Spurious Weather Effects

30 Pages Posted: 4 Jun 2015

See all articles by Jo Thori Lind

Jo Thori Lind

University of Oslo - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Multiple version iconThere are 2 versions of this paper

Date Written: May 30, 2015

Abstract

Rainfall is a truly exogeneous variable and hence popular as an instrument for many outcomes. But by its very nature, rainfall in nearby areas tends to be correlated. I show theoretically that if there are also spatial trends in outcomes of interest, this may create spurious correlation. In panel data models where fixed features can be dummied out, the same problem can occur if time trends are spatially dependent. Using Monte Carlo analysis, I show that standard tests can reject true null hypotheses in up to 99% of cases. I also show that this feature is present in a study of the effect of precipitation on electoral turnout in Norway. Using precipitation on non-election days, I show that the distribution of parameter estimates is far away from the theoretical distribution. To solve the problem, I suggest controlling for spatial and spatio-temporal trends using multi-dimensional polynomial approximations.

Keywords: rainfall, spurious correlation, spatial correlation, Legendre polynomial

JEL Classification: C130, C140, C210, D720

Suggested Citation

Lind, Jo Thori, Spurious Weather Effects (May 30, 2015). CESifo Working Paper Series No. 5365, Available at SSRN: https://ssrn.com/abstract=2613896

Jo Thori Lind (Contact Author)

University of Oslo - Department of Economics ( email )

P.O. Box 1095 Blindern
N-0317 Oslo
Norway

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

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