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Welfare Estimation Using Aggregate and Individual‐Observation Models: A Comparison Using Monte Carlo Techniques
Author(s) -
Hellerstein Daniel
Publication year - 1995
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 - 10.2307/1243230
Subject(s) - estimator , econometrics , monte carlo method , aggregate (composite) , variance (accounting) , sample (material) , model selection , estimation , economics , computer science , statistics , mathematics , materials science , chemistry , accounting , chromatography , composite material , management
Due to the weak behavioral foundations of aggregate demand models, zonal travel cost models have been largely abandoned in favor of models based on individual observations. However, sample selection difficulties in individual‐observation models often require the use of distribution‐sensitive limited‐dependent variables estimators. In this paper I use Monte‐Carlo simulations to investigate whether the bias from aggregation is worse than possible bias from these narrowly specified estimators. Somewhat surprisingly, the results indicate that zonal models often outperform the individual‐observation models, especially when using an aggregate model that incorporates intrazonal variance of the explanatory variables.