Inflation persistence and the rationality of inflation expectations

Brissimis, Sophocles and Migiakis, Petros (2011): Inflation persistence and the rationality of inflation expectations.

Abstract

The rational expectations hypothesis for survey and model-based inflation forecasts − from the Survey of Professional Forecasters and the Greenbook respectively − is examined by properly taking into account the persistence characteristics of the data. The finding of near-unit-root effects in the inflation and inflation expectations series motivates the use of a local-to-unity specification of the inflation process that enables us to test whether the data are generated by locally non-stationary or stationary processes. Thus, we test, rather than assume, stationarity of near-unit-root processes. In addition, we set out an empirical framework for assessing relationships between locally non-stationary series. In this context, we test the rational expectations hypothesis by allowing the co-existence of a long-run relationship obtained under the rational expectations restrictions with short-run "learning" effects. Our empirical results indicate that the rational expectations hypothesis holds in the long run, while forecasters adjust their expectations slowly in the short run. This finding lends support to the hypothesis that the persistence of inflation comes from the dynamics of expectations.

• Item Type: MPRA Paper
• Language: English
• Keywords: Inflation; rational expectations; high persistence
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D84 - Expectations ; Speculations; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - General; 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; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications

References

Akerlof, G.A., 2007. The missing motivation in macroeconomics. American Economic Review 97, 5-36.

Andolfatto, D., Hendry, S., Moran, K., 2008. Are inflation expectations rational? Journal of Monetary Economics 55, 406-422.

Ball, L., 2000. Near-rationality and inflation in two monetary regimes. Working Paper Series 7988, National Bureau of Economic Research.

Berk, J.M., Hebbink, G., 2006. The anchoring of European inflation expectations. Working Papers Series 116, Netherlands Central Bank.

Brissimis, S.N., Magginas, N.S., 2008. Inflation forecasts and the New Keynesian Phillips curve. International Journal of Central Banking 4, 1-22.

Bryan, M.F., Palmqvist, S., 2005. Testing near-rationality using detailed survey data. Working Paper Series 05-02, Federal Reserve Bank of Cleveland.

Carroll C.D., 2003. Macroeconomic expectations of households and professional forecasters. Quarterly Journal of Economics 118, 269-298.

Chevillon, G., Massmann, M., and Mavroeidis, S., 2010. Inference in models with adaptive learning. Journal of Monetary Economics 57, 341-351.

Clarida, R., Gali, J., Gertler, M., 1999. The science of monetary policy: a new Keynesian perspective. Journal of Economic Literature 37, 1661–1707.

Dickey, D.A., Fuller W.A., 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427-431.

Elliott, G., Rothenberg, T.J., Stock, J.H., 1996. Efficient tests for an autoregressive unit root. Econometrica 64, 813-836.

Elliott, G., 1998. On the robustness of cointegration methods when regressors almost have unit roots. Econometrica 66, 149-158.

Engle, R.F., Granger C.W.J., 1987. Co-integration and error correction: representation, estimation and testing. Econometrica 55, 251-276.

Evans, G.W., Honkapohja S., 2001. Learning and Expectations in Macroeconomics. Princeton University Press: Princeton, New Jersey.

Evans, G.W., Honkapohja S., 2003. Adaptive learning and monetary policy design. Journal of Money, Credit, and Banking 35, 1045-1072.

Forsells, M., Kenny, G., 2002. The rationality of consumers' inflation expectations: survey-based evidence for the euro area. Working Paper Series 163, European Central Bank.

Gagnon, J.E., 2008. Inflation regimes and inflation expectations. Federal Reserve Bank of St. Louis Review 90, 229-243.

Gali, J., Gertler, M., 1999. Inflation dynamics: a structural econometric analysis. Journal of Monetary Economics 44, 195-222.

Grant, A.P., Thomas, L.B., 1999. Inflationary expectations and rationality revisited. Economics Letters 62, 331-338.

Hjalmarsson, E., Österholm, P., 2010. Testing for cointegration using the Johansen methodology when variables are near-integrated: size distortions and partial remedies. Empirical Economics 39, 51-76.

Kapetanios, G., Shin, G.Y., Snell, A., 2003. Testing for a unit root in the non-linear STAR framework. Journal of Econometrics 112, 359-379.

Kim S., Lima L.R., 2010. Local persistence and the PPP hypothesis. Journal of International Money and Finance 29, 555-569.

Lanne, M., 2001. Near unit root and the relationship between inflation and interest rates: a reexamination of the Fisher effect. Empirical Economics 26, 357-366.

Lima, L.R., Xiao Z., 2007. Do shocks last forever? Local persistency in economic time series. Journal of Macroeconomics 29, 103-122.

Mankiw, N.G., Reis, R., 2002. Sticky information versus sticky prices: a proposal to replace the New-Keynesian Phillips curve. Quarterly Journal of Economics 117, 1295-1328.

McCallum, B.T., 2010. Michael Woodford’s contributions to monetary economics. In: Wieland, V. (Ed.), The Science and Practice of Monetary Policy Today. Springer-Verlag, Berlin Heidelberg, pp. 3-8.

Mishkin, F.S., 2010. Will monetary policy become more of a science? In: Wieland, V. (Ed.), The Science and Practice of Monetary Policy Today. Springer-Verlag, Berlin Heidelberg, pp. 81-103.

Ng, S., Perron, P., 2001. Lag length selection and the construction of unit root tests with good size and power. Econometrica 69, 1519-1554.

Orphanides, A., Williams, J.C., 2002. Robust monetary policy rules with unknown natural rates. Brookings Papers on Economic Activity 33, 63-118.

Orphanides, A., Williams, J.C., 2005. Imperfect knowledge, inflation expectations, and monetary policy. In: Bernanke B.S., and Woodford M. (Eds.), The Inflation Targeting Debate. University of Chicago Press, Chicago, pp. 201-234.

Phillips, P.C.B., Perron, P., 1988. Testing for a unit root in time series regression. Biometrika 75, 335-346.

Phillips, P.C.B., Moon H.R., Xiao, Z., 2001. How to estimate autoregressive roots near unity. Econometric Theory 17, 29–69.

Roberts, J.M., 1998. Inflation expectations and the transmission of monetary policy. Finance and Economics Discussion Series 98-43, Board of Governors of the Federal Reserve System.

Romer C., Romer D., 2000. Federal Reserve information and the behavior of interest rates. American Economic Review 90, 429-457.

Thomas, L.B., 1999. Survey measures of expected U.S. inflation. Journal of Economic Perspectives 13, 125-144.