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Proyecciones Macroeconómicas en Chile: Una Aproximación Bayesiana

En el presente trabajo se investiga la importancia de la introducción de información de fuera de la muestra (priors) en las proyecciones macroeconómicas en Chile. Para esto se evalúan tres tipos de modelos lineales que son de uso generalizado en los bancos centrales: BVAR, modelos reducidos neo Keynesianos y DSGE; todos estimados con econometría bayesiana. Además, usamos como benchmark modelos univariados de series de tiempo (AR(1) y random walk) pero estimados con MCO. Los resultados indican que (i) los DSGE entregan proyecciones similares a los BVAR dentro de un horizonte de un año para la inflación, brecha del PIB y la TPM, (ii) los priors son sólo útiles si provienen de modelos bien fundamentados, (iii) los modelos keynesianos reducidos -al adolecer de estos fundamentos- obtuvieron los peores resultados y (iv) en las proyecciones del tipo de cambio real (brecha) los modelos univariados (puzzle de Meese-Rogoff) siguen siendo superiores a todas las demás versiones multivariadas que fueron consideradas.

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Paper provided by Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines in its series ILADES-Georgetown University Working Papers with number inv262.

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Length: 48 pages
Date of creation: Dec 2010
Handle: RePEc:ila:ilades:inv262
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