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Panel estimation of state-dependent adjustment when the target is unobserved

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  • Ulf Kalckreuth

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Abstract

Understanding adjustment processes has become central in economics. Empirical analysis is fraught with the problem that the target is usually unobserved. This paper develops, simulates and applies GMM methods for estimating dynamic adjustment models in a panel data context with partially unobserved targets and endogenous, time-varying persistence. In this setup, the standard first difference GMM procedure fails. I propose three estimation strategies. One is based on quasi-differencing, and it leads to two different, but related sets of moment conditions. The second is characterised by a statedependent filter, while the third is an adaptation of the GMM level estimator. -- Ökonomische Anpassungsvorgänge auf der Mikroebene sind inhärent schwierig zu schätzen, da typischerweise das Ziel der Anpassung nur unvollkommen beobachtet werden kann. Das vorliegende Papier untersucht zustandsabhängige ökonomische Anpassungsprozesse, wie sie sich bei zeitlich variablen Beschränkungen ergeben, wie etwa unter finanziellen Restriktionen. Das Problem latenter Zielniveaus wird hier mit Hilfe von Panelinformationen und einem Fehlerkomponentenansatz angegangen. Die Standardmethoden dynamische Panelmodelle, wie sie von Anderson and Hsiao (1982), Arellano and Bond (1991), Arellano and Bover (1995) and Blundell and Bond (1998) entwickelt wurden, sind auf diesen Fall nicht anwendbar, da sie eine zeitlich invariante lineare Dynamik voraussetzen. Das Papier zeigt, wie die GMM-Methodik auf den Fall ökonomischer Anpassungsvorgänge verallgemeinert werden können, bei denen das Ziel teilweise unbeobachtet ist und die Nichtlinearität die Form diskreter Regime annimmt. Dies ist nicht trivial, weil der unbekannte und zeitlich variable Anpassungskoeffizient mit dem ebenso unbekannten individuellen Störterm interagiert. Aber der Ertrag ist reichhaltig, weil eine Reihe wohlbekannter Prozeduren und Standardtests für das Problem der ökonomischen Anpassung nutzbar gemacht werden kann. Die hie

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 40 (2011)
Issue (Month): 1 (February)
Pages: 205-235

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Handle: RePEc:spr:empeco:v:40:y:2011:i:1:p:205-235

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Keywords: Dynamic panel data methods; Economic adjustment; GMM; Quasi-differencing; Non-linear estimation; C23; C15; D21;

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  1. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  2. von Kalckreuth, Ulf, 2008. "Financing constraints, firm level adjustment of capital and aggregate implications," Discussion Paper Series 1: Economic Studies 2008,11, Deutsche Bundesbank, Research Centre.
  3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  4. Ricardo J. Caballero & Eduardo M.R.A. Engel, 1994. "Explaining Investment Dynamics in U.S. Manufacturing: A Generalized (S,s) Approach," NBER Working Papers 4887, National Bureau of Economic Research, Inc.
  5. Bayer, Christian, 2006. "Investment dynamics with fixed capital adjustment cost and capital market imperfections," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1909-1947, November.
  6. Stephen Bond & Julie Ann Elston & Jacques Mairesse & Beno�t Mulkay, 2003. "Financial Factors and Investment in Belgium, France, Germany, and the United Kingdom: A Comparison Using Company Panel Data," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 153-165, February.
  7. Russell Cooper & Jonathan L. Willis, 2003. "The economics of labor adjustment: mind the gap," Staff Report 310, Federal Reserve Bank of Minneapolis.
  8. Ricardo J. Caballero & Eduardo M.R.A. Engel, 2004. "A Comment on the Economics of Labor Adjustment: Mind the Gap: Reply," American Economic Review, American Economic Association, vol. 94(4), pages 1238-1244, September.
  9. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  10. Bayer, Christian, 2008. "On the interaction of financial frictions and fixed capital adjustment costs: Evidence from a panel of German firms," Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3538-3559, November.
  11. Ulf Von Kalckreuth, 2006. "Financial Constraints and Capacity Adjustment: Evidence from a Large Panel of Survey Data," Economica, London School of Economics and Political Science, vol. 73(292), pages 691-724, November.
  12. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  13. Ricardo J. Caballero & Eduardo M. R. A. Engel & John C. Haltiwanger, 1995. "Plant-Level Adjustment and Aggregate Investment Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(2), pages 1-54.
  14. Bean, Charles R, 1981. "An Econometric Model of Manufacturing Investment in the UK," Economic Journal, Royal Economic Society, vol. 91(361), pages 106-21, March.
  15. Ricardo J. Caballero & Eduardo M.R.A. Engel, 2004. "Three Strikes and You're Out: Reply to Cooper and Willis," Cowles Foundation Discussion Papers 1456, Cowles Foundation for Research in Economics, Yale University.
  16. Ricardo J. Caballero & Eduardo M.R.A. Engel & John Haltiwanger, 1995. "Aggregate Employment Dynamics: Building From Microeconomic Evidence," NBER Working Papers 5042, National Bureau of Economic Research, Inc.
  17. Russell Cooper & Jonathan L. Willis, 2004. "A Comment on the Economics of Labor Adjustment: Mind the Gap," American Economic Review, American Economic Association, vol. 94(4), pages 1223-1237, September.
  18. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
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