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 u201cconsistencyu201d 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.
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机译：继Meese和Rogoff（1983）之后，先前对名义汇率确定的评估集中在一组狭窄的模型上。 Cheung等。 （2005年）增加了基于生产率的模型和“行为均衡汇率”模型，并评估了长达5年的绩效。在本文中，我们进一步扩展了模型集，以包括泰勒规则基本面，收益率曲线因素，并结合影子利率以及风险和流动性因素。将这些模型的性能与随机游走基准进行比较。这些模型是根据纠错和一阶差分规格估算的。我们使用不同的指标（均方误差，变化方向）以及Cheung and Chinn（1998）的检验来检验在各种预测范围（1个季度，4个季度，20个季度）的模型性能。尽管购买力平价的确相当不错，但没有任何一种模型能够通过均方误差度量始终胜过随机游走。而且，沿着变化方向的维度，某些结构模型的确具有优于随机行走的统计意义。尽管人们发现这些预测与汇率的实际价值是协整的，但在大多数情况下，预测相对于实际价值的弹性不同于统一性。总体而言，在一个时期内运作良好的模型/规格/货币组合不一定会在另一个时期内运作良好。
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