Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-22T09:59:31.507Z Has data issue: false hasContentIssue false
  • English
  • Français

LABOR MARKET DYNAMICS UNDER TECHNOLOGY SHOCKS: THE ROLE OF SUBSISTENCE CONSUMPTION

Published online by Cambridge University Press:  11 June 2021

Sangyup Choi  and
Myungkyu Shim
Sangyup Choi*
Affiliation:
Yonsei University
Myungkyu Shim
Affiliation:
Yonsei University
*
Address correspondence to: Sangyup Choi, School of Economics, Yonsei University, Yonsei-ro 50, Seodaemun-gu, Seoul 03722, Republic of Korea. email: sangyupchoi@yonsei.ac.kr. Phone: +82 2 2123 2492.
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper establishes new stylized facts about labor market dynamics in developing economies, which are distinct from those in advanced economies, and then proposes a simple model to explain them. We first show that the response of hours worked and employment to a technology shock—identified by a structural VAR model with either short-run or long-run restrictions—is substantially smaller in developing economies. We then present compelling empirical evidence that several structural factors related to the relevance of subsistence consumption across countries can jointly account for the relative volatility of employment to output and that of consumption to output. We argue that a standard real business cycle (RBC) model augmented with subsistence consumption can explain the several salient features of business cycle fluctuations in developing economies, especially their distinct labor market dynamics under technology shocks.

Keywords

Business CyclesDeveloping EconomiesSubsistence ConsumptionLabor Market DynamicsIncome EffectVector Autoregressions
Type
Articles
Information
Macroeconomic Dynamics , Volume 26 , Issue 8 , December 2022 , pp. 1965 - 1993
Copyright
© Cambridge University Press 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We would like to thank two anonymous referees and the co-editor (Lee Ohanian) for their valuable comments. We are also grateful to Yongsung Chang, Chaoran Chen, Woojin Choi, Hyeon-Seung Huh, Jinwook Hur, Yongseung Jung, David Kim, Jinill Kim, Kwang Hwan Kim, David Lagakos, Byungchan Lee, Thomas Lubik, Jung Jae Park, Kwanho Shin, Denis Tkachenko, Donghoon Yoo, Andres Zambrano, and the seminar participants at the Korea Development Institute, Korea Institute for International Economic Policy, Korea University, National University of Singapore, Sogang University, University of Seoul, Yonsei University, the Fall 2018 Midwest Macroeconomic Meetings at Vanderbilt University, the 2018 China Meeting of the Econometric Society, the 1st Yonsei Macro-Finance Mini Conference, and the 13th Joint Economics Symposium of Six Leading East Asian Universities at Fudan University for their helpful comments and suggestions. All remaining errors are ours. Shim acknowledges the financial support from Yonsei University (Yonsei University Humanities and Social Science Research Grant (2020-22-0387)).

