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EFFICIENCY, INEFFICIENCY, AND THE MENA FRONTIER

Published online by Cambridge University Press:  22 June 2017

Dimitris K. Christopoulos  and
Peter McAdam
Dimitris K. Christopoulos
Affiliation:
Panteion University
Peter McAdam*
Affiliation:
European Central Bank and University of Surrey
*
Address correspondence to: Peter McAdam, DG Research, European Central Bank, Sonnemannstrasse 20, 60314 Frankfurt am Main, Germany; e-mail: [email protected].
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Abstract

We examine technical efficiency in the Middle East and North Africa (MENA). In addition to economic indicators, political and social ones play a role in development and efficiency profiles. The MENA have been characterized by increasing economic efficiency over time but with marked polarization. We analyze and nest many key hypotheses, e.g., the contributions of religion, of natural resources, demographic pressures, human capital, etc. The originality of our contribution is the use of a large data set (including principal components), and extensive robustness checks. It should set a comprehensive benchmark and cross-check for related studies of development and technical efficiency.

Keywords

Frontier EfficiencyMENA
Type
Articles
Information
Macroeconomic Dynamics , Volume 23 , Issue 2 , March 2019 , pp. 489 - 521
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

We thank two referees, William H. Greene, Ian Jolliffe, Stas Kolenikov, Peter Schmidt, Elias Tzavalis, and many seminar audiences. The views expressed are those of the authors and not necessarily those of the ECB.

