Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-22T17:33:32.392Z Has data issue: false hasContentIssue false

Inside the Black Box: Uncovering Dynamics and Characteristics of the Chilean Central Government Bureaucracy with a Novel Dataset

Published online by Cambridge University Press:  09 January 2024

Daniel Brieba
Affiliation:
Daniel Brieba is an LSE Fellow in political science and public policy at the School of Public Policy, London School of Economics and Political Science (LSE), London, UK, and an assistant professor at the School of Government, Universidad Adolfo Ibáñez, Santiago, Chile. [email protected].
Mauricio-René Herrera-Marín
Affiliation:
Mauricio-René Herrera-Marín is an associate professor and director of basic sciences at the Faculty of Engineering, Universidad del Desarrollo, Santiago, Chile. [email protected].
Marcelo Riffo
Affiliation:
Marcelo Riffo is a researcher at the School of Government, Universidad Adolfo Ibáñez, Santiago, Chile. [email protected].
Danilo Garrido
Affiliation:
Danilo Garrido is an adjunct lecturer at the Faculty of Engineering, Universidad del Desarrollo, Santiago, Chile. [email protected].
Rights & Permissions [Opens in a new window]

Abstract

This article examines bureaucracies using a novel dataset of Chilean central government employees from 2006 to 2020. Unlike perception-based sources, this dataset provides objective, disaggregated, and longitudinal insights into bureaucrats’ characteristics and careers. The authors validate it against official employment statistics and conduct an exploratory and descriptive analysis, presenting six descriptive findings about the Chilean bureaucracy that cannot be discovered using available aggregate data. The analysis reveals significant degrees of personnel stability and professionalization in the civil service, but with considerable rigidity in careers and substantial interagency heterogeneity in turnover, wages, and exposure to political cycles. These findings suggest that the Chilean national bureaucracy is mostly well developed along Weberian lines, though not uniformly so. These measurements also serve as a benchmark for comparing other Latin American bureaucracies in the future.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of University of Miami

Public bureaucracies are a key actor in the policy process of modern democracies. Moreover, clean and competent bureaucracies are a core component of a state’s capacity to deliver valuable social and economic goals. Despite their empirical and normative importance, their study in Latin America has received comparatively scant attention in political science, in no small part because the development of the subfield has been hampered by “the difficulty in collecting, maintaining, and sharing data on public agencies, the civil service, and the state in Latin America” (Polga-Hecimovich and Trelles Reference Polga-Hecimovich and Trelles2016, 71).

In this article, we seek to advance their study by empirically quantifying and examining some key features of the Chilean central government’s bureaucracies. We do so by assembling and using a novel dataset about these bureaucracies that—much along the lines of Bersch et al.’s Reference Bersch, Praça and Taylor2017 data for the Brazilian federal government—is intranational, highly disaggregated, and based on objective administrative information. The data are based on individual, monthly observations of civil servants for most central government agencies (excluding those in the Ministry of Health) between 2006 and 2020. They include information on the employee’s name, agency, employment regime (permanent, yearly, or temporary), geographical region of work, wage, qualifications, function, administrative rank (such as professional, technician, auxiliary, and managerial), and administrative degree (with lower degrees signaling a higher position). To this, we have added information on gender and an estimation of age. This allows us to advance our empirical knowledge of the Chilean bureaucracy on three counts.

First, the richness of the information on bureaucrats’ characteristics allows for mapping the public workforce according to many variables of interest, such as those just mentioned. Second, the panel structure over 172 months allows us to study individual bureaucrats’ careers over time, and thus measure the degree of stability of their employment and whether it is affected by exogenous events, such as election outcomes. The previous paucity of continuous data on national bureaucracies has particularly impeded this longitudinal analysis. Third, because individuals are nested within agencies and agencies are nested within ministries, the data can be analyzed cross-sectionally and longitudinally at these different levels of aggregation, allowing for empirical differentiation in our measures of the Chilean civil service. For example, stable, highly paid, and highly qualified civil servants might be a feature of some agencies but not of others.

We start by characterizing bureaucracies according to their dominant mode of recruiting personnel and discussing how meritocratic bureaucracies empirically differentiate themselves from patrimonial and politicized bureaucracies. We also discuss why disaggregated measures of bureaucratic characteristics may be valuable to advance our understanding of bureaucracies’ functioning and situate Latin American bureaucracies comparatively. In the third section, we briefly explain how we assembled the dataset and validate it against aggregate personnel statistics from the Budget Office (which are constructed independently from our own). In the fourth section, we use this dataset to conduct an exploratory data analysis and present six descriptive findings that help characterize the Chilean civil service, along three dimensions of career stability and progression, professionalization, and agency heterogeneity, which cannot be replicated with existing data. The final section discusses what these findings tell us about the structure and functioning of the Chilean civil service.

Meritocratic Bureaucracies and Their Characteristics

A substantial body of literature has argued that Weberian civil services are a key component of greater state capacity and contribute to the achievement of a host of desirable economic and social outcomes (e.g., Evans and Rauch Reference Evans and Rauch1999; Henderson et al. Reference Henderson, Hulme, Jalilian and Phillips2007; Cingolani et al. Reference Cingolani, Thomsson and de Crombrugghe2015; Nistotskaya and Cingolani Reference Nistotskaya and Cingolani2016). In terms of personnel selection, the key aspect of Weberian bureaucracies is that they are, above all, meritocratic: they recruit impartially, based on applicants’ qualifications, experience, and expected performance on the job, rather than on political or other criteria. In systems where meritocracy is the rule, the careers of politicians and bureaucrats become separated, and so do the chains of accountability between them, allowing bureaucrats to monitor politicians without fear of reprisal (Dahlström et al. Reference Dahlström, Lapuente and Teorell2012). How this is achieved—whether through the granting of legal tenure to bureaucrats or through other means—is less crucial for performance than the consistent use of merit as a criterion for selection and promotion of bureaucratic personnel (Dahlström and Lapuente Reference Dahlström and Lapuente2017).

Meritocratic bureaucracies stand in contrast to patrimonial and politicized bureaucracies. Patrimonial bureaucracies recruit personnel based on personal and social connections (e.g., nepotism), while politicized ones recruit based on party loyalty or ideological congruence (Andersen and Møller Reference Andersen and Møller2019, 288). Both types select bureaucrats for reasons other than competence for the job, implying appointing bureaucrats through patronage, which is “the power of political actors to appoint individuals by discretion to nonelective positions in the public sector, regardless of the legality of the decision and the merits of the appointee” (Panizza et al. Reference Panizza, Guy Peters and Ramos Larraburu2022, 5). Merit and patronage are thus distinct and opposing ways of selecting bureaucrats, even if not all positions in a bureaucracy (and particularly those at the top) ought necessarily to be chosen on merit alone (Toral Reference Toral2023; Grindle Reference Grindle2012; Andersen and Møller Reference Andersen and Møller2019).

In the polarity between meritocratic bureaucracies and patrimonial or politicized ones, Latin American countries have usually been closer to the latter pole (e.g., Munck and Luna Reference Munck and Pablo Luna2022, 4; Andersen and Møller Reference Andersen and Møller2019). Scholars agree that patronage is prevalent in most of the region’s bureaucracies (Panizza et al. Reference Panizza, Guy Peters and Ramos Larraburu2022; Iacoviello and Strazza Reference Iacoviello and Strazza2014, 54). These two opposing logics of merit and patronage coexist, with “large-scale patronage practices” operating alongside or even within formally “bureaucratic-Weberian models” (Ramos and Milanesi Reference Ramos and Milanesi2017, 10); indeed, the distance between de jure institutions and their de facto functioning has been noted as a feature of many Latin American institutions (Brinks et al. Reference Brinks, Levitsky and Victoria Murillo2020). Existing empirical measures also bear out the view of Latin American bureaucracies as having a shortage of meritocracy. For instance, in Kopecký et al.’s Reference Kopecký, Meyer Sahling and Panizza2016 survey of 22 countries, the Latin American countries studied occupy 4 of the 5 places with the most patronage in the sample. Similarly, in the 2020 Quality of Government (QoG) Expert Survey (Nistotskaya et al. Reference Nistotskaya and Stefan Dahlberg2021, 42), Latin American countries tended to score low on meritocracy, with 7 of the 11 countries in the region ranked in the lower half of the 86 countries studied (including 2 of the last 3 places).

