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UNEMPLOYMENT PERSISTENCE AND QUANTILE PARAMETER HETEROGENEITY

Published online by Cambridge University Press:  28 September 2016

Corrado Andini  and
Monica Andini
Corrado Andini*
Affiliation:
University of Madeira, CEEAplA, and IZA
Monica Andini
Affiliation:
Bank of Italy
*
Address correspondence to: Corrado Andini, University of Madeira, 9000-390 Funchal, Portugal; e-mail: andini@uma.pt.
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Abstract

We argue that a random-coefficients representation of the classical Barro's model of unemployment dynamics can be used as a theoretical basis for a panel quantile autoregressive model of the unemployment rate. Estimating the latter with State-level data for the United States (1980–2010), we find that (i) unemployment persistence increases along quantiles of the conditional unemployment distribution; (ii) disregarding State-fixed effects implies an overestimation of unemployment persistence along unemployment quantiles; (iii) a macroeconomic shock changes not only the location but also the dispersion of the distribution of the State unemployment rates; (iv) a federal policy equally applied in each State can reduce unemployment inequality among States; (v) “hysteresis” and “natural rate” hypotheses can co-exist along quantiles of the unemployment distribution, with the former being not rejected at upper quantiles. In sum, while the standard approach to the estimation of unemployment persistence implicitly assumes that quantile parameter heterogeneity does not matter, we suggest that it does.

Keywords

Quantile RegressionUnemploymentDynamic Models
Type
Articles
Information
Macroeconomic Dynamics , Volume 22 , Issue 5 , July 2018 , pp. 1298 - 1320
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

We are grateful to an associate editor and two anonymous referees for valuable comments and suggestions, which have greatly improved the paper. We would like to thank Ivan Canay for extremely useful comments on an earlier version of this article. In addition, we are grateful to Gabriel Montes-Rojas for sharing a code in R used in his own work, which has helped us to understand some technical issues with the estimations performed in this paper. Finally, we are indebted to Steve Fleetwood, who has helped us to present our ideas more clearly. The views expressed in this paper do not necessarily reflect those of the institutions with which we are affiliated. The usual disclaimer applies.

