Consistent covariance matrix estimation with spatially dependent panel data

• 成果类型: Article
• 署名作者: Driscoll, JC; Kraay, AC
• 署名单位: Brown University; The World Bank
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/003465398557825
• 发表日期: 1998-11
• 页码: 549-560
• 关键词: procyclical productivity; heteroskedasticity; returns

摘要

Many panel data sets encountered in macroeconomics, international economics, regional science, and finance are characterized by cross-sectional or spatial'' dependence. Standard techniques that fail to account for this dependence will result in inconsistently estimated standard errors. In this paper we present conditions under which a simple extension of common nonparametric covariance matrix estimation techniques yields standard error estimates that are robust to very general forms of spatial and temporal dependence as the time dimension becomes large. We illustrate the relevance of this approach using Monte Carlo simulations and a number of empirical examples.