Within the region, Chile (and Brazil) have usually been considered nonetheless as partial exceptions. For instance, in the same 2020 QoG survey, Chile ranked number 20 (out of 88) in the merit indicator, above countries such as Germany and the United States. Likewise, in the Inter-American Development Bank’s comprehensive study of the development of Latin American civil service systems, Brazil and Chile also come out consistently on top on most measures, although on the specific Merit subindex, related mainly to meritocratic hiring, Brazil comes out far ahead, while Chile ranks fourth (Iacoviello and Strazza Reference Iacoviello and Strazza2014, 47). Panizza et al.’s recent work on patronage in seven Latin American countries, on the other hand, notes that in all countries patronage was widespread and that Chilean presidents used their appointment powers extensively (Panizza et al. Reference Panizza, Guy Peters and Ramos Larraburu2022, 221).

Nevertheless, all these studies ultimately rely on perceptions, whether of experts, citizens, or bureaucrats. However, these measures have limitations. First, perceptions about bureaucratic meritocracy and performance may be contaminated by “halo” effects (Kaufmann et al. Reference Kaufmann, Kraay and Mastruzzi2007; Kurtz and Schrank Reference Kurtz and Schrank2007), whereby ex-post policy results influence our perception of the ex-ante bureaucratic process. Second, evaluations may be based selectively on more visible or salient evidence—for instance, on what happens in some levels of government or agencies. Third, evaluators may disagree on complex concepts such as “meritocratic bureaucracy” or “patronage,” and these evaluators may, moreover, change over time, making the validity and reliability of expert judgments questionable (Fukuyama Reference Fukuyama2013). Furthermore, these exercises typically result in a single, aggregate country score, hiding internal variability and leading to the “levels of analysis” problem (Gingerich Reference Gingerich2013; Bersch et al. Reference Bersch, Praça and Taylor2017; Fukuyama Reference Fukuyama2013).

Thus, there is room for complementing perception-based measures with administrative information. The data we use here has several advantages. They allow us to precisely quantify relevant phenomena, such as employment turnover, salaries, and qualifications, that are highly relevant to our judgments of bureaucratic professionalization and meritocracy. Our data cover more than 14 continuous years of central government employment, which allows for the study of individual bureaucratic careers over time, as well as for the evolution of some key characteristics of the state. Additionally, the panel structure data on individuals allow us to produce disaggregated measures of the relevant phenomena at the agency level.

For this purpose, we will conduct an exploratory data analysis to examine the degree to which Chile’s bureaucracy conforms more to a merit-based model or to a patronage-based one (both understood as ideal types) along three interrelated dimensions.

First, a Weberian bureaucracy has substantial career stability, coupled with advancement opportunities, due to the existence of tenure protections and an established career track. Patrimonial or politicized bureaucracies are generally more unstable because they lack these characteristics, and a change of government can imply large turnover effects. This instability is costly: such bureaucracies suffer from a loss of expertise and institutional memory, shortened time horizons, and recurrent discontinuation of projects, as Cornell (Reference Cornell2014) found in Peru and Bolivia. Long-tenure bureaucrats can also have a greater influence on politicians and help stabilize policy across governments (Schnose Reference Schnose2015). More generally, there is evidence of the costs of staff rotation for organizational performance in both private and public sector organizations (e.g., Park and Shaw Reference Park and Shaw2013; Fuenzalida and Riccucci Reference Fuenzalida and Riccucci2019; Akhtari et al. Reference Akhtari, Moreira and Trucco2022).Footnote 1 Additionally, if performance or “merit” is to matter once inside an organization, chances of promotion within it should exist and be awarded on that basis.

However, as Dahlström and Lapuente (Reference Dahlström and Lapuente2017) show, many highly meritocratic bureaucracies do not provide the strong employment protections that “closed Weberian” bureaucracies (as they call them) deem necessary. They contrast these to “managerial bureaucracies,” such as Sweden or New Zealand, which have lower formal employment protections and a less established vertical promotion track but more flexible horizontal and diagonal professional mobility (Dahlström and Lapuente Reference Dahlström and Lapuente2017, 198). In both these models, however, bureaucrats are shielded from political interference and face stable career prospects, even if performance incentives and advancement paths in each may differ to some degree.

The second dimension is that as patronage is based on trust, in nonmeritocratic bureaucracies politicians may choose less qualified but more loyal people to serve. This cost in qualifications is not guaranteed, since patronage can be used to bring highly qualified technocrats into government (Panizza et al. Reference Panizza, Guy Peters and Ramos Larraburu2022). However, it may happen if patronage is used as a reward mechanism for supporters (e.g., Colonnelli et al. Reference Colonnelli, Prem and Teso2020, who indeed find that patronage lowers quality), or else for building political support in Congress, as Bersch et al. (Reference Bersch, López and Taylor2022) show for Brazil. In Chile, Ferraro (Reference Ferraro2008) has noted the influence of legislators on some bureaucratic nominations in Chile.

The third dimension is that extensive patronage can mean high heterogeneity between agencies in the same state. This can happen if presidents must choose which parts of the bureaucracy to use as a “spoils system” to reward partisans and build political support in Congress, and which must be meritocratically insulated to deliver key public goods (Geddes Reference Geddes1990). Typically, finance ministries and other economic institutions have been insulated from extensive patronage because they are perceived to be “strategic” (Ramos and Milanesi Reference Ramos and Milanesi2017; Salazar-Morales and Lauriano Reference Salazar-Morales, Amaral Lauriano, Sullivan, Dickinson and Henderson2020). This segmentation can generate some “islands of excellence” or “pockets of effectiveness,” even in countries with extensive patronage (McDonnell and Vilaça Reference McDonnell, Vilaca, Bågenholm, Bauhr, Grimes and Rothstein2021). However, anticipating which government sectors or agencies will be more meritocratic in each country is not obvious (Gingerich Reference Gingerich2013).

Using our novel dataset, we propose to examine the Chilean bureaucracy along these three dimensions of career stability and progression, qualifications, and agency heterogeneity. In a fully Weberian bureaucracy, we would expect to see long-term employment within the bureaucracy, as well as evidence of within-agency career advancement; well-qualified personnel, particularly in top positions; and significant degrees of agency homogeneity in terms of stability, wages, and exposure to political cycles.

In part, we follow along the lines of Bersch et al. (Reference Bersch, Praça and Taylor2017), who studied the Brazilian bureaucracy at the agency level using individual-level data on bureaucrats. However, rather than building abstract measures of autonomy and capacity for each agency, we choose to use descriptive data to shed light on measures regarding the professionalization of the Chilean bureaucracy. We believe that these descriptive findings contribute empirical knowledge to the scholarly and public policy communities, advance our comparative understanding of the region’s bureaucracies, and serve as a benchmark for future studies in other countries in the region.

The Chilean State

Chile is, along with Brazil, one of the Latin American states with the most developed civil service systems in the region (Iacoviello and Strazza Reference Iacoviello and Strazza2014, 20). It is also—along with Uruguay—one of the countries in the region with the lowest levels of corruption (Kaufmann and Kraay Reference Kaufmann and Kraay2023).

In 1989, the outgoing military dictatorship (1973–90) passed a civil service law, or administrative statute, that remains the core of the central government’s employment laws (Alberts et al. Reference Alberts, Dávila, Valenzuela, Guy Peters, Tercedor and Ramos2021). The statute created a standard civil service career track with robust employment protections, akin to a “closed” Weberian system. Positions are defined by grades in a clear hierarchy tied to remuneration and rank according to the nature of the job—such as support staff, administrative staff, technicians, inspectors, professionals, and managers.Footnote 2 The civil service career ends at the mid-levels of the managerial rank, with the highest positions being defined as positions of trust to steer the bureaucracy in the direction desired by the government. Roughly half of managerial positions are civil service career positions, while the rest are trust-based (Centro de Estudios Públicos et al. 2018, 13). Remunerations are organized according to a governmentwide unified scale that specifies compensation according to grade. However, many agencies have different salary scales, such as superintendencies; indeed, a study identified 66 agencies (outside the judicial, education, and health sectors) that have at least partially special employment regimes (Pardo and Orellana Reference Pardo and Orellana2009).

