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An inflation expectations horserace

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Author Info

  • Guzman, Giselle C.

Abstract

For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Survey. While these measures have been useful in developing models of forecasting inflation, the data are low frequency measures which appear anachronistic in the modern era of high frequency and real-time data. I present a collection of 37 different measures of inflation expectations, including many previously unexploited monthly and real-time measures of inflation expectations. These higher frequency measures tend to outperform the standard three low frequency survey measures in tests of accuracy, predictive power, and rationality, indicating that there are benefits to using higher frequency measures of inflation expectations. Out of sample forecasts confirm the findings.

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File URL: http://mpra.ub.uni-muenchen.de/40233/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 36511.

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Date of creation: 25 Jan 2010
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Handle: RePEc:pra:mprapa:36511

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Related research

Keywords: Inflation; expectations; surveys; households; economists; rationality; efficiency; unbiasedness; forecast accuracy; out-of-sample forecasts; Granger Causality; high-frequency data; price level; money and prices; CPI; PPI; PCE;

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References

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  1. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  2. Joseph E. Stiglitz, 2011. "Rethinking Macroeconomics: What Failed, And How To Repair It," Journal of the European Economic Association, European Economic Association, vol. 9(4), pages 591-645, 08.
  3. N. Gregory Mankiw & Ricardo Reis, 2001. "Sticky information versus sticky prices: a proposal to replace the New-Keynesian Phillips curve," Proceedings, Federal Reserve Bank of San Francisco, issue Jun.
  4. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
  5. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  6. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
  7. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
  8. Mariano, Roberto S. & Preve, Daniel, 2012. "Statistical tests for multiple forecast comparison," Journal of Econometrics, Elsevier, vol. 169(1), pages 123-130.
  9. Giannone, Domenico & Reichlin, Lucrezia & Small, David H., 2006. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Working Paper Series 0633, European Central Bank.
  10. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  11. Gramlich, Edward M, 1983. "Models of Inflation Expectations Formation: A Comparison of Household and Economist Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 15(2), pages 155-73, May.
  12. Grant, Alan P. & Thomas, Lloyd B., 1999. "Inflationary expectations and rationality revisited," Economics Letters, Elsevier, vol. 62(3), pages 331-338, March.
  13. Guzman, Giselle C., 2008. "Using sentiment surveys to predict GDP growth and stock returns," MPRA Paper 36653, University Library of Munich, Germany.
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Cited by:
  1. Joseph E. Stiglitz, 2011. "Rethinking Macroeconomics: What Failed, And How To Repair It," Journal of the European Economic Association, European Economic Association, vol. 9(4), pages 591-645, 08.

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