References

REFERENCES

Alogoskoufis, G. and Manning, A. (1988) Wage setting and unemployment persistence in Europe, Japan and the USA. European Economic Review 32 (2–3), 698–706.CrossRefGoogle Scholar
Anderson, T.W. and Hsiao, C. (1981) Estimation of dynamic models with error components. Journal of the American Statistical Association 76 (375), 598–606.Google Scholar
Andini, M. and Andini, C. (2014) Finance, growth and quantile parameter heterogeneity. Journal of Macroeconomics 40, 308–322.Google Scholar
Arias, O., Hallock, K.F., and Sosa-Escudero, W. (2001) Individual heterogeneity in the returns to schooling: Instrumental variables quantile regression using twins data. Empirical Economics 26 (1), 7–40.Google Scholar
Barnichon, R. (2012) Vacancy posting, job separation and unemployment fluctuations. Journal of Economic Dynamics and Control 36 (3), 315–330.Google Scholar
Barnichon, R. and Figura, A. (2015) Labor market heterogeneity and the aggregate matching function. American Economic Journal: Macroeconomics 7 (4), 222–249.Google Scholar
Barro, R. (1988) The persistence of unemployment. American Economic Review 78 (2), 32–37.Google Scholar
Blanchard, O. (1991) Wage bargaining and unemployment persistence. Journal of Money, Credit and Banking 23 (3), 277–292.CrossRefGoogle Scholar
Blanchard, O. and Summers, L. (1986) Hysteresis and the European unemployment problem. In Fischer, S. (ed.), NBER Macroeconomics Annual 1986, vol. 1, pp. 15–78. Cambridge, MA: National Bureau of Economic Research.Google Scholar
Blundell, R.W. and Bond, S.R. (1998) Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87 (1), 115–143.Google Scholar
Canay, I. (2011) A simple approach to quantile regression for panel data. Econometrics Journal 14 (3), 368–386.Google Scholar
Cheng, K.M., Durmaz, N., Kim, H., and Stern, M. (2012) Hysteresis vs. natural rate of US unemployment. Economic Modelling 29 (2), 428–434.Google Scholar
Chernozhukov, V. and Hansen, C. (2006) Instrumental quantile regression inference for structural and treatment effect models. Journal of Econometrics 123 (2), 491–525.CrossRefGoogle Scholar
Chernozhukov, V. and Hansen, C. (2008) Instrumental variable quantile regression: A robust inference approach. Journal of Econometrics 142 (1), 379–398.CrossRefGoogle Scholar
Chernozhukov, V., Hansen, C., and Jansson, M. (2007) Inference approaches for instrumental variable quantile regression. Economics Letters 95 (2), 272–277.Google Scholar
Dromel, N.L., Kolakez, E., and Lehmann, E. (2010) Credit constraints and the persistence of unemployment. Labour Economics 17 (5), 823–834.CrossRefGoogle Scholar
Elmeskov, J. and MacFarlan, M. (1993) Unemployment persistence. OECD Economic Studies 21, 59–88.Google Scholar
Elsby, M.W.L., Hobijn, B., and Şahin, A. (2013) Unemployment dynamics in the OECD. Review of Economics and Statistics 95 (2), 530–548.Google Scholar
Fujita, S. and Ramey, G. (2009) The cyclicality of separation and job finding rates. International Economic Review 50 (2), 415–430.Google Scholar
Fujita, S. and Ramey, G. (2012) Exogenous versus endogenous separation. American Economic Journal: Macroeconomics 4 (4), 68–93.Google Scholar
Galvao, A.F. (2011) Quantile regression for dynamic panel data with fixed effects. Journal of Econometrics 164 (1), 142–157.Google Scholar
Galvao, A.F. and Montes-Rojas, G.V. (2009) Instrumental Variables Quantile Regression for Panel Data with Measurement Errors. Discussion paper number 09/06, Department of Economics, City University London.Google Scholar
Galvao, A.F. and Montes-Rojas, G.V. (2010) Penalized quantile regression for dynamic panel data. Journal of Statistical Planning and Inference 140 (11), 3476–3497.Google Scholar
Greenwald, B. and Stiglitz, J. (1995) Labor-market adjustments and the persistence of unemployment. American Economic Review 85 (2), 219–225.Google Scholar
Hall, R. (1979) A theory of the natural unemployment rate and the duration of employment. Journal of Monetary Economics 5 (2), 153–169.Google Scholar
Hamilton, J.D. (1994) Time Series Analysis. Princeton, NJ: Princeton University Press.Google Scholar
Harding, M. and Lamarche, C. (2009) A quantile regression approach for estimating panel data models using instrumental variables. Economics Letters 104 (3), 133–135.CrossRefGoogle Scholar
Jimeno, J.F. and Bentolila, S. (1998) Regional unemployment persistence (Spain, 1976–1994). Labour Economics 5 (1), 25–51.CrossRefGoogle Scholar
Khalifa, S. (2012) Job competition, crowding out, and unemployment fluctuations. Macroeconomic Dynamics 16 (1), 1–34.CrossRefGoogle Scholar
Koenker, R. (2004) Quantile regression for longitudinal data. Journal of Multivariate Analysis 91 (1), 74–89.Google Scholar
Koenker, R. and Bassett, G. (1978) Regression quantiles. Econometrica 46 (1), 33–50.CrossRefGoogle Scholar
Koenker, R. and Xiao, Z. (2006) Quantile autoregression. Journal of the American Statistical Association 101 (475), 980–990.CrossRefGoogle Scholar
Lamarche, C. (2010) Robust penalized quantile regression estimation for panel data. Journal of Econometrics 157 (2), 396–408.Google Scholar
Lee, S. (2007) Endogeneity in quantile regression models: A control function approach. Journal of Econometrics 141 (2), 1131–1158.CrossRefGoogle Scholar
León-Ledesma, M. (2002) Unemployment hysteresis in the US states and the EU: A panel approach. Bulletin of Economic Research 54 (2), 95–103.Google Scholar
Lin, H.Y. (2012) Dynamic Panel Quantile Regression. Mimeo, National Chengchi University.Google Scholar
Lin, H.Y. and Chu, H.P. (2013) Are fiscal deficits inflationary? Journal of International Money and Finance 32, 214–233.Google Scholar
Lindbeck, A. and Snower, D. (1987) Union activity, unemployment persistence and wage-employment ratchets. European Economic Review 31 (1/2), 157–167.CrossRefGoogle Scholar
Martins, P.S. and Pereira, P.T. (2004) Does education reduce wage inequality? Quantile regression evidence from 16 countries. Labour Economics 11 (3), 355–371.CrossRefGoogle Scholar
Mitchell, W.F. (1993) Testing for unit roots and persistence in OECD unemployment rates. Applied Economics 25 (12), 1489–1501.Google Scholar
Mortensen, D. (1989) The persistence and indeterminacy of unemployment in search equilibrium. Scandinavian Journal of Economics 91 (2), 347–370.CrossRefGoogle Scholar
Mortensen, D. and Pissadires, C. (1994) Job creation and job destruction in the theory of unemployment. Review of Economic Studies 61 (3), 397–415.Google Scholar
Ortigueira, S. (2006) Skills, search and the persistence of high unemployment. Journal of Monetary Economics 53 (8), 2165–2178.Google Scholar
Parente, P.M. and Silva, J.M. Santos (2016) Quantile regression with clustered data. Journal of Econometric Methods 5 (1), 1–15.CrossRefGoogle Scholar
Raurich, X., Sala, H., and Sorolla, V. (2006) Unemployment, growth, and fiscal policy: New insights on the hysteresis hypothesis. Macroeconomic Dynamics 10 (3), 285–316.CrossRefGoogle Scholar
Romero-Ávila, D. and Usabiaga, C. (2007) Unit root tests, persistence, and the unemployment rate of the U.S. states. Southern Economic Journal 73 (3), 698–716.Google Scholar
Rosen, A.M. (2012) Set identification via quantile restrictions in short panels. Journal of Econometrics 166 (1), 127–137.Google Scholar
Sephton, P.S. (2009) Persistence in U.S. state unemployment rates. Southern Economic Journal 76 (2), 458–466.Google Scholar
Shimer, R. (2012) Reassessing the ins and outs of unemployment. Review of Economic Dynamics 15 (2), 127–148.CrossRefGoogle Scholar