References

Abrigo, M. R. M. and Love, I. (2016) Estimation of panel vector autoregression in Stata. Stata Journal 16(3), 778–804.10.1177/1536867X1601600314CrossRefGoogle Scholar
Aguiar, M. and Gopinath, G. (2007) Emerging market business cycles: the cycle is the trend. Journal of Political Economy 115(1), 69–102.10.1086/511283CrossRefGoogle Scholar
Aknc, Ö. (2013) Global financial conditions, country spreads and macroeconomic fluctuations in emerging countries. Journal of International Economics 91(2), 358–371.Google Scholar
Basu, S., Fernald, J. G., and Kimball, M. S. (2006) Are technology improvements contractionary?. American Economic Review 96(5), 1418–1448.10.1257/aer.96.5.1418CrossRefGoogle Scholar
Bick, A., Fuchs-Schündeln, N., and Lagakos, D. (2018) How do hours worked vary with income? Cross-country evidence and implications. American Economic Review 108(1), 170–199.10.1257/aer.20151720CrossRefGoogle Scholar
Blanchard, O. J. and Quah, D. (1989) The Dynamic effects of aggregate demand and supply disturbances. American Economic Review 79(4), 655–673.Google Scholar
Boppart, T. and Krusell, P. (2020) Labor supply in the past, present, and future: a balanced growth perspective. Journal of Political Economy 128(1), 118–157.10.1086/704071CrossRefGoogle Scholar
Boz, E., Durdu, C. B., and Li, N. (2015) Emerging market business cycles: The role of labor market frictions. Journal of Money, Credit and Banking 47(1), 31–72.10.1111/jmcb.12168CrossRefGoogle Scholar
Canova, F. and Ciccarelli, M. (2013) Panel Vector Autoregressive Models: A Survey. In VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims (Advances in Econometrics, Vol. 32), 205-246, Emerald Group Publishing Limited.10.1108/S0731-9053(2013)0000031006CrossRefGoogle Scholar
Chang, Y. and Hong, J. H. (2006) Do technological improvements in the manufacturing sector raise or lower employment?. American Economic Review 96(1), 352–368.10.1257/000282806776157687CrossRefGoogle Scholar
Cho, D., Mok, J., and Shim, M. (2021) Leaning-against-the-wind: which policy and when?. The B.E. Journal of Macroeconomics 21(1), 125–150.10.1515/bejm-2019-0142CrossRefGoogle Scholar
Christiano, L. J. and Eichenbaum, M., and Vigfusson, R. (2004) The response of hours to a technology shock: evidence based on direct measures of technology. Journal of the European Economic Association 2(2-3), 381–395.10.1162/154247604323068078CrossRefGoogle Scholar
Da-Rocha, J. M. and Restuccia, D. (2006) The role of agriculture in aggregate business cycles. Review of Economic Dynamics 9(3), 455–482.10.1016/j.red.2005.12.002CrossRefGoogle Scholar
Dupaigne, M. and Féve, P. (2009) Technology shocks around the world. Review of Economic Dynamics 12(4), 592–607.10.1016/j.red.2008.12.002CrossRefGoogle Scholar
Fatás, A. and Mihov, I. (2001) Government size and automatic stabilizers: international and intranational evidence. Journal of International Economics 55(1), 3–28.10.1016/S0022-1996(01)00093-9CrossRefGoogle Scholar
Francis, N., and Ramey, V. A. (2005) Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited. Journal of Monetary Economics 52(8), 1379–1399.10.1016/j.jmoneco.2004.08.009CrossRefGoogle Scholar
Galí, J. (1999) Technology, employment, and the business cycle: do technology shocks explain aggregate fluctuations?. American Economic Review 89(1), 249–271.10.1257/aer.89.1.249CrossRefGoogle Scholar
Galí, J. (2004) On the role of technology shocks as a source of business cycles: Some new evidence. Journal of the European Economic Association 2(2-3), 372–380.10.1162/154247604323068069CrossRefGoogle Scholar
Galí, J. (2008) Monetary Policy, Inflation, and the Business Cycle. Princeton, NJ: Princeton University Press.Google Scholar
Garcia-Cicco, J., Pancrazi, R., and Uribe, M. (2010) Real business cycles in emerging countries?. American Economic Review 100(5), 2510–31.10.1257/aer.100.5.2510CrossRefGoogle Scholar
Greenwood, J., Hercowitz, Z., and Huffman, G. W. (1988) Investment, capacity utilization, and the real business cycle. American Economic Review 78(3), 402–417.Google Scholar
Horvath, J. (2018) Business cycles, informal economy, and interest rates in emerging countries. Journal of Macroeconomics 55, 96–116.10.1016/j.jmacro.2017.10.002CrossRefGoogle Scholar
Iacoviello, M. o (2015) Financial business cycles. Review of Economic Dynamics 18(1), 140–163.10.1016/j.red.2014.09.003CrossRefGoogle Scholar
Im, K. S., Hashem Pesaran, M., and Shin, Y. (2003) Testing for unit roots in heterogeneous panels. Journal of Econometrics 115(1), 53–74.10.1016/S0304-4076(03)00092-7CrossRefGoogle Scholar
Jaimovich, N. and Rebelo, S. (2009) Can News about the future drive the business cycle?. American Economic Review 99(4), 1097–1118.10.1257/aer.99.4.1097CrossRefGoogle Scholar
