Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/71996 
Erscheinungsjahr: 
2001
Schriftenreihe/Nr.: 
Working Paper No. 461
Verlag: 
The Johns Hopkins University, Department of Economics, Baltimore, MD
Zusammenfassung: 
We develop a new estimation methodology for dynamic optimization models with unobserved state variables Our approach is semiparametric in the sense of not requiring explicit parametric assumptions to be made concerning the distribution of these unobserved state variables We propose a two-step pairwise-difference estimator which exploits two common features of dynamic optimization problems: (1) the weak monotonicity of the agent's decision (policy) function in the unobserved state variables conditional on the observed state variables; and (2) the state-contingent nature of optimal decision-making which implies that conditional on the observed state variables the variation in observed choices across agents must be due to randomness in the unobserved state variables across agents We apply our estimator to a model of dynamic competitive equilibrium in the market for milk production quota in Ontario Canada
Schlagwörter: 
Pairwise-difference Estimators
Dynamic Optimization Models
JEL: 
C13
C50
Dokumentart: 
Working Paper

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