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Information Rigidities in Economic Growth Forecasts; Evidence from a Large International Panel

  • Jonas Dovern
  • Ulrich Fritsche
  • Prakash Loungani
  • Natalia T. Tamirisa

We examine the behavior of forecasts for real GDP growth using a large panel of individual forecasts from 30 advanced and emerging economies during 1989–2010. Our main findings are as follows. First, our evidence does not support the validity of the sticky information model (Mankiw and Reis, 2002) for describing the dynamics of professional growth forecasts. Instead, the empirical evidence is more in line with implications of "noisy" information models (Woodford, 2002; Sims, 2003). Second, we find that information rigidities are more pronounced in emerging economies than advanced economies. Third, there is evidence of nonlinearities in forecast smoothing. It is less pronounced in the tails of the distribution of individual forecast revisions than in the central part of the distribution.

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Paper provided by International Monetary Fund in its series IMF Working Papers with number 13/56.

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Length: 24
Date of creation: 27 Feb 2013
Date of revision:
Handle: RePEc:imf:imfwpa:13/56
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  1. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economic Research Papers 2009-091, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  2. N. Gregory Mankiw & Ricardo Reis, 2001. "Sticky Information Versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," NBER Working Papers 8290, National Bureau of Economic Research, Inc.
  3. Khan, Hashmat & Zhu, Zhenhua, 2006. "Estimates of the Sticky-Information Phillips Curve for the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(1), pages 195-207, February.
  4. Roy Batchelor, 2007. "Forecaster Behaviour and Bias in Macroeconomic Forecasts," Ifo Working Paper Series Ifo Working Paper No. 39, Ifo Institute for Economic Research at the University of Munich.
  5. Prakash Loungani, 2000. "How Accurate Are Private Sector Forecasts; Cross-Country Evidence From Consensus Forecasts of Output Growth," IMF Working Papers 00/77, International Monetary Fund.
  6. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  7. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
  8. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116 - 159.
  9. Jörg Döpke & Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2006. "Sticky Information Phillips Curves: European Evidence," Discussion Papers of DIW Berlin 615, DIW Berlin, German Institute for Economic Research.
  10. Olivier Coibion & Yuriy Gorodnichenko, 2010. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," NBER Working Papers 16537, National Bureau of Economic Research, Inc.
  11. Kajal Lahiri & Gultekin Isiklar, 2006. "How Far Ahead Can We Forecast? Evidence From Cross-country Surveys," Discussion Papers 06-04, University at Albany, SUNY, Department of Economics.
  12. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
  13. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  14. Roland Bénabou, 2009. "Groupthink: Collective Delusions in Organizations and Markets," NBER Working Papers 14764, National Bureau of Economic Research, Inc.
  15. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
  16. Dovern, Jonas & Fritsche, Ulrich & Slacalek, Jiri, 2009. "Disagreement among forecasters in G7 countries," Working Paper Series 1082, European Central Bank.
  17. Christopher W. Crowe, 2010. "Consensus Forecasts and Inefficient Information Aggregation," IMF Working Papers 10/178, International Monetary Fund.
  18. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
  19. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  20. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
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