References

REFERENCES

Acemoglu, D., Aghion, P. and Zilibotti, F. (2006) Distance to frontier, selection, and economic growth. Journal of the European Economic Association 4 (1), 37–74.10.1162/jeea.2006.4.1.37Google Scholar
Acemoglu, D. and Robinson, J. (2012) Why Nations Fail. New York: Crown Business.Google Scholar
Aigner, D., Knox Lovell, C. and Schmidt, P. (1977) Formulation and estimation of stochastic frontier production function models. Journal of Econometrics 6 (1), 21–37.10.1016/0304-4076(77)90052-5Google Scholar
Amin, M., Assaad, R., al-Baharna, N., Dervis, K., Desai, R. M., Dhillon, N. S., Galal, A., Ghanem, H., Graham, C. and Kaufmann, D. (2012) After the Spring. New York: Oxford University Press.Google Scholar
Battese, G. and Coelli, T. (1995) A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics 20 (2), 325–332.10.1007/BF01205442Google Scholar
Benhabib, J. and Spiegel, M. (2005) Human capital and technology diffusion. In Aghion, P. and Durlauf, S. (eds.), Handbook of Economic Growth, vol. 1, chap. 13, pp. 935–966. North Holland: Elsevier.Google Scholar
Boutayeb, A. and Serghini, M. (2006) Health indicators and human development in the Arab region. International Journal of Health Geographics 61 (5), 1–13.Google Scholar
Charnes, A., Cooper, W. W. and Rhodes, E. L. (1978) Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444.10.1016/0377-2217(78)90138-8Google Scholar
Chen, Y.-Y., Schmidt, P. and Wang, H. -J. (2014) Consistent estimation of the fixed effects stochastic frontier model. Journal of Econometrics 181 (2), 65–76.10.1016/j.jeconom.2013.05.009Google Scholar
Christopoulos, D. K. (2007) Explaining country's efficiency performance. Economic Modelling 24 (2), 224–235.10.1016/j.econmod.2006.07.002Google Scholar
Christopoulos, D. K. and León-Ledesma, M. A. (2014) Efficiency and production Frontiers in the aftermath of recessions: International evidence. Macroeconomic Dynamics 18 (6), 1326–1350.10.1017/S1365100512000983Google Scholar
Dal Bo, E. and Rossi, M. A. (2007) Corruption and inefficiency: Theory and evidence from electric utilities. Journal of Public Economics 91 (5–6), 939–962.10.1016/j.jpubeco.2006.11.005Google Scholar
Draper, N. and Smith, H. (1981) Applied Regression Analysis. New York: John Wiley and Sons.Google Scholar
Faria, J. R. and McAdam, P. (2015) Macroeconomic adjustment under regime change: From social contract to Arab Spring. Journal of International Money and Finance 56, 1–22.10.1016/j.jimonfin.2015.04.001Google Scholar
Farrell, M. J. (1957) The measurement of productive efficiency. Journal of the Royal Statistical Society 120 (3), 253–290.10.2307/2343100Google Scholar
Galor, O. and Mountford, A. (2008) Trading population for productivity. Review of Economic Studies 75 (4), 1143–1179.10.1111/j.1467-937X.2008.00501.xGoogle Scholar
Gente, K., León-Ledesma, M. and Nourry, C. (2015) External constraints and endogenous growth: Why didn't some countries benefit from capital flows? Journal of International Money and Finance 56, 223–249.10.1016/j.jimonfin.2014.09.007Google Scholar
Gourdon, J. (2010) FDI flows and export diversification. In López-Cálix, J. R., Walkenhorst, P. and Diop, N. (eds.), Trade Competitiveness of the Middle East and North Africa, vol. 1, pp. 13–44. Washington, DC: World Bank Publications.Google Scholar
Greene, W. H. (2005) Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics 126, 269–303.10.1016/j.jeconom.2004.05.003Google Scholar
Greene, W. H. (2008a) Econometric Analysis. Upper Saddle River, NJ: Prentice Hall.Google Scholar
Greene, W. H. (2008b) The econometric approach to efficiency analysis. In Fried, H., Knox Lovell, C. and Schmidt, P. (eds.), The Measurement of Productive Efficiency, pp. 92–250. New York: Oxford University Press.10.1093/acprof:oso/9780195183528.003.0002Google Scholar
Growiec, J. (2012) The world technology frontier: What can we learn from the US States? Oxford Bulletin of Economics and Statistics 74 (6), 777–807.10.1111/j.1468-0084.2011.00686.xGoogle Scholar
Gylfason, T. (2001) Natural resources, education, and economic development. European Economic Review 45 (4–6), 847–859.10.1016/S0014-2921(01)00127-1Google Scholar
Henderson, D. J., Parmeter, C. F. and Russell, R. R. (2008) Modes, weighted modes, and calibrated modes. Journal of Applied Econometrics 23 (5), 607–638.10.1002/jae.1023Google Scholar
Henderson, D. J. and Russell, R. R. (2005) Human capital and convergence: A production-frontier approach. International Economic Review 46 (4), 1167–1205.10.1111/j.1468-2354.2005.00364.xGoogle Scholar
Henry, M., Kneller, R. and Milner, C. (2009) Trade, technology transfer and national efficiency in developing countries. European Economic Review 53 (2), 237–254.10.1016/j.euroecorev.2008.05.001Google Scholar
Herrala, R. and Turk Ariss, R. (2013) Credit Constraints, Political Instability, and Capital Accumulation: Evidence from the MENA Region. Working paper no. 13/246, International Monetary Fund.Google Scholar
Heyneman, S. (1993) Human development in the Middle East and North Africa Region. In El-Naggar, S. (ed.), Economic Development of the Arab Countries, vol. 1, pp. 204–226. Washington, DC: International Monetary Fund.Google Scholar
Huang, C. J. and Liu, J. -T. (1994) Estimation of a non-neutral stochastic frontier production function. Journal of Productivity Analysis 5, 171–180.10.1007/BF01073853Google Scholar
Imbs, J. and Wacziarg, R. (2003) Stages of diversification. American Economic Review 93 (1), 63–86.10.1257/000282803321455160Google Scholar
