Manzan, Sebastiano and Zerom, Dawit (2009): Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?
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Much of the US inflation forecasting literature deals with examining the ability of macroeconomic indicators to predict the mean of future inflation, and the overwhelming evidence suggests that the macroeconomic indicators provide little or no predictability. In this paper, we expand the scope of inflation predictability and explore whether macroeconomic indicators are useful in predicting the distribution of future inflation. To incorporate macroeconomic indicators into the prediction of the conditional distribution of future inflation, we introduce a semi-parametric approach using conditional quantiles. The approach offers more flexibility in capturing the possible role of macroeconomic indicators in predicting the different parts of the future inflation distribution. Using monthly data on US inflation, we find that unemployment rate, housing starts, and the term spread provide significant out-of-sample predictability for the distribution of core inflation. Importantly, this result is obtained for a forecast evaluation period that we intentionally chose to be after 1984, when current research shows that macroeconomic indicators do not add much to the predictability of the future mean inflation. This paper discusses various findings using forecast intervals and forecast densities, and highlights the unique insights that the distribution approach offers, which otherwise would be ignored if we relied only on mean forecasts.
|Item Type:||MPRA Paper|
|Original Title:||Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?|
|Keywords:||Conditional quantiles; Distribution; Inflation; Predictability; Phillips curve; Combining|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods; Simulation Methods
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level; Inflation; Deflation
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 > C2 - Single Equation Models; Single Variables > C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
|Depositing User:||Dawit Zerom|
|Date Deposited:||01. Apr 2009 04:40|
|Last Modified:||14. Feb 2013 13:34|
Amisano, G. and Giacomini, R. (2007). Comparing density forecasts via Weighted Likelihood Ratio Tests. Journal of Business & Economic Statistics, 25, 177–190.
Ang, A., Bekaert, G. and Wei, M. (2006). Do macro variables, asset markets, or surveys forecast inflation better? Journal of Monetary Economics, 54, 1163–1212.
Atkenson, A. and Ohanian, L. (2001). Are Phillips Curves useful for forecasting inflation? Federal Reserve Bank of Minneapolis Quarterly Review, 25, 2–11.
Bao, Y., Lee, T.-H. and Saltoglu, B. (2007). Comparing density forecast models. Journal of Forecasting, 26, 203–225.
Cenesizoglu, T. and Timmermann, A. (2008). Is the distribution of stock returns predictable? working paper.
Chernozhukov, V., Fernandez-Val, I. and Galichon, A. (2006). Quantile and probability curves without crossing. working paper.
Clark, T.E. and McCracken, M.W. (2006). The predictive content of the output gap for inflation: resolving in-sample and out-of-sample evidence. Journal of Money, Credit, and Banking, 38, 1127–1148.
Cogley, T., Morozov, S. and Sargent, T.J. (2005). Bayesian fan charts for U.K. inflation: forecasting and sources of uncertainty in an evolving monetary system. Journal of Economic Dynamics and Control, 29, 1893–1925.
Corradi, V. and Swanson, N.R. (2006). Predictive density and conditional confidence interval accuracy tests. Journal of Econometrics, 135, 187–228.
de Gooijer, J.G. and Zerom, D. (2003). On additive conditional quantiles with highdimensional covariates. Journal of the American Statistical Association, 98, 135–146.
Diebold, F.X., Gunther, T.A. and Tay, A.S. (1998). Evaluating density forecasts with application to financial risk management. International Economic Review, 39, 863–883.
Fisher, J.D.M., Liu, C.T. and Zhou, R. (2002). When can we forecast inflation? Federal Reserve Bank of Chicago Economic Perspectives 30–42.
Giacomini, R. and White, H. (2006). Tests of conditional predictive ability. Econometrica, 74, 1545–1578.
Greenspan, A. (1998). Problems of price measurement. Federal Reserve Board, Testimony and Speeches (January 3rd).
Greenspan, A. (2004). Risk and uncertainty in monetary policy. American Economic Review, 94, 33–40.
Hodrick, R.J. and Prescott, E.C. (1997). Postwar U.S. business cycles: an empirical investigation. Journal of Money, Credit, and Banking, 29, 1–16.
Hong, Y., Li, H. and Zhao, F. (2007). Can the random walk model be beaten in outof- sample density forecasts? evidence from intraday foreign exchange rates. Journal of Econometrics, 141, 736–776.
Inoue, A. and Kilian, L. (2004). In-sample or out-of-sample tests of predictability? Which one should we use? Econometric Reviews, 23, 371–402.
Kilian, L. and Manganelli, S. (2008). The central banker as a risk manager: estimating the Federal Reserve’s preferences under Greenspan. Journal of Money, Credit, and Banking, 40, 1103–1129.
Koenker, R. and Bassett, G. (1978). Regression quantiles. Econometrica, 46, 33–50.
Mitchell, J. and Hall, S.G. (2005). Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR fan charts of inflation. Oxford Bulleting of Economics and Statistics, 67, 995–1003.
Robertson, J.C., Tallman, E.W. and Whiteman, C.H. (2005). Forecasting using relative entropy. Journal of Money, Credit, and Banking, 37, 383–401.
Stock, J.H. and Watson, M.W. (1999). Forecasting inflation. Journal of Monetary Economics, 44, 293–335.
Stock, J.H. and Watson, M.W. (2007). Why has U.S. inflation become harder to forecast. Journal of Money, Credit, and Banking, 39, 3–33.
Stock, J.H. and Watson, M.W. (2008). Phillips curve inflation forecasts. working paper.
Timmermann, A. (2006). Forecast combinations. In Handbook of Economic Forecasting (eds C.W.J. Granger, G. Elliot and A. Timmerman). Elsevier.