Along with the permanent (planta) career track, two other roads into government employment exist: the yearly contract (contrata) and the temporary contract (honorarios). The yearly contract can be indefinitely renewed and was meant to supplement permanent workers. These workers have a grade and a rank, can assume all responsibilities of permanent workers except managerial positions, and receive compensation according to their agency’s salary scale. The temporary contract was meant for tasks not part of the regular operation of an agency (such as an IT project or a consultancy). They are not governed by the administrative statute and do not have a grade or rank. Both contracts were thought to be complements to the standard permanent track; by law, yearly employees cannot exceed 20 percent of permanent positions (Alberts et al. Reference Alberts, Dávila, Valenzuela, Guy Peters, Tercedor and Ramos2021; Rajevic Reference Rajevic2018). However, over time, they became ways to hire long-term workers without creating new permanent positions. The yearly contract regime has grown and is now the dominant employment regime within the state, as Congress has regularly overridden the 20 percent limit with yearly provisions in the budget law (Rajevic Reference Rajevic2018).

The only major civil service reform since the dictatorship was the creation in 2003 of a specific career track for top management positions that used to be chosen solely on trust. Since this reform, an open, competitive process preselects the top candidates, and the president chooses only among these, thus now combining trust with merit (Olavarría-Gambi and Dockendorff Reference Olavarría-Gambi and Dockendorff2016). However, the implementation of this reform has been fraught, and studies have highlighted the high rotation of these positions, particularly when a new government comes in, partly frustrating the aspiration to create a more professionalized upper management (González-Bustamante et al. Reference González-Bustamante, Alejandro Olivares, Abarca and Molina2016; González-Bustamante Reference González-Bustamante2020; Fraile Reference Fraile2018; Grindle Reference Grindle2012). Of the rest of the civil service, however, we know little. An important recent exception is Moya Díaz and Garrido (Reference Moya Díaz and Garrido2022), who studied patronage in Chile through surveys and interviews. They concluded that patronage is far more prevalent in upper positions of the civil service: 60 percent of their interviewees thought that “nearly all” those positions were political, as opposed to 30 percent in middle levels and 10 percent in lower levels (Moya Díaz and Garrido Reference Moya Díaz and Garrido2022, 96–97).

The Dataset: Data Wrangling, Characteristics, and Validation

As part of a drive for greater public transparency, since 2006 Chilean central government ministries and agencies have been mandated to publish online individualized information on their employees and their positions.Footnote 3 This includes employees’ full name, qualifications (as free text), position description, gross salary, geographical location, administrative grade and rank, type of employment relationship, and dates of entry and exit, among others.Footnote 4 We downloaded, processed, and cleaned all available data to create this novel dataset for all public services between January 2006 and April 2020, except for those pertaining to the Ministry of Health.

Cleaning and Record Linkage

The data were dispersed in hundreds of web pages and thousands of tables, often in different formats, making downloading them a major undertaking. We cleaned and standardized the data, as mistakes and inconsistencies were abundant. The greatest challenge was using bureaucrats’ inconsistently written names to assign a unique identifier to each, to track them accurately over time. A semi-automated process using fuzzy matching, logical rules, and human supervision to correct mistakes yielded a sizable reduction in names. This was supplemented by joining names to the electoral register to confirm identities, resolve ambiguities, and extract individual genders. Our final estimate is that the data cover 323,695 distinct individuals (in 15.8 million rows), a 16 percent reduction from the set of cleaned names in the data, and a 29 percent reduction from the 457,688 unique “as-downloaded” names in the dataset.Footnote 5

Coverage and Quality of the Data

To assess how much we can trust this dataset, we validated it against official aggregate employment statistics published by the Budget Office (DIPRES). We used two separate DIPRES sources, one for the 2006–10 period (DIPRES 2011) and another for the 2011–19 period (DIPRES 2023). We found that the deficit in overall personnel varies between about 14 percent and 37 percent, depending on the year; however, the lion’s share of this deficit is explained by just two large agencies, the prison guard service and (in 2011 and 2018 only) the nursery service (JUNJI), both of which are extremely large.Footnote 6 In figure 2, we report the percentage of personnel missing in total, once we eliminate the prison guard service and other smaller military institutions with incomplete data, and when, in addition to that, we eliminate JUNJI. Without military institutions, missing personnel drops to between 0 percent and 20 percent. If we also eliminate JUNJI, deficits range between 3 percent and 18 percent; after 2010, the highest deficit is 10 percent (see figure 1).

Figure 1. Difference in Total Employees Between DIPRES and Our Data, by Year (percent)

These final results are largely explained by agency coverage: in the first three years (2006–8), about 16 to 18 percent of agencies did not report data, but by 2013, we have data for 94 percent of them, and in fact in every year from 2010 on, coverage is above 90 percent (see figure A5 in online annex 2).

Perhaps the most important point is about the quality of the data we do have. To investigate this, we compared our estimates of (permanent and yearly) personnel to the DIPRES figures.Footnote 7 We calculated the percentage of deviation of our data from DIPRES data for each agency/year for which both sources have at least some data. We then classified each agency/year as “Good” if the deviation was within +/–10 percent of the DIPRES number, as with “Some problems” if the deviation was between 10 and 30 percent, as “Poor” if it was between 30 percent and 50 percent, and as “Very poor” if the deviation was over 50 percent.

Our results show that 85 percent of data points are “Good” for 2006–10, and this rises to 89 percent for the 2011–19 period; the “Very poor” data are 4 percent or less in each period. In figure 2 we report scatterplots of DIPRES and our data for each agency/year in the 2011–19 period (including missing agencies), but leaving out the largest agencies for ease of visualization of deviations from the diagonal line. We color-coded the data according to the categories above. As can be seen, most points are very close to the diagonal. It also means that the name-matching procedure utilized was crucial for this, as without it, our data would have included 16 percent to 30 percent more (spurious) identities. Red points, representing large deviations, correspond mostly to cases in which Transparency has missing data, and are laid out along the x axis.

Figure 2. Total of Employees by Agency/Year, DIPRES vs. Our Data

Note: Scatterplots of the Budget Office’s estimates of employees in each agency/year against the same estimates derived from our data. Only agency/years with up to five thousand employees in the x axis (which are nearly all) are shown. For a plot covering all agencies, see figure A7 in online annex 2.

Thus, we conclude that our data are highly accurate for the overwhelming majority of agency/years, but one should be cautious in drawing conclusions for the state as a whole if there is reason to believe they might be materially affected by the agency/years for which data are missing, such as military institutions.Footnote 8

Results and Findings

In what follows, we present our main findings, organized along the three dimensions of career stability and progression, professionalization, and agency heterogeneity.

Career stability and progression

Descriptive finding #1. Though the permanent contract has severely declined, people hired on yearly contracts have only slightly lower job stability, and political cycles do not have great impact on either contract modality—even if they do have a small effect on overall turnover.

Using aggregate data, previous studies have noted the increasing dominance of the yearly contract regime over the permanent contract (Alberts et al. Reference Alberts, Dávila, Valenzuela, Guy Peters, Tercedor and Ramos2021; Centro de Estudios Públicos et al. 2018). Recent rulings by the Chilean Supreme Court have given some degree of protection to yearly workers (Rajevic Reference Rajevic2018, 410), but their de jure status is clearly inferior. This shrinking of the permanent contract employment regime has amounted to the “destruction” of the civil service career model enshrined in the 1989 law, according to a leading authority (Rajevic Reference Rajevic2018, 408). In figure 3, we plot the yearly evolution of all three employment regimes.Footnote 9 The growing dominance of the yearly contract is stark, as is the shrinking of permanent positions. Temporary jobs grew until the mid-2010s, then diminished quickly as many were converted to yearly contracts. We thus confirm that the standard civil service career path is now relatively marginal within the state.

Figure 3. Distribution of Employment Regime by Year (percent)

Note: Data include all agencies that have full data (i.e., beginning no later than February 2006 and ending on or after March 2020), but exclude JUNJI (which has missing data for 2011). Data are for the month of March in each year. See online annex 6 for the full list of included agencies.