Judson, R. A and Owen, A. L. (1999) Estimating dynamic panel data models: a guide for macroeconomists. Economics letters 65(1), 9–15.10.1016/S0165-1765(99)00130-5CrossRefGoogle Scholar
Kim, S. (2015) Country characteristics and the effects of government consumption shocks on the current account and real exchange rate. Journal of International Economics 97(2), 436–447.10.1016/j.jinteco.2015.07.007CrossRefGoogle Scholar
King, R. G, Plosser, C. I, and Rebelo, S. T. (1988) Production, growth and business cycles: I. The basic neoclassical model. Journal of Monetary Economics 21(2-3), 195–232.10.1016/0304-3932(88)90030-XCrossRefGoogle Scholar
Kiviet, J. F. (1995) On bias, inconsistency, and efficiency of various estimators in dynamic panel data models. Journal of Econometrics 68(1), 53–78.10.1016/0304-4076(94)01643-ECrossRefGoogle Scholar
Kose, M. A., Otrok, C., and Whiteman, C. H. (2003) International business cycles: World, region, and country-specific factors. American Economic Review 93(4), 1216–1239.CrossRefGoogle Scholar
Li, Q., Shim, M., and Wen, Y. (2017) The implication of subsistence consumption for economic welfare. Economic Letters 158, 30–33.10.1016/j.econlet.2017.06.038CrossRefGoogle Scholar
Malik, A. and Temple, J. R. W. (2009) The geography of output volatility. Journal of Development Economics 90(2), 163–178.10.1016/j.jdeveco.2008.10.003CrossRefGoogle Scholar
Mendoza, E. G. (1991) Real business cycles in a small open economy. American Economic Review 81(4), 797–818.Google Scholar
Miyamoto, W. and Nguyen, T. L. (2017) Business cycles in small open economies: evidence from panel data between 1900 and 2013. International Economic Review 58(3), 1007–1044.10.1111/iere.12243CrossRefGoogle Scholar
Neumeyer, P. A. and Perri, F. (2005) Business cycles in emerging economies: the role of interest rates. Journal of Monetary Economics 52(2), 345–380.10.1016/j.jmoneco.2004.04.011CrossRefGoogle Scholar
Nickell, S. (1981) Biases in dynamic models with fixed effects. Econometrica 49(6), 1417–1426.10.2307/1911408CrossRefGoogle Scholar
Ohanian, L., Raffo, A., and Rogerson, R. (2008) Long-term changes in labor supply and taxes: Evidence from OECD countries, 1956-2004. Journal of Monetary Economics 55(8), 1353–1362.10.1016/j.jmoneco.2008.09.012CrossRefGoogle Scholar
Ohanian, L. and Raffo, A. (2012) Aggregate hours worked in OECD countries: New measurement and implications for business cycles. Journal of Monetary Economics 59(1), 40–56.10.1016/j.jmoneco.2011.11.005CrossRefGoogle Scholar
Özbilgin, H. M. (2010) Financial market participation and the developing country business cycle. Journal of Development Economics 92(2), 125–137.10.1016/j.jdeveco.2009.03.005CrossRefGoogle Scholar
Pesavento, E. and Rossi, B. (2005) Do technology shocks drive hours up or down? A little evidence from an agnostic procedure. Macroeconomic Dynamics 9(4), 478–488.10.1017/S1365100505040356CrossRefGoogle Scholar
Ravn, M. O., Schmitt-Grohe, S., and Uribe, M. (2008) The macroeconomics of subsistence points. Macroeconomic Dynamics 12(Supplement 1), 136–147.10.1017/S1365100507070095CrossRefGoogle Scholar
Restrepo-Echavarria, P. (2014) Macroeconomic volatility: the role of the informal economy. European Economic Review 70, 454–469.10.1016/j.euroecorev.2014.06.012CrossRefGoogle Scholar
Rodrik, D. (1998) Why do more open economies have bigger governments? Journal of Political Economy 106(5), 997–1032.10.1086/250038CrossRefGoogle Scholar
Schneider, F., Buehn, A., and Montenegro, C. E. (2010) New estimates for the shadow economies all over the world. International Economic Journal 24(4), 443–461.10.1080/10168737.2010.525974CrossRefGoogle Scholar
Sharif, M. (1986) The concept and measurement of subsistence: a survey of the literature. World Development 14(5), 555–577.10.1016/0305-750X(86)90124-5CrossRefGoogle Scholar
Steger, T. M. (2000) Economic growth with subsistence consumption. Journal of Development Economics 62(2), 343–361.10.1016/S0304-3878(00)00088-2CrossRefGoogle Scholar
Stock, J. H. and Watson, M. W. (2005) Understanding changes in international business cycle dynamics. Journal of the European Economic Association 3(5), 968–1006.10.1162/1542476054729446CrossRefGoogle Scholar
Storesletten, K., Zhao, B., and Zilibotti, F. (2019) Business cycle during structural change: Arthur Lewis’ Theory from a Neoclassical Perspective. NBER Working Paper No. 26181.10.3386/w26181CrossRefGoogle Scholar
Uribe, M. and Yue, V. Z. (2006) Country spreads and emerging countries: Who drives whom?. Journal of International Economics 69(1), 6–36.10.1016/j.jinteco.2005.04.003CrossRefGoogle Scholar
Yao, W. and Zhu, X. (in press) Structural change and aggregate employment fluctuations in China. International Economic Review. Google Scholar
Supplementary material: PDF

Choi and Shim supplementary material

Choi and Shim supplementary material

Download Choi and Shim supplementary material(PDF)
PDF 934.7 KB