How quickly do forecasters incorporate news? Evidence from cross-country surveys

Isiklar, Gultekin and Lahiri, Kajal and Loungani, Prakash (2006): How quickly do forecasters incorporate news? Evidence from cross-country surveys. Published in: Journal of applied econometrics , Vol. 21, (2006): pp. 703-725.

Abstract

Using forecasts from Consensus Economics Inc., we provide evidence on the efficiency of real GDP growth forecasts by testing whether forecast revisions are uncorrelated. As the forecast data used are multi-dimensional—18 countries, 24 monthly forecasts for the current and the following year and 16 target years—the panel estimation takes into account the complex structure of the variance–covariance matrix due to propagation of shocks across countries and economic linkages among them. Efficiency is rejected for all 18 countries: forecast revisions show a high degree of serial correlation. We then develop a framework for characterizing the nature of the inefficiency in forecasts. For a smaller set of countries, the G-7, we estimate a VAR model on forecast revisions. The degree of inefficiency, as mananifested in the serial correlation of forecast revisions, tends to be smaller in forecasts of the USA than in forecasts for European countries. Our framework also shows that one of the sources of the inefficiency in a country’s forecasts is resistance to utilizing foreign news. Thus the quality of forecasts for many of these countries can be significantly improved if forecasters pay more attention to news originating from outside their respective countries. This is particularly the case for Canadian and French forecasts, which would gain by paying greater attention than they do to news from the USA and Germany, respectively.

• Item Type: MPRA Paper
• Language: English
• Keywords: Consensus economics; forecast inefficiency; GMM; VAR; panel data
• Subjects: E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E17 - Forecasting and Simulation: Models and Applications; F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance > F47 - Forecasting and Simulation: Models and Applications; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications

References

Artis MJ, Zhang W. 1997. International business cycles and the ERM: Is there a European business cycle? International Journal of Finance and Economics, 2: 1-16.

Ash JCK, Smyth DJ, Heravi SM. 1998. Are OECD forecasts rational and useful? A directional analysis. International Journal of Forecasting 14: 381-391.

Batchelor RA. 2001. How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus, Applied Economics 33: 225-35.

Batchelor RA, Dua P. 1991. Blue Chip rationality tests, Journal of Money, Credit and Banking 23: No: 4.

Breusch, TS, Pagan AR. 1980. The Lagrange Multiplier test and its application to model specifications in econometrics, Review of Economic Studies, 47, 239-53.

Canova F, Marrinan J. 1998. Sources and propagation of international output cycles: common shocks and transmission, Journal of International Economics, 46: 133- 166.

Clements MP. 1995. Rationality and the role of judgment in macroeconomic forecasting, Economic Journal, 105: 410-420.

Clements MP. 1997. Evaluating the rationality of fixed-event forecasts, Journal of Forecasting, 16: 225-239.

Clements MP, Hendry DE. 1998. Forecasting Economic Time Series, Cambridge University Press; Cambridge, UK.

Davies A, Lahiri K. 1995. A new framework for analyzing survey forecasts using threedimensional panel data, Journal of Econometrics 68: 205-227.

Davies A, Lahiri K. 1999. Reexamining the rational xpectations hypothesis using panel data on multi-period forecasts,” in Analysis of Panels and Limited Dependent Variable Models (eds. C. Hsiao et al.), Cambridge University Press: Cambridge,226-254.

Faust J, Rogers JH, Wright JH. 2005. News and noise in G-7 GDP announcements,Journal of Money, Credit and Banking, Forthcoming.

Fildes R, Stekler H. 2002. “The state of macroeconomic forecasting,” Journal of Macroeconomics, 24: 435-468.

Gallo GM, Granger CWJ, Jeon Y. 2002. Copycats and common swings: the impact of the use of the forecasts in information sets, IMF staff Papers 49: 4-21.

Harvey DI, Leybourne SJ, Newbold P. 2001. Analysis of a panel of UK macroeconomic forecasts. Econometrics Journal 4: 37-55.

Henriksson RD, Merton C. 1981. On market timing and investment performance 2:Statistical procedures for evaluating forecasting skills, Journal of Business 54: 513-533.

Koop G, Pesaran MH, Potter SM. 1996. Impulse response analysis in nonlinear multivariate models, Journal of Econometrics 17: 107-12.

Loungani P. 2001. How accurate are private sector forecasts? Cross- country evidence from consensus forecasts of output growth. International Journal of Forecasting 17: 419-432.

Merton RC. 1981. On market timing and investment performance 1: an equilibrium theory of value for market forecasts,” Journal of Business 54: 363-406.

Muth JF. 1961. Rational expectations and the theory of price movements. Econometrica 29: 315-335.

Nordhaus W.1987. Forecasting efficiency: concepts and applications. The Review of Economics and Statistics 69: 667-674.

Öller L-E, Barot B. 2000. The accuracy of European growth and inflation forecasts. International Journal of Forecasting 16: 293-315.

Pesaran MH. 2004. General Diagnostic Tests for cross section dependence in panels, mimeo. University of Cambridge, June 2004.

Pesaran MH, Timmerman AG. 1992. A simple nonparametric test of predictive performance. Journal of Business and Economics Statistics 10: 461-465.

Pesaran MH, Shin Y. 1998. Generalized impulse response analysis in linear multivariate models. Economics Letters 58: 17-29.

Pesaran, MH, Schuermann T, Weiner SM. 2003. Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconomic Model. Journal of Business & Economic Statistics, 22, 129-162.

Pons J. 2000. The accuracy of IMF and OECD forecasts for G7 countries. Journal of Forecasting 19: 53-63.

Stock JH, Watson MW. 2003. Understanding changes in international business cycle dynamics. NBER Working Papers No. w9859, July. Cambridge, MA.