer

The Afrobarometer is a representative sample survey that aims to collect attitudes of African citizens towards democracy, governance, living conditions, civil society, and related topics. It is managed by a network of think-tanks in Africa and presently covers thirty-five countries.

When comparing Tanzania with neighbour countries,Footnote 8 the striking institutional feature observed in the 2012 wave of the Afrobarometer is doubtlessly the relative lack of trust of its citizens.Footnote 9 Tanzanians do not trust their governments very much, but they are also reluctant to trust their friends and relatives. They also report being dissatisfied with the functioning of their democracy, despite their democracy being stronger than elsewhere – as expert-based synthetic indicators analysed earlier strongly suggest.

Their comparatively limited trust of the state apparatus is surprisingly not related to major differences in how Tanzanians evaluate the performance of their government. If anything, Tanzanians are slightly more satisfied than their neighbours in terms of the delivery of public goods – education, health, possibly water. One potential explanation of this apparent contradiction may be a higher level of expectations. Independently of other considerations, it seems only natural to them that their government delivers in terms of public services.Footnote 10 This is surprisingly in stark contrast with neighbour countries.

Another factor correlated to the low level of trust in Tanzania is probably the perception of high-level corruption. A third of survey respondents think that most people in the office of the prime minister and the president were corrupt. This figure is two times lower in neighbouring countries, even accounting for the fact that Burundi pushes the average upwards. For members of parliament and government officials, Tanzania is ranked the highest in perception of corruption. Still, when people are asked about the actual corruption that they directly experience, the picture is more nuanced. Mozambique and Kenya show a lower frequency of bribes than Tanzania, whether it is to get documents, secure access to water, health, and education services, or to avoid trouble with the police, whereas the opposite is true of Uganda, Malawi, and Burundi. However, one type of side payment is three times more frequent in Tanzania than in neighbouring countries: it consists of compensatory gifts, whether food and money, in return for votes (27 per cent versus 9 per cent).

Tanzanians also express rather different views from their neighbours on democracy and the way it is supposed to work. Half of the surveyed people think that their country is not a democracy, or that it is a democracy with major problems. Again, these figures reflect the perception of citizens about their institutions and not the hard facts about how institutions work. They substantially differ from the expert opinion reviewed earlier and depend a lot on respondents’ reference points or hopes for their country. Still, digging further, Tanzanians also complain about not being able to say what they want (55 per cent in Tanzania versus 14 per cent in neighbouring countries) and not being free to join political organisations (69 per cent versus 10 per cent). More than two-thirds of Tanzanian citizens call for a more accountable government, even at the cost of slower political decisions.

As an intermediate conclusion, it is important to put these perceptions in perspective. Among the six neighbouring countries being compared, Tanzania ranks second in terms of GDP per capita (purchasing power parity corrected) and growth rate. If Kenya is slightly above Tanzania, the other four countries are way below. Despite this good relative performance, only one-fifth of Tanzanians assess the economic performance of their country as fairly good or very good, while one-third of the neighbouring populations do. Actually, Tanzanians may display a negative bias in making judgements about their country, an attitude that may reflect high expectations and not necessarily unsatisfactory achievements.

This bias is even more striking when comparing the 2012 and 2016 waves of the Afrobarometer. Abrupt changes are observed. The perception of corruption is then on a par with neighbour countries, if not below, whereas trust in the government and state apparatus rises above most neighbour countries. Of course, this sudden and abrupt change in perceptions should be taken with care – on the one hand because actual behaviour has not changed as much, and on the other hand because the 2016 Afrobarometer wave in Tanzania was clearly very much affected by the recent election of a rather disruptive candidate to the presidency on a rather aggressive anti-corruption platform. To conform with the focus of the present study on the pre-Magufuli period, the preceding discussion of the Afrobarometer results refer to the 2012 wave.

D Insights Gained by Comparing Tanzania with Other Countries

The main conclusion from the comparison of Tanzania with other countries is that Tanzania does not show any clear specificity in terms of institutional quality among neighbouring countries when obvious outlier comparators – that is, Burundi and Rwanda – are ignored. This conclusion has several possible explanations. One is that the indicators used in the comparison are too vague and too aggregate to show how specific the institutional landscape may be in a given country. More detailed indicators could show deeper differences, but, by their construction, they would refer to one, possibly limited, side of the landscape. The comparison with those countries that outperformed Tanzania’s growth does not show a clear institutional disadvantage of the latter in recent years. However, it is clearly the case that outperformers have been able to substantially improve their institutional quality in the last fifteen years – that is, between 2005 and 2018 – whereas Tanzania did not in any significant way. Neighbour countries also improved, albeit by less than outperformers – Rwanda being from that point of view a clear outlier.

Representative surveys conducted among firm managers and citizens yield additional insights. More than in the case of expert-based synthetic indicators, however, the problem of the reference point emerges when comparing countries. It is not clear whether differences between Tanzania and comparator countries are driven by intrinsic differences in institutional quality or by distinct reference points among respondents living in different environments. Both the World Bank Enterprise Survey and the Afrobarometer suggest that Tanzanians are more demanding of their formal institutions. This could ease up institutional reforms but does not say much about how constraining the quality of institutions may be for development.

A last remark is in order about the comparison exercise conducted in this section, in the spirit of so many studies of this kind. As already mentioned, the choice of comparator countries is crucial. Observed differences may possibly reveal a particular challenge in a country, which then needs deeper investigation. In the present case, however, care must be taken because comparator countries as well as Tanzania have in common an institutional context of relatively low quality. It is not because the control of corruptions is estimated to be slightly better in Tanzania than in the comparator countries used in the present analysis that corruption may not be detrimental to its development. In other words, the often-heard argument that corruption or another symptom of institutional deficiency ‘is as bad here than among neighbours or even outperformers’ in no way reduces their deleterious potential impact on development.

II The Country Institutional Survey: Tanzanian Decision Makers’ Opinions on Their Institutions

The Country Institutional Survey (CIS) is a sample survey tool developed as part of the Institutional Diagnostic Project.Footnote 11 It aims to identify institutional challenges as they are perceived by people most likely to confront them on a regular basis. Given its broad sample of respondents, CIS intends to yield more diverse views and deeper insights into the way institutions work than expert-based institutional indicators in international databases.

The pilot CIS, carried out in Tanzania in early 2017, targeted individuals who had been or were in a first- or second-tier decision-making position in business, public administration, academia, non-profit organisations, or local branches of development agencies. They daily interacted with Tanzanian institutions, and possibly also affected the way they functioned as part of their activity. They were thus expected to have a better knowledge of the country’s institutions, their strengths and weaknesses.

The remainder of this section is organised into six sub-sections. The first describes the design of the questionnaire. The second explains how the survey was implemented. Results are then discussed, with emphasis first on how development-constraining institutional areas are perceived by respondents in the third sub-section, and then on perceived specific institutional strengths and weaknesses in the fourth. The fifth sub-section is devoted to the way respondents see future institutional changes engineered by a disruptive president completing his first year in power. A final sub-section puts the survey in perspective and concludes.

A The Survey: Design of the Questionnaire

The questionnaire has four intertwined components: (1) the personal characteristics of the respondents; (2) institutional areas perceived as the most constraining for the development of Tanzania; (3) the perception of the functioning of institutions; and (4) current (at the time of the survey) institutional developments in the country.

The questionnaire first collects information about personal characteristics of the respondents, including nationality, gender, level of education, place of birth. In a final part, it gathers more sensitive information on the past and present occupation of respondents as well as on their political affinity.

