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Heterogeneity in dynamic discrete choice models

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  • Martin Browning
  • Jesus Carro

Abstract

We consider dynamic discrete choice models with heterogeneity in both the levels parameter and the state dependence parameter. We first analyse the purchase of full fat milk using a long consumer panel (T > 100) on many households. The large T nature of the panel allows us to consistently estimate the parameters of each household separately. This analysis indicates strongly that the levels and the state dependence parameter are heterogeneous and dependently distributed. This empirical analysis motivates the theoretical analysis which considers the estimation of dynamic discrete choice models on short panels, allowing for more heterogeneity than is usually accounted for. The theoretical analysis considers a simple two state, first order Markov chain model without covariates in which both transition probabilities are heterogeneous. Using such a model we are able to derive small sample analytical results for bias and mean squared error. We discuss the maximum likelihood approach, a novel bias corrected version of the latter and we also develop a new estimator that minimises the integrated mean square error, which we term MIMSE. The attractions of the latter estimator are that it is very easy to compute, it is always identified and it converges to maximum likelihood as T becomes large so that it inherits all of the desirable large sample properties of MLE. Our main finding is that in almost all short panel contexts the MIMSE significantly outperforms the other two estimators in terms of mean squared error.

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Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 287.

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Date of creation: 01 Oct 2006
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Handle: RePEc:oxf:wpaper:287

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Keywords: Unobserved Heterogeneity; Heterogeneous Slopes; Fixed Effects; Binary Choice; Panel Data;

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References

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  1. Bo E. Honoré & Elie Tamer, 2002. "Bounds on Parameters in Dynamic Discrete Choice Models," CAM Working Papers 2004-23, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics, revised Aug 2004.
  2. M. Hashem Pesaran & Takashi Yamagata, 2005. "Testing Slope Homogeneity in Large Panels," IEPR Working Papers 05.14, Institute of Economic Policy Research (IEPR).
  3. Martin Browning & Mette Ejrnaes, 2006. "Modelling income processes with lots of heterogeneity," Economics Series Working Papers 285, University of Oxford, Department of Economics.
  4. MacKinnon, James G. & Smith Jr., Anthony A., 1998. "Approximate bias correction in econometrics," Journal of Econometrics, Elsevier, vol. 85(2), pages 205-230, August.
  5. Jinyong Hahn & Whitney Newey, 2003. "Jackknife and analytical bias reduction for nonlinear panel models," CeMMAP working papers CWP17/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  6. Arellano, M. & Honore, B., 2000. "Panel Data Models: Some Recent Developments," Papers 0016, Centro de Estudios Monetarios Y Financieros-.
  7. 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.
  8. Manuel Arellano, 2003. "Discrete choices with panel data," Investigaciones Economicas, Fundación SEPI, vol. 27(3), pages 423-458, September.
  9. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
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Citations

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Cited by:
  1. Fabio Berton & Francesco Devicienti & Lia Pacelli, 2011. "Are temporary jobs a port of entry into permanent employment?: Evidence from matched employer-employee," International Journal of Manpower, Emerald Group Publishing, vol. 32(8), pages 879-899, November.
  2. Browning, Martin & Carro, Jesus M., 2014. "Dynamic binary outcome models with maximal heterogeneity," Journal of Econometrics, Elsevier, vol. 178(2), pages 805-823.
  3. Arthur Lewbel, 2006. "Modeling Heterogeneity," Boston College Working Papers in Economics 650, Boston College Department of Economics.
  4. Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  5. Biørn, Erik & Bjørnsen, Hild-Marte, 2013. "What Motivates Farm Couples to Seek Off-farm Labour? A Logit Analysis of Job Transitions," Memorandum 09/2013, Oslo University, Department of Economics.
  6. Stefan Hochguertel & Henry Ohlsson, 2011. "Wealth mobility and dynamics over entire individual working life cycles," BCL working papers 56, Central Bank of Luxembourg.

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