An Evaluation of the Exchange Rate Forecasting Performance of the New Keynesian Model

Vitek, Francis (2007): An Evaluation of the Exchange Rate Forecasting Performance of the New Keynesian Model.

Abstract

This paper evaluates the dynamic out of sample nominal exchange rate forecasting performance of the canonical New Keynesian model of a small open economy. A novel Bayesian procedure for jointly estimating the hyperparameters and trend components of a state space representation of an approximate linear panel unobserved components representation of this New Keynesian model, conditional on prior information concerning the values of hyperparameters and trend components, is developed and applied for this purpose. In agreement with the existing empirical literature, we find that nominal exchange rate movements are difficult to forecast, with a random walk generally dominating the canonical New Keynesian model of a small open economy in terms of predictive accuracy at all horizons. Nevertheless, we find empirical support for the common practice in the theoretical open economy macroeconomics literature of imposing deterministic equality restrictions on deep structural parameters across economies, both in sample and out of sample.

• Item Type: MPRA Paper
• Language: English
• Keywords: Exchange rate forecasting; New Keynesian model; Small open economy
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General; F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance > F41 - Open Economy Macroeconomics; F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance > F47 - Forecasting and Simulation: Models and Applications; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models