The second section of the questionnaire enumerates ten broad institutional areas listed below in Table 3.2 and respondents were asked to select the three areas that, according to them, most constrain development in Tanzania. Respondents then had to allocate twenty points among these three areas – the higher the number of points, the more detrimental the area for development. The selected areas are important for the analysis but also for the subsequent part of the survey because they determined the set of questions presented to the respondent in the main part of the survey.

Table 3.2 Definition of institutional areas in the CIS survey

Institutional areaSub-areas
Political institutionsFunctioning of political institutions and political life; participation of the population; civil liberties; transparency and accountability; corruption; state capacity; interference of non-state organisations in policy making; recruitment of politicians
Law and order, justice, securityRule of law; functioning of the judicial system; protection of civil liberties; control of violence; supervision of public companies; business law and its implementation
Functioning of public administrationsState capacity; transparency of economic policies and reporting; corruption; public procurement; supervision of public companies; geographical coverage of public services; relationship with business sector; regulation; decentralisation
Ease of doing businessRelationship with public administration; privatisation; public procurement; price controls; competition regulation; foreign direct investments; functioning of the credit and capital markets; litigation procedures; labour market regulation; role of trade unions; recruitment of business leaders
Dealing with land rightsAccess to land for business purposes (urban and rural); role of local communities; role of public administration; security of property rights (or equivalent in view of the state property principle); conflict settlement and functioning of land courts
Long-term and strategic planningEx-ante and ex-post evaluation of policies; communication on economic policy; capacity to coordinate stakeholders; long-run and strategic vision of development; obstacles to public action; decentralisation
Market regulationCapacity to regulate market competition; regulation of utilities; regulation of foreign direct investments; regulation of the financial sector; regulation of the labour market; quality of the system of information on firms
Security of transactions and contractsSecurity of contracts and property rights; insolvency law; litigation procedures; business laws and business courts
Relating to the rest of the worldTrade openness; financial openness; relationship with neighbouring countries; attitude towards foreign direct investments; ease to start a business; land tenure security, relationship with donors;
Social cohesion, social protection and solidarityParticipation of population to policy debate; civil liberties; access to the justice system; sense of national identity, discrimination practices; geographical coverage of public services; instruments of social protection; traditional solidarity

The core section of the CIS comprises 345 questions on the perception of institutions. All rely on a Likert scale, ranging from ‘Not at all’ and ‘little’ to ‘moderately so’, ‘much’, and ‘very much’. Responses are then converted into discrete numbers, ranging from one to five, for the analysis. The questionnaire is inspired by the Institutional Profile Database (IPD), an expert survey conducted jointly by the Economic Services of the French Embassies, the Centre for Prospective Studies and International Information in Paris, and the University of Maastricht (Bertho, Reference Barrett, Mtana, Osaki and Rubagumya2013). The last wave of that survey taken in 2012 covered 143 countries in 2012. Respondents were staff members of the Economic Department of French Embassies or country offices of the French Agency for Development. The CIS questionnaire differs in several dimensions, mostly because many questions were adapted to the Tanzanian context. Yet about 40 per cent of the CIS questions remain similar to their IPD counterpart.

From a practical point of view, administering the whole questionnaire was not an option owing to its length. To shorten the time needed to complete the questionnaire, every question was associated with at least one of the ten general institutional areas in Table 3.2, and respondents were asked to answer only the questions related to the three institutional areas they selected in the previous step of the questionnaire, as well as questions related to a fourth area, randomly drawn from the remaining ones. This original feature of the questionnaire guaranteed that all institutional areas are at least partly covered at the end of the survey. In practice, respondents had to answer around half of all questions, as some questions appeared under several institutional areas.

Because the survey was taken only a year after the election of a new president whose mandate had been announced as rather disruptive, respondents were explicitly asked to answer the questionnaire as if no change had yet taken place in the institutional framework of the country. Enumerators were specifically trained to convey that message to the respondents. As institutions are persistent, there is little doubt that answers to the survey describe the way in which decision makers of various types in Tanzania perceived the institutional landscape that prevailed before the election of President Magufuli and the kind of influence it had exerted on the development path of the country.

Because of this potential disruption in some institutions or in the perception of them, a last section of the questionnaire was devoted to the most recent institutional changes. Respondents were asked to identify the questions to which they would have answered differently if they had been about the recent past or the near future of Tanzania. In this open-ended part of the questionnaire, respondents also had the possibility to mention institutional features that they thought were important for development and were not covered in the survey.

B Execution of the Survey

The Tanzania CIS survey was conducted between the end of January and early February 2017 in a collaborative effort between Institutional Diagnostic Project researchers, OPM, and REPOA, a Tanzanian think-tank. A total of 101 individuals were sampled in a purposively stratified sample aimed at collecting the views of people involved in, or in close contact with, institutions. Respondents had been or were in first- or second-tier positions in the decision-making structure of public, private, or civil society organisations. Their selection followed two steps.

First, survey designers defined sample strata in terms of occupation, position level, geographical constraints, and, tentatively, gender balance. By design, half of the sample were surveyed in Dar-es-Salaam, with the remaining half divided into five major cities: Dodoma, Morogoro, Mwanza, Mbeya, and Arusha. The sample also had to include a quarter of respondents from economic spheres, another quarter from the political sphere, a third quarter from the civil society in a broad sense, and the remaining quarter from various areas including the donor community, diplomats, the police and military forces, or the judiciary.Footnote 12 Note, however, that many respondents occupied other positions in the past and thus had experience in more than one area.

It must be stressed that the CIS survey sample design had no intention to be representative of any particular population, a fortiori of the whole population. From that point of view, it is not an opinion survey, as for instance the Afrobarometer could be. People with direct experience of the way institutions work in Tanzania were targeted, and a stratification was built in within that population so that a diversity of viewpoints could be obtained. The reason for that choice is that the goal of the CIS survey was to learn from the experience of people with knowledge of the state of institutions in Tanzania rather than what a majority of these people would think about the functioning of the judiciary or the work of the auditor general.

As we targeted top-tier decision makers, they turned out to be different from the standard profile in the whole population. They were older and more educated than the general population. A majority of respondents were in their forties, eighty of them had a university degree, while twenty-nine reported to have studied abroad. Almost all of them lived in urban areas, but half were born in rural areas. Even though not in the sample stratification procedure, political diversity was achieved: eighteen respondents declared a political affinity with the ruling party, seventeen with the opposition, and forty-five reported no political affinity.Footnote 13 Such a diversity is reassuring as it avoids excessively laudatory or critical views in questions addressing the role of the government.

C Critical Institutions for the Development of Tanzania

Figure 3.5 shows the institutional areas most frequently mentioned by respondents as constraining development. Institutions behind public administration came first and political institutions second. Business-related institutions were in third position. On the other side of the spectrum, only four respondents chose ‘security of transactions and contracts’, possibly because this area was considered to be more specific and technical than others. Similar conclusions are obtained when taking respondents’ weighting into account, yet political institutions then rank first.

Figure 3.5 Choice of institutional areas as most constraining for development

A framing bias could partially drive the ranking of the areas, with the first areas in the list appearing more often among the choices of respondents. Still, the allocation of the twenty points by respondents over the three selected field is less sensitive to this sorting as respondents have to focus on three fields only when they allocate the points. It has remarkably little effect on the ranking. Last but not least, qualitative insights collected in the preparation of the survey and described in the next section are very much in line with the current conclusions.

