[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/582.html
   My bibliography  Save this paper

Estimating dynamic models from repeated cross-sections

Author

Listed:
  • Verbeek, M.J.C.M.
  • Vella, F.
Abstract
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.

Suggested Citation

  • Verbeek, M.J.C.M. & Vella, F., 2002. "Estimating dynamic models from repeated cross-sections," Econometric Institute Research Papers EI 2002-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:582
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/582/feweco20020213102507.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Richard Blundell & Martin Browning & Costas Meghir, 1994. "Consumer Demand and the Life-Cycle Allocation of Household Expenditures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(1), pages 57-80.
    2. 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.
    3. Verbeek, Marno & Nijman, Theo, 1992. "Can Cohort Data Be Treated as Genuine Panel Data?," Empirical Economics, Springer, vol. 17(1), pages 9-23.
    4. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    5. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    6. McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
    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. Verbeek, Marno & Nijman, Theo, 1993. "Minimum MSE estimation of a regression model with fixed effects from a series of cross-sections," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 125-136, September.
    9. 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.
    10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    11. 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.
    12. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Can cohort data be treated as genuine panel data?," Other publications TiSEM d4eada8f-b91c-4fe7-a58c-7, Tilburg University, School of Economics and Management.
    13. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rumman Khan, 2018. "Assessing cohort aggregation to minimise bias in pseudo-panels," Discussion Papers 2018-01, University of Nottingham, CREDIT.
    2. Inoue, Atsushi, 2008. "Efficient estimation and inference in linear pseudo-panel data models," Journal of Econometrics, Elsevier, vol. 142(1), pages 449-466, January.
    3. Dolores Collado, M., 1997. "Estimating dynamic models from time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 82(1), pages 37-62.
    4. Rumman Khan, 2021. "Assessing Sampling Error in Pseudo‐Panel Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 742-769, June.
    5. Paul J. Devereux, 2007. "Small-sample bias in synthetic cohort models of labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 839-848.
    6. Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers CWP40/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Tamvada, Jagannadha Pawan, 2010. "The Dynamics of Self-employment in a Developing Country: Evidence from India," MPRA Paper 20042, University Library of Munich, Germany.
    8. Charles Ackah, & Oliver Morrissey, & Simon Appleton, 2007. "Who Gains from Trade Protection in Ghana? A Household-Level Analysis," Discussion Papers 07/02, University of Nottingham, CREDIT.
    9. McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
    10. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2018. "Territorial and individual educational inequality: A Capability Approach analysis for Italy," Economic Modelling, Elsevier, vol. 71(C), pages 247-262.
    11. David Aristei & Luca Pieroni, 2010. "Habits, Complementarities and Heterogeneity in Alcohol and Tobacco Demand: A Multivariate Dynamic Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 428-457, August.
    12. Inkmann, Joachim & Klotz, Stefan & Pohlmeier, Winfried, 1998. "Growing into Work - Pseudo Panel Data Evidence on Labor Market Entrance in Germany," ZEW Discussion Papers 98-47, ZEW - Leibniz Centre for European Economic Research.
    13. Rosati, Nicoletta, 2013. "Efficiency of repeated-cross-section estimators in fixed-effects models," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1770-1775.
    14. Ortiz, Rodrigo & Fernandez, Viviana, 2022. "Business perception of obstacles to innovate: Evidence from Chile with pseudo-panel data analysis," Research in International Business and Finance, Elsevier, vol. 59(C).
    15. Dang,Hai-Anh H. & Lanjouw,Peter F., 2013. "Measuring poverty dynamics with synthetic panels based on cross-sections," Policy Research Working Paper Series 6504, The World Bank.
    16. D. Lederman & W.F. Maloney & J. Messina, 2011. "The Fall of Wage Flexibility," World Bank Publications - Reports 23575, The World Bank Group.
    17. Paquet, Marie-France & Bolduc, Denis, 2004. "Le problème des données longitudinales incomplètes : une nouvelle approche," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 341-361, Juin-Sept.
    18. Lavin, Felipe Vasquez & Bratti, Luna & Orrego, Sergio & Barrientos, Manuel, 2020. "Assessing the Use of Pseudo-panels to Estimate the Value of Statistical Life in Developing Countries," EfD Discussion Paper 20-20, Environment for Development, University of Gothenburg.
    19. Hai‐Anh H. Dang & Peter F. Lanjouw, 2023. "Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross Sections," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 599-622, June.
    20. Lederman, Daniel & Rojas, Diego, 2014. "Export shocks and the volatility of returns to schooling : evidence from twelve Latin American economies," Policy Research Working Paper Series 7144, The World Bank.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    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:ems:eureir:582. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.