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Heterogeneity and Microeconometrics Modelling

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Author Info

  • Martin Browning

    (Department of Economics, University of Copenhagen)

  • Jesus Carro

    (Department of Economics, Carlos III, Madrid)

Abstract

Presented at the 2005 Econometric Society World Congress Plenary Session on "Modelling Heterogeneity". We survey the treatment of heterogeneity in applied microeconometrics analyses. There are three themes. First, there is usually much more heterogeneity than empirical researchers allow for. Second, the inappropriate treatment of heterogeneity can lead to serious error when estimating outcomes of interest. Finally, once we move away from the traditional linear model with a single 'fixed effect', it is very difficult to account for heterogeneity and fit the data and maintain coherence with theory structures. The latter task is one for economists: "heterogeneity is too important to be left to the statisticians". The paper concludes with a report of our own research on dynamic discrete choice models that allow for maximal heterogeneity.

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File URL: http://www.econ.ku.dk/cam/wp0910/wp0406/2006-03.pdf/
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Bibliographic Info

Paper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2006-03.

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Length: 25 pages
Date of creation: Jan 2006
Date of revision:
Handle: RePEc:kud:kuieca:2006_03

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Related research

Keywords: heterogeneity; applied microeconometrics; fixed effects; dyanamic discrete choice;

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References

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  1. Costas Meghir & Luigi Pistaferri, 2001. "Income variance dynamics and heterogenity," IFS Working Papers W01/07, Institute for Fiscal Studies.
  2. Pedro Mira & Jes�s M. Carro, 2006. "A dynamic model of contraceptive choice of Spanish couples," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 955-980.
  3. Flavio Cunha & James J. Heckman & Salvador Navarro, 2005. "Separating Uncertainty from Heterogeneity in Life Cycle Earnings," NBER Working Papers 11024, National Bureau of Economic Research, Inc.
  4. Tiemen Woutersen, 2002. "Robustness against Incidental Parameters," UWO Department of Economics Working Papers 20028, University of Western Ontario, Department of Economics.
  5. Martin Browning & Jesus Carro, 2006. "Heterogeneity in dynamic discrete choice models," Economics Series Working Papers 287, University of Oxford, Department of Economics.
  6. Keane, Michael P & Wolpin, Kenneth I, 1997. "The Career Decisions of Young Men," Journal of Political Economy, University of Chicago Press, vol. 105(3), pages 473-522, June.
  7. James J. Heckman & Rosa Matzkin & Lars Nesheim, 2003. "Simulation and Estimation of Nonaddative Hedonic Models," NBER Working Papers 9895, National Bureau of Economic Research, Inc.
  8. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.
  9. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
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Citations

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Cited by:
  1. Martin Browning & Jesus M. Carro, 2007. "Dynamic Binary Outcome Models with Maximal Heterogeneity," CAM Working Papers 2009-08, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics, revised Feb 2009.
  2. Martin Browning & Jesus M. Carro, 2013. "The Identification of a Mixture of First-Order Binary Markov Chains," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 455-459, 06.
  3. Hiroyuki Kasahara & Katsumi Shimotsu, 2006. "Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices," Working Papers 1092, Queen's University, Department of Economics.
  4. Ralph Stinebrickner & Todd R. Stinebrickner, 2013. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," NBER Working Papers 19165, National Bureau of Economic Research, Inc.
  5. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
  6. Stéphane Bonhomme & Elena Manresa, 2012. "Grouped Patterns Of Heterogeneity In Panel Data," Working Papers wp2012_1208, CEMFI.
  7. Stefan Hochguertel & Henry Ohlsson, 2011. "Wealth mobility and dynamics over entire individual working life cycles," BCL working papers 56, Central Bank of Luxembourg.
  8. M. Dolores Collado & Martín Browning, 2006. "Habits And Heterogeneity In Demands: A Panel Data Analysis," Working Papers. Serie AD 2006-25, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  9. Geert Dhaene & Koen Jochmans, 2010. "Split-panel jackknife estimation of fixed-effect models," Sciences Po publications info:hdl:2441/eu4vqp9ompq, Sciences Po.
  10. Peter C.B. Phillips & Donggyu Sul, 2007. "Transition Modeling and Econometric Convergence Tests," Cowles Foundation Discussion Papers 1595, Cowles Foundation for Research in Economics, Yale University.
  11. Helmers, Christian & Patnam, Manasa, 2011. "The formation and evolution of childhood skill acquisition: Evidence from India," Journal of Development Economics, Elsevier, vol. 95(2), pages 252-266, July.
  12. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," Sciences Po Economics Discussion Papers 2014-03, Sciences Po Departement of Economics.
  13. Victor Chernozhukov & Iván Fernández-Val & Stefan Hoderlein & Hajo Holzmann & Whitney Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers CWP66/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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