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Correcting Standard Errors in Two‐stage Estimation Procedures with Generated Regressands

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  • Michel Dumont
  • Glenn Rayp
  • Olivier Thas
  • Peter Willemé

Abstract

Feenstra and Hanson [NBER Working Paper No. 6052 (1997)] propose a procedure to correct the standard errors in a two‐stage regression with generated dependent variables. Their method has subsequently been used in two‐stage mandated wage models [Feenstra and Hanson, Quarterly Journal of Economics (1999) Vol. 114, pp. 907–940; Haskel and Slaughter, The Economic Journal (2001) Vol. 111, pp. 163–187; Review of International Economics (2003) Vol. 11, pp. 630–650] and for the estimation of the sector bias of skill‐biased technological change [Haskel and Slaughter, European Economic Review (2002) Vol. 46, pp. 1757–1783]. Unfortunately, the proposed correction is negatively biased (sometimes even resulting in negative estimated variances) and therefore leads to overestimation of the inferred significance. We present an unbiased correction procedure and apply it to the models reported by Feenstra and Hanson (1999) and Haskel and Slaughter (2002).

Suggested Citation

  • Michel Dumont & Glenn Rayp & Olivier Thas & Peter Willemé, 2005. "Correcting Standard Errors in Two‐stage Estimation Procedures with Generated Regressands," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(3), pages 421-433, June.
  • Handle: RePEc:bla:obuest:v:67:y:2005:i:3:p:421-433
    DOI: 10.1111/j.1468-0084.2005.00126.x
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    References listed on IDEAS

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    7. Haskel, Jonathan E. & Slaughter, Matthew J., 2002. "Does the sector bias of skill-biased technical change explain changing skill premia?," European Economic Review, Elsevier, vol. 46(10), pages 1757-1783, December.
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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