Critical area choices vary by the characteristics of respondents and yield contrasting stories. For instance, female respondents gave very little weight to political institutions, but they consider that social cohesion and protection, solidarity, and relations with the rest of the world matter more for development than do the male respondents. Political affinity also played a role, with respondents closer to the ruling party, CCM, emphasising the difficulties arising from land rights, while the opposition stressed the constraints related to political institutions and to the public administration.

The choice of the top three constraints to development, according to respondents’ opinions, is a piece of information in itself, but it also determines most of the questions asked of each respondent. Areas that were not chosen by many respondents may actually work well, or they may work imperfectly without constraining development. The fourth area, randomly selected among the remaining field and imposed upon the respondents, permits an examination of that issue. Indeed, the less critical institutional field, namely ‘security of transaction and contracts’, ended up being covered by a fifth of respondents. There is thus enough statistical power to understand why this area was considered as less critical by respondents.

D The Perceived Functioning of Institutions in Tanzania

Within and across areas, the CIS aimed to identify, as precisely as possible, which specific institutions were perceived as constraining by respondents. The subsequent analysis first evaluated questions by their mean response on a scale ranging from 1, ‘most negative’, to 5, ‘most positive’. For questions asked in a negative way, the Likert scale was inverted to make sure that a higher value always meant a better perception. Questions were then ranked according to the top weaknesses and strengths of Tanzanian institutions. The last part of the analysis explored the heterogeneity of answers across sub-samples and tried to determine whether the perception of institutional weaknesses was correlated with some salient characteristics of respondents.

As in many opinion surveys, there was a mass of answers around the central position, which may reflect the default choice of respondents if they were unsure about their position. It is therefore more relevant to look at the tails of the distribution, namely questions with clearly positive or negative answers. Forty-six questions – or 13 per cent of all questions – had an average score below 2.5, while only twenty-seven scored above 3.5.

An alternative to asking respondents which were the problematic institutional areas is to look at the proportion of low-score answers among all questions that fell under that area. This is equivalent to comparing the distribution of low-score answers by institutional area to the distribution of all questions as done in Figure 3.6.

Figure 3.6 Proportion of questions by institutional areas according to their average scores

The first part of the graph shows the distribution of all questions across the ten areas.Footnote 14 For instance, the first bar in Figure 3.6 shows that 15 per cent of the 345 questions of the CIS fall under ‘political institutions’. The first bar in the second group reports that 13 per cent of the forty-six questions with a score below 2.5 are related to political institutions. In the third group, which plots the distribution of questions with an average response above 3.5, 14.8 per cent of questions are part of the political institutions cluster. Not all areas exhibit such a balanced pattern, however. ‘Public administration’, ‘ease of doing business’, and ‘land rights’ are largely overrepresented among low scores, which suggests that they comprised relatively more obstacles to development than others. This conclusion agrees with the identification of critical areas in Figure 3.5. This is not the case for land rights, of which treatment was almost unanimously perceived as unsatisfactory. On the other side of the spectrum, the ‘social cohesion, social protection, and solidarity’ area represents 20 per cent of all questions, but only 4 per cent of low-scores and 48 per cent of high scores.

A closer look at the questions that collected the lowest average scores permits us to bring more precision to the identification of institutional weaknesses by respondents. In this perspective, issues related to land come at the forefront. What comes out of detailed questions is that land laws do not seem well understood at the local level, and at this level it is common to have operations outside the legal framework, with limited transparency, and eventually involving corruption. Respondents qualified land tenure as insecure, leading to frequent land disputes and eventually feeding open conflict. Overall, the unequal and fractionalised distribution of land was often found to be a constraint for development.

The second most cited negative item is corruption. This is thought to permeate many institutions of the country, whether at the political level or in the relations between the bureaucracy, the citizenry, and business. The delegation of missions by the state to public monopolies such as electricity production and distribution (the Tanzania Electric Supply Company, TANESCO) or natural resource extraction (gas) is found to be not very transparent. Corruption in the privatisation process of public companies that took place in the recent past is also denounced. Respondents estimated that transfer prices were too low and that promised gains in efficiency were not achieved. These points remain relevant in the current management of natural resources and respondents anticipated that they will be so in the future. On a smaller scale, the role of corruption in increasing the cost and the hardship of starting a business was also mentioned.

In the agricultural sector, respondents complained about low price levels and their volatility, which they imputed to the role of intermediaries. Access to physical and financial inputs was also felt as being restricted. Both were thought to constrain the development of the agricultural sector.

Other weak points reported are more scattered, including the absence of independent trade unions, the non-indexation of wages on inflation, the low prospect of university graduates getting a position in line with their training, and the dependence of Tanzania on foreign stakeholders.

Strengths are also worth mentioning. Respondents praised the limited discrimination based on geographical origin, religion, and ethnicity, for instance, in access to public services such as school and education. More generally, the sense of Tanzanian identity appeared to be quite strong. These positive statements should, however, be put into perspective. First, given the peculiar format of the questionnaire, less than a third of respondents had to answer these questions. Second, the risk of internal conflict based on regional differences, religion, or ethnic lines is nevertheless seen by respondents as moderately high, which seems somewhat contradictory. In a different perspective, respondents consistently emphasised the feeling of security. They were also satisfied that people were free to form associations of a varying nature, violence against political organisations was limited, and the executive had strong control over the police.

Although respondents complained about the role of foreign stakeholders, they underlined the positive role of foreign aid. It was widely recognised as a source of funding for infrastructure and a driver of improvements in the health and education sector. However, its impact on corruption was also emphasised.

At the grassroots level, respondents underscored the traditional solidarity links (family, neighbours, associations, religious organisations, etc.), which provide support to those in need, as well as the role of informal microfinance institutions such as rotating saving and credit associations. On the other hand, respondents were confident that formal social protection mechanisms, such as the Tanzania Social Action Fund, would act as a complement to rather than as a substitute for informal instruments.

Perceptions of institutions varied across groups of respondents, as evidenced by an analysis of the heterogeneity of answers. For instance, women, who, in our sample, disproportionally came from the civil society, criticised the Tanzanian state for discriminating along gender, religious, ethnic, and regional lines in terms of access to the judicial system, health care and administrative services. They were also more concerned about the influence of interest groups in the design of policies.

The same disaggregation was implemented in many subgroups. It yielded results that fitted expectations. Respondents who positioned themselves closer to the opposition party had rather negative perceptions about the independence of the judiciary, the army, and the police. They also felt civil liberties were restricted. Unsurprisingly, being close to the ruling party yielded opposite views. Respondents who studied abroad were more sensitive to matters related to trade and to the influence of foreign stakeholders in national policies. They perceived Tanzania as being very exposed to competition from foreign firms, whether from neighbouring countries, other developing countries, or advanced economies. They were also concerned by the fact that foreign firms, governments, and multilateral organisations are an obstacle to the implementation of autonomous policies and reforms.

Being involved in business raised the awareness of respondents about foreign firms having an easier time establishing themselves in Tanzania and gaining access to funds from local banks. Despite being active in the private sector, these respondents found that access to information about the ownership structure of large firms was quite difficult. Overall, business managers were rather pessimistic about the progress of the middle class and considered that networks were important for accessing top official positions, compared with merit-based promotion.

E Prospective Assessment of Institutional Changes

It should be kept in mind that the CIS survey intended to capture the perception of institutions as they operated during the five to ten years prior to the time of the survey, which was about one year after President Magufuli was sworn in with an ambitious reform programme, most importantly concerning corruption. The timing of the survey is therefore quite interesting for gaining some insights into the respondents’ anticipations about the new regime. At the end of the interview, respondents were thus asked how Tanzanian institutions had recently evolved and whether their answers to the questions on the core part of the questionnaire would have been different if reference had been made to the recent past or the near future of Tanzania. In total, 90 per cent of the respondents wished to express their opinion, even though in some cases very briefly.

