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REGIONAL DISPARITIES IN LABOUR PRODUCTIVITY AND THE ROLE OF CAPITAL STOCK

Published online by Cambridge University Press:  28 July 2020

Ben Gardiner ,
Bernard Fingleton  and
Ron Martin
Ben Gardiner
Affiliation:
Director, Cambridge Econometrics, CambridgeUK, e-mail: [email protected].
Bernard Fingleton
Affiliation:
Department of Land Economy, University of Cambridge, e-mail: [email protected]
Ron Martin
Affiliation:
Department of Geography, University of Cambridge, e-mail: [email protected].
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Abstract

This paper reports on the availability of regional capital stock data,1 in the form of new/updated regional (NUTS2 level) capital stock estimates,2 building on an approach (Perpetual Inventory Method) which had been previously developed for the European Commission. The particular focus here is on the UK and how these data are used to shed light on regional labour productivity disparities. Using a NUTS2 level dataset constructed for the period 2000–16, we use a dynamic spatial panel approach from Baltagi et al. (2019) to estimate a model relating productivity to output (growth or levels) and augmented by explicit incorporation of capital stock plus various other covariates such as human capital. We find that regional variations in capital stocks per worker make a significant contribution to regional variations in labour productivity, but the geography of human capital is also highly relevant. Moreover, we give evidence to show that as human capital rises, notably as we move from the regions to London, the impact of capital stock per worker is less. The effect of capital stock depends on the level of human capital.

Keywords

Regional DisparitiesLabour ProductivityCapital StockDynamic Spatial Panel ModelC23C33D24O47R12
Type
Research Article
Information
National Institute Economic Review , Volume 253 , August 2020 , pp. R29 - R43
Copyright
© National Institute of Economic and Social Research, 2020