Though this de jure aspect is undoubtedly important, we still want to know whether individuals on yearly contracts experience lower job stability, are more politically exposed, or have less projection in their careers. Previous studies have suggested that yearly workers’ careers are just as stable as permanent staff (Alberts et al. Reference Alberts, Dávila, Valenzuela, Guy Peters, Tercedor and Ramos2021), though without providing evidence. Aggregate turnover data (for permanent and yearly staff taken together) do not suggest that turnover is affected by political turnover cycles in government (Centro de Estudios Públicos et al. 2018, 14).

To tackle these questions, in figure 4 we first show turnover data by year, separated by employment regime; we include all workers except managers (virtually none of whom have yearly contracts, thus potentially biasing the comparison).Footnote 10 As expected, the temporary category exhibits a much higher turnover than the other two regimes, which are very similar. Yearly turnover averages 5.3 percent for permanent contracts and 7 percent for yearly ones, compared to almost 31 percent for temporary contracts. Therefore, the long-term replacement of the permanent modality by the yearly one does not seem to have implied significantly higher turnover, as the difference between them has been substantively small. Significantly, a combined yearly turnover rate of slightly over 6 percent is virtually identical to the average turnover of the federal civil service in the United States (Bolton et al. Reference Bolton, de Figueiredo and Lewis2021). Though this does not mean that people under yearly contracts are in the same situation or face identical incentives to tenured employees on permanent contracts (they may, for instance, feel more pressured to comply with specific instructions, political or otherwise), it does at least suggest that differences are not so great as to translate into greater instability or politicization of yearly workers.

Figure 4. Turnover Rates by Contract Type and Year (with 95 percent confidence intervals)

Note: Data include all agencies that have full data (see online annex 6), excluding the statistics agency (see figure A4 in annex 1 for an explanation of this exclusion). “Presidential year” is defined in the text. Managerial positions are excluded.

Indeed, figure 4 also allows us to see if there is any indication of political cycles in turnover. To measure more precisely, instead of the usual calendar years, we measure turnover by “presidential year,” beginning in March of each year and ending in February of the next. Changes in government occurred in March 2006, 2010, 2014, and 2018. Only the first of these changes occurred between two governments of the same (center-left) coalition, with the other three being shifts from the center-left to the center-right (2010, 2018) or vice versa (2014). As per previous findings, however, we do not see systematic evidence of political cycles in turnover for any contract type.

This is perhaps puzzling, considering that 49 percent of bureaucrats surveyed by Schuster et al. (Reference Schuster, Meyer-Sahling, Sass Mikkelsen and González Parrao2017, 64) declare that government turnovers affect their job stability. To explore this in more depth, we look at permanent and yearly workers combined, this time including managers, in figure 5. However, we exclude JUNJI, which is by far the largest agency in our data and may hide tendencies present in the rest of the government.Footnote 11 We now find a clearer pattern in which, in the first year of a new government, there is a jump in employee turnover (whether voluntary or involuntary) of about 1.5 percentage points, or 20 to 25 percent more than in a “normal” year. We should note, in any case, that this analysis includes employment at all levels, and that therefore, larger political cycles could exist for particular positions, ranks, or agencies.

Figure 5. Turnover Rates by Year, Without JUNJI (with 95 percent confidence intervals)

Note: Data include all ranks and all agencies with full data (see online annex 6), except JUNJI. Permanent and yearly contracts only.

Descriptive finding #2. Job stability varies very significantly according to rank.

Overall careers seem to be largely stable, but is this true for all levels in the administrative hierarchy? One useful way to study these differences is through survival analysis. For our data, we define a job spell as a term of uninterrupted employment of person A in agency Y. If the individual switches to another agency, we count that as a separate job spell.Footnote 12 With this definition in place, we look in figure 6 at the Kaplan Meier survival graph for all job spells according to rank. What we find is that top positions are considerably more unstable than lower ones.

Figure 6. Kaplan Meier Survival Estimates by Rank (2006–2020)

Note: Data include all agencies that have full data (see online annex 6).

The variation among ranks is very large. Naturally, political authorities (such as ministers, undersecretaries, and regional delegates, among others) have the shortest lifespan, ending their job spells in 48 months at the latest, which is the length of a presidential cycle. But managerial positions are highly volatile, too: slightly over 50 percent leave their job within 48 months, and this suggests considerably more volatility in these positions than in the United States, where their turnover is only a few percentage points higher than the average (Bolton et al. Reference Bolton, de Figueiredo and Lewis2021). This lower longevity is only partly explained by trust-based senior management positions (ADP), 50 percent of which have left in 3 years, according to González-Bustamante (Reference González-Bustamante2020). The next most short-lived rank is the professional rank (which is also the largest), where 50 percent of job spells last 90 months or less, or slightly less than 2 full governments. Administrative and technical jobs are more stable, with 50 percent of job spells ending after approximately three governments. Furthermore, the much smaller inspector rank—which only exists in 15 agencies in our data—is extremely stable. Since managers and professionals have the lowest survival rates, we can infer that stability is generally lower in the upper half of the hierarchy, and this may have consequences for the stability of public policies and organizational performance.

Descriptive finding #3. Bureaucratic careers are stable to the point of immobility, with scant opportunities for advancement.

Meritocratic bureaucracies offer opportunities for career advancement to those who perform well. These typically lie within the agency itself, as better positions become available, though they could also appear in other agencies. In this regard, a large survey of Chilean central government bureaucrats (Schuster et al. Reference Schuster, Meyer-Sahling, Sass Mikkelsen and González Parrao2017, 45–46) found that only 41 percent of employees agreed that they had “good opportunities” to advance their career within their agency, and 43 percent answered affirmatively regarding the state in general. What do our data suggest?

To answer this, we looked at how many job spells employees have had, how many agencies they have worked in, whether they changed employment regimes, and what typical grade advancement they achieved, whether within a single job spell or across job spells. We find substantial degrees of immobility on all counts.

First, there is substantial regime immobility. To see this, we classified job spells according to their initial and final employment regime (see table 1). We see that for all three regimes, over 80 percent of job spells began and ended under the same modality. When there was a change, it typically was toward the ever-growing yearly regime; thus, changes from permanent to yearly were more than three times more probable (conditional on the initial regime) than from yearly to permanent. Fourteen percent of temporary jobs moved on to a yearly contract, which suggests this is an avenue of improvement for some. However, stability in regimes dominates.

Table 1. Initial and Final Contract Type, by Job Spell (totals and row percentages)

Second, over the 14-year period, 86 percent of employees registered just one job spell, and if we exclude job spells that were fully temporary from the calculation (meaning the job spell began and ended as temporary), this rises to 90 percent. This shows that people who come and go within the same agency (some of which might only work for a “friendly” government in two separate job spells; e.g., 2006–10 and 2014–18) are few. If we examine those rare cases that do have more than one (nontemporary) job spell, we find that it is the upper ranks that are likelier to be in that group (see figure 7).

Figure 7. Percentage of Individuals with Only One Job Spell (Discounting All Fully Temporary Job Spells), by Rank

Note: Includes all agencies.

Similarly, 89 percent worked for only one agency, and this rises to 93 percent if we exclude fully temporary job spells. These figures suggest very low sideways mobility: barely 7 percent of nontemporary workers have been employed, over the course of 14 years, in more than one agency—though, again, upper ranks are likelier to move sideways, with 12 percent of professionals and 19 percent of managers having worked in at least two agencies.

In addition, we looked at grade progression over job spells. Across all agencies for which we have full (2006–20) data, the median grade improvement was 0 for job spells and 0 for individuals (which may have more than one job spell).Footnote 13 The respective averages were 1.36 and 1.59. Considering that (for instance) professional grades range approximately from grade 18 to grade 4, a one-grade improvement is marginal indeed. Unsurprisingly, longer job spells had more grade progression, as can be seen in figure 8. Thus, for job spells that lasted 12 years or longer, the median grade progression was 3 grades. Within the 16 percent of individuals who climbed 4 or more grades within a single nontemporary job spell, the lower ranks—particularly the administrative—are heavily overrepresented; this makes sense, since they begin from a lower (numerically higher) grade, so have more room for advancement (see figure A10 in online annex 4). In contrast, 92 percent of professional job spells advanced 3 grades or fewer, and 64 percent did not advance at all.

Figure 8. Grade Progression by Length of Job Spell (in years)

Note: Calculation includes all nontemporary job spells in agencies with full data (see online annex 6). For ease of visualization, 0.12 percent of observations were excluded.

