Priors about Observables in Vector Autoregressions
AbstractStandard practice in Bayesian VARs is to formulate priors on the autoregres- sive parameters, but economists and policy makers actually have priors about the behavior of observable variables. We show how this kind of prior can be used in a VAR under strict probability theory principles. We state the inverse problem to be solved and we propose a numerical algorithm that works well in practical situations with a very large number of parameters. We prove various convergence theorems for the algorithm. As an application, we first show that the results in Christiano et al. (1999) are very sensitive to the introduction of various priors that are widely used. These priors turn out to be associated with undesirable priors on observables. But an empirical prior on observables helps clarify the relevance of these estimates: we find much higher persistence of out- put responses to monetary policy shocks than the one reported in Christiano et al. (1999) and a significantly larger total effect.
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Bibliographic InfoPaper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number 929.13.
Date of creation: 18 Mar 2013
Date of revision:
Vector Autoregression; Bayesian Estimation; Prior about Observables; Inverse Problem; Monetary Policy Shocks;
Other versions of this item:
- Marek Jarocinski & Albert Marcet, 2013. "Priors about Observables in Vector Autoregressions," Working Papers 684, Barcelona Graduate School of Economics.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-04-13 (All new papers)
- NEP-ECM-2013-04-13 (Econometrics)
- NEP-ETS-2013-04-13 (Econometric Time Series)
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- Christiano, Lawrence J. & Trabandt, Mathias & Walentin, Karl, 2011.
"Introducing financial frictions and unemployment into a small open economy model,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 35(12), pages 1999-2041.
- Mathias Trabandt & Karl Walentin & Lawrence J. Christiano, 2008. "Introducing Financial Frictions and Unemployment into a Small Open Economy Model," 2008 Meeting Papers 423, Society for Economic Dynamics.
- Christiano, Lawrence J. & Trabandt, Mathias & Walentin, Karl, 2007. "Introducing Financial Frictions and Unemployment into a Small Open Economy Model," Working Paper Series 214, Sveriges Riksbank (Central Bank of Sweden), revised 01 Jun 2011.
- Lawrence J. Christiano & Mathias Trabandt & Karl Walentin, 2010. "Introducing financial frictions and unemployment into a small open economy model," CQER Working Paper 2010-04, Federal Reserve Bank of Atlanta.
- Jarociński, Marek & Marcet, Albert, 2010.
"Autoregressions in small samples, priors about observables and initial conditions,"
Working Paper Series
1263, European Central Bank.
- Marek Jarocinski & Albert Marcet, 2011. "Autoregressions in Small Samples, Priors about Observables and Initial Conditions," CEP Discussion Papers dp1061, Centre for Economic Performance, LSE.
- Ivan Canay & Andres Santos & Azeem Shaikh, 2012. "On the testability of identification in some nonparametric models with endogeneity," CeMMAP working papers CWP18/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Robert B. Litterman, 1985.
"Forecasting with Bayesian vector autoregressions five years of experience,"
274, Federal Reserve Bank of Minneapolis.
- Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
- Kadane, Joseph B. & Chan, Ngai Hang & Wolfson, Lara J., 1996. "Priors for unit root models," Journal of Econometrics, Elsevier, vol. 75(1), pages 99-111, November.
- Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
- Bonhomme, S. & Robin, J.-M., 2010.
"Generalized non-parametric deconvolution with an application to earnings dynamics,"
Open Access publications from University College London
http://discovery.ucl.ac.u, University College London.
- Stéphane Bonhomme & Jean-Marc Robin, 2010. "Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 491-533.
- Stéphane Bonhomme & Jean-Marc Robin, 2008. "Generalized nonparametric deconvolution with an application to earnings dynamics," CeMMAP working papers CWP03/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Christopher A. Sims & Tao Zha, 1996.
"Bayesian methods for dynamic multivariate models,"
96-13, Federal Reserve Bank of Atlanta.
- Whitney K. Newey & James L. Powell, 2003. "Instrumental Variable Estimation of Nonparametric Models," Econometrica, Econometric Society, vol. 71(5), pages 1565-1578, 09.
- Adjemian, Stéphane & Bastani, Houtan & Karamé, Fréderic & Juillard, Michel & Maih, Junior & Mihoubi, Ferhat & Perendia, George & Ratto, Marco & Villemot, Sébastien, 2011. "Dynare: Reference Manual Version 4," Dynare Working Papers 1, CEPREMAP, revised Apr 2013.
- Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
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