Spatial Unit Roots and Spurious Regression

IF 6.6 1区经济学 Q1 ECONOMICS

Econometrica Pub Date : 2024-09-27 DOI:10.3982/ECTA21654

Ulrich K. Müller, Mark W. Watson

引用次数: 0

Abstract

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.

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空间单位根与虚假回归

本文提出了一个经济变量空间依赖性很强的模型，并对其后果进行了研究。我们的研究结果与相应的 "单位根 "时间序列文献不谋而合：空间单位根过程会诱发虚假显著的回归结果，即使使用聚类标准误差或空间 HAC 修正也是如此。我们开发了大样本有效单位根和静止性检验，可以检测出这种强烈的空间依赖性。最后，我们用模拟的方法研究了在有持续空间数据的回归中进行有效推断的策略，如空间类似的第一次差分变换。我们使用 Chetty、Hendren、Kline 和 Saez（2014 年）的回归来说明问题和方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Econometrica 社会科学-数学跨学科应用

CiteScore

11.00

自引率

3.30%

发文量

审稿时长

6-12 weeks

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