Does sunspot numbers cause global temperatures? A reconsideration using non-parametric causality tests

Abstract

Highlights• A non-parametric Singular Spectrum Analysis based causality test is proposed.• SSA-based causality test outperformed time and frequency domain causality tests.• The new non-parametric technique can capture the possibly existing nonlinearities.• Predictive ability is detected from sunspot numbers on global temperatures. ABSTRACTIn a recent paper, Gupta et al., (2015), analyzed whether sunspot numbers cause global temperatures based on monthly data covering the period 1880:1-2013:9. The authors find that standard time domain Granger causality test fails to reject the null hypothesis that sunspot numbers does not cause global temperatures for both full and sub-samples, namely 1880: 1-1936:2, 1936:3-1986:11 and 1986:12-2013:9 (identified based on tests of structural breaks). However, frequency domain causality test detects predictability for the full-sample at short (2 to 2.6 months) cycle lengths, but not the sub-samples. But since, full-sample causality cannot be relied upon due to structural breaks, Gupta et al., (2015) concludes that the evidence of causality running from sunspot numbers to global temperatures is weak and inconclusive. Given the importance of the issue of global warming, our current paper aims to revisit this issue of whether sunspot numbers cause global temperatures, using the same data set and sub-samples used by Gupta et al., (2015), based on an nonparametric Singular Spectrum Analysis (SSA)-based causality test. Based on this test, we however, show that sunspot numbers have predictive ability for global temperatures for the three sub-samples, over and above the full-sample. Thus, generally speaking, our non-parametric SSA-based causality test outperformed both time domain and frequency domain causality tests and highlighted that sunspot numbers have always been important in predicting global temperatures.Keywords: Causality; Singular Spectrum Analysis; frequency domain; global temperatures predictability; sunspot numbers JEL classification: C32 1 IntroductionGlobal warming, i.e., rising temperature of the earth's surface, is undoubtedly the biggest topic of research amongst researchers working on environment. While, analyzing the impact of global warming cannot be ignored, but what factors drive it is perhaps more important, as it not only allows us to predict global warming, but also takes measures to control it. It is quite well-accepted that global warming is due to greenhouse gases, additionally, there is a large literature 1 that relates the same with solar activity. However, the evidence from this literature is, at best, mixed. While there are studies (see for example, Rind, 1998, 2009; West, 2003, 2005;Scafetta et al., 2004;Scaffeta, 2009 Scaffeta, , 2011Folland et al., 2013;Zhou and Tung, 2013) that find significant relationships between solar radiation and global temperatures, one one hand. On the other hand, there are some authors who claim that the two variables are unrelated (see for example, Pittock, 1978Pittock, , 1983Pittock, , 2009Love et al., 2011;Usoskin, e...

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