Overall, therefore, most people do not switch between employment regimes or agencies, and progress through the hierarchy within the same agency is mostly marginal. We conclude that meritocratic advancement opportunities, whether horizontal or vertical, are more the exception than the rule. However, significant grade progression is relatively likelier for lower ranks, while job switching is likelier for upper ones.

Professionalization

Descriptive finding #4. The higher positions in the state are dominated by the same elite professions as the higher positions in the private sector—but they are combined with sector-specific expertise.

Meritocratic bureaucracies select on “merit,” usually meaning (at the very least) having the required educational credentials for a job. Since modern states perform a wide range of highly differentiated functions, they require significant technical and professional expertise to be performed successfully (Fukuyama Reference Fukuyama2013). They also need managerial skills to run large organizations. However, measuring the level and kinds of human capital a state possesses is hard, as this requires access to individual-level qualifications. Even then, we typically know only whether a person holds (for example) a university degree or not; however, not all degrees are equal. Our data in this sense are novel in that they include free text in which each bureaucrat’s qualifications must be specified. We have codified keywords in the free text to extract professions -or job qualifications.Footnote 14 Though not perfect, these keywords provide a powerful first approximation to describing the state’s human capital, allowing us to capture richer information about the kind of qualifications (e.g., lawyer, engineer) people hold.Footnote 15

We first show word clouds for the most frequent qualifications in the top four grades (figure 9a) and for all positions, including temporary personnel (figure 9a/b). Lawyers (abogados) are predominant in both, along with other professions, such as pedagogy (teachers), civil engineering, and so forth. However, in figure 9a/b, covering the full spectrum of positions, we see nonprofessional qualifications such as mere “experience” and high school diplomas (educación media).

Figure 9. Word Clouds of Most Frequent Professions, for Top Grades Only and for All Individuals

Note: Includes all agencies.

In a meritocratic bureaucracy, we would expect the top positions in the state to be occupied by the most qualified people. In this context, this would mean that individuals possessing the most prestigious degrees would be particularly prevalent at the top. Interestingly, using university admission test scores, Zimmerman (Reference Zimmerman2019) classifies law, civil engineering, and business administration/economics (in Chile the two are studied together as ingeniería comercial) as the three most prestigious professions and those that are most likely to lead, together with other conditions, to a position on the most important company boards. Law and business/economics are also considered the most prestigious professions in studies that examine ministerial careers in Chile (González-Bustamante and Olivares Reference González-Bustamante and Olivares2016).

What is the distribution in the top positions of government? We focus on the roughly 3 percent of top positions of the state that are grade 4 or higher (and not political authorities). Grades 1 to 3 are managerial only, while grade 4 is about one-third managerial positions and two-thirds very top professional ones. In table 2 we see a frequency table for the top ten professions in that bracket, as measured once yearly between 2016 and 2020. What we find is a very high concentration from just three professions, which together dominate the top echelons of the state: lawyers (20 percent), civil engineers—industrial or otherwise—(19 percent), and business managers/economists (14 percent). Together, these three professions occupy a remarkable 53 percent of all top positions. They are followed at some distance by public administrators (6 percent), who are specifically trained for general-purpose jobs in the public sector; but that is not as socially prestigious a profession as the previous three. We can therefore confirm that those three professions’ dominance extends also to the public sector. We also take this to be a sign of meritocracy, as lawyers are fundamental to government and are the most prestigious nonmathematical profession, while business and engineering provide valuable numerical and managerial skills that are essential for top positions.

Table 2. Most Frequent Professions in Top Grades

Interestingly, however, other professions that have sector-relevant expertise occupy top positions in the related agencies and ministries. As can be seen in table 3, accountants are the most prevalent profession in the top positions of the Tax Agency, as are architects in the Housing Ministry, civil engineers in the Public Works Ministry, teachers in the Education Ministry, and agronomists in the Ministry of Agriculture. Economists, for their part, strongly dominate the Budget Office and lawyers are preponderant in the Ministry of Internal Affairs. Thus, what we see is a mixture in which the top positions in the state combine a strong presence of the three “prestigious” professions that also dominate the private sector, with the specific sector-relevant skills of other professions. Again, this suggests that professional expertise is highly valued for top positions in the bureaucracy, and that selection on merit is taking place. Notably, this is occurring in both specialized agencies, such as the Tax and Budget Offices, and in ministries.

Table 3. Most Frequent Professions in Top Grades, Selected Agencies

Agency Heterogeneity

Descriptive finding #5. Job duration varies greatly between agencies, and (mostly) smaller agencies have noticeable spikes in turnover in the first year of a new government.

In terms of longevity, we find substantive variation among agencies. In figure 10, we compute the Kaplan-Meier survival functions of employees of eight government agencies, chosen as illustrative of the full range of variation present in the data. Two institutions with very high job stability are the Tax Agency (SII) and the Aviation Authority (DGAC), where, after 172 months, almost 70 percent of staff were still at their jobs. The Ministry of Foreign Affairs (MINREL) also has moderately high stability. Then two institutions with middling survival rates are the National Service for Minors (SENAME) and the Civil Registry office (Registro Civil). These agencies have lost 50 percent of their staff after 108 to 132 months. Furthermore, three agencies with significantly lower survival rates are the Public Works Department (DGOP), which loses half its personnel in about 4 years, the regional and provincial presidential offices (GOBERNINTEND), and the Institute for Youth (INJUV), which lose half their personnel in just over 2 years.Footnote 16

Figure 10. Kaplan-Meier Survival Estimates, Selected Agencies, 2006–2020

Note: Shorter lines correspond to agencies with fewer than 172 months of data.

Moreover, we observe sharp jumps in turnover for many agencies during electoral years. To see this, in figure 11 we plot the average turnover for each agency in the first presidential year of an incoming administration (2006, 2010, 2014, and 2018) on the y axis, and the average turnover in the remaining three years on the x axis. We also plot two lines, one representing y = x and another representing y = 2x. Thus, agencies that fall on or beneath the lower line (y = x) have an average turnover in the first year of a new government that is lower or equal to their average turnover in years 2 to 4. On the other hand, agencies that fall above the upper line have an average first-year turnover that is more than twice their turnover in years 2 to 4. As can be seen, year 1 rotation is highly correlated to years 2–4 rotation, but we can also see that for most agencies the year 1 turnover is higher, and for a nontrivial number of agencies, much higher.

Figure 11. Turnover by Agency, Year 1 of New Government vs Other Years

Note: Data include all agencies with full data (see online annex 6). Two agencies have two years of missing data. Presidential years (as defined in the text) are used.

How do we reconcile this finding with the small electoral cycles found in figure 5? An important factor is that very large agencies are, on average, more stable than the rest. We can see this in figure 11, where agencies that between 2006 and 2019 had on average of more than one thousand workers (permanent and yearly only) are represented with a hollow circle. Almost all such agencies, including JUNJI—by far the largest and therefore the most influential—lie around or below the y = x line, thus stabilizing turnover when calculated across individuals regardless of agency (as in figures 4 and 5). Therefore, we find that the overall numbers mask significant electoral cycles in many agencies, such as in the Youth Institute (INJUV), the Women’s Service (SERNAMEG), the Indigenous Development Commission (CONADI), the Labor Ministry (SUBTRAB), agencies or ministries in the political core of government (PRESID, SEGPRES, SEGEGOB), and the Ministry of the Economy (SUBSECECONOMIA), among others, all of which lie above or near the y = 2x line.

Descriptive finding #6. Some economics-related agencies are highly paid and have very low turnover, suggesting that they may be “islands of excellence.”

Following Fukuyama (Reference Fukuyama2013), capable agencies are those that have well-qualified staff and adequate resources, while autonomous ones are those that do not suffer political interference. Autonomy is particularly important at managerial and upper professional levels, since (as we have seen) these are the most exposed jobs—and also the most influential for organizational direction and performance. In figure 12, we therefore plot the average 2010–19 wages for the top 8 grades only—a measure of an agency’s relative ability to attract and retain highly qualified personnel—against turnover in this same group—a measure of autonomy. It is true that Bersch et al. (Reference Bersch, Praça and Taylor2017) use turnover as a measure of capacity, leaving autonomy for party membership only. However, high rotation may be due to political interference. It also allows those currently in power greater opportunities for staffing the agency with their own recruits. We therefore believe that turnover, particularly in these top positions where patronage is concentrated (Panizza et al. Reference Panizza, Guy Peters and Ramos Larraburu2022), is a reasonable indicator of autonomy. Thus, if there are any “islands of excellence” in the Chilean state, we should expect them to be well paid and have low turnover—though these are probably necessary but not sufficient conditions for high performance.

