Review of World Economics

, Volume 154, Issue 3, pp 617–647 | Cite as

The effects of globalization and technology on the elasticity of substitution

  • Hector Sala
  • Pedro Trivín
Original Paper


The elasticity of substitution between capital and labor (\(\sigma\)) is usually considered a “deep parameter”. This paper shows, in contrast, that \(\sigma\) is affected by both globalization and technology, and that different intensities in these drivers have different consequences for the OECD and the non-OECD economies. In the OECD, we find that the elasticity of substitution between capital and labor is below unity; that it increases along with the degree of globalization; but it decreases with the level of technology. Although results for the non-OECD area are more heterogeneous, we find that technology enhances the substitutability between capital and labor. We also find evidence of a non-significant impact of the capital-output ratio on the labor share irrespective of the degree of globalization (which would be consistent with an average aggregate Cobb–Douglas technology). Given the relevance of \(\sigma\) for economic growth and the functional distribution of income, the intertwined linkage among globalization, technology and the elasticity of substitution should be taken into account in any policy makers’ objective function.


Labor share Capital-output ratio Elasticity of substitution Globalization Technology 

JEL Classification

E25 F62 E22 O33 



We acknowledge helpful comments from three anonymous referees, which have led to significant improvements in the original version of this paper. Pedro Trivín acknowledges the warm hospitality received from the School of Economics and Finance of Queen Mary University of London, where the bulk of this work was developed. We are grateful to Ángel López, Matteo Fragetta, the participants in the XXIX Italian Conference of Labor Economics, the XI Spanish Conference of Labor Economics, the 39th SAEe, and the Economics Seminars at Ryerson University. We are also grateful to the Spanish Ministry of Economy and Competitiveness for financial support through Grant ECO2016-75623-R.

Supplementary material

10290_2018_315_MOESM1_ESM.pdf (278 kb)
Supplementary material 1 (pdf 277 KB)


