Korobilis, Dimitris (2009): Assessing the transmission of monetary policy shocks using dynamic factor models.
This is the latest version of this item.

PDF
MPRA_paper_35087.pdf Download (584kB)  Preview 
Abstract
This paper extends the current literature which questions the stability of the monetary transmission mechanism, by proposing a factoraugmented vector autoregressive (VAR) model with timevarying coefficients and stochastic volatility. The VAR coefficients and error covariances may change gradually in every period or be subject to abrupt breaks. The model is applied to 143 postWorld War II quarterly variables fully describing the US economy. I show that both endogenous and exogenous shocks to the US economy resulted in the high inflation volatility during the 1970s and early 1980s. The timevarying factor augmented VAR produces impulse responses of inflation which significantly reduce the price puzzle. Impulse responses of other indicators of the economy show that the most notable changes in the transmission of unanticipated monetary policy shocks occurred for GDP, investment, exchange rates and money.
Item Type:  MPRA Paper 

Original Title:  Assessing the transmission of monetary policy shocks using dynamic factor models 
Language:  English 
Keywords:  Structural FAVAR; time varying parameter model; monetary policy 
Subjects:  C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C32  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models E  Macroeconomics and Monetary Economics > E5  Monetary Policy, Central Banking, and the Supply of Money and Credit > E52  Monetary Policy C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General 
Item ID:  35087 
Depositing User:  Dimitris Korobilis 
Date Deposited:  29. Nov 2011 12:20 
Last Modified:  25. Sep 2015 08:24 
References:  Belviso, F. and Milani, F. (2006). `Structural factoraugmented VARs (SFAVARs) and the effects of monetary policy', Topics in Macroeconomics, Vol. 6, pp.14431443. Bernanke, B. S. and Blinder, A. S. (1992). `The Federal funds rate and the channels of monetary transmission', American Economic Review, Vol. 82, pp. 90121. Bernanke, B. S. and Boivin, J. (2003). `Monetary policy in a datarich environment', Journal of Monetary Economics, Vol. 50, pp. 525546. Bernanke, B. S., Boivin, J. and Eliasz, P. (2005). `Measuring the effects of monetary policy: A factoraugmented vector autoregressive (FAVAR) approach', Quarterly Journal of Economics, Vol. 120, 387422. Boivin, J. and Giannoni, M. P. (2006a). `DSGE models in a datarich environment', NBER Technical Working Papers 0332, National Bureau of Economic Research, Inc. Boivin, J. and Giannoni, M. P. (2006b). `Has monetary policy become more effective?', The Review of Economics and Statistics, Vol. 88, pp. 445462. Boivin, J. and Ng, S. (2005). `Understanding and comparing factorbased forecasts', International Journal of Central Banking, Vol. 3, pp. 111151. Campbell, J. and Hercowitz, Z. (2006). `The Role of Collateralized Households Debt in Macroeconomic Stabilization', Federal Reserve Bank of Chicago and Tel Aviv University, mimeo. Canova, F. and Gambetti, L. (2009). `Structural changes in the U.S. economy: Is there a role for monetary policy?', Journal of Economic Dynamics and Control, Vol. 33, pp. 477490. Carter, C. K. and Kohn, R. (1994). `On Gibbs sampling for state space models', Biometrika, Vol. 81, pp. 541553. Castelnuovo, E. and Surico, P. (2010). `Monetary policy shifts, inflation expectations and the price puzzle', Economic Journal, Vol. 120, pp. 12621283. Clarida, R, Galí, J. and Gertler, M. (2000). `Monetary policy rule and macroeconomic stability: Evidence and some theory', Quarterly Journal of Economics, Vol. 115, pp. 147  180. Cogley, T. and Sargent, T. (2001). `Evolving postWorld War II inflation dynamics', NBER Macroeconomic Annual, Vol. 16, pp. 331373. Cogley, T. and Sargent, T. (2005). `Drifts and volatilities: Monetary policies and outcomes in the post WWII U.S.', Review of Economic Dynamics, Vol. 8, pp. 262302. Doan, T., Litterman, R. and