Figure 12. Average Wage and Average Turnover by Agency, Top 8 Grades Only

Note: Data include all agencies that have data beginning on or before January 2010 and ending on or after January 2020. Wages in nominal Chilean pesos. The y axis begins at 1,500,000 for better visualization. N = 86; four agencies have one or two years of missing data.

We do see such a cluster in the upper left-hand corner of figure 12. Consistent with the literature, these are mainly superintendencies or agencies related to economic functions, such as the Budget Authority (DIPRES), the electricity regulator (SEC), the Pension Regulator (SP), the Tax Agency (SII), the financial regulator (CMF), and the Customs Agency (aduana), among others. These agencies, for the most part, correspond to those that are on the supervisory wage scale, as they are in charge of oversight functions (Pardo and Orellana Reference Pardo and Orellana2009, 508). The only noneconomic agency in this cluster is the Public Defender’s Office (DPP). Below this group, we see a dense cloud where most agencies lie, at fairly low levels of turnover (on or below 15 percent) and lower salaries. A third cluster has slightly higher wages than the second cluster, but higher turnover. This group has a high prevalence of ministries, together with the Youth and the Women’s Agencies. Save for the Ministry of Finance (hacienda) and the public procurement agency (CHILECOMPRA), we do not see high-wage, high-rotation cases.

Overall, we see that these differences between agencies have structure, with different kinds of agencies situated at distinct places on the graph. These differences make political sense: ministries and undersecretary positions tend to have less autonomy because they are part of the political command structure of a government, led by political authorities (undersecretaries and ministers). Nevertheless, high turnover in them seems to go considerably beyond the trust-based managerial positions, including significant rotation in the top professional positions (grades 4 to 8).

For their part, regulatory agencies are meant to be highly qualified, neutral, and politically independent. However, it is remarkable that agencies such as the Pension Regulator (SP), the Financial Regulator (CMF), and the Insolvency Regulator (SUPERIR) have low turnover, because all their positions are based on trust alone (Pardo and Orellana Reference Pardo and Orellana2009, 496). Yet they behave nonetheless on par with similar institutions under standard public sector employment laws. It is also notable that the Tax and Budget Agencies exhibit significant autonomy and seem to be staffed as neutrally as supervisory agencies, despite being crucial to any government’s political projects. On the other hand, places such as the Youth Institute (INJUV) seem to be where patronage can be dispensed more freely.

Discussion and Conclusions

The preceding analysis suggests that the Chilean bureaucracy seems to lie closer to the Weberian meritocratic ideal type than to patrimonial or politicized models of the bureaucracy. Its career paths show significant stability, regardless of whether workers are on a permanent or yearly contract; in fact, they are similar to the US federal civil service. Political cycles have, at most, a small effect on aggregate turnover, suggesting that most personnel are not subject to one of the most obvious consequences of politicization. The state’s top positions are staffed mostly by highly qualified professionals with the most prestigious degrees, paralleling the private sector. At the agency level, these prestigious professions coexist with sector-specific ones, suggesting that top personnel are selected (at least to a significant degree) for their expertise.

On the other hand, the Chilean state seems to be less than fully developed in the Weberian sense. Career paths are largely static, suggesting a lack of a strong career civil service track and low incentives for high performance. However, there is some horizontal mobility in the professional and managerial ranks, resembling (to a modest degree) more open managerial bureaucracies. Job stability is considerable for lower ranks, but managerial positions are short-lived, creating instability at the top and thereby undermining bureaucratic autonomy. Individual agencies are highly heterogeneous, with some being more unstable or impacted by the political cycle. These differences, along with wage differences, suggest a highly diversified map of agencies in which stability, professionalization, and lack of patronage are not evenly distributed across organizations.

Furthermore, despite the de facto stability of yearly positions, their de jure position is weaker (though not entirely unprotected), and an administration determined to restaff the civil service might make things difficult for yearly workers. A survey shows that only 29 percent of bureaucrats believe that it would be difficult to remove them from the public sector (Schuster et al. Reference Schuster, Meyer-Sahling, Sass Mikkelsen and González Parrao2017, 63). However, this lack of full civil service protections is not necessarily inimical to meritocracy and performance, and has arguably moved Chile from a closed Weberian model to a more open, managerial one (Dahlström and Lapuente Reference Dahlström and Lapuente2017). The balance between protecting the civil service from politicization and incentivizing flexibility and performance is difficult, but at the very least we can say that the long-term growth of the yearly regime does not seem—thus far—to have resulted in instability or large-scale patronage.

These results highlight the importance and limits of de jure institutions in shaping behavior, as well as the relevance of politics. Public bureaucracies would be thought to be tightly shaped by formal law, but this is only partially true. The law does determine some behaviors, such as higher wages for agencies on the supervisory scale. However, other laws seem irrelevant, such as the 20 percent cap on yearly contracts, which Congress regularly overrides through budget amendments, in a move of dubious constitutionality (Rajevic Reference Rajevic2018, 413) that could perhaps be considered a legalistic form of “noncompliance” (Brinks et al. Reference Brinks, Levitsky and Victoria Murillo2020). Perhaps more surprisingly, agencies with special employment laws designating all positions as trust-based (such as the Pension Regulator) are not more unstable or exposed to political cycles. Moreover, the large variability in turnover between agencies, most based on the same standard employment rules (e. g., the Budget Office and the Youth Institute), suggests that turnover is the product of political equilibria, with some institutions regarded by different governments as outside interference and others considered “fair game” for personnel rotation.

All in all, our study confirms some facts we knew from the literature, such as the increasing dominance of the yearly regime, the perception that the civil service offers few possibilities for advancement, and that agencies vary widely in their personnel management practices (Schuster et al. Reference Schuster, Meyer-Sahling, Sass Mikkelsen and González Parrao2017). However, we have provided novel quantification of these phenomena. Our study has also revealed some original findings, such as the existence of a small political cycle in employment, the structure of professions within the state, and the difference in stability of employment among different ranks. We have also produced mappings of agencies along crucial dimensions, such as wages and turnover, none of which have, to our knowledge, been known or assessed in the literature.

We believe that these descriptive findings advance our empirical knowledge of Latin American bureaucracies (and beyond) by quantifying important bureaucratic indicators related to personnel characteristics and career dynamics. These results also can set a comparative benchmark to study other bureaucracies in the region. Given that Chile is thought to be a relatively Weberian case in Latin America, we would expect higher turnover rates and lower professionalization in most other cases, though with “pockets of effectiveness” coexisting with more politicized agencies almost everywhere. Future research and more widespread data availability will be needed to determine if this is the case.

Acknowledgments

This study received financial support from ANID through FONDEF ID19I10198. The authors would like to thank three anonymous reviewers for their helpful comments and suggestions. They would also like to thank the research assistance of Javiera Monreal, Daniela Saralegui, Paula Dastres, Diego Correa, and particularly Samanta Oliva, who at different times and in different capacities over the years helped with the downloading and/or cleaning of the data for this project. Daniel Brieba would also like to thank Andrés Scherman for his comments on an earlier version of this paper in the Seminario Escuela de Gobierno, Universidad Adolfo Ibáñez, in October 2022.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.1017/lap.2023.41

Supporting Information

Additional supporting materials may be found with the online version of this article on the publisher’s website: Appendix.

Footnotes

Conflict of interest: The authors declare no conflict of interest in the publication of this manuscript.

1 We use “rotation” and “turnover” as synonyms in what follows.

2 See figure A8 in annex 3 to see how grades are distributed according to rank.

3 By presidential directive in 2006, and by law since 2009.

4 It is important to note that not all these fields were required from the start. For instance, information on wages is available for most services only from 2010–11 on.

5 For a more detailed explanation of the process of data downloading, cleaning, and record linkage, see annex 1 online.

6 In fact, we have full data for this agency for November 2018 and January 2019, so the absence of December 2018—which is the month used by DIPRES to report its data—is not actually problematic.

