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Identification and Panel Data Models with Endogenous Regressors

In: Econometrics, Statistics And Computational Approaches In Food And Health Sciences

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  • ALOK BHARGAVA

    (University of Houston, USA)

Abstract

This paper provides sufficient conditions for the identification of both static and dynamic models containing endogenous regressors from panel data by utilizing the restrictions across time periods on the parameters. It is shown that identification is achieved under quite weak conditions even in the presence of a general pattern of correlation between the errors and the time-varying variables. Efficient estimation procedures for the models considered and some specification tests are outlined. Finally, static formulations relating individuals' intakes of nutrients in the previous 24 hours to household incomes are estimated using (ICRISAT) panel data from rural India.

Suggested Citation

  • Alok Bhargava, 2006. "Identification and Panel Data Models with Endogenous Regressors," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 3, pages 49-60, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789812773319_0003
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    Keywords

    Econometrics; Nutrition; Health; Child Development; Psychology; Behavioral Nutrition; Demography; Anthropology; Economic Development; Agricultural Economics; Environmental Sciences; Epidemiology; Nonlinear Optimization;

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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