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References

REFERENCES

Alaimo, L.S. and Solivetti, L.M. (2019), ‘Territorial determinants of the Brexit vote’, Social Indicators Research, Springer, 144(2), pp. 647–67, July.10.1007/s11205-019-02066-3CrossRefGoogle Scholar
Alexander, W.R. (1994), ‘The investment–output ratio in growth regressions’, Applied Economic Letters, 1, pp 74–6.10.1080/135048594358177CrossRefGoogle Scholar
Arellano, M. and Bond, S.R. (1991), ‘Some tests of specification for panel data: Monte Carlo evidence and an application to employment’, Review of Economic Studies, 58, pp. 277–97.CrossRefGoogle Scholar
Bailey, N., Holly, S. and Pesaran, M.H. (2016), ‘A two-stage approach to spatio-temporal analysis with strong and weak cross-sectional dependence’, Journal of Applied Econometrics 31, pp. 249–80.CrossRefGoogle Scholar
Baltagi, B.H., Fingleton, B. and Pirotte, A. (2014), ‘Estimating and forecasting with a dynamic spatial panel model’, Oxford Bulletin of Economics and Statistics, 76, pp. 112–38.CrossRefGoogle Scholar
Baltagi, B.H., Fingleton, B. and Pirotte, A. (2019), ‘A time-space dynamic panel data model with spatial moving average errors’, Regional Science and Urban Economics, 76, pp. 13–31.CrossRefGoogle Scholar
Beaudry, C. and Schiffauerova, A. (2009), ‘Who’s right, Marshall or Jacobs? The localization versus urbanisation debate’, Research Policy, 38, pp. 318–37.10.1016/j.respol.2008.11.010CrossRefGoogle Scholar
Bond, S.R. (2002), ‘Dynamic panel data models: a guide to micro data methods and practice’, Portuguese Economic Journal, 1, pp. 141–62.CrossRefGoogle Scholar
Crafts, N. (2005), ‘Regional GDP in Britain, 1971–1911: some estimates’, Scottish Journal of Political Economy, 52, pp. 54–64.CrossRefGoogle Scholar
Derbyshire, J., Gardiner, B. and Waights, S. (2011), ‘Estimating the capital stock for the NUTS2 regions of the EU27’, Applied Economics, 45:9, pp. 1133–49.CrossRefGoogle Scholar
Duranton, G. and Puga, D. (2004), ‘Micro-foundations of urban agglomeration economies’, in Henderson, J.V. and Thisse, J-F. (Eds), Handbook of Regional and Urban Economics, Volume 4, Amsterdam: North-Holland, pp 2063–117.Google Scholar
Fingleton, B. and Szumilo, N. (2019), ‘Simulating the impact of transport infrastructure investment on wages: a dynamic spatial panel model approach’, Regional Science and Urban Economics, 75, pp. 148–64.CrossRefGoogle Scholar
Funk, M. and Strauss, J. (2000), ‘The long run relationship between productivity and capital’, Economic Letters, 69, pp. 213–7.10.1016/S0165-1765(00)00281-0CrossRefGoogle Scholar
Geary, F. and Stark, T. (2015), ‘Regional GDP in the UK, 1861–1911: new estimates’, Economic History Review, 68, pp. 123–44.10.1111/1468-0289.12061CrossRefGoogle Scholar
Geary, F. and Stark, T. (2016), ‘What happened to regional inequality in Britain in the twentieth century’, Economic History Review, 69, pp. 216–28.10.1111/ehr.12114CrossRefGoogle Scholar
Harris, R., Moffat, J., Evenhuis, E., Martin, R., Pike, A. and Sunley, P. (2019), ‘Does spatial proximity raise firm productivity? Evidence from British manufacturing’, Cambridge Journal of Regions, Economy and Society, 12, 3, November, pp. 467–87.Google Scholar
Haskel, J. and Westlake, S. (2018), Capitalism without Capital: The Rise of the Intangible Economy, Princeton University Press.10.1515/9781400888320CrossRefGoogle Scholar
H.M. Government (2010), Local Growth: Realising Every Place’s Potential, Cmnd 7961, London: H.M. Government.Google Scholar
H.M. Government (2017), Industrial Strategy: Building a Britain Fit for the Future, London: H.M. Government.Google Scholar
Marshall, A. (1890), Principles of Economics, London: Macmillan.Google Scholar
Martin, R.L. (1988), The Political Economy of Britain’s North-South Divide, Transactions of the Institute of British Geographers.CrossRefGoogle Scholar
Martin, R.L. (2004), ‘The contemporary debate over the North-South Divide: images and realities of regional inequality in late-twentieth century Britain’, in Baker, A.R.H. and Billinge, M. (Eds) Geographies of England: The North South Divide, Imagined and Material, Cambridge: Cambridge University Press, pp. 15–43.CrossRefGoogle Scholar
Martin, R.L. and Gardiner, B. (2017), ‘Reviving the Northern ‘Powerhouse’ and spatially rebalancing the British economy’, Chapter 2 in Berry, C. and Giovannini, A. (Eds), Developing England’s North: The Political Economy of the Northern Powerhouse, London: Palgrave-Macmillan, pp. 23–58.Google Scholar
Martin, R.L., Sunley, P., Gardiner, B.Evenhuis, E. and Tyler, P. (2018), ‘The city dimension to the productivity growth puzzle: the relative role of structural change and within-sector slowdown’, Journal of Economic Geography, 18, pp. 539–70.CrossRefGoogle Scholar
Manual, OECD (2009), Measuring Capital, Paris: OECD, available at http://www.oecd.org/dataoecd/16/16/43734711.pdf.Google Scholar
OECD (2020), The Spatial Dimension of Productivity: Connecting the Dots Across Firms, Industries and Places, Regional Development Report 2020/1, Paris: OECD.Google Scholar
Office for National Statistics (2019), Understanding spatial productivity in the UK, https://www.ons.gov.uk/employmentandlabourmarket/ people in work/labour produ ctivity/articles/understandingspatiallabourproductivityintheuk/2019-05-03.Google Scholar
Owyang, M. (2018), How Capital Deepening Affects Labour Productivity, Federal Reserve Bank of St Louis, https://www.stlouisfed.org/on-the-economy/2018/april/capital-deepening-affects-labor-productivity.Google Scholar
Pérez, J.E., and García, J.M. (2014), ‘New estimates of capital stocks for European regions (1995–2007)’, Revista de Economía Aplicada, 66, vol. XXII, pp. 113–37.Google Scholar
Pesaran, M.H. (2015), ‘Testing weak cross-sectional dependence in large panels’, Econometric Reviews, 34 (6–10), pp. 1088–116.CrossRefGoogle Scholar
Price Waterhouse, Coopers (2019), ‘What drives regional productivity gaps across the UK and how can these be closed?’, https://www.pwc.co.uk/economic-services/ukeo/ukeo-november-2019-regional-productivity.pdf.Google Scholar
Rosenthal, S. and Strange, W. (2003), ‘Geography, industrial organization, and agglomeration’, Review of Economics and Statistics, 85, pp. 377–93.CrossRefGoogle Scholar
Scott, P. (2007), The Triumph of the South: A Regional Economic History of Early Twentieth Century Britain, Farnham: Ashgate.Google Scholar
Zymek, R. and Jones, B. (2020), UK Regional Productivity Differences: An Evidence Review, Industrial Strategy Council.Google Scholar
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