As many as 28 respondents explicitly mentioned a fall in corruption and increased transparency and accountability as major recent changes in the Tanzanian institutional landscape. They explained that civil servants abided by the law more, and side payments and bribes had been drastically reduced. If questions had been about the recent past and not on a longer timeframe, most felt that corruption would probably be less frequently mentioned as a major institutional weakness.

A corollary of the reduction in corruption was the improvement of tax collection. Fifteen respondents said that the recent surge in tax collection efficiency would have changed the way they answered the core part of the survey. They felt that taxpayers had a harder time bypassing their tax duties. According to a few respondents, changes in tax collection had pushed some businesses into financial trouble. They mentioned that some firms had to close operations, that many of them faced liquidity constraints, and that it had become harder to make money. On the public spending side, more effective tax collection was viewed as raising the capacity of the state to accomplish its mission. It was expected that, combined with greater accountability, this would be a guarantee of better use of public resources. Eighteen respondents mentioned that public service provision was improving, especially in the dimensions related to education, health, and infrastructure. A few of them thought this was the result of a change in the work spirit of civil servants and would eventually lead to more equal coverage of public services, to less discrimination, and to less importance of social networks when applying for a position in the public service. Clearly, however, these perspectives of a more equal and meritocratic society were aspirations and hopes, rather than what respondents had already experienced. In effect, some respondents questioned the depth and sustainability of current changes, and whether they could alter the development path of the country.

These positive prospects were somewhat counterbalanced by concerns about the transparency and accountability of the new regime. More than 10 per cent of the sample explicitly pointed out that it had become hard to express views challenging the government, although free press, free media, and even free demonstrations were essential for the accountability and transparency of public affairs. The independence of the judiciary system was also mentioned as crucial for the credibility of the executive towards citizens and firms, a view that was not limited to respondents aligned with the opposition. Actually, several respondents expressed their fears that the new administration could depart from these principles. The risk of an autocratic drift was even mentioned in a few cases.

F Discussion and Conclusions

From the CIS, a broad consensus emerges pointing to several institutional challenges. As far as general institutional areas are concerned, the major concern is about political institutions, public administration, and the ease of doing business. The judiciary system comes just afterwards. Other areas are further down, but one may also consider that they are included in the areas at the top – for example, land right management may be covered by public administration and security of contracts by the judiciary. The problem here is that it is difficult to define institutional areas that do not overlap with each other. To a large extent, this difficulty is also present in the definition of synthetic institutional indicators. It is unavoidable when institutional areas are defined in too broad a way, but breaking them down would lead to a large number of sub-areas among which it would be difficult to decide which is more constraining than others for the development of the country.

As general as it is, the institutional decomposition used in the CIS survey and the ranking given by respondents is nevertheless instructive, even though it clearly requires further analysis to grasp its meaning and its implications. In a way, this will be done throughout the rest of this volume. At this stage, it is worth stressing the convergence of the CIS-survey and the analysis of synthetic indicators in pointing to administrative capacity as a major obstacle to faster development in Tanzania, and to the lack of competitiveness of the production sector that is potentially due to a suboptimal business environment.

Individual questions in the core part of the questionnaire yield more precise insights about respondents’ perception. Summarising them leads to the following list of consensual institutional challenges:

  • the management of land rights and, more generally, the allocation of land;

  • corruption at the level of both politics and the public administration;

  • the regulation of the economy, in particular of infrastructure;

  • the lack of transparency and accountability of the state.

Note that these challenges fit in their own way the ranking of broad institutional themes by respondents. Corruption, and the transparency and accountability of the state clearly affect how the functioning of both political institutions and the public administration are perceived. On their side, the management of land rights and the regulation of the economy also cut across broad themes such as public administration and the ease of doing business.

On the strength side, the survey again shows some consensus around the sense of national identity and security, which implicitly seems to point to political stability.

The open-ended discussion with the respondents at the end of the interview made it possible to check that the recommendation to complete the questionnaire bearing in mind the institutional Tanzanian context during the last five to ten years had been complied with. This did not prevent optimistic expectations and hopes about the way the new administration would address some of the preceding challenges.

Stepping back from the analysis of results, the question then arises of whether a survey which relies on the country’s political, economic, and social decision-making population leads to a different evaluation of institutional quality than the expert-based institutional indicators found in international databases. As a way of testing this, use has been made of the fact that many questions in the CIS overlap with the IPD questionnaire submitted to some French diplomats posted in Tanzania. Based on common questions between the two questionnaires, it is possible to measure the degree of correlation between the opinions of a sample of 100 economic, administrative, or academic actors in Tanzania and those of a few close foreign observers. There is some convergence between the two surveys, but it is very partial.

If we select the 130 questions that are identical in the CIS and the IPD, the correlation of answers between the two surveys is only 0.30.Footnote 15 On the same set of questions but within the CIS, the correlation between Tanzanian respondents and foreigners is also limited, reaching 0.5. This rather low degree of correlation, combined with the heterogeneity analysis, shows the importance of the identity of respondents to this type of survey. Many studies rely on few respondents per country, who often share a similar position in society. They have their own view of institutions, which may not be shared by Tanzanian or even other foreign diplomats active in Tanzania (the correlation between French diplomats and foreign respondents is only 0.22).

By enlarging the sample of respondents, the CIS survey is innovative and offers a more diverse view on institutions. Within broad areas, the CIS yields more precise answers on what is found to go wrong and for whom. Most importantly, it allows us to analyse the diversity of perceptions across population groups in the society, which is essential in interpreting sample averages. From that point of view, the Tanzanian experience suggests that a substantially larger sample of respondents would have yielded more precise estimates of cross-averages.

III Open-Ended Interviews with Top Decision Makers and Policymakers

In addition to formally surveying a large number of private and public decision makers and observers of political, social, and economic life in Tanzania, several experts, some of whom are or had been at the highest level of responsibility in the country, were also interviewed on an open-ended basis. They were not asked to complete a questionnaire, but were simply invited to share their thoughts about the binding institutional constraints in Tanzania. Other issues came up in the general discussion. The main points drawn from these interviews from the perspective of an institutional diagnostic of Tanzania are summarised after briefly introducing the respondents.

The experts who were interviewed were not representative of any specific population sub-group. They were simply people who, because of the responsibility they currently had, or had in the past, as political leaders, top civil servants, business executives, non-governmental organisation (NGO) directors, or researchers, had been led to deeply reflect on Tanzanian institutions, their potential role in slowing down economic development, and possible directions for reform. Yet, in approaching them, care was taken to have as much diversity of viewpoints as possible, either in terms of occupation – that is, the various occupations listed above – or in terms of perspectives on the Tanzanian economy – for example,. ruling party versus opposition. One may thus say that, taken together, the opinions of the personalities who were interviewed made up a sample of the way the various components of the elite think about the nature of Tanzanian institutions and their potential role in preventing faster development. It can be seen from the list of people who were interviewed – see appendix – that they were fairly diverse, from think-tank directors and academics, to leading business leaders, to personalities at the very top of the state hierarchy, including two past presidents, the Chief Justice and the Controller Auditor General at the time the study was completed.

