Open AccessNonstationary dynamic models with finite dependence
Author(s) -
Arcidiacono Peter,
Miller Robert A.
Publication year - 2019
Publication title -
quantitative economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.062
H-Index - 27
eISSN - 1759-7331
pISSN - 1759-7323
DOI - 10.3982/qe626
Subject(s) - discrete choice , class (philosophy) , sample (material) , conditional expectation , econometrics , mathematics , computer science , discrete time and continuous time , value (mathematics) , horizon , mathematical optimization , statistical physics , mathematical economics , statistics , physics , artificial intelligence , thermodynamics , geometry
The estimation of nonstationary dynamic discrete choice models typically requires making assumptions far beyond the length of the data. We extend the class of dynamic discrete choice models that require only a few‐period‐ahead conditional choice probabilities, and develop algorithms to calculate the finite dependence paths. We do this both in single agent and games settings, resulting in expressions for the value functions that allow for much weaker assumptions regarding the time horizon and the transitions of the state variables beyond the sample period.