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A State Space Approach for Estimating VAR Models for Panel Data with Latent Dynamic Components

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    Abstract

    The econometric literature offers various modeling approaches for analyzing micro data in combination with time series of aggregate data. This paper discusses the estimation of a VAR model that allows unobserved heterogeneity across observation unit, as well as unobserved time-specific variables. The time-latent component is assumed to consist of a persistent and a transient term. By using a Helmert-type orthogonal transformation of the variables it is demonstrated that the likelihood function can be expressed on a state space form. The dimension of the state vector is low and independent of the time and cross section dimensions. This fact makes it convenient to employ an ECM algorithm for estimating the parameters of the model. An empirical application provides new insight into the problem of making forecasts for aggregate variables based on information from micro data.

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    File URL: http://www.ssb.no/a/publikasjoner/pdf/DP/dp295.pdf
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    Bibliographic Info

    Paper provided by Research Department of Statistics Norway in its series Discussion Papers with number 295.

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    Date of creation: Mar 2001
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    Handle: RePEc:ssb:dispap:295

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    Keywords: State space models; panel vector autoregressions; random components; latent time series; maximum likelihood; Kalman filter; Helmert transformation; aggregation; prediction.;

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    1. 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.
    2. Michael Binder & Cheng Hsiao & M. Hashem Pesaran, 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Banco de Espa�a Working Papers 0005, Banco de Espa�a.
    3. 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.
    4. R Blundell & Steven Bond, . "Initial conditions and moment restrictions in dynamic panel data model," Economics Papers W14&104., Economics Group, Nuffield College, University of Oxford.
    5. Biorn, Erik, 1981. "Estimating economic relations from incomplete cross-section/time-series data," Journal of Econometrics, Elsevier, vol. 16(2), pages 221-236, June.
    6. Danny Quah & Thomas J. Sargent, 1993. "A Dynamic Index Model for Large Cross Sections," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 285-310 National Bureau of Economic Research, Inc.
    7. 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.
    8. 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.
    9. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
    10. Michael Binder & Cheng Hsiao & M. Hashem Pesaran, 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Banco de Espa�a Working Papers 0005, Banco de Espa�a.
    11. Clements, Michael P & Hendry, David F, 1996. "Intercept Corrections and Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 475-94, Sept.-Oct.
    12. Cabalero, R.J., 1997. "Aggregaete Investment," Working papers 97-20, Massachusetts Institute of Technology (MIT), Department of Economics.
    13. Pesaran, M. H., 1999. "On Aggregation of Linear Dynamic Models," Cambridge Working Papers in Economics 9919, Faculty of Economics, University of Cambridge.
    14. Nyblom, Jukka & Harvey, Andrew, 2000. "Tests Of Common Stochastic Trends," Econometric Theory, Cambridge University Press, vol. 16(02), pages 176-199, April.
    15. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    16. Johansen, Soren, 1995. "The Role of Ancillarity in Inference for Non-stationary Variables," Economic Journal, Royal Economic Society, vol. 105(429), pages 302-20, March.
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