English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/59048
Title: Translating Priors about Observables in Autoregressions and the Role of Initial Conditions in Small Samples
Authors: Marcet, Albert
Issue Date: 2010
Citation: A cemmap workshop: Applied macroeconomics and macroeconometrics (2010)
Abstract: We discuss estimation of autoregressive models with a prior about initial growth rates of the modeled series. This prior allows to specify prior beliefs about the behavior of time series in a natural way and it serves to replace arbitrary assumptions on initial conditions. To implement this prior we develop a technique for translating priors about observables into priors about coecients. The posterior mean is attractive even from the frequentist point of view: it is often less biased than the OLS estimate and has better frequentist risk than bias corrected estimates. We apply our prior to some empirical studies from the literature and that it makes a big diference for the estimated persistence of output responses to monetary policy shocks in a vector autoregression for the United States.
URI: http://hdl.handle.net/10261/59048
Appears in Collections:(IAE) Comunicaciones congresos
Files in This Item:
File Description SizeFormat 
Translating Priors.pdf342,45 kBAdobe PDFThumbnail
Show full item record

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.