Sims, C. A. (1984). `Forecasting and conditional projection using realistic prior distributions', Econometric Reviews, Vol. 3, pp. 1100. Dynan, K., Elmendorf, D. and Sichel, D. (2006). `Can financial innovation help to explain the reduced volatility of economic activity?,' Journal of Monetary Economics, Vol. 53, pp. 123150. George, E. I. and McCulloch, R. E. (1997). `Approaches for Bayesian variable selection', Statistica Sinica, Vol. 7, pp. 339373. Gerlach, R., Carter, C. and Kohn, R. (2000). `Efficient Bayesian inference in dynamic mixture models', Journal of the American Statistical Association, Vol. 95, pp. 819828. Giannone, D., Lenza, M. and Reichlin, L. (2008). `Explaining the great moderation: It is not the shocks', Journal of the European Economic Association, Vol. 6, pp. 621633. Giannone, D., Reichlin, L. and Small, D. (2008). `Nowcasting: The realtime informational content of macroeconomic data', Journal of Monetary Economics, Vol. 55, pp. 665676. Giordani, P. and Kohn, R. (2008). `Efficient Bayesian inference for multiple changepoint and mixture innovation models', Journal of Business and Economic Statistics, Vol. 26, pp. 6677. Kim, C.J. and Nelson, C. R. (1999). `Has the U.S. economy become more stable? A Bayesian approach based on a markovswitching model of the business cycle', The Review of Economics and Statistics, Vol. 81, pp. 608616. Kahn, J. A., McConnell, M. and PerezQuiros, G. (2002). `On the causes of the increased stability of the U.S. economy,' Federal Reserve Bank of New York, Economic Policy Review, Vol. 8, pp. 183202. Koop, G. (2003). Bayesian econometrics. Wiley, Chichester. Koop, G. and Korobilis, D. (2010). `Bayesian multivariate time series methods for empirical macroeconomics', Foundations and Trends in Econometrics, Vol. 3: No 4, pp 267358. Koop, G., LeonGonzales, R. and Strachan, R. (2009). `On the evolution of the monetary policy transmission mechanism', Journal of Economic Dynamics and Control, Vol. 33, pp. 9971017. Koop, G., Pesaran, H. M. and Potter, S. M. (1996). `Impulse response analysis in nonlinear multivariate models', Journal of Econometrics, Vol. 74, pp. 77118. Koop, G and Potter, S. M. (2008). `Time varying VARs with inequality restrictions', manuscript available at http://personal.strath.ac.uk/gary.koop/koop_potter14.pdf. Lopes, H. F. and West, M. (2004). `Bayesian model assessment in factor analysis', Statistica Sinica, Vol. 14, pp. 4167. Lütkepohl, H. (2005). New introduction to multiple time series analysis. SpringerVerlag. McConnell, M. and PerezQuiros, G. (2000). `Output fluctuations in the United States: What has changed since the early 1980s', American Economic Review, Vol. 90, pp. 14641476. Primiceri, G. E. (2005). `Time varying structural vector autoregressions and monetary policy', Review of Economic Studies, Vol. 72, pp. 821852. Sims, C. and T. Zha (2006). `Were there regime switches in macroeconomic policy?', American Economic Review, Vol. 96, pp. 5481. Stock, J. H. and Watson, M. W. (2002). `Has business cycle changed and why?', NBER Macroeconomics Annual, Vol. 17, pp. 159218. Stock, J. H. and Watson, M. W. (2005). `Implications of dynamic factor models for VAR analysis', NBER Working Papers 11467, National Bureau of Economic Research, Inc. Strachan, R. (2003). `Valid Bayesian estimation of the cointegrating error correction model', Journal of Business and Economic Statistics, Vol. 21, pp. 185195. Uhlig, H. (2005). `What are the effects of monetary policy on output? Results from an agnostic identification procedure', Journal of Monetary Economics, Vol. 52, pp. 381419. Woodford, M. (2003). Interest and Prices: Foundations of a Theory of Monetary Policy, Princeton University Press, Princeton. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/35087 
Available Versions of this Item

Assessing the transmission of monetary policy using dynamic factor models. (deposited 21. Dec 2010 08:10)
 Assessing the transmission of monetary policy shocks using dynamic factor models. (deposited 29. Nov 2011 12:20) [Currently Displayed]