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Record Nr. |
UNINA9910155202503321 |
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Autore |
Andrle Michal |
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Titolo |
System Priors for Econometric Time Series / / Michal Andrle, Miroslav Plašil |
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Pubbl/distr/stampa |
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Washington, D.C. : , : International Monetary Fund, , 2016 |
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ISBN |
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1-4755-5584-9 |
1-4755-5591-1 |
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Descrizione fisica |
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1 online resource (19 pages) : illustrations |
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Collana |
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Altri autori (Persone) |
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Soggetti |
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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 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Sommario/riassunto |
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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 |
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