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Dynamic binary outcome models with maximal heterogeneity

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Author Info
Martin Browning ()
Jesus M. Carro ()

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Abstract

Most econometric schemes to allow for heterogeneity in micro behaviour have two drawbacks: they do not fit the data and they rule out interesting economic models. In this paper we consider the time homogeneous first order Markov (HFOM) model that allows for maximal heterogeneity. That is, the modelling of the heterogeneity does not impose anything on the data (except the HFOM assumption for each agent) and it allows for any theory model (that gives a HFOM process for an individual observable variable). `Maximal' means that the joint distribution of initial values and the transition probabilities is unrestricted. We establish necessary and sufficient conditions for the point identification of our heterogeneity structure and show how it depends on the length of the panel. A feasible ML estimation procedure is developed. Tests for a variety of subsidiary hypotheses such as the assumption that marginal dynamic effects are homogeneous are developed. We apply our techniques to a long panel of Danish workers who are very homogeneous in terms of observables. We show that individual unemployment dynamics are very heterogeneous, even for such a homogeneous group. We also show that the impact of cyclical variables on individual unemployment probabilities differs widely across workers. Some workers have unemployment dynamics that are independent of the cycle whereas others are highly sensitive to macro shocks.

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Paper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we091710.

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Date of creation: Feb 2009
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Handle: RePEc:cte:werepe:we091710

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Related research
Keywords: Discrete choice; Markov processes; Nonparametric identification; Unemployment dynamics;

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Find related papers by JEL classification:
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models
J64 - Labor and Demographic Economics - - Mobility, Unemployment, and Vacancies - - - Unemployment: Models, Duration, Incidence, and Job Search

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  1. Bo E. Honoré & Elie Tamer, 2006. "Bounds on Parameters in Panel Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 74(3), pages 611-629, 05. [Downloadable!] (restricted)
  2. Martin Browning & Jesus Carro, 2006. "Heterogeneity in dynamic discrete choice models," Economics Series Working Papers 287, University of Oxford, Department of Economics. [Downloadable!]
  3. Pedro Mira & Jesús 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. [Downloadable!]
  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. [Downloadable!]
  5. Gary S. Becker & Michael Grossman & Kevin M. Murphy, 1994. "An Empirical Analysis of Cigarette Addiction," NBER Working Papers 3322, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Ham, John C. & Shore-Sheppard, Lara, 2005. "The effect of Medicaid expansions for low-income children on Medicaid participation and private insurance coverage: evidence from the SIPP," Journal of Public Economics, Elsevier, vol. 89(1), pages 57-83, January. [Downloadable!] (restricted)
  7. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
  8. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier. [Downloadable!] (restricted)
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  11. Hiroyuki Kasahara & Katsumi Shimotsu, 2009. "Nonparametric Identification of Finite Mixture Models of Dynamic Discrete Choices," Econometrica, Econometric Society, vol. 77(1), pages 135-175, 01. [Downloadable!] (restricted)
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