  1. Abel, A. B., & Blanchard, O. J. (1983). An intertemporal model of saving and investment. Econometrica, 51(3), 675–92.CrossRefGoogle Scholar
  2. Acemoglu, D. (2003). Labor and capital-augmenting technical change. Journal of the European Economic Association, 1(1), 1–37.CrossRefGoogle Scholar
  3. Acemoglu, D., & Guerrieri, V. (2008). Capital deepening and nonbalanced economic growth. Journal of Political Economy, 116(3), 467–498.CrossRefGoogle Scholar
  4. Antony, J. (2009a). Capital/labor substitution, capital deepening, and FDI. Journal of Macroeconomics, 31(4), 699–707.CrossRefGoogle Scholar
  5. Antony, J. (2009b). A dual elasticity of substitution production function with an application to cross-country inequality. Economics Letters, 102(1), 10–12.CrossRefGoogle Scholar
  6. Antony, J. (2010). A class of changing elasticity of substitution production functions. Journal of Economics, 100(2), 165–183.CrossRefGoogle Scholar
  7. Antràs, P. (2004). Is the US aggregate production function Cobb–Douglas? New estimates of the elasticity of substitution. Contributions to Macroeconomics, 4(1), 1–36.Google Scholar
  8. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–97.CrossRefGoogle Scholar
  9. Arpaia, A., Pérez, E., & Pichelmann, K. (2009). Understanding labour income share dynamics in europe. MPRA Paper 15649, University Library of Munich, Germany.Google Scholar
  10. Barro, R., & Sala-i Martin, X. (2004). Economic Growth. McGraw-Hill Advanced Series in Economics. McGraw-Hill.Google Scholar
  11. Bentolila, S., & Saint-Paul, G. (2003). Explaining movements in the labor share. The B.E. Journal of Macroeconomics, 3(1), 1–33.Google Scholar
  12. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.CrossRefGoogle Scholar
  13. Bond, B., Hoeffler, A., & Temple, J. (2001). GMM estimation of empirical growth models. Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.Google Scholar
  14. Bond, S. (2002). Dynamic panel data models: A guide to micro data methods and practice. Portuguese Economic Journal, 1(2), 141–162.CrossRefGoogle Scholar
  15. Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding interaction models: Improving empirical analyses. Political Analysis, 14, 63–82.CrossRefGoogle Scholar
  16. Caselli, F., & Coleman, W. J. (2001). Cross-country technology diffusion: The case of computers. American Economic Review, 91(2), 328–335.CrossRefGoogle Scholar
  17. Chirinko, R. S. (2008). \(\sigma\): The long and short of it. Journal of Macroeconomics, 30(2), 671–686. The CES Production Function in the Theory and Empirics of Economic Growth.CrossRefGoogle Scholar
  18. Chirinko, R. S., & Mallick, D. (2014). The substitution elasticity, factor shares, long-run growth, and the low-frequency panel model. CESifo Working Paper Series 4895, CESifo Group Munich.Google Scholar
  19. Chudik, A., & Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188(2), 393–420. Heterogeneity in Panel Data and in Nonparametric Analysis in honor of Professor Cheng Hsiao.CrossRefGoogle Scholar
  20. Chudik, A., Pesaran, M. H., & Tosetti, E. (2011). Weak and strong crosssection dependence and estimation of large panels. Econometrics Journal, 14(1), C45–C90.CrossRefGoogle Scholar
  21. Coe, D. T., & Helpman, E. (1995). International R&D spillovers. European Economic Review, 39(5), 859–887.CrossRefGoogle Scholar
  22. de La Grandville, O. (1989). In quest of the slutsky diamond. American Economic Review, 79(3), 468–81.Google Scholar
  23. Dreher, A. (2006). Does globalization affect growth? Evidence from a new index of globalization. Applied Economics, 38(10), 1091–1110.CrossRefGoogle Scholar
  24. Eberhardt, M., Helmers, C., & Strauss, H. (2013). Do spillovers matter when estimating private returns to R&D? The Review of Economics and Statistics, 95(2), 436–448.CrossRefGoogle Scholar
  25. Eberhardt, M., & Presbitero, A. F. (2015). Public debt and growth: Heterogeneity and non-linearity. Journal of International Economics, 97(1), 45–58.CrossRefGoogle Scholar
  26. Eberhardt, M., & Teal, F. (2011). Econometrics for grumblers: A new look at the literature on crosscountry growth empirics. Journal of Economic Surveys, 25(1), 109–155.CrossRefGoogle Scholar
  27. Eberhardt, M., & Teal, F. (2013). Structural change and cross-country growth empirics. Policy Research Working Paper Series 6335, The World Bank.Google Scholar
  28. Falvey, R., Foster, N., & Greenaway, D. (2004). Imports, exports, knowledge spillovers and growth. Economics Letters, 85(2), 209–213.CrossRefGoogle Scholar
  29. Feenstra, R., & Hanson, G. (2001). Global production sharing and rising inequality: A survey of trade and wages. NBER Working Papers 8372, National Bureau of Economic Research, Inc.Google Scholar
  30. Feenstra, R. C., & Hanson, G. H. (1999). The impact of outsourcing and high-technology capital on wages: Estimates for the united states, 1979–1990. The Quarterly Journal of Economics, 114(3), 907–940.CrossRefGoogle Scholar
  31. Goldin, C., & Katz, L. F. (1996). The origins of technology-skill complementarity. NBER Working Papers 5657, National Bureau of Economic Research, Inc.Google Scholar