The first question asked as an introduction to the discussion was: ‘In your opinion, which kind of institution, formal or informal, is preventing economic development in Tanzania from accelerating?’ Then an open, mostly informal, and definitely ‘off the record’ discussion followed, very much led by the person being interviewed. The following paragraphs offer a synthesis of what could be drawn from these very rich interviews for the present study. They cannot do justice to the richness of about fifty fascinating hours of discussion and the deep insights they provided for the pursuit of this institutional diagnostic exercise.

The four areas most intensively discussed directly or indirectly have to do with the management of the state and civil service. More precisely, they are: (1) the issue of corruption; (2) the functioning of the civil service, including the issue of decentralisation; (3) the regulation of public and private firms; and (4) land use rights. All these areas are closely related, as it can be seen that corruption is the natural consequence, and at the same time the cause, of a dysfunctional bureaucracy and/or badly coordinated regulations. Likewise, it is the multiplicity of regulations and laws that makes civil service inefficient. Finally, the management of land use rights, which was almost systematically cited as a major obstacle to development – both in agriculture and in urban areas – may be taken as a good example of the effect of weak capacity and corruption in some parts of the bureaucracy and a partial understanding of a well-crafted but complex law.

Three other general institutional areas were stressed, but with less frequency and less strength, by the personalities being interviewed. The first one was the issue of political checks and balances, or more generally the actual functioning of the political system; the second one was the mindset of the population, including that of the public bureaucracy; the final one was the capacity and functioning of the judiciary system.

Corruption was uniformly seen as both a widespread evil and a fundamentally deleterious factor for development in Tanzania, even though the point was sometimes made that Tanzania is not necessarily worse than its neighbours in East Africa or even than better performing countries in terms of economic growth. However, corruption undoubtedly plays an important role in public opinion and is a central issue in election times. As was explained in Chapter 1, it arose around the end of the socialist era and grew more rapidly under President Mwinyi’s mandate at the time of the transition towards a market economy. President Mkapa was elected on the basis of an anti-corruption platform and commissioned Judge Warioba to produce a report on corruption, which revealed how widespread it was and proposed some corrective measures. Yet major corruption scandals have taken place during each presidential mandate ever since President Mwinyi. President Magufuli was elected in large part on his reputation of high integrity and his anti-corruption platform.

The causes of petty and grand corruption may be different, but they are seen as equally detrimental to development. Corruption is often attributed to the relatively low level of income of politicians and civil servants in comparison with the private sector and, for politicians, in view of the uncertainty of their position. Yet ‘needs’ is only one part of the story. Greed and a mindset that does not consider paying or accepting bribes as dishonest is the other part of the story. Moreover, the lack of coordination of regulations, administrative rules, and laws offers numerous rent-seeking opportunities in the various layers of the bureaucracy. Raising salaries – and, for high-level politicians, creating compensation that facilitates life after leaving office – may be part of the solution to reduce corruption to a tolerable level. Reforming the organisation of the state by coordinating laws and rules so as to eliminate rent-seeking opportunities is equally important. Yet publicly identifying and formally prosecuting those found guilty of corruption, whether as a corruptor or a person who is corrupted, is central to any anti-corruption strategy.

Even though some of the personalities interviewed tended to minimise the consequences of corruption, most stressed the development costs arising from the misallocation of resources involved in grand corruption, the undermining of the profitability of some investments through import smuggling (e.g. sugar, rice), bribes to acquire business licences, land use rights or trade permits, and, most importantly, the loss of tax revenues leading to inefficient, and ineffective, higher tax rates.

The inefficiency of the civil service, stressed by most interviewees, has very much to do with corruption, but, as suggested earlier, both find their root cause in the way the state bureaucracy functions. A weakness frequently pointed to was the multiplicity of regulatory bodies, ministerial bureaus or public agencies that have their say in specific areas. One expert mentioned that the production and commercialisation of a new food product would require twenty-two authorisations from different administrations. Another reported that the farming sector was administered through fifteen different public entities. Others mentioned the frequent discrepancy between local government decisions and rules enacted by the central government. Of course, the problem may not be the number of public entities having a say on some aspect of the economy, but the lack of coordination among them, leading to ineffectiveness and rent-seeking opportunities for bureaucrats who have the power to short-circuit the whole system. A good example of a reform aimed at simplifying things was the creation in 1995 of the Tax Revenue Authority, which centralised tax collection operations formerly under the responsibility of various decentralised administrative entities. Another more recent example of the need for coordination among public entities is the creation of the President’s Delivery Bureau, in charge of coordinating efforts to reach the National Key Result Areas through the monitoring and evaluation of various administrations.Footnote 16

Another weakness of the civil service stressed by a number of experts was the low capacity of the bureaucracy. This might be due as much to insufficient human capital at all levels as to excessive movements of bureaucrats caused by political cycles. There seemed to be a consensus that it was at the local level that the bureaucracy was the least effective. In particular, the point was made that the poor understanding of laws by the public gives undue power to local bureaucrats, which they use for inefficient decisions and, often, their own profit. More generally, the question was raised as to the efficiency of the way decentralisation is being implemented.

The regulation of production activities is of utmost importance for economic growth as it affects the competitiveness of the production apparatus and the investment climate. It is judged to be deficient in Tanzania in several ways. First, companies that are still state-owned, after the wave of privatisation that took place throughout the 1990s and early 2000s, were reported by some experts as inefficiently managed or inefficiently regulated. The most obvious case seems to be that of TANESCO, the public company responsible for the distribution and most of the production of electrical power – an area where Tanzania appears to be lagging behind most African countries. It was reported that its regulatory agency, the Energy and Water Utilities Regulatory Authority (EWURA), maintains a cap on the price of electricity, which essentially makes TANESCO unprofitable, increases its debt burden, and prevents it from investing in a badly needed expansion of coverage. It was also reported that several public–private partnerships in power generation failed because of inadequate tariffs and uncertainty about potential nationalisation. A major reorganisation of TANESCO has recently been confirmed, which consists of breaking the company into various functional entities – that is, ‘unbundling’ – and issuing shares to the public. How regulation will be modified is not yet clear. Other state-owned companies that have been found to be underperforming include the telephone company Tanzania Telecommunications Company Ltd and the petroleum company Tanzania Petroleum Development Corporation.

It is worth stressing that interviewees with a deeper knowledge of the energy sector pointed to a rather different diagnostic about the difficulties of the power sector. It was pointed out that the agency, which had been operating for a relatively short period of time but enjoyed international recognition for its professionalism, was making rigorous recommendations and followed world best practice in this area. The interpretation was therefore that political pressure often meant their recommendations were being imperfectly and incompletely implemented.Footnote 17

With regard to state-owned companies, it was also fairly surprising to learn in one of the interviews that many of the numerous privatised state-owned companies were no longer functional. This suggests that those parastatals were indeed extremely inefficient and were bought essentially for their equipment and buildings, rather than their activity. It is also possible that the private management of these companies did not benefit from the same competitive advantages as when they were state-owned.

Concerning the private sector, the complaint most often heard was that too many regulations are a strong disincentive for investment, whether domestic or foreign. In natural resources, the view was that capital, knowledge, and know-how are needed but that foreign investors still fear the risk of nationalisation – despite a foreign direct investment act explicit in dismissing that risk. In manufacturing, the opinion was that domestic firms prefer investing in trade than in production, subject to more and heavier regulation. Foreign direct investments are more oriented towards the exploration and extraction of natural resources, telecommunication services, and tourism, all sectors where regulation is apparently also heavy.

The excessive number and complexity of regulations were also mentioned as the main reason why small and medium-sized enterprises are not formed. A more fundamental reason, not mentioned by the respondents but well established in many other developing countries, might also be that the actual gain of creating formal enterprises is small. This may also be the case in Tanzania.

