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The Implications of Model Specification for Welfare Estimation in Nested Logit Models
Author(s) -
Kling Catherine L.,
Thomson Cynthia J.
Publication year - 1996
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1243782
Subject(s) - nested logit , econometrics , estimator , logit , welfare , mixed logit , economics , nested set model , construct (python library) , model selection , selection (genetic algorithm) , estimation , logistic regression , discrete choice , specification , nesting (process) , value (mathematics) , statistics , mathematics , computer science , engineering , market economy , mechanical engineering , management , artificial intelligence , relational database , programming language , database
Nested logit models are increasingly being used to value environmental amenities. The implications of nesting structure, choice of estimator (FIML or sequential), and restrictions on parameters across nested groups on welfare estimates are examined. These issues have received little previous attention. Model selection criteria that can be used to distinguish among the models are extended and applied. Additionally, a simulation procedure is implemented to construct standard errors for the welfare measures.