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Are Forecast Updates Progressive?

Chang, Chia-Lin and Franses, Philip Hans and McAleer, Michael (2011) Are Forecast Updates Progressive? [ Documentos de trabajo del Instituto Complutense de Análisis Económico; nº 3, 2011, ] (Unpublished)

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Abstract

Many macro-economic forecasts and forecast updates, such as those from the IMF and OECD, typically involve both a model component, which is replicable, as well as intuition (namely, expert knowledge possessed by a forecaster), which is non-replicable. . Learning from previous mistakes can affect both the replicable component of a model as well as intuition. If learning, and hence forecast updates, are progressive, forecast updates should generally become more accurate as the actual value is approached. Otherwise, learning and forecast updates would be neutral. The paper proposes a methodology to test whether macro-economic forecast updates are progressive, where the interaction between model and intuition is explicitly taken into account. The data set for the empirical analysis is for Taiwan, where we have three decades of quarterly data available of forecasts and their updates of two economic fundamentals, namely the inflation rate and real GDP growth rate. The empirical results suggest that the forecast updates for Taiwan are progressive, and that progress can be explained predominantly by improved intuition.


Item Type:Working Paper or Technical Report
Additional Information:

JEL Classifications: C53, C22, E27, E37.

Uncontrolled Keywords:Macro-economic forecasts, Econometric models, Intuition, learning, Progressive forecast updates, Forecast errors
Subjects:Social sciences > Economics > Econometrics
Social sciences > Economics > Macroeconomics
Series Name:Documentos de trabajo del Instituto Complutense de Análisis Económico
Volume:2011
Number:3
ID Code:12434
References:

Bunn, D.W. and A.A. Salo (1996), Adjustment of forecasts with model consistent expectations, International Journal of Forecasting, 12, 163-170.

Chang, C.-L., P.H. Franses and M. McAleer (2009), How accurate are government forecasts of economic fundamentals? The case of Taiwan, to appear in International Journal of Forecasting. Available at SSRN: http://ssrn.com/abstract=1431007.

Clark, T.E. and M.W. McCracken (2001), Tests of equal forecast accuracy and encompassing for nested models, Journal of Econometrics, 105, 85-110.

Fiebig, D.G., M. McAleer and R. Bartels (1992), Properties of ordinary least squares estimators in regression models with non-spherical disturbances, Journal of Econometrics, 54, 321-334.

Franses, P.H., M. McAleer and R. Legerstee (2009), Expert opinion versus expertise in forecasting, Statistica Neerlandica, 63, 334-346.

McAleer, M. (1992), Efficient estimation: the Rao-Zyskind condition, Kruskal's theorem and ordinary least squares, Economic Record, 68, 65-72.

McAleer, M. and C. McKenzie (1991), When are two step estimators efficient?, Econometric Reviews, 10, 235-252.

Oxley, L. and M. McAleer (1993), Econometric issues in macroeconomic models with generated regressors, Journal of Economic Surveys, 7, 1-40.

Pagan, A.R. (1984), Econometric issues in the analysis of regressions with generated regressors, International Economic Review, 25, 221-247.

Smith, J. and M. McAleer (1994), Newey-West covariance matrix estimates for models with generated regressors, Applied Economics, 26, 635-640.

Welch, B.L. (1951). On the comparison of several mean values: An alternative approach, Biometrika, 38, 330-336.

Deposited On:16 Mar 2011 08:20
Last Modified:21 Nov 2013 12:21

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