The management of land use rights is the best example of the consequences of an inefficient and sometimes corrupt bureaucracy and a legislation that is complex and thus not well known or understood by the public. The uncertainty on land rights is very often cited as a real handicap in developing the agricultural and agro-industrial sector, and in some cases even industrial projects in urban areas. As far as the latter are concerned, a frequently cited example is that of the two to three years it took to get the land use right needed to construct a liquefied gas terminal on Tanzania’s coast. In agriculture, everybody seems aware of the long delays investors face in acquiring land rights and the bribes they end up offering to shortcut cumbersome processes whether at the local or the national level. Land is the subject of the second largest number of judicial cases, often with individual investors confronting the local or regional authorities responsible for the allocation of land. Many disputes also arise from farmers squatting or claiming back land allocated to investors but not fully utilised.

Land is the property of the state in Tanzania, and was actually collectivised during the socialist era. After a long maturation process, a Land Act was passed in 1999 to codify the operations on land use rights, in particular to facilitate investment. It is considered to be a good law, but its implementation at lower government levels is said to be problematic because of the lack of capacity of local bureaucracies and a poor understanding of the law by villagers. There also seems to be little accountability of the civil servants responsible for land operations with respect to both investors and the local population. Records of these operations are also said to be badly managed.

In a country where land is abundant and agriculture has great potential, such ambiguity around land use rights is unfortunate. It also has negative consequences in urban areas.

The functioning of the political system naturally came up in the interviews. The main issue was the accountability of the government and the nature of checks and balances on the executive. Emphasis was put in particular on the key role of the Controller Auditor General and the need for the content of his annual report to be better publicised and publicly debated, and for the auditing of public entities to go beyond official accounts. The view was expressed that parliamentary debates should receive more space to review the government’s actions. This seemed to several experts all the more important in a country where the president enjoys considerable power, and until recently was able to control the entire bureaucracy and to some extent the legislature. Things may be changing as the opposition and political competition are rising. The relationship between the two members of the Tanzanian Union – that is, the mainland and Zanzibar – was also seen as a sensitive issue that has now been discussed for some time in relation with a reform of the constitution.

The judicial system would seem to be the main instrument to fight corruption. The interviews emphasised its lack of resources. At present 16 per cent of the 180 districts do not have a court and a third of the regions have no high (i.e. appeal) court. The judicial system is thus in a constant state of congestion. Corruption is also present among the staff, in no small part because of outdated information technology that generates frequent involuntary (or deliberate?) losses of key pieces of evidence.

Although on the edge of institutional issues, the mindset of the population with respect to specific issues was frequently mentioned in the interviews as being responsible for slowing down economic development. Several experts indeed thought there was still a suspicion with respect to the private sector in the civil service and possibly in public opinion, which somehow acted as a brake on development. The lack of a true culture of business was also emphasised, with evidence for this perhaps lying in the disproportionate number of non-indigenous among entrepreneurs, the opposite being true in the political sphere.

IV Conclusion

It is striking to see that, altogether, the three preceding approaches to the quality of institutions are convergent on the likely constraints that Tanzania’s institutions enact on economic development, independently of the capacity of the country to devote the resources necessary to key development functions. By the very nature of the analysis, conclusions are less clear in the case of the institutional indicators, in part because they combine many different dimensions of institutions and in part because they result from a comparative exercise that is somewhat arbitrary – that is, weaknesses may be the same in Tanzania as in the comparator countries, including the highly performing ones. Even in that case, however, there is clearly some convergence among the various approaches in pointing damaging weaknesses in administrative and regulatory capacity, or ‘government effectiveness’.

What emerge more precisely from the three exercises, as well as from the institutional implications of the growth diagnostics briefly reviewed in Chapter 2, are the following themes:

  • land issues featured very clearly in the CIS survey, and the limitations due to the uncertainty surrounding land use rights;

  • the regulation of firms, in particular the electricity company, TANESCO.

Corruption was mentioned in practically all approaches, but, as mentioned earlier, corruption is a symptom, the cause of which has to be found in the poor functioning of several institutions. From that point of view, the open-ended interviews with top decision makers, as well as the institutional indicators, unambiguously point to:

  • the organisation of the civil service; and

  • the coordination between state entities – in particular, the relationship between central and local governments.

These various themes are analysed in-depth in the second part of this volume.

Footnotes

1 Tanzania in a Geographic, Demographic, and Historical Perspective

1 See Sutton (Reference Skinlo1969).

2 See also Kimambo et al. (Reference Kapika2017).

3 This short historical account relies heavily on several key references, in particular, Edwards (Reference Dixit2012, Reference Dixit2014); Coulson (Reference Collins2013); Lofchie (Reference Lawry, Samii, Hall, Leopold, Hornby and Mtero2014); Ndulu and Mwase (Reference Mwamila, Kulindwa, Kibazohi, Majamba, Mlinga and Charles2017); and Shivji (Reference Rodrik2021) for the fifth phase.

4 See Nyerere (Reference North1967), United Republic of Tanzania (1967).

5 See Collier and Wangwe (Reference Chandra, Kacker, Li and Utz1986).

6 See Nyerere (Reference North, Wallis and Weingast1968), United Republic of Tanzania (2017a, pp. 54–6).

7 For instance, the state machinery made the decision to ban the Ruvuma Development Association, which is regarded by some scholars as having been a genuine socialist organisation emulating members’ participation in its development affairs – see Ibbott (Reference Hulst, Mafuru and Mpenzi2014).

8 Implemented under President Mkapa in 1996.

10 See Edwards (Reference Dixit2012, pp. 27–40), Lofchie (Reference Lawry, Samii, Hall, Leopold, Hornby and Mtero2014, Chapter 4).

11 The current president, J. P. Magufuli, was elected on a very strong anti-corruption platform and has sent strong signs of his determination in this area since taking office in 2016.

12 And, more recently, South Sudan.

13 Numerous scandals struck under Magufuli’s predecessors. Three major ones strongly impacted public opinion: (1) side payments in the tendering of an energy project to a foreign company that proved unfavourable to Tanzania; (2) more recently and still in connection with this tender a scandal stuck because of fraudulent payments to CCM politicians out of an escrow account opened by the National Electricity Company (TANESCO); and (3) fraudulent payments involving high-ranking politicians and bureaucrats made from an external payment arrears (EPA) account set up at the Central Bank to help service the balance of payments.

14 See Shivji (Reference Rodrik2021).

15 See Shivji (Reference Rodrik2021).

16 Conversation with Dr Kitima, a priest, vice chancellor of the University of Dar es Salaam, and member of the Tanzanian Academy of Science, in his personal capacity.

2 Features and Challenges of Economic Development

a Sectoral productivity relative to overall productivity at the bottom of the column (1997 = 100), i.e. GDP divided by Empl. column

a Sectoral productivity relative to overall productivity at the bottom of the column (1997 = 100), i.e. GDP divided by Empl. column

a Government account indicators are defined over the fiscal year from 01/07 to 30/06; accordingly, GDP, savings and investment figures have been transformed into 2-years averages for consistency

b Including non-government public entities

c Excluding foreign grants included in Official Development Assistance

1 They are also imprecise outside big sectors such as agriculture, manufacturing, and government services. This may be seen from abnormally high relative productivity in the low employment sector in 1960. For instance, the sectoral productivity in the construction sector would be halved if its share of employment were 0.4 instead of 0.2 per cent, although this is a tiny difference.

