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



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Autore: Andrle Michal Visualizza persona
Titolo: System Priors for Econometric Time Series / / Michal Andrle, Miroslav Plašil Visualizza cluster
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  Visualizza cluster
ISBN: 1-4755-5584-9
1-4755-5591-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910155202503321
Lo trovi qui: Univ. Federico II
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Serie: IMF Working Papers; Working Paper ; ; No. 2016/231