IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v40y2011i1p205-235.html
   My bibliography  Save this article

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

Author

Listed:
  • Ulf Kalckreuth

    ()

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Ulf Kalckreuth, 2011. "Panel estimation of state-dependent adjustment when the target is unobserved," Empirical Economics, Springer, vol. 40(1), pages 205-235, February.
    • Handle: RePEc:spr:empeco:v:40:y:2011:i:1:p:205-235
    DOI: 10.1007/s00181-010-0419-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-010-0419-y
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    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.
    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, 1999. "Explaining Investment Dynamics in U.S. Manufacturing: A Generalized (S,s) Approach," Econometrica, Econometric Society, vol. 67(4), pages 783-826, July.
    5. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    6. Stephen Bond & Julie Ann Elston & Jacques Mairesse & Benoît 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 W. Cooper & Jonathan L. Willis, 2001. "The economics of labor adjustment : mind the gap," Research Working Paper RWP 01-06, Federal Reserve Bank of Kansas City.
    8. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    9. Bean, Charles R, 1981. "An Econometric Model of Manufacturing Investment in the UK," Economic Journal, Royal Economic Society, vol. 91(361), pages 106-121, March.
    10. Caballero, Ricardo J. & Engel, Eduardo M.R.A., 2004. "Three Strikes and You're Out: Reply to Cooper and Willis," Center Discussion Papers 28498, Yale University, Economic Growth Center.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Caballero, Ricardo J & Engel, Eduardo M R A & Haltiwanger, John, 1997. "Aggregate Employment Dynamics: Building from Microeconomic Evidence," American Economic Review, American Economic Association, vol. 87(1), pages 115-137, March.
    18. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    19. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

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

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:40:y:2011:i:1:p:205-235. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://www.springer.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.