The perils of aggregating foreign variables in panel data models

Arbeitspapier

The curse of dimensionality refers to the difficulty of including all relevant variables in empirical applications due to the lack of sufficient 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 first is to show under what conditions the aggregation of foreign variables (AFV) leads to consistent estimates (as the time dimension T is fixed and the cross section dimension N -> infinite). 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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: ECB Working Paper ; No. 1444

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models ; Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models ; Open Economy Macroeconomics
• Subject: current account ; Curse of dimensionality ; panel data models

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ca' Zorzi, Michele ; Chudik, Alexander ; Dieppe, Alistair
• Event: Veröffentlichung
• (who): European Central Bank (ECB)
• (where): Frankfurt a. M.
• (when): 2012

Further information

• Handle: http://hdl.handle.net/10419/153877
• Last update: 10.03.2025, 11:42 AM CET