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Estimation of models with grouped and ungrouped data by means of "2SLS"

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  • Dhrymes, Phoebus J.
  • Lleras-Muney, Adriana

Abstract

This paper deals with a special case of estimation with grouped data, where the dependent variable is only available for groups, whereas the endogenous regressor(s) is available at the individual level. By estimating the first stage using the available individual data, and then estimating the second stage at the aggregate level, it might be possible to gain efficiency relative to the OLS and 2SLS estimators that use only grouped data. We term this the Mixed- 2SLS estimator (M2SLS). The M2SLS estimator is consistent and asymptotically normal. We also provide a test of efficiency of M2SLS relative to OLS and 2SLS estimators.
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Suggested Citation

  • Dhrymes, Phoebus J. & Lleras-Muney, Adriana, 2006. "Estimation of models with grouped and ungrouped data by means of "2SLS"," Journal of Econometrics, Elsevier, vol. 133(1), pages 1-29, July.
  • Handle: RePEc:eee:econom:v:133:y:2006:i:1:p:1-29
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    References listed on IDEAS

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    Cited by:

    1. Mick Silver, 2009. "The Hedonic Country Product Dummy Method and Quality Adjustments for Purchasing Power Parity Calculations," IMF Working Papers 09/271, International Monetary Fund.
    2. Fu, Shihe & Viard, Brian & Zhang, Peng, 2017. "Air Quality and Manufacturing Firm Productivity: Comprehensive Evidence from China," MPRA Paper 78914, University Library of Munich, Germany.
    3. Massa, Massimo & ┼Żaldokas, Alminas, 2014. "Investor base and corporate borrowing: Evidence from international bonds," Journal of International Economics, Elsevier, vol. 92(1), pages 95-110.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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