Pang, Iris Ai Jao (2010): Were Fed’s active monetary policy actions necessary?
Download (1MB) | Preview
This work applies the two-stage Factor Augmented Vector Autoregression (FAVAR) developed by Bernanke, Boivin and Eliasz (2005) to investigate the appropriateness of frequent monetary policy actions that involve frequent adjustments of the policy interest rate in a prolonged manner. From time to time there are claims that the Federal Reverse Bank cut or raised the fed funds rate too frequently. This raises the concern that the Federal Reserve Bank mistakenly cut interest rate for too long and too frequently and then paused too short and raised rate again to “undo” the previous unnecessary interest rate cut or vice versa. To verify if such a claim is valid, we generate hypothetical scenarios assuming that the Federal Reserve Bank had shortened the time period of active monetary policies and lengthened the period of a pause. Then, we compare economic activities implied by impulse response functions from hypothetical scenarios with those generated from actual fed policies under the record of Alan Greenspan (1987-2006). We find that a less active monetary policy approach could control inflation with less negative impact on real economic activities, and major economic variables would be less volatile in a 48-month horizon. The investigation provides insights on the implementation of monetary policies not only for the U.S., but also for all central banks that control interest rates as their major monetary policy tool.
|Item Type:||MPRA Paper|
|Original Title:||Were Fed’s active monetary policy actions necessary?|
|English Title:||Were Fed’s Active Monetary Policy Actions Necessary?|
|Keywords:||Fed; monetary policy; Factor Model; Factor Augmented VAR; FAVAR|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods
E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit
|Depositing User:||Iris A.J. Pang|
|Date Deposited:||30. Jul 2011 16:59|
|Last Modified:||16. Feb 2013 10:34|
Bai, J. (2003). “Inferential Theory for Factor Models of Large Dimensions,” Econometrica, 71:1, 135-171.
Bai, J. and Ng, S. (2002). “Determining the Number of Factors in Approximate Factor Models,” Econometrica, 70:1, 191-221.
Bai, J. and Ng, S. (2006). “Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions,” Econometrica, 74:4, 1133-1150.
Bai, J. and Ng, S. (2007). “Forecasting Economic Time Series Using Targeted Predictors,” manuscript.
Bernanke, B. and Boivin, J. (2003). “Monetary Policy in a Data-Rich Environment,” Journal of Monetary Economics, 50, 525-526.
Bernanke, B., Boivin, J. and Eliasz, P. (2005). “Measuring the Effects of Monetary Policy: A Factor-augmented Vector Autoregressive (FAVAR) Approach,” The Quarterly Journal of Economics, 120:1, 387-422.
Bernanke, B. and Mihov, I. (1998). “The liquidity effect and long-run neutrality,” NBER Working Paper, w6608.
Boivin, J., Giannoni, M. and Mihov, I. (2007). “Sticky Prices and Monetary Policy: Evidence from Disaggregated U.S. Data,” NBER Working Paper, w12824.
Breitung, J. and Eickmeier, S. (2005). “Dynamic Factor Models,” Deutsche Bundesbank Discussion Paper, Series 1: Economic Studies, 38.
Fernándes-Villaverde, J., Rubio-Ramírez, J. Sargent, T. and Watson, M. (2007). “ABCs (and Ds) of Understanding VARs,” The American Economic Revew, June, 1021-1026.
Feyzioglu, T., Porter, N. and Takats, E. (2009). “Interest Rate Liberalization in China,” IMF Working Paper, WP/09/171.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L.(2000). “The generalized factor model: identification and estimation”, The Review of Economics and Statistics 82, 540–554.
Marcellino, M., Stock, J. and Watson, M. (2006). “A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series,” Journal of Econometrics, 135:1-2, 499-526.
Mönch, E. (2005). “Forecasting the Yield Curve in a Data-Rich Environment: A No-Arbitrage Factor-Augmented VAR Approach”, manuscript, May 31st, Humboldt University. Shibamoto, M. (2005) “An Analysis of Monetary Policy Shocks in Japan: a Factor Augmented Vector Autoregressive Approach,” Discussion Paper Series, 95, Graduate School of Economics, Osaka University.
Shibamoto, M. (2006) “The Estimation of Monetary Policy Reaction Function in a Data-Rich Environment: the Case of Japan,” Discussion Paper Series, 150, Graduate School of Economics, Osaka University.
Stock, J. and Watson, M. (1998). “Diffusion Indexes,” NBER Working Paper, w6702, August.
Stock, J. and Watson, M. (1999). “Forecasting Inflation,” Journal of Monetary Economics, 44, pp.293-335.
Stock, J. and Watson, M. (2002). “Macroeconomic Forecasting Using Diffusion Indexes”, Journal of Business Economics and Statistics, 20:2, 147-162.
Stock, J. and Watson, M. (2002). “Forecasting Using Principal Components From a Large Number of Predictors,” Journal of American Statistical Association, 97:260, pp.1167-1179.
Stock, J. and Watson, M. (2005) “Implications of Dynamic Factor Models for VAR Analysis”, manuscript. http://www.economics.harvard.edu/faculty/stock/files/simsconf_stock_watson_jmcb_submission.pdf