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Estimating and testing a quantile regression model with interactive effects

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  • Harding, Matthew
  • Lamarche, Carlos

Abstract

This paper proposes a quantile regression estimator for a model with interactive effects potentially correlated with covariates. We provide conditions under which the estimator is asymptotically Gaussian and we investigate the finite sample performance of the method. An approach to testing the specification against a competing fixed effects specification is introduced. The paper presents an application to study the effect of class size and composition on educational attainment. The evidence suggests that while smaller classes are beneficial for low performers, larger classes are beneficial for high performers. The fixed effects specification is rejected in favor of the interactive effects specification.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:econom:v:178:y:2014:i:p1:p:101-113
    DOI: 10.1016/j.jeconom.2013.08.010
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    Cited by:

    1. Temple, Jonathan & Van de Sijpe, Nicolas, 2017. "Foreign aid and domestic absorption," Journal of International Economics, Elsevier, vol. 108(C), pages 431-443.
    2. Hartley, Robert Paul & Lamarche, Carlos, 2017. "Behavioral Responses and Welfare Reform: Evidence from a Randomized Experiment," IZA Discussion Papers 10905, Institute for the Study of Labor (IZA).
    3. Ding, Weili & Lehrer, Steven F., 2014. "Understanding the role of time-varying unobserved ability heterogeneity in education production," Economics of Education Review, Elsevier, vol. 40(C), pages 55-75.
    4. Badi H. Baltagi & Peter Egger, 2016. "Estimation of structural gravity quantile regression models," Empirical Economics, Springer, vol. 50(1), pages 5-15, February.
    5. Simplice Asongu & Jacinta Nwachukwu, 2016. "Welfare Spending and Quality of Growth in Developing Countries: A Note on Evidence from Hopefuls, Contenders and Best Performers," Working Papers 16/028, African Governance and Development Institute..
    6. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Papers 1708.08622, arXiv.org.
    7. Nadine Levratto & Aziza Garsaa & Luc Tessier, 2013. "La Corse est-elle soluble dans le modèle méditerranéen ?," Working Papers hal-00842059, HAL.
    8. Harding, Matthew & Lamarche, Carlos, 2014. "A Hausman–Taylor instrumental variable approach to the penalized estimation of quantile panel models," Economics Letters, Elsevier, vol. 124(2), pages 176-179.
    9. Chen, Liang, 2015. "Set identification of panel data models with interactive effects via quantile restrictions," Economics Letters, Elsevier, vol. 137(C), pages 36-40.
    10. Carolina Castagnetti, 2015. "The Analysis of the Gender Wage Gap in the Italian Public Sector: a Quantile Approach for Panel Data," DEM Working Papers Series 109, University of Pavia, Department of Economics and Management.
    11. Nadine Levratto & Aziza Garsaa & Luc Tessier, 2013. "La Corse est-elle soluble dans le modèle méditerranéen ? Une analyse à partir d’une régression quantile sur données d’entreprises en panel entre 2004 et 2010. Is the Corsican economy a part of the Med," EconomiX Working Papers 2013-20, University of Paris Nanterre, EconomiX.
    12. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    13. Sylvie Charlot & Riccardo Crescenzi & Antonio Musolesi, 2014. "Augmented and Unconstrained: revisiting the Regional Knowledge Production Function," SEEDS Working Papers 2414, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Aug 2014.
    14. Sherrilyn Billger & Carlos Lamarche, 2015. "A panel data quantile regression analysis of the immigrant earnings distribution in the United Kingdom and United States," Empirical Economics, Springer, vol. 49(2), pages 705-750, September.
    15. repec:eee:econom:v:200:y:2017:i:1:p:59-78 is not listed on IDEAS
    16. Gonzalo, Jesús & Dolado Lobregad, Juan José & Chen, Liang, 2017. "Quantile Factor Models," UC3M Working papers. Economics 25299, Universidad Carlos III de Madrid. Departamento de Economía.

    More about this item

    Keywords

    Quantile regression; Panel data; Interactive effects; Instrumental variables;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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