Jensen, R. (2007) The digital provide. Quarterly Journal of Economics 122 (3), 879–924.10.1162/qjec.122.3.879Google Scholar
Jolliffe, I. (2004) Principal Component Analysis. Amsterdam: Springer.Google Scholar
Kee, H. L., Nicita, A. and Olarreaga, M. (2009) Estimating trade restrictiveness indices. Economic Journal 119 (534), 172–199.Google Scholar
Kim, Y. and Schmidt, P. (2000) A review and empirical comparison of Bayesian and classical approaches to inference on efficiency levels in stochastic frontier models with panel data. Journal of Productivity Analysis 14 (2), 91–118.10.1023/A:1007801006988Google Scholar
Klump, R., McAdam, P. and Willman, A. (2007) Factor substitution and factor augmenting technical progress in the US. Review of Economics and Statistics 89, 183–192.10.1162/rest.89.1.183Google Scholar
Kneller, R. and Stevens, P. (2003) The specification of the aggregate production function in the presence of inefficiency. Economics Letters 81 (2), 223–226.10.1016/S0165-1765(03)00173-3Google Scholar
Kolenikov, S. and Angeles, G. (2009) Socioeconomic status measurement with discrete proxy variables. Review of Income and Wealth 55 (1), 128–165.10.1111/j.1475-4991.2008.00309.xGoogle Scholar
Kumar, S. and Russell, R. R. (2002) Technological change, technological catch-up, and capital deepening: Relative contributions to growth and convergence. American Economic Review 92 (3), 527–548.10.1257/00028280260136381Google Scholar
Kumbhakar, S. and Wang, H. -J. (2005) Estimation of growth convergence using a stochastic production frontier approach. Economics Letters 88 (3), 300–305.10.1016/j.econlet.2005.01.023Google Scholar
León-Ledesma, M., McAdam, P. and Willman, A. (2010) Identifying the elasticity of substitution with biased technical change. American Economic Review 100 (4), 1330–1357.10.1257/aer.100.4.1330Google Scholar
Lipset, S. (1959) Some social prerequisites for democracy. American Political Science Review 53 (1), 69–105.10.2307/1951731Google Scholar
Makdisi, S., Fattah, Z. and Liman, I. (2003) Determinants of Growth in the MENA Countries. Arab Planning Institute working paper no. 39.Google Scholar
Malik, A. and Awadallah, B. (2013) The economics of the Arab spring. World Development 45 (1), 296–313.10.1016/j.worlddev.2012.12.015Google Scholar
Meeusen, W. and van den Broeck, J. (1977) Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review 8, 435–444.10.2307/2525757Google Scholar
Myers, R. (1986) Classical and Modern Regression with Applications. Boston: Duxbury Press.Google Scholar
Nabli, M. (2007) Long term economic development challenges and prospects for the Arab countries. In Nabli, M. (ed.), Breaking the Barriers to Higher Economic Growth, vol. 1, pp. 3–28. Washington, DC: The World Bank.Google Scholar
Olson, M. (2000) Power and Prosperity. New York: Basic Books.Google Scholar
Ortega, J. F. and Gavilan, J. M. (2014) A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models. Communications in Statistics - Simulation and Computation 14 (7), 1714–1725.10.1080/03610918.2012.743564Google Scholar
Pires, J. O. and Garcia, F. (2012) Productivity of nations: A stochastic frontier approach to tfp decomposition. Economics Research International, Article ID 584869 (1–19).Google Scholar
Pritchett, L. (1999) Has Education Had a Growth Payoff in the MENA Region? Middle East and North Africa working paper 18, World Bank.Google Scholar
Rodrik, D. (2005) Growth strategies. In Aghion, P. and Durlauf, S. (eds.), Handbook of Economic Growth, vol. 1, pp. 967–1014. North Holland: Elsevier.Google Scholar
Rodrik, D. (2013) Unconditional convergence in manufacturing. Quarterly Journal of Economics 128 (1), 165–204.10.1093/qje/qjs047Google Scholar
Salehi-Isfahani, D., Tulani, I. and Assaad, R. (2009) A comparative study of returns to education of urban men in Egypt, Iran and Turkey. Middle East Development Journal 1 (2), 145–187.10.1142/S1793812009000085Google Scholar
Saliola, F. and Seker, M. (2011) Total Factor Productivity Across the Developing World. Enterprise Note 23, World Bank Group.Google Scholar
Schmidt, P. and Sickles, R. (1984) Production frontiers and panel data. Journal of Business and Economic Statistics 2 (4), 367–374.Google Scholar
Schwarz, R. (2013) War and State Building in the Middle East. Gainesville, FL: University Press of Florida.Google Scholar
Simar, L. and Wilson, P. W. (2007) Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics 136 (1), 31–64.10.1016/j.jeconom.2005.07.009Google Scholar
UNCTAD (2011) UN Conference on Trade and Development Database. www.unctad.org/Templates.Google Scholar
van den Broeck, J., Koop, G., Osiewalski, J. and Steel, M. (1994) Stochastic frontier models: A Bayesian perspective. Journal of Econometrics 61, 273–303.10.1016/0304-4076(94)90087-6Google Scholar
Walton, C. (2013) Revolution and Redistribution. Reflections on France and Egypt. www.booksandideas.net/IMG/pdf/20130423_revolution_walton.pdf.Google Scholar
Wang, H.-J. (2002) Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model. Journal of Productivity Analysis 18 (3), 241–253.10.1023/A:1020638827640Google Scholar
Wijeweera, A., Villano, R. and Dollery, B. (2010) Economic growth and FDI inflows: A stochastic frontier analysis. Journal of Developing Areas 43 (2), 143–158.10.1353/jda.0.0059Google Scholar
World Bank, T. (2004) Unlocking the Employment Potential in the Middle East and North Africa. MENA Development report, World-Bank Publications.Google Scholar
World Bank, T. (2009) From Privilege to Competition. Washington, DC: World-Bank Publications.10.1596/978-0-8213-7877-9Google Scholar