Addressing the Asymmetric Causality Between Technological Progress, Economic Globalization, and Income Distribution: The Application of Hatemi-J Approach

Year 2021, Volume: 5 Issue: 8, 35 - 55, 28.08.2021

Onur Özdemir

Abstract

Bölüşümle ilgili sorunlara ilişkin mevcut literatür son kırk yılda iki ana faktörün büyük bir öneme sahip olduğuna işaret etmektedir: (i) teknolojik ilerleme ve (ii) ekonomik küreselleşme. Ancak mevcut çalışmaların çoğu gelir dağılımı üzerindeki olumsuz yan etkilerinin aksine, her bir değişkenin ekonomik ilişkilerde tamamen yayılımını ön plana çıkaran argümanı desteklemektedir. Bu noktadan hareketle mevcut çalışma teknolojik ilerleme ve ekonomik büyümeden gelir dağılımına (emek payı ile ölçülen) nedensellik ilişkini 1970-2018 arası dönemde G-7 ekonomileri için emek payı üzerinde pozitif ve negatif şoklar sonucunda ortaya çıkan etkilerin yönünü belirlemek adına Hatemi-J asimetrik nedensellik testini uygulayarak araştırmaktadır. Ampirik bulgular teknolojik ilerlemenin ve ekonomik küreselleşmenin, şokların var olduğu durumda, emek payı üzerinde, ana akım görüşlerin aksine, büyük ölçüde olumsuz etkileri olduğunu göstermektedir.

Keywords

Gelir Dağılımı, Emek Payı, Teknolojik İlerleme, Ekonomik Küreselleşme, Hatemi-J Asimetrik Nedensellik Testi

Addressing the Asymmetric Causality Between Technological Progress, Economic Globalization, and Income Distribution: The Application of Hatemi-J Approach

Abstract

The existing literature on distributional concerns has been substantially pointed out the crucial importance of two major factors in the last four decades: (i) technological progress and (ii) economic globalization. However, instead of their negative side-effects on income distribution, most of the current studies have put forward the arguments that each indicator should be spread in the economic relations. Starting from that point of view, this paper investigates the causal relationship from technological progress and economic growth to income distribution (proxied by labor share of income) by implementing the Hatemi-J asymmetric causality test, which divides positive and negative shocks on the benchmark variables, across the G-7 economies over the 1970-2018 period. The empirical findings show that there are large negative effects of technological progress and economic globalization on labor’s share in the presence of shocks, which also contradicts with the mainstream wisdom.

Keywords

Income Distribution,, Labor Share of Income, Technological Progress, Economic Globalization, Hatemi-J Asymmetric Causality Test