2 See also World Bank (2014a, pp. 33–5).

3 The same decomposition for Tanzania’s productivity growth for the period 2002–12 can be found in McMillan et al. (Reference Martinez-Vazquez and Vaillancourt2017), with results intermediate to those for the periods 1997–2007 and 2007–18 in Table 2.2, that is a strongly positive structural change effect and a much smaller (positive) effect for the within-sector productivity component.

4 This conclusion may seem to contradict the widely publicised view in McMillan et al. (Reference Masaki2014) that structural change had a negative impact on sub-Saharan growth. Tanzania may be an outlier. However, note that McMillan et al.’s estimate is for the period 1990–2005, which includes part of the long recession that hit the whole region. In Tanzania, the contribution of structural change to growth was indeed close to zero, if not negative, during that period, but the country got out of stagnation before the rest of the region and then grew faster.

5 The recent discovery of sizeable offshore fields of natural gas is discussed below together with foreign trade issues.

6 Although data may not be as precise, the opposite evolution seems to have taken place in the 1980s and early 1990s, when the GDP-share of the agricultural sector was increasing and the economy was in a deep recession.

7 With a capital-output ratio of 2.5, a depreciation rate of 4 per cent, and a population growth rate of 3 per cent, maintaining the overall capital-labour ratio requires an investment rate of 17.5 per cent. However, this figure becomes higher when it is assumed that most capital is used outside agriculture and the non-agricultural sector must absorb a net flow of workers out of agriculture. A net flow equal to 1 per cent of the labour force is equivalent to employment having to grow by 4 per cent a year on top of demographic growth outside agriculture. Then a 27.5 per cent overall investment rate would be needed to absorb the net labour flow from agriculture without changes in sectoral capital-labour ratios.

8 Using the same assumptions as in the preceding footnote, an investment rate of 35 per cent as observed in the recent years would permit a 3 per cent annual increase in within-sector productivity instead of the observed 2.2 per cent. This estimate would be higher if, of course, it was assumed that some capital is used in agriculture, unlike in the preceding footnote.

9 On export fluctuations and their causes during this period, see Kweka (Reference King2004).

10 Recall that the real exchange rate is defined there as the price of domestic over foreign goods.

11 See also Eichengreen (Reference Easterly2008).

12 This remains true despite the increase observed since the mid-2020s.

13 A report by NRGI, a New-York-based non-governmental organisation specialising in advice on natural resource policies, estimates the Tanzanian revenue of the Lindi LNG gas project to be 1.2 per cent of GDP, if the project goes ahead (Olingo, Reference Nyerere2017). Henstridge and Rweyemamu (Reference Hampton2017) assume lower extraction prices that would make the investment profitable. Yet their detailed calculation leads to actual revenues of around 1.5 per cent of GDP in the twenty years following investment – at least five years or more from now.

14 As the GDP share of consumption in 2000 was around 80 per cent and that of imports was 13 per cent, the 36 per cent share of consumption goods in exports corresponds to an average household propensity to consume imported goods of (0.36 × 0.13/0.80 = 0.06). Assuming this propensity remained constant, the 20 per cent drop in the GDP share of household consumption between 2000 and now would have generated a drop of 1.2 per cent in the GDP share of imported consumption goods, or 6 per cent of imports in 2018–19 instead of the observed 11 per cent (i.e. 36–25 per cent).

15 See WTO (2019, p. 270).

16 A detailed analysis is provided by Andreoni et al. (Reference Andreoni, Mushi and Therkildsen2020).

17 Averaging partly eliminates year to year variations in the need for external funding that arise from the volatility of changes in inventories.

18 The so-called Dutch disease arises in the presence of sizeable foreign currency inflows that do not result from a rise in exports or import substitution. They make non-tradable sectors relatively more attractive to investors, thus undermining the industrialisation potential of the country.

19 See, for instance, Deaton (2013)’s indictment of foreign aid, and in the specific case of Tanzania Edwards (Reference Dixit2014).

20 On the first crisis, see Catterson and Lindahl (Reference Boex and Muga1999) and Helleiner (Reference Grimm, Munyehirwe, Peters and Sievert2002a); on the second, see Furukawa (Reference Fjeldstad, Ali and Katera2014) and Helleiner (Reference Helleiner2002b). Helleiner was the chair of the reconciling commission appointed by Denmark.

21 A detailed analysis of these issues in the specific case of Tanzania’s development is provided by Edwards (Reference Dixit2014).

22 Besides mining (50 per cent), other major sectors of foreign investment include financial services (11 per cent) and power generation (8 per cent). These proportions refer to 2013 (NBS, Reference Mukandala2015) and may have changed since then, despite referring to stocks rather than flows of foreign investment.

23 Differences in the methodology of the two sources have been discussed in some length in various papers (Hoogeveen and Ruhinduka, Reference Harris and Todaro2009; Mkenda et al., Reference Miller and Holms2010; Atkinson and Lugo, Reference Atkinson and Lugo2014).

24 Another data source on poverty is the National Panel Survey (NPS) designed to track people and analyse individual poverty dynamics. In contradiction with data from the HBS used both by the NBS and the World Bank, it shows an increase of poverty between 2008 and 2013. Belghith et al. (Reference Barker, Bhagavan, Mitschke-Collande and Wield2018) show that the discrepancy is due to the NPS and NBS estimates using different price indices to compare real expenditure over time.

25 See Arndt et al. (Reference Amsden2017a). A unit elasticity was also implicit in the evolution of poverty projected by the National Strategy of Growth and Reduction of Poverty, locally known as MKUKUTA – see United Republic of Tanzania (Reference Ali, Deininger and Goldstein2005, pp. 35–9).

26 Arndt et al. (Reference Aminzade2017b)’s estimate of change in poverty through five deprivations (water, sanitation, housing, education, and TV/radio) recorded in various editions of the Demographic and Health Survey is also worth mentioning. Over 1992–2010, they find that poverty has unambiguously diminished.

27 Yet see Atkinson (Reference Andreoni, Mushi and Therkildsen2011) for a historical estimation of top incomes in Tanzania. According to his estimates, based on income tax date, the top 0.1 per cent was earning 5 per cent of total personal income in 1970 – declining since colonial times. This figure is comparable to the concentration of income at the top in the United States today. The publication of income tax tabulations in Tanzania was disrupted in 1970.

28 This is the last year recorded in the Barro-Lee database.

29 The expected number of years of schooling is the number of years a child is expected to stay in school, and it is approximated by the sum of age-specific enrolment rates. The learning adjusted years of schooling is obtained by multiplying the preceding number by a harmonised test score.

30 The net enrolment rate is defined as the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age, whereas the gross enrolment rate would include all children in school. The gross enrolment rate is the ratio between all students enrolled in primary education, regardless of age, and the population of official primary education age.

31 See Han and Peirolo (Reference Gray2021).

32 The first figure is derived from information collected by UNESCO, whereas the second one is based on demographic growth estimates. To this estimate should be added the effect of the recent rebound in gross enrolment. UNESCO reports an increase in the pupil–teacher ratio in primary schools from 42:1 in 2016 to 56:1 in 2019.

33 These figures are drawn from the various Tanzania Demographic and Health Survey reports. Note that they refer to a period extending to up to five years before the survey.

34 The surge in expenditures in 2006 and the following two years may be explained by the severe drought that hit the country at that time and had serious consequences for the nutrition and the health of the population.

35 It is not certain that the fluctuation shown for 2010 is statistically significant.

36 See for instance Benin (Reference Barker and Saul2016, Chapter 2).

37 All the preceding figures are from World Bank (2021). Nothing is said there about the way the poverty estimate was obtained.

