Analytical Prediction of Transitions Probabilities in the Conditional Logit Model
AbstractThe paper derives analytical transitions probabilities following an exogenous shock to the deterministic component in the conditional logit model. The solution draws on the postestimation distribution of the model’s stochastic component, identified on the basis of a direct utility maximization interpretation of agents’ revealed choice. Computational experiments confirm that analytical prediction of transitions probabilities might perform substantially better than the established calibration method with few repetitions. However, results obtained in an empirical application studying labor supply responses to social insurance reform in Germany suggest that previous calibration-based results accurately indicate the direction of incentive effects, while underpredicting small transitions frequencies.
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Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1015.
Length: 22 pages
Date of creation: Feb 2004
Date of revision:
Publication status: published in: Economics Letters, 2006, 90 (1), 102-107
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Other versions of this item:
- Bonin, Holger & Schneider, Hilmar, 2006. "Analytical prediction of transition probabilities in the conditional logit model," Economics Letters, Elsevier, vol. 90(1), pages 102-107, January.
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-02-23 (All new papers)
- NEP-DCM-2004-02-23 (Discrete Choice Models)
- NEP-ECM-2004-02-23 (Econometrics)
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