Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T05:48:28.989Z Has data issue: false hasContentIssue false

LABOR MARKET VOLATILITY, SKILLS, AND FINANCIAL GLOBALIZATION

Published online by Cambridge University Press:  03 April 2013

Claudia M. Buch
Affiliation:
University of Tübingen IAW and CESifo
Christian Pierdzioch*
Affiliation:
Helmut Schmidt University
*
Address correspondence to: Christian Pierdzioch, Department of Economics, Helmut-Schmidt-University, Holstenhofweg 85, 22008 Hamburg, Germany; e-mail: c.pierdzioch@hsu-hh.de.

Abstract

We analyze the impact of financial globalization on volatilities of hours worked and wages of high-skilled and low-skilled workers. Using cross-country, industry-level data for the years 1970–2004, we establish stylized facts that document how volatilities of hours worked and wages of workers with different skill levels have changed over time. We then document that the volatility of hours worked by low-skilled workers has increased the most in response to the increase in financial globalization. We develop a dynamic stochastic general equilibrium model of a small open economy that is consistent with the empirical results. The model predicts that greater financial globalization increases the volatility of hours worked, and this effect is strongest for low-skilled workers.

Type
Articles
Copyright
Copyright © Cambridge University Press 2013 

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.)

References

REFERENCES

Abowd, J.M. and Kramarz, F. (2003) The costs of hiring and separations. Labour Economics 10, 499530.Google Scholar
Adda, J. and Cooper, R. (2003) Dynamic Economics: Quantitative Methods and Applications. Cambridge, MA: MIT Press.Google Scholar
Atolia, M. and Buffie, E.B. (2011) Solving the unit root problem in models with an exogenous world market interest rate. Macroeconomic Dynamics 15, 681712.Google Scholar
Bates, D. and Maechler, M. (2009) Matrix: Sparse and Dense Matrix Classes and Methods. R package version 1.0-6. Available at http://CRAN.R-project.org/package=Matrix.Google Scholar
Blatter, M., Muehlemann, S., and Schenker, S. (2012) The costs of hiring skilled workers. European Economic Review 56, 2035.Google Scholar
Broersma, L. (2008) Differences in Unemployment by Educational Attainment in the US and Europe: What Role for Skill-Bias Technological Change and Institutions? EUKLEMS working paper 20, Groningen.Google Scholar
Campbell, J.R. and Hercowitz, Z. (2005) The Role of Collateralized Household Debt in Macroeconomic Stabilization. NBER working paper 11330, Cambridge, MA.Google Scholar
Coeurdacier, N. and Rey, H. (2012) Home Bias in Open Economy Financial Macroeconomics. CEPR discussion paper 8746, London.Google Scholar
Comin, D., Groshen, E.L., and Rabin, B. (2009) Turbulent firms, turbulent wages? Journal of Monetary Economics 56, 109133.Google Scholar
Crifo-Tillet, P. and Lehmann, E. (2004) Why will technical change not be permanently skill-biased? Review of Economic Dynamics 7, 157180.Google Scholar
Davidson, C. and Matusz, S.J. (2000) Globalisation and labour-market adjustment: How fast and at what cost? Oxford Review of Economic Policy 16, 4256.CrossRefGoogle Scholar
Davis, S.J. and Kahn, J.A. (2008) Interpreting the great moderation: Changes in the volatility of economic activity at the micro and macro levels. Journal of Economic Perspectives 22, 155180.CrossRefGoogle Scholar
Dew-Becker, I. and Gordon, R.J. (2008) The Role of Labor Market Changes in the Slowdown of European Productivity Growth. NBER working paper 13840, Cambridge MA.CrossRefGoogle Scholar
Di Giovanni, J and Levchenko, A.A. (2009) Trade openness and volatility. Review of Economics and Statistics 91, 558585.Google Scholar
European Central Bank [ECB] (2008) Financial Integration in Europe. Frankfurt am Main.Google Scholar
Feenstra, R.C. and Hanson, G.H. (1996) Globalisation, outsourcing, and wage inequality. American Economic Review 86, 240245.Google Scholar
Feenstra, R.C., Lipsey, R.E., Deng, H., Ma, A.C., and Mo, H. (2005) World Trade Flows: 1962–2000. NBER working paper 11040, Cambridge, MA.Google Scholar
Gali, J., López-Salido, J.D., and Vallés, J. (2007) Understanding the effects of government spending on consumption. Journal of the European Economic Association 5, 227270.Google Scholar
Gorbachev, O. (2011) Did household consumption become more volatile? American Economic Review 101, 22482270.CrossRefGoogle Scholar
Helpman, E. and Itskhoki, O. (2010) Labor market rigidities, trade and unemployment. Review of Economic Studies 77, 11001137.Google Scholar
Janko, Z. (2008) Nominal wage contracts, labor adjustment costs, and the business cycle. Review of Economic Dynamics 11, 434448.Google Scholar
Kim, S.H. and Kose, M.A. (2003) Dynamics of open-economy business-cycle models: Role of the discount factor. Macroeconomic Dynamics 7, 263290.Google Scholar
King, R.G. and Watson, M.W. (2002) System reduction and solution algorithms for singular linear difference systems under rational expectations. Computational Economics 20, 5786.Google Scholar
Kramarz, F. and Michaud, M.-L. (2010) The shape of hiring and separation costs in France. Labour Economics 17, 2737.Google Scholar
Krusell, P., Ohanian, L.E., Rios-Rull, J.V., and Violante, G.L. (2000) Capital-skill complementarity and inequality: A macroeconomic analysis. Econometrica 68, 10291053.Google Scholar
Lindquist, M.J. (2004) Capital-skill complementarity and inequality over the business cycle. Review of Economic Dynamics 7, 519540.Google Scholar
Mandelman, F.S. and Zlate, A. (2008) Immigration and the Macroeconomy. Working paper 2008-25, Federal Reserve Bank of Atlanta.Google Scholar
Organisation for Economic Co-Operation and Development [OECD] (2007) OECD workers in the global economy: Increasingly vulnerable?, Ch. 3, pp. 105–155. Paris: OECD.Google Scholar
Pesaran, M.H. (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 9671012.Google Scholar
Polgreen, L. and Silos, P. (2008) Capital-skill complementarity and inequality: A sensitivity analysis. Review of Economic Dynamics 11, 302313.Google Scholar
R Development Core Team (2012) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. Available at http://www.R-project.org.Google Scholar
Schindler, M. (2008) Measuring Financial Integration: A New Data Set. IMF Staff Papers 56, 222238.CrossRefGoogle Scholar
Schmitt-Grohé, S. and Uribe, M. (2003) Closing small open economy models. Journal of International Economics 61, 163185.CrossRefGoogle Scholar
Sitchinava, N. (2008) Trade, Technology, and Wage Inequality: Evidence from U.S. Manufacturing, 1989–2004. Mimeo, University of Oregon.Google Scholar
Stokey, N.L. (1996) Free trade, factornreturns, and factor accumulation. Journal of Economic Growth 1, 421447.Google Scholar
Timmer, M., O'Mahony, M., and van Ark, B. (2007) The EUKLEMS growth and productivity accounts: An overview. International Productivity Monitor 14, 7185.Google Scholar