期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2012
出版社：European Central Bank
摘要：The curse of dimensionality refers to the di¢ culty of including all relevant variables in empirical applications due to the lack of su¢ cient degrees of freedom. A common solution to alleviate the problem in the context of open economy models is to aggregate foreign variables by constructing trade-weighted cross-sectional averages. This paper provides two key contributions in the context of static panel data models. The rst is to show under what conditions the aggregation of foreign variables (AFV) leads to consistent estimates (as the time dimension T is xed and the cross section dimension N ! 1). The second is to design a formal test to assess the admissibility of the AFV restriction and to evaluate the small sample properties of the test by undertaking Monte Carlo experiments. Finally, we illustrate an application in the context of the current account empirical literature where the AFV restriction is rejected.
关键词：Curse of Dimensionality; Panel Data Models; Current Account.