3 Gathering Evidence on the Quality of Institutions

1 The methodology used in the construction of these synthetic indicators may be found in Kaufmann and Kraay (Reference Kaufmann and Kraay2002), whereas the datasets of individual expert-based institutional indicators utilised are listed in WGI-Interactive Data Access on WorldBank.org.

2 South Sudan and Democratic Republic of Congo were not included owing to a lack of data.

3 Unfortunately, the collection of datasets in the QoG database changes over time, which makes comparability over time difficult, or applies constraints when working on the limited number of datasets available over the time span being studied.

4 For a similar cluster analysis approach, see Chavent et al. (Reference Bryceson2011).

5 A statistical test permits us to check how significant it would be to further disaggregate the set of individual indicators. It would have been possible to go beyond six categories, but with the risk of finding an increasing number of categories comprising a restricted number of individual indicators.

6 These synthetic indicators are also sometimes used in companion case studies within the Institutional Diagnostic Project.

7 One may wonder why no direct use was made of the Country Policy and Institutions Assessments published annually by the World Bank for low and lower-middle-income countries. The point is that this dataset, as well as its equivalent in other multilateral development banks, is already included in the datasets that the WGI are based upon.

8 Owing to data availability, neighbour countries include Burundi, Kenya, Malawi, Mozambique, and Uganda. Rwanda is not among them because the government did not authorise the Afrobarometer surveying of the population.

9 The Afrobarometer survey is taken approximately every four years, but the 2016 wave was very much influenced by the recent election of President Magufuli with a rather disruptive platform. The 2012 wave seemed more typical of the pre-Magufuli era, which is the main focus of the present study.

10 This is the interpretation given by a large majority of Tanzanians choosing statement b) from between the two following statements (question 21): a) The government is like a parent. It should decide what is good for us; b) The government is like our employee. We are the bosses and should tell government what to do.

11 At this stage, the authors would like to acknowledge the role of the Research on Development Policy (REPOA) in completing and analysing this survey. REPOA appointed and trained enumerators, contacted respondents, and administered the survey. Abel Kinyondo provided detailed comments on the questionnaire and then on responses that greatly improved the analysis of the results, although he may not agree with all of the conclusions stated here. Last but not least, Katie McIntosh, then from Oxford Policy Management (OPM), dedicated very much of her time to the supervision of the survey. Her role has been crucial for its satisfactory completion.

12 See details in Table A.2 in the appendix.

13 Twenty-one explicitly preferred not to answer the question.

14 It sums to more than 100 per cent as some questions are, by design, relevant for several institutional areas.

15 The IPD was conducted in 2012 and asked questions on the prevailing institutional conditions at that time. The CIS was carried out in 2017 but covered institutions in the previous five to ten years, creating a large overlap between the two surveys.

16 These areas correspond to the implementation of the BRN (Big Results Now) initiative by President Kikwete to accelerate progress towards the 2025 Tanzanian Development Vision, including the status of a middle-income country.

17 The head of EWURA was replaced by the president shortly after he had recommended a tariff increase that followed agreed pre-defined rules. The tariff increase was not implemented. This occurred a few weeks after he was interviewed with his management for the present study.

Figure 0

Figure 2.1 Tanzania’s GDP per capita (absolute and relative to sub-Saharan Africa) and growth rate, 1960–2020

Source: Penn World Tables 9.1 1960–2009; WDI 2019–20
Figure 1

Table 2.1a Evolution of the sectoral structure of employment and GDP, 1960–97 (GGDC Release 2014, GDP at constant 2005 prices)

Source: Author’s calculation from Groningen Growth Development Centre database.
Figure 2

Table 2.1b Evolution of the sectoral structure of employment and GDP, 1997–2018 (GGDC Release 2021, GDP at constant 2015 prices)

Source: Author’s calculation from Groningen Growth Development Centre database.
Figure 3

Table 2.2 Decomposition of the change in overall labour productivity into structural change and within-sector productivity effect, 1960–2018

Source: Calculation in Appendix
Figure 4

Figure 2.2 Absorption and expenditures on GDP, 1985–2018 (percentage of GDP)Note: Because of a shift in the base of Tanzanian national accounts in 2015, the IMF today reports only data after 2012. Figures for the period before 2012 are taken from previous 2005-based national account series after adjusting them proportionally so that they coincide with the new definition in 2012

Source: IMF, International Financial Statistics
Figure 5

Figure 2.3 Foreign trade and terms of trade, 1990–2019 (shares of GDP or 2010 based indices)Note: The real effective exchange rate is defined as the ratio of the price of domestic over foreign goods. It is obtained by dividing the consumer price index in Tanzania by the product of the exchange rate (in Tanzanian Shillings per dollar) and the mean GDP deflator of partner countries. Trade partners were identified by the mean share of merchandise exports and imports across the two sub-periods 1997–9 and 2013–15. Only partners with shares above 2 per cent were considered. The resulting list of countries is, in order of importance, India, South Africa, China, Kenya, Japan, UK, Saudi Arabia, Germany, UAE, Switzerland, Netherlands, USA, and Belgium

Source: Author’s calculation from World Development Indicators (see figure note)
Figure 6

Figure 2.4 Composition of merchandise exports, 1995–2019 (shares of total)

Source: Calculation from Bank of Tanzania annual reports (1995–2019)
Figure 7

Table 2.3 The financing of the Tanzanian economy, 2010–18

Source: Author’s calculation from IMF, Government Accounts and Balance of payments data in annual reports of the Bank of Tanzania.
Figure 8

Figure 2.5 Consumption per capita, poverty and inequality, 1991–2017

Source: HBS (since 1990), NBS data (1991–2017), World Bank Povcalnet database (1991–2017)
Figure 9

Figure 2.6 Primary and secondary school enrolment (gross and net) in Tanzania and the sub-Saharan region, 1970–2015 (per cent)

Source: UNESCO, WDI and NBS
Figure 10

Figure 2.7 Some health care indicators in Tanzania and sub-Saharan Africa, 1990–2018

Source: WDI and Tanzania Demographic and Health Survey (DHS)
Figure 11

Table 2.A.1 Full decomposition of overall labour productivity growth into structural change and within-sector productivity components, 1960–2018

Source: Author’s calculation from Groningen Growth Development Centre database.
Figure 12

Figure 3.1a WGI: Tanzania and neighbour countries, 2018

Figure 13

Figure 3.1b WGI: Tanzania and outperforming peer countries, 2018

Figure 14

Figure 3.2a WGI: Tanzania and neighbour countries, 2005

Figure 15

Figure 3.2b WGI: Tanzania and outperforming peer countries, 2005

Figure 16

Table 3.1 The six QoG-DGC synthetic indicators

Figure 17

Figure 3.3a QoG-DGC synthetic indicators: Tanzania versus neighbour countries

Figure 18

Figure 3.3b QoG-DGC synthetic indicators: Tanzania versus outperforming peer countries

Figure 19

Figure 3.4a Perceived constraints in World Bank Enterprise Surveys: Tanzania versus neighbour countries

Figure 20

Figure 3.4b Perceived constraints in World Bank Enterprise Surveys: Tanzania versus outperforming peer countries

Figure 21

Table 3.2 Definition of institutional areas in the CIS survey

Figure 22

Figure 3.5 Choice of institutional areas as most constraining for development

Figure 23

Figure 3.6 Proportion of questions by institutional areas according to their average scores

Figure 24

Table 3.A.1 Stratification of the CIS sample

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×