7 We excluded temporary personnel because DIPRES (2011) does not report them for the 2006–10 period. For the 2011–19 period, our data are highly accurate for most agencies, though we register slightly more temporary employees than does DIPRES.

8 For a detailed analysis of the coverage and quality of the data, see annex 2 online.

9 In what follows, we use the expressions “contract regime,” “employment regime,” “contract type,” and “contract modality” interchangeably.

10 Turnover (here and throughout) is measured as the percentage of job spells that ended in a given year as a proportion of all job spells active during that year.

11 This agency represents between 11 percent and 18 percent of all data in a given year. See annex 3 for the same graph but with JUNJI included.

12 See annex 1 for a detailed explanation of how job spells were created.

13 Progression in job spells was calculated as “Grade in first month of job spell” minus “Grade in last month of job spell” (excluding all job spells that began or ended as temporary). Progression for individuals was calculated as “Grade in first month of first job spell” minus “Grade in last month of last job spell.” Substantively similar results are obtained if we use minimum and maximum grades across job spells and individuals, but these are slightly misleading, as they eliminate negative values and are more sensitive to errors in the data.

14 See annex 1 for a brief explanation of this procedure.

15 The quality of this data improves over time, and from 2012 on we have a nonmissing qualification for 98 percent of individuals each year.

16 These agencies disappeared after a reform that came into effect in 2021.

References

Akhtari, Mitra, Moreira, Diana, and Trucco, Laura. 2022. Political Turnover, Bureaucratic Turnover, and the Quality of Public Services. American Economic Review 112, 2: 442–93.CrossRefGoogle Scholar
Alberts, Susan, Dávila, Marcela, and Valenzuela, Arturo. 2021. Modernizing the State to Strengthen Democracy: Public Sector Reforms in Chile. In The Emerald Handbook of Public Administration in Latin America, ed. Guy Peters, B., Tercedor, Carmen Avilés, and Ramos, Carlos. Leeds: Emerald Publishing. 81114.CrossRefGoogle Scholar
Andersen, David, and Møller, Jørgen. 2019. The Transhistorical Tension Between Bureaucratic Autonomy and Political Control. Political Studies Review 17, 3: 284–95.CrossRefGoogle Scholar
Bersch, Katherine, López, Lee J., and Taylor, Matthew M.. 2022. The Patronage Coalition: Party Discipline and Support for the Government in Brazil. Legislative Studies Quarterly 47, 1: 130.Google Scholar
Bersch, Katherine, Praça, Sérgio, and Taylor, Matthew M.. 2017. State Capacity, Bureaucratic Politicization, and Corruption in the Brazilian State. Governance 30: 105–24.CrossRefGoogle Scholar
Bolton, Alexander, de Figueiredo, John M., and Lewis, David E.. 2021. Elections, Ideology, and Turnover in the US Federal Government. Journal of Public Administration Research and Theory 31, 2: 451–66.CrossRefGoogle Scholar
Brinks, Daniel M., Levitsky, Steven, and Victoria Murillo, María, eds. 2020. The Politics of Institutional Weakness in Latin America. Cambridge: Cambridge University Press. doi: 10.1017/9781108776608.CrossRefGoogle Scholar
Centro de Estudios Públicos, Chile 21, Espacio Público, and Libertad y Desarrollo. 2018. Gestión de Personas en el Estado. https://www.cepchile.cl/wp-content/uploads/2022/09/libro_gestion_3ene2018.pdf Google Scholar
Cingolani, Luciana, Thomsson, Kaj, and de Crombrugghe, Denis. 2015. Minding Weber More Than Ever? The Impacts of State Capacity and Bureaucratic Autonomy on Development Goals. World Development 72: 191207.CrossRefGoogle Scholar
Colonnelli, Emanuele, Prem, Mounu, and Teso, Edoardo. 2020. Patronage and Selection in Public Sector Organizations. American Economic Review 110, 10: 3071–99.CrossRefGoogle Scholar
Cornell, Agnes. 2014. Why Bureaucratic Stability Matters for the Implementation of Democratic Governance Programs. Governance 27, 2: 191214.CrossRefGoogle Scholar
Dahlström, Carl, and Lapuente, Victor. 2017. Organizing Leviathan: Politicians, Bureaucrats, and the Making of Good Government. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Dahlström, Carl, Lapuente, Victor, and Teorell, Jan. 2012. The Merit of Meritocratization: Politics, Bureaucracy, and the Institutional Deterrents of Corruption. Political Research Quarterly 65, 3: 656–68.CrossRefGoogle Scholar
Dirección de Presupuestos del Ministerio de Hacienda (DIPRES). 2011. Estadísticas de recursos humanos del sector público, 2001–2010. https://www.dipres.gob.cl/598/articles-82274_doc_pdf.pdf Accessed August 16, 2023.Google Scholar
Dirección de Presupuestos del Ministerio de Hacienda (DIPRES). 2023. Personal disponible en el Gobierno Central al final de cada año, 2011–2022. Excel file. https://www.dipres.gob.cl/598/articles-190248_doc_18.xlsx. Accessed August 20, 2023.Google Scholar
Evans, Peter B., and Rauch, James E.. 1999. Bureaucracy and Growth: A Cross-National Analysis of the Effects of “Weberian” State Structures on Economic Growth. American Sociological Review 64, 5: 748–65.Google Scholar
Ferraro, Agustín. 2008. Friends in High Places: Congressional Influence on the Bureaucracy in Chile. Latin American Politics and Society 50, 2: 101–29.CrossRefGoogle Scholar
Fraile, Amaya. 2018. 13 años de funcionamiento del Sistema de Alta Dirección Pública. Un modelo de gestión incompleto. In Un estado para la ciudadanía, ed. Isabel Aninat and Slaven Razmilic. Santiago: Centro de Estudios Públicos, 403–432.Google Scholar
Fuenzalida, Javier, and Riccucci, Norma M.. 2019. The Effects of Politicization on Performance: The Mediating Role of HRM Practices. Review of Public Personnel Administration 39, 4: 544–69. https://doi.org/10.1177/0734371X18758378.CrossRefGoogle Scholar
Fukuyama, Francis. 2013.What Is Governance? Governance 26, 3: 347–68.CrossRefGoogle Scholar
Geddes, Barbara. 1990. Building “State” Autonomy in Brazil, 1930–1964. Comparative Politics 22, 2: 217–35.CrossRefGoogle Scholar
Gingerich, Daniel. 2013. Governance Indicators and the Level of Analysis Problem: Empirical Findings from South America. British Journal of Political Science 43, 3: 505–40.CrossRefGoogle Scholar
González-Bustamante, Bastián. 2020. The Politics-Administration Dichotomy: A Case Study of the Chilean Executive During the Democratic Post-Transition. Bulletin of Latin American Research 39, 5: 582–97. https://doi.org/10.1111/blar.13044 CrossRefGoogle Scholar
González-Bustamante, Bastián, and Olivares, Alejandro. 2016. Cambios de gabinete y supervivencia de los ministros en Chile durante los gobiernos de la Concertación (1990–2010). Colombia Internacional 87: 81108.CrossRefGoogle Scholar
González-Bustamante, Bastián, Alejandro Olivares, L., Abarca, Pedro, and Molina, Esteban. 2016. Servicio civil en Chile, análisis de los directivos de primer nivel jerárquico (2003–13). Revista de Administração Pública 50, 1: 5979.CrossRefGoogle Scholar
Grindle, Merilee S. 2012. Jobs for the Boys: Patronage and the State in Comparative Perspective. Cambridge: Harvard University Press.CrossRefGoogle Scholar
Henderson, Jeffrey, Hulme, David, Jalilian, Hossein, and Phillips, Richard. 2007. Bureaucratic Effects: “Weberian” State Agencies and Poverty Reduction. Sociology 41, 3: 515–32.CrossRefGoogle Scholar
Iacoviello, Mercedes, and Strazza, Luciano. 2014. Diagnostic of the Civil Service in Latin America. In Serving Citizens: A Decade of Civil Service Reforms in Latin America (2004–2013), ed. Juan Carlos Cortázar Velarde et al. Washington, DC: Inter-American Development Bank.Google Scholar
Kaufmann, Daniel, and Kraay, Aart. 2023. Worldwide Governance Indicators, 2023. Update..www.govindicators.org), Accessed October 19, 2023.Google Scholar
Kaufmann, Daniel, Kraay, Aart, and Mastruzzi, Massimo. 2007. Growth and Governance: A Reply. Journal of Politics 69, 2: 555–62.CrossRefGoogle Scholar
Kopecký, Petr, Meyer Sahling, Jan-Hinrik, Panizza, Francisco, et al. 2016. Party Patronage In Contemporary Democracies: Results From An Expert Survey In 22 Countries From Five Regions. European Journal of Political Research 55, 2: 416–31.CrossRefGoogle Scholar
Kurtz, Marcus J., and Schrank, Andrew. 2007. Growth and Governance: Models, Measures, and Mechanisms. Journal of Politics 69, 2: 538–54.CrossRefGoogle Scholar
McDonnell, Erin, and Vilaca, Luiz. 2021. Pockets of Effectiveness and Islands of Integrity: Variation in Quality of Government Within Central State Administrations. In The Oxford Handbook of the Quality of Government, ed. Bågenholm, Andreas, Bauhr, Monika, Grimes, Marcia, and Rothstein, Bo. Oxford: Oxford University Press, 662–683.Google Scholar
Moya Díaz, Emilio, and Garrido, Victor. 2022. Patronage in Chile: A Process in Reconfiguration. In Panizza 2022. 90–110.CrossRefGoogle Scholar
Munck, Gerardo L., and Pablo Luna, Juan. 2022. Latin American Politics and Society: A Comparative and Historical Analysis. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Nistotskaya, Marina, and Cingolani, Luciana. 2016. Bureaucratic Structure, Regulatory Quality, and Entrepreneurship in a Comparative Perspective: Cross-Sectional and Panel Data Evidence. Journal of Public Administration and Research Theory 26, 3: 519–34.CrossRefGoogle Scholar
Nistotskaya, Marina, Stefan Dahlberg, Carl Dahlström, et al. 2021. The Quality of Government Expert Survey 2020 (Wave III): Report. University of Gothenburg: QoG Working Paper Series 2021: 2. https://www.gu.se/en/quality-government/qog-data/data-downloads/qog-expert-survey Google Scholar
Olavarría-Gambi, Mauricio, and Dockendorff, Alejandra. 2016. Implementing Meritocracy in Senior Public Administration: The Dilemma for Chilean Politicians. Public Organization Review 16: 561–82.CrossRefGoogle Scholar
Panizza, Francisco, Guy Peters, B., and Ramos Larraburu, Conrado, eds. 2022. The Politics of Patronage Appointments in Latin American Central Administrations. Pittsburgh: University of Pittsburgh Press.Google Scholar
Pardo, Carlos, and Orellana, Patricia. 2009. Otros regímenes laborales especiales. In Un mejor estado para Chile: propuestas de modernización y reforma. Santiago: Consorcio para la Reforma del Estado. 489–524.Google Scholar
Park, Tae-Youn, and Shaw, Jason D.. 2013. Turnover Rates and Organizational Performance: A Meta-analysis. Journal of Applied Psychology 98, 2: 268309.CrossRefGoogle ScholarPubMed
Polga-Hecimovich, John, and Trelles, Alejandro. 2016. The Bureaucratic Politics of Administrative Reform in Latin America. Latin American Politics and Society 58, 4: 7196.Google Scholar
Rajevic, Enrique. 2018. La crisis de la regulación del empleo público en Chile. Ideas para un nuevo modelo. In Un estado para la ciudadanía: estudios para su modernización, ed. Isabel Aninat and Slaven Razmilic. Santiago: Centro de Estudios Públicos, 403–432.Google Scholar
Ramos, Conrado, and Milanesi, Alejandro. 2017. Public Management Models, Latin America. In Global Encyclopedia of Public Administration, Public Policy, and Governance, ed. Ali Farazmand. Cham: Springer International. 5148–55.Google Scholar
Salazar-Morales, Diego A., and Amaral Lauriano, Lucas. 2020. A Typology of the Latin American Civil Servant: Patronage Appointee, Technocrat, Loyalist, or Careerist. In The Palgrave Handbook of the Public Servant, ed. Sullivan, Helen, Dickinson, Helen, and Henderson, Hayley. Cham: Palgrave Macmillan. https://link.springer.com/referenceworkentry/10.1007/978-3-030-03008-7_71-1#chapter-info.Google Scholar
Schnose, Viktorya. 2015. Who Is In Charge Here? Legislators, Bureaucrats and the Policy Making Process. Party Politics 23, 4: 342–63.CrossRefGoogle Scholar
Schuster, Christian, Meyer-Sahling, Jan, Sass Mikkelsen, Kim, and González Parrao, Carolina. 2017. Prácticas de gestión de personas para un servicio público más motivado, comprometido y ético en Chile. Report prepared for the National Directorate of the Civil Service, Government of Chile. Santiago.Google Scholar
Toral, Guillermo. 2023. How Patronage Delivers: Political Appointments, Bureaucratic Accountability, and Service Delivery in Brazil. American Journal of Political Science. https://onlinelibrary.wiley.com/doi/10.1111/ajps.12758.Google Scholar
Zimmerman, Seth D. 2019. Elite Colleges and Upward Mobility to Top Jobs and Top Incomes. American Economic Review 109, 1: 147.CrossRefGoogle Scholar
Figure 0