References

• Acemoglu, D. (1998). Why Do New Technologies Complement Skills? Directed Technical Change and Wage Inequality. Quarterly Journal of Economics, 113(4), 1055-1089.
• Acemoglu, D. (2003). Labor- and Capital-Augmenting Technical Change. Journal of the European Economic Association, 1(1), 1-37.
• Aghion, P., Akcigit, U., Bergeaud, A., Blundell, R. and Hemous, D. (2019). Innovation and Top Income Inequality. The Review of Economic Studies, 86(1), 1-45.
• Akerlof, G. A. (1970). The Market for “Lemons”: Quality Uncertainty and the Market Mechanism. Quarterly Journal of Economics, 84(3), 488-500.
• Andersson, M. and Stone, T. A. (2017). Global Sourcing and Technical Efficiency – A Firm Level Study on the ICT Industry in Sweden. Journal of Business Economics and Management, 18(5), 877-896.
• Briguglio, L. and Vella, M. (2016). Technological Advance, the Labour Share of National Income and Income Inequality in the EU. Retrieved from https://core.ac.uk/download/pdf/83022416.pdf
• Dabla-Norris, M. E., Kochhar, M. K. Suphaphiphat, M. N., Ricka, M. F. and Tsounta, E. (2015). Causes and Consequences of Income Inequality: A Global Perspective. IMF Working Papers, SDN/15/13, June.
• Feenstra, R. C., Inklaar, R. and Timmer, M. P. (2015). The Next Generation of the Penn World Table. American Economic Review, 105(10), 3150-3182.
• Granger, C. W. J. and Yoon, G. (2002). Hidden Cointegration. Royal Economic Society Annual Conference 2002 92, Royal Economic Society.
• Gygli, S., Haelg, F., Potrafke, N. and Sturm, J.-E. (2019). The KOF Globalisation Index – Revisited. Review of International Organizations, 14(3), 543-574.
• Hatemi-J., A. (2012). Asymmetric Causality Tests with an Application. Empirical Economics, 43, 447-456.
• Hatemi-J., A., Gupta, R., Kasongo, A., Mboweni, T. and Netshitenzhe, N. (2014). Are there Asymmetric Causal Relationships between Tourism and Economic Growth in a Panel of G-7 Countries? Working Papers, 201476, University of Pretoria, Department of Economics.
• Im, K. S., Pesaran, M. H. and Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53-74.
• Maddala, G. S. and Wu, S. (1999). A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test. Oxford Bulletin of Economics and Statistics, 61(S1), 631-652.
• Mnif, S. (2016). Bilateral Relationship Between Technological Changes and Income Inequality in Developing Countries. Atlantic Review of Economics, Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, 1, 1-11.
• Neto, A. S. M. and Ribeiro, R. S. M. (2019). A Neo-Kaleckian Model of Skill-Biased Technological Change and Income Distribution. Review of Keynesian Economics, 7(3), 292-307.
• Ostry, J. D., Berg, A. and Tsangarides, C. G. (2014). Redistribution, Inequality, and Growth. IMF Working Papers, SDN/14/02, February.
• Pernica, M. (2017). The Business Impact Analysis of the Minimum Wage Valorisation. Business: Theory and Practice, 18, 88-95.
• Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. IZA Discussion Paper, No. 1240, August.
• Pesaran, M. H. (2006). Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica, 74(4), 967-1012.
• 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.
• Pesaran, M. H. and Yamagata, T. (2008). Testing Slope Homogeneity in Large Panels. Journal of Econometrics, 142, 50-93.
• Rajan, R. G. (2015). Democracy, Inclusion, and Prosperity. Speech at the D. D. Kosambi Ideas Festival Goa, India, February 20.
• Sanusi, K. A., Meyer, D. and Ślusarczyk, B. (2017). The Relationship Between Changes in Inflation and Financial Development. Polish Journal of Management Studies, 16(2), 253-265.
• Simionescu, M., Lazányi, K., Sopková, G., Dobeš, K. and Adam, P. B. (2017). Determinants of Economic Growth in V4 Countries and Romania. Journal of Competitiveness, 8(1), 103-116.
• Singh, A. and Dhumale, R. (2000). Globalization, Technology, and Income Inequality: A Critical Analysis. UNU World Institute for Development Economics Research, Working Papers No. 210, December.
• Solt, F. (2020). Measuring Income Inequality Across Countries and Over Time: The Standardized World Income Inequality Database. Social Science Quarterly, 101(3), 1183-1199.
• Spence, A. M. (1973). Job Market Signaling. Quarterly Journal of Economics, 87(3), 355-374.
• Stiglitz, J. (1974). Growth with Exhaustible Natural Resources: Efficient and Optimal Growth Paths. The Review of Economic Studies, 41, 123-137.
• Vveinhardt, J. and Kuklytė, J. (2016). Development Improvement Programme of Social Business Models in Lithuania. Forum Scientiae Oeconomia, 4(4), 149-170.
• Zarotiadis, G. and Gkagka, A. (2013). European Union: A Diverging Union? Journal of Post Keynesian Economics, 35(4), 537-568.
• Zhang, X., Wan, G., Wang, C. and Luo, Z. (2017). Technical Change and Income Inequality in China. World Economy, 2017;00:1-25.
• Zygmunt, A. (2017). Innovation Activities of Polish Firms. Multivariate Analysis of the Moderate Innovator Countries. Oeconomia Copernicana, 8(4), 505-521.