Behavioral Multistate Duration Models: What should they look like ?
AbstractThis paper discusses how specification of probabilistic models for multistate duration data generated by individual choices should be justified on a priori theoretical grounds. Preferences are assumed represented by random utilities, where utilities are viewed as random also to the agent himself. First, the paper proposes a characterization of exogenous preferences, (that is, in the special case with no state dependence effects). The main assumption asserts that when preferences are exogenous the current and future indirect utilities are uncorrelated with current and past choices, given unobservables that are perfectly known to the agent. It is demonstrated that under rather weak and general regularity conditions this characterization yields an explicit structure of the utility function as a so-called Extremal stochastic process. Furthermore, from this utility representation it follows that the choice process is a Markov Chain (in continuous- or discrete time), with a particular functional form of the transition probabilities, as explicit functions of the parameters of the utility function and choice set. Subsequently, we show how the model can be extended to allow for structural state dependence effects, and how such state dependence effects can be identified. Moreover, it is discussed how a version of Chamberlain’s conditional estimation method applies in the presence of fixed effects. Finally, we discuss two examples of applications.
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Bibliographic InfoPaper provided by Oslo University, Department of Economics in its series Memorandum with number 17/2012.
Length: 46 pages
Date of creation: 20 May 2012
Date of revision:
Contact details of provider:
Postal: Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway
Phone: 22 85 51 27
Fax: 22 85 50 35
Web page: http://www.oekonomi.uio.no/indexe.html
More information through EDIRC
Duration models; Random utility models; Habit persistence; True state dependence; Extremal process; Markov chain;
Find related papers by JEL classification:
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-09-03 (All new papers)
- NEP-ECM-2012-09-03 (Econometrics)
- NEP-ORE-2012-09-03 (Operations Research)
- NEP-UPT-2012-09-03 (Utility Models & Prospect Theory)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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