文章基本信息

标题：Testing Forward Exchange Rate Unbiasedness Efficiently: A Semiparametric Approach
其他标题：Testing Forward Exchange Rate Unbiasedness Efficiently: A Semiparametric Approach
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作者：Douglas J. Hodgson ; Oliver Linton ; Keith Vorkink 等
期刊名称：Journal of Applied Economics
印刷版ISSN：1514-0326
电子版ISSN：1667-6726
出版年度：2004
卷号：7
期号：1
页码：325-353
DOI：10.1080/15140326.2004.12040608
摘要：We apply semiparametric efficient estimation procedures for a seemingly unrelated regression model where the multivariate error density is elliptically symmetric to study the efficiency of the foreign exchange market. We consider both cointegrating regressions and standard stationary regressions. The elliptical symmetry assumption allows us to avoid the curse of dimensionality problem that typically arises in multivariate semiparametric estimation procedures, because the multivariate elliptically symmetric density function can be written as a function of a scalar transformation of the observed multivariate data. We test the unbiasedness hypothesis on both weekly and daily exchange rate data and strongly reject unbiasedness at the weekly horizon, but fail to reject the unbiasedness hypothesis on the daily data. Estimates of the semiparametric procedure in some cases differ substantially from traditional OLS estimates.
关键词：forward exchange market;time series econometrics;nonparametric statistics