  32. Gollin, D. (2002). Getting income shares right. Journal of Political Economy, 110(2), 458–474.CrossRefGoogle Scholar
  33. Griliches, Z. (1969). Capital-skill complementarity. The Review of Economics and Statistics, 51(4), 465–68.CrossRefGoogle Scholar
  34. Hijzen, A., & Swaim, P. (2010). Offshoring, labour market institutions and the elasticity of labour demand. European Economic Review, 54(8), 1016–1034.CrossRefGoogle Scholar
  35. Irmen, A. (2008). Comment on “On the openness to trade as a determinant of the macroeconomic elasticity of substitution”. Journal of Macroeconomics, 30(2), 703–706.CrossRefGoogle Scholar
  36. Jayadev, A. (2007). Capital account openness and the labour share of income. Cambridge Journal of Economics, 31(3), 423–443.CrossRefGoogle Scholar
  37. Jones, L. E., & Manuelli, R. E. (1990). A convex model of equilibrium growth: Theory and policy implications. Journal of Political Economy, 98(5), 1008–38.CrossRefGoogle Scholar
  38. Jones, R., & Kierzkowski, H. (1998). Globalization and the consequences of international fragmentation. In G. C. Rudiger Dornbusch & M. Obsfeld (Eds.), Money, factor mobility and trade: The Festschrift in honor of Robert A. Mundell. Cambridge, MA: MIT Press.Google Scholar
  39. Karabarbounis, L., & Neiman, B. (2014). The global decline of the labor share. The Quarterly Journal of Economics, 129(1), 61–103.CrossRefGoogle Scholar
  40. Klump, R., & de La Grandville, O. (2000). Economic growth and the elasticity of substitution: Two theorems and some suggestions. American Economic Review, 90(1), 282–291.CrossRefGoogle Scholar
  41. Krusell, P., Ohanian, L. E., Ríos-Rull, J.-V., & Violante, G. L. (2000). Capital-skill complementarity and inequality: A macroeconomic analysis. Econometrica, 68(5), 1029–1054.CrossRefGoogle Scholar
  42. Madsen, J. (2010). Growth and capital deepening since 1870: Is it all technological progress? Journal of Macroeconomics, 32(2), 641–656.CrossRefGoogle Scholar
  43. Nickell, S. J. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–26.CrossRefGoogle Scholar
  44. Pedroni, P. (2007). Social capital, barriers to production and capital shares: implications for the importance of parameter heterogeneity from a nonstationary panel approach. Journal of Applied Econometrics, 22(2), 429–451.CrossRefGoogle Scholar
  45. Pesaran, M. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics 0435, Faculty of Economics, University of Cambridge.Google Scholar
  46. Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967–1012.CrossRefGoogle Scholar
  47. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22(2), 265–312.CrossRefGoogle Scholar
  48. Pesaran, M. H. (2015). Time series and panel data econometrics. Oxford: Oxford University Press.CrossRefGoogle Scholar
  49. Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79–113.CrossRefGoogle Scholar
  50. Raurich, X., Sala, H., & Sorolla, V. (2012). Factor shares, the price markup, and the elasticity of substitution between capital and labor. Journal of Macroeconomics, 34(1), 181–198.CrossRefGoogle Scholar
  51. Revankar, N. S. (1971). A class of variable elasticity of substitution production functions. Econometrica, 39(1), 61–71.CrossRefGoogle Scholar
  52. Rodrik, D. (1997). Has globalization gone too far?. Washington, DC: Peterson Institute for International Economics.Google Scholar
  53. Rognlie, M. (2015). Deciphering the fall and rise in the net capital share. Brookings papers on economic activity, BPEA.Google Scholar
  54. Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in stata. Stata Journal, 9(1), 86–136.Google Scholar
  55. Saam, M. (2008). Openness to trade as a determinant of the macroeconomic elasticity of substitution. Journal of Macroeconomics, 30(2), 691–702.CrossRefGoogle Scholar
  56. Sachs, J. (2000). Globalization and patterns of economic development. Review of World Economics, 136(4), 579–600.CrossRefGoogle Scholar
  57. Sato, R., & Hoffman, R. (1968). Production functions with variable elasticity of factor substitution: Some analysis and testing. The Review of Economics and Statistics, 50, 453–460.CrossRefGoogle Scholar
  58. Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. Horrace & R. Sickles (Eds.), The Festschrift in honor of Peter Schmidt. New York, NY: Springer.Google Scholar
  59. Slaughter, M. J. (2001). International trade and labor-demand elasticities. Journal of International Economics, 54(1), 27–56.CrossRefGoogle Scholar
  60. Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312–320.CrossRefGoogle Scholar
  61. Srinivasan, T. N. (1995). Long-run growth theories and empirics: Anything new? In Growth theories in light of the East Asian experience, NBER-EASE, Volume 4, NBER Chapters, pp. 37–70. National Bureau of Economic Research, Inc.Google Scholar
  62. Young, A. T., & Lawson, R. A. (2014). Capitalism and labor shares: A cross-country panel study. European Journal of Political Economy, 33(C), 20–36.CrossRefGoogle Scholar

Copyright information

© Kiel Institute 2018

Authors and Affiliations

  1. 1.Departament d’Economia AplicadaUniversitat Autònoma de BarcelonaBellaterraSpain
  2. 2.IZABonnGermany
  3. 3.Departament d’EconomiaUniversitat de GironaGironaSpain

Personalised recommendations