文章基本信息

标题：The Stochastic Coefficients Approach to Econometric Modeling, Part III: Estimation, Stability Testing, and Prediction
本地全文：下载
作者：Swamy, P.A.V.B. ; Conway, Roger K. ; LeBlanc, Michael 等
期刊名称：Journal of Agribusiness
印刷版ISSN：0738-8950
出版年度：1988
期号：suppl
出版社：Journal of Agribusiness
摘要：In this final article of our three-part series, we demonstrate why stochastic coefficients models are well suited to predict future variables We analyze the forecasting problem and consider various criteria of prediction If a forecaster must choose one from among several coherent predictors, then the choice should be the one with the best track record Decomposing the forecast error shows that stochastic coefficients models can cover more possible sources of prediction error and correct for them The empirical record shows that stichastic coefficients models can substantially reduce out-of-sample forecast errors more than fixed coefficients models Our assessment of coefficient stability tests is they are contradictory , misleading, and without empirical value
关键词：Stochastic coefficients;fixed coefficients;conditional expectation;Bayesian inference;coherencem estimation;prediction;stability tests