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Estimating dynamic models from repeated cross-sections

  • Verbeek, M.J.C.M.
  • Vella, F.

An important feature of panel data is that it allows the estimation of parameters characterizing dynamics from individual level data. Several authors argue that such parameters can also be identified from repeated cross-section data and present estimators to do so. This paper reviews the identification conditions underlying these estimators. As grouping data to obtain a pseudo-panel is an application of instrumental variables (IV), identification requires that standard IV conditions are met. This paper explicitly discuss the implications of these conditions for empirical analyses. We also propose a computationally attractive instrumental variables estimator that is consistent under a relatively weak set of conditions. A Monte Carlo study indicates that this estimator may work well in practice.

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Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2002-05.

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Date of creation: 13 Feb 2002
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Handle: RePEc:ems:eureir:582
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  1. Verbeek, M. & Nijman, T., 1992. "Minimum MSE Estimatin of a Regression Model with Fixed Effects from a Series of Cross Sections," Papers 9201, Tilburg - Center for Economic Research.
  2. Girma, Sourafel, 2000. "A quasi-differencing approach to dynamic modelling from a time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 98(2), pages 365-383, October.
  3. Richard Blundell & Martin Browning & Costas Meghir, 1993. "Consumer demand and the life-cycle allocation of household expenditures," IFS Working Papers W93/11, Institute for Fiscal Studies.
  4. Alessie, Rob & Devereux, Michael P. & Weber, Guglielmo, 1997. "Intertemporal consumption, durables and liquidity constraints: A cohort analysis," European Economic Review, Elsevier, vol. 41(1), pages 37-59, January.
  5. Verbeek, M.J.C.M. & Nijman, T.E., 1990. "Can cohort data be treated as genuine panel data?," Discussion Paper 1990-64, Tilburg University, Center for Economic Research.
  6. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
  7. Angrist, Joshua D., 1991. "Grouped-data estimation and testing in simple labor-supply models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 243-266, February.
  8. McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
  9. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  11. Moffitt, Robert, 1993. "Identification and estimation of dynamic models with a time series of repeated cross-sections," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 99-123, September.
  12. Nijman, T.E. & Verbeek, M.J.C.M., 1993. "Minimum MSE estimation of a regression model with fixed effects from a series of cross sections," Other publications TiSEM 34c1104a-a64b-4030-be99-b, Tilburg University, School of Economics and Management.
  13. 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.
  14. repec:ner:tilbur:urn:nbn:nl:ui:12-153277 is not listed on IDEAS
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