IDEAS home Printed from https://ideas.repec.org/p/ila/ilades/inv262.html
   My bibliography  Save this paper

Proyecciones Macroeconómicas en Chile: Una Aproximación Bayesiana

Author

Abstract

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.

Suggested Citation

  • Carlos Garcia & Pablo Gonzalez & Antonio Moncado, 2010. "Proyecciones Macroeconómicas en Chile: Una Aproximación Bayesiana," ILADES-Georgetown University Working Papers inv262, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines.
  • Handle: RePEc:ila:ilades:inv262
    as

    Download full text from publisher

    File URL: http://fen.uahurtado.cl/wp-content/uploads/2010/07/I-262-Garcia-Gonzalez-Moncado.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    2. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    3. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    4. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
    5. Schmitt-Grohe, Stephanie & Uribe, Martin, 2003. "Closing small open economy models," Journal of International Economics, Elsevier, vol. 61(1), pages 163-185, October.
    6. Pierre-Olivier Gourinchas & Hélène Rey, 2007. "International Financial Adjustment," Journal of Political Economy, University of Chicago Press, vol. 115(4), pages 665-703, August.
    7. Christopher A. Sims, 1993. "A Nine-Variable Probabilistic Macroeconomic Forecasting Model," NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 179-212 National Bureau of Economic Research, Inc.
    8. Jordi Galí & Mark Gertler, 2007. "Macroeconomic Modeling for Monetary Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 21(4), pages 25-46, Fall.
    9. Luis Felipe Céspedes & Jorge A. Fornero & Jordi Galí, 2013. "Non-Ricardian Aspects of Fiscal Policy in Chile," Central Banking, Analysis, and Economic Policies Book Series,in: Luis Felipe Céspedes & Jordi Galí (ed.), Fiscal Policy and Macroeconomic Performance, edition 1, volume 17, chapter 8, pages 283-322 Central Bank of Chile.
    10. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, pages 586-606.
    11. Pincheira Brown, Pablo & Rubio Hurtado, Hernán, 2015. "El escaso poder predictivo de simples curvas de Phillips en Chile," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    12. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not As Bad As You Think," NBER Chapters,in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441 National Bureau of Economic Research, Inc.
    13. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, Oxford University Press, vol. 125(3), pages 1145-1194.
    14. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2008. "The new area-wide model of the euro area: a micro-founded open-economy model for forecasting and policy analysis," Working Paper Series 944, European Central Bank.
    15. Christoffel, Kai & Warne, Anders & Coenen, Günter, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    16. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    17. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2006. "SIGMA: A New Open Economy Model for Policy Analysis," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    18. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
    19. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    20. Carlos Garcia & Wildo Gonzalez, 2010. "Is more exchange rate intervention necessary in small open economies? The role of risk premium and commodity shocks," ILADES-Georgetown University Working Papers inv248, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines.
    21. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    22. Garcia, Carlos J. & Restrepo, Jorge E. & Tanner, Evan, 2011. "Fiscal rules in a volatile world: A welfare-based approach," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 649-676, July.
    23. Juan Pablo Medina & Claudio Soto, 2007. "The Chilean Business Cycles Through the Lens of a Stochastic General Equilibrium Model," Working Papers Central Bank of Chile 457, Central Bank of Chile.
    24. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    25. Douglas Laxton & Andrew Berg & Philippe D Karam, 2006. "Practical Model-Based Monetary Policy Analysis; A How-To Guide," IMF Working Papers 06/81, International Monetary Fund.
    26. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    27. Laxton, Douglas & Pesenti, Paolo, 2003. "Monetary rules for small, open, emerging economies," Journal of Monetary Economics, Elsevier, vol. 50(5), pages 1109-1146, July.
    28. Keiko Honjo & Benjamin L Hunt, 2006. "Stabilizing Inflation in Iceland," IMF Working Papers 06/262, International Monetary Fund.
    29. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
    30. Llosa, Gonzalo & Tuesta, Vicente & Vega, Marco, 2006. "Un modelo de proyección BVAR para la inflación peruana," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 13.
    31. Verónica Mies & Felipe Morandé & Matías Tapia, 2002. "Política Monetaria y Mecanismos de Transmisión: Nuevos Elementos para una Vieja Discusión," Working Papers Central Bank of Chile 181, Central Bank of Chile.
    32. Patricio Jaramillo, 2009. "Estimación de Var Bayesianos para la Economía Chilena," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, vol. 24(1), pages 101-126, Junio.
    33. Pablo Pincheira Brown & Álvaro García Marín, 2009. "Forecasting Inflation in Chile With an Accurate Benchmark," Working Papers Central Bank of Chile 514, Central Bank of Chile.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Modelos de Proyección; Modelos DSGE; Intermediarios;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ila:ilades:inv262. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marcela Perticara). General contact details of provider: http://edirc.repec.org/data/deilacl.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.