Figure 1. Difference in Total Employees Between DIPRES and Our Data, by Year (percent)

Figure 1

Figure 2. Total of Employees by Agency/Year, DIPRES vs. Our DataNote: Scatterplots of the Budget Office’s estimates of employees in each agency/year against the same estimates derived from our data. Only agency/years with up to five thousand employees in the x axis (which are nearly all) are shown. For a plot covering all agencies, see figure A7 in online annex 2.

Figure 2

Figure 3. Distribution of Employment Regime by Year (percent)Note: Data include all agencies that have full data (i.e., beginning no later than February 2006 and ending on or after March 2020), but exclude JUNJI (which has missing data for 2011). Data are for the month of March in each year. See online annex 6 for the full list of included agencies.

Figure 3

Figure 4. Turnover Rates by Contract Type and Year (with 95 percent confidence intervals)Note: Data include all agencies that have full data (see online annex 6), excluding the statistics agency (see figure A4 in annex 1 for an explanation of this exclusion). “Presidential year” is defined in the text. Managerial positions are excluded.

Figure 4

Figure 5. Turnover Rates by Year, Without JUNJI (with 95 percent confidence intervals)Note: Data include all ranks and all agencies with full data (see online annex 6), except JUNJI. Permanent and yearly contracts only.

Figure 5

Figure 6. Kaplan Meier Survival Estimates by Rank (2006–2020)Note: Data include all agencies that have full data (see online annex 6).

Figure 6

Table 1. Initial and Final Contract Type, by Job Spell (totals and row percentages)

Figure 7

Figure 7. Percentage of Individuals with Only One Job Spell (Discounting All Fully Temporary Job Spells), by RankNote: Includes all agencies.

Figure 8

Figure 8. Grade Progression by Length of Job Spell (in years)Note: Calculation includes all nontemporary job spells in agencies with full data (see online annex 6). For ease of visualization, 0.12 percent of observations were excluded.

Figure 9

Figure 9. Word Clouds of Most Frequent Professions, for Top Grades Only and for All IndividualsNote: Includes all agencies.

Figure 10

Table 2. Most Frequent Professions in Top Grades

Figure 11

Table 3. Most Frequent Professions in Top Grades, Selected Agencies

Figure 12

Figure 10. Kaplan-Meier Survival Estimates, Selected Agencies, 2006–2020Note: Shorter lines correspond to agencies with fewer than 172 months of data.

Figure 13

Figure 11. Turnover by Agency, Year 1 of New Government vs Other YearsNote: Data include all agencies with full data (see online annex 6). Two agencies have two years of missing data. Presidential years (as defined in the text) are used.

Figure 14

Figure 12. Average Wage and Average Turnover by Agency, Top 8 Grades OnlyNote: Data include all agencies that have data beginning on or before January 2010 and ending on or after January 2020. Wages in nominal Chilean pesos. The y axis begins at 1,500,000 for better visualization. N = 86; four agencies have one or two years of missing data.

Supplementary material: File

Brieba et al. supplementary material

Brieba et al. supplementary material

Download Brieba et al. supplementary material(File)
File 873.7 KB