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Set identification via quantile restrictions in short panels

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  • Rosen, Adam M.

Abstract

This paper studies the identifying power of conditional quantile restrictions in short panels with fixed effects. In contrast to classical fixed effects models with conditional mean restrictions, conditional quantile restrictions are not preserved by taking differences in the regression equation over time. This paper shows however that a conditional quantile restriction, in conjunction with a weak conditional independence restriction, provides bounds on quantiles of differences in time-varying unobservables across periods. These bounds carry observable implications for model parameters which generally result in set identification. The analysis of these bounds includes conditions for point identification of the parameter vector, as well as weaker conditions that result in point identification of individual parameter components.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 166 (2012)
Issue (Month): 1 ()
Pages: 127-137

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Handle: RePEc:eee:econom:v:166:y:2012:i:1:p:127-137

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Web page: http://www.elsevier.com/locate/jeconom

Related research

Keywords: Bound analysis; Conditional quantiles; Partial identification; Panel data; Fixed effects;

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References

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Citations

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Cited by:
  1. David Powell, 2010. "Unconditional Quantile Regression for Panel Data with Exogenous or Endogenous Regressors," Working Papers 710-1, RAND Corporation Publications Department.
  2. Damette, Olivier & Delacote, Philippe, 2012. "On the economic factors of deforestation: What can we learn from quantile analysis?," Economic Modelling, Elsevier, vol. 29(6), pages 2427-2434.
  3. Cooke, Edgar F. A., 2012. "Is the impact of AGOA heterogeneous?," MPRA Paper 43277, University Library of Munich, Germany.
  4. Antecol, Heather & Eren, Ozkan & Ozbeklik, Serkan, 2013. "The effect of Teach for America on the distribution of student achievement in primary school: Evidence from a randomized experiment," Economics of Education Review, Elsevier, vol. 37(C), pages 113-125.
  5. Shakeeb Khan & Maria Ponomareva & Elie Tamer, 2011. "Identification of Panel Data Models with Endogenous Censoring," Working Papers 11-07, Duke University, Department of Economics.
  6. Kwak, Sungil, 2011. "The Impact of Taxes on Charitable Giving: Empirical Evidence from the Korean Labor and Income Panel Study," MPRA Paper 36845, University Library of Munich, Germany.
  7. Harding, Matthew & Lamarche, Carlos, 2012. "Estimating and Testing a Quantile Regression Model with Interactive Effects," IZA Discussion Papers 6802, Institute for the Study of Labor (IZA).
  8. Harding, Matthew & Lamarche, Carlos, 2014. "Estimating and testing a quantile regression model with interactive effects," Journal of Econometrics, Elsevier, vol. 178(P1), pages 101-113.
  9. Antecol, Heather & Eren, Ozkan & Ozbeklik, Serkan, 2013. "The Effect of Teach for America on the Distribution of Student Achievement in Primary School: Evidence from a Randomized Experiment," IZA Discussion Papers 7296, Institute for the Study of Labor (IZA).
  10. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.

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