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Alternative specifications of the error process in the stochastic simulation of econometric models
Author(s) -
Sterbenz Frederic P.,
Calzolari Giorgio
Publication year - 1990
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950050203
Subject(s) - variance reduction , variance (accounting) , monte carlo method , econometrics , econometric model , stochastic simulation , computer science , process (computing) , stochastic modelling , statistics , mathematics , economics , accounting , operating system
This paper analyses the stochastic simulation of econometric models using three different methods for specifying the probability distribution of the structural error terms. The impact of these different assumptions on the simulation bias and model variance is explored empirically. Monte Carlo variance reduction techniques are used to distinguish the effects of the different specifications.