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来源类型Working Paper
规范类型报告
DOI10.3386/w23267
来源IDWorking Paper 23267
Exchange Rate Prediction Redux: New Models, New Data, New Currencies
Yin-Wong Cheung; Menzie D. Chinn; Antonio Garcia Pascual; Yi Zhang
发表日期2017-03-27
出版年2017
语种英语
摘要Previous assessments of nominal exchange rate determination, following Meese and Rogoff (1983) have focused upon a narrow set of models. Cheung et al. (2005) augmented the usual suspects with productivity based models, and "behavioral equilibrium exchange rate" models, and assessed performance at horizons of up to 5 years. In this paper, we further expand the set of models to include Taylor rule fundamentals, yield curve factors, and incorporate shadow rates and risk and liquidity factors. The performance of these models is compared against the random walk benchmark. The models are estimated in error correction and first-difference specifications. We examine model performance at various forecast horizons (1 quarter, 4 quarters, 20 quarters) using differing metrics (mean squared error, direction of change), as well as the “consistency” test of Cheung and Chinn (1998). No model consistently outperforms a random walk, by a mean squared error measure, although purchasing power parity does fairly well. Moreover, along a direction-of-change dimension, certain structural models do outperform a random walk with statistical significance. While one finds that these forecasts are cointegrated with the actual values of exchange rates, in most cases, the elasticity of the forecasts with respect to the actual values is different from unity. Overall, model/specification/currency combinations that work well in one period will not necessarily work well in another period
主题International Economics ; International Finance ; International Macroeconomics
URLhttps://www.nber.org/papers/w23267
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/580941
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GB/T 7714
Yin-Wong Cheung,Menzie D. Chinn,Antonio Garcia Pascual,et al. Exchange Rate Prediction Redux: New Models, New Data, New Currencies. 2017.
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