Understanding forecast failure in ESTAR models of real exchange rates

Buncic, Daniel (2009): Understanding forecast failure in ESTAR models of real exchange rates.

Abstract

The forecast performance of the empirical ESTAR model of Taylor et al. (2001) is examined for 4 bilateral real exchange rate series over an out-of-sample evaluation period of nearly 12 years. Point as well as density forecasts are evaluated relative to a simple AR(1) specification, considering horizons up to 22 steps head. The results of this study suggest that no forecast gains over a simple AR(1) model exist at any of the forecast horizons that are considered, regardless of whether point or density forecasts are used. Using simulation and non-parametric techniques in conjunction with graphical methods, this study shows that the non-linearity in the point forecasts of the ESTAR model decrease as the forecast horizon increases. Multiple steps ahead density forecasts of the ESTAR model are approximately normal looking, with no signs of skewness or bimodality. For an applied forecaster, there do not appear to exist any gains in using the non-linear ESTAR model over a simple AR(1) specification.

• Item Type: MPRA Paper
• Language: English
• Keywords: Purchasing power parity, regime modelling, non-linear real exchange rate models, ESTAR, forecast evaluation, density forecasts, non-parametric methods
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance > F47 - Forecasting and Simulation: Models and Applications; F - International Economics > F3 - International Finance > F31 - Foreign Exchange

References

Amisano, Gianni and Raffaella Giacomini (2007): “Comparing Density Forecasts via Weighted Likelihood Ratio Tests”, Journal of Business and Economic Statistics, 25 (2), 177–190.

Bao, Yong, Tae-Hwy Lee and Burak Saltoglu (2007): “Comparing density forecast models”, Journal of Forecasting, 26 (3), 203–225.

Breunig, Robert V., Serineh Najarian and Adrian R. Pagan (2003): “Specification Testing of Markov Switching Models”, Oxford Bulletin of Economics and Statistics, 65 (S1), 703–725.

De Grauwe, Paul and Marianna Grimaldi (2005): “Heterogeneity of Agents, Transaction Costs and the Exchange Rate”, Journal of Economic Dynamics and Control, 29 (4), 691–719.

–———— (2006): “Exchange Rate Puzzles: A Tale of Switching Attractors”, European Economic Review, 50 (1), 1–33.

Diebold, Francis X. and Roberto S. Mariano (1995): “Comparing Predictive Accuracy”, Journal of Business and Economic Statistics, 13 (1), 253–263.

Eitrheim, Øyvind and Timo Terasvirta (1996): “Testing the Adequacy of Smooth Transition Autoregressive Models”, Journal of Econometrics, 74 (1), 59–75.

Franses, Philip Hans and Dick van Dijk (2000): Nonlinear Time Series Models in Empirical Finance, Cambridge: Cambridge University Press.

Gallant, A. Ronald (1987): Nonlinear Statistical Models, New York: JohnWiley.

Granger, Clive W. J. and Timo Ter¨asvirta (1993): Modelling Nonlinear Economic Relationships, Oxford: Oxford University Press.

Harvey, David I., Stephen J. Leybourne and Paul Newbold (1997): “Testing the Equality of Prediction Mean Squared Errors”, International Journal of Forecasting, 13 (2), 281–291.

McCracken, MichaelW. and Kenneth D. West (2002): “Inference about Predictive Ability”, in A Companion to Economic Forecasting, edited by Michael P. Clements and David F. Hendry, Oxford: Blackwell Publishers, 299–321.

Mitchell, James and Stephen G. Hall (2005): “Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ’Fan’ Charts of Inflation”, Oxford Bulletin of Economics and Statistics, 67 (S1), 995–1033.

Newey, Whitney K. and Kenneth D. West (1987): “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix”, Econometrica, 55 (3), 703–708.

Obstfeld, Maurice and Alan M. Taylor (1997): “Nonlinear Aspects of Goods-Market Arbitrage and Adjustment: Hecksher’s Commodity Points Revisited”, Journal of the Japanese and International Economies, 11 (4), 441–479.

Pagan, Adrian R. (2002): “Learning About Models and Their Fit to Data”, International Economic Journal, 16 (2), 1–18.

Pagan, Adrian R. and Aman Ullah (1999): Nonparametric Econometrics, New York: Cambridge University Press.

Rapach, David E. and Mark E. Wohar (2006): “The out-of-Sample Forecasting Performance of Nonlinear Models of Real Exchange Rate Behavior”, International Journal of Forecasting, 22 (2), 341– 361.

Rogoff, Kenneth S. (1996): “The Purchasing Power Parity Puzzle”, Journal of Economic Literature, 34 (2), 647– 668.

Scott, David W. (1992): Multivariate Density Estimation: Theory, Practice, and Visualization, New York, Chichester: JohnWiley and Sons.

Taylor, Mark P., David A. Peel and Lucio Sarno (2001): “Nonlinear Adjustment in Real Exchange Rates: Towards a Solution to the Purchasing Power Parity Puzzles”, International Economic Review, 42 (4), 1015–1042.

van Dijk, Dick and Philip Hans Franses (2003): “Selecting a Nonlinear Time Series Model Using Weighted Tests of Equal Forecast Accuracy”, Oxford Bulletin of Economics and Statistics, 18 (S1), 727–744.

Westerhoff, Frank H. and Stefan Reitz (2003): “Nonlinearities and Cyclical Behavior: The Role of Chartists and Fundamentalists”, Studies in Nonlinear Dynamics and Econometrics, 7 (4), Article 3.