System Priors for Econometric Time Series / / Michal Andrle, Miroslav Plašil

• Autore: Andrle Michal
• Pubblicazione: Washington, D.C. : , : International Monetary Fund, , 2016
• Descrizione fisica: 1 online resource (19 pages) : illustrations
• Soggetto topico: Econometrics; Macroeconomics; Bayesian Analysis: General; Model Construction and Estimation; Methodological Issues: General; Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data); Economic growth; Business cycles
• Altri autori: PlašilMiroslav
• Nota di bibliografia: Includes bibliographical references.
• Sommario/riassunto: The paper introduces “system priors”, their use in Bayesian analysis of econometric time series, and provides a simple and illustrative application. System priors were devised by Andrle and Benes (2013) as a tool to incorporate prior knowledge into an economic model. Unlike priors about individual parameters, system priors offer a simple and efficient way of formulating well-defined and economically-meaningful priors about high-level model properties. The generality of system priors are illustrated using an AR(2) process with a prior that most of its dynamics comes from business-cycle frequencies.
• Titolo autorizzato: System Priors for Econometric Time Series
• ISBN: 1-4755-5591-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910155202503321
• Lo trovi qui: Univ. Federico II
• Serie: IMF Working Papers; Working Paper ; ; No. 2016/231