Spatial Unit Roots and Spurious Regression

• 成果类型: Article
• 署名作者: Muller, Ulrich K.; Watson, Mark W.
• 署名单位: Princeton University
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA21654
• 发表日期: 2024
• 页码: 1661-1695
• 关键词: economic time-series; EFFICIENT TESTS; cointegration; stationarity; THEOREM

摘要

This paper proposes a model for, and investigates the consequences of, strong spatial dependence in economic variables. Our findings echo those of the corresponding unit root time series literature: Spatial unit root processes induce spuriously significant regression results, even with clustered standard errors or spatial HAC corrections. We develop large-sample valid unit root and stationarity tests that can detect such strong spatial dependence. Finally, we use simulations to study strategies for valid inference in regressions with persistent spatial data, such as spatial analogues of first-differencing transformations. Regressions from Chetty, Hendren, Kline, and Saez (2014) are used to illustrate the issues and methods.