Predicting the Conditional Distributions of Inflation and Inflation Uncertainty in South Africa: The Role of Climate Risks

Mehmet Balcilar (), Kenny Kutu (), Sonali Das () and Rangan Gupta ()
Additional contact information
Mehmet Balcilar: Department of Economics and Business Analytics, University of New Haven, West Haven, Connecticut, United States; Department of Economics, OSTIM Technical University, Ankara, Turkiye
Kenny Kutu: Department of Business Management, University of Pretoria, Pretoria, 0002, South Africa
Sonali Das: Department of Business Management, University of Pretoria, Pretoria, 0002, South Africa
Rangan Gupta: Department of Business Management, University of Pretoria, Pretoria, 0002, South Africa

No 202529, Working Papers from University of Pretoria, Department of Economics

Abstract: This paper analyzes the predictive effect of climate risks on inflation and inflation uncertainty in an inflation targeting emerging economy through a multivariate nonparametric higher-order causality-in-quantiles test. In this regard, we obtain a monthly Google Trends search-based Climate Attention Index for South Africa (CAI-SA), which incorporates both local and global terms dealing with physical and transition risks between January 2004 and September 2024. Using the CAI-SA, we find that linear Granger causality tests fail to show any evidence of prediction of overall and food and non-alcoholic beverages inflation rates, due to model misspecifications from nonlinearity and structural breaks. However, the robust multivariate nonparametric framework depicts statistically significant predictability over the entire conditional distribution of not only the two inflation rates, but also their respective volatilities, i.e., squared values. The strongest predictive impact is observed at the tails of the conditional distributions of the first- and second-moment of the two inflation rates. Our findings, in general, are robust to alternative definitions of inflation volatility, exclusion of the control variables, different methods of construction of the CAI, and a bootstrapped version of the test to account for size distortion and low power. Analyses involving signs of the causal impact reveal significant positive association between the CAI-SA and the inflation rates and their volatilities, thus having serious implications for monetary policy decisions in South Africa in the wake of heightened climate risks.

Keywords: Climate Attention Index; Inflation; Inflation Uncertainty; Higher-Order Multivariate Causality-in-Quantiles Test; South Africa (search for similar items in EconPapers)
JEL-codes: C22 C53 E31 Q54 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2025-08
New Economics Papers: this item is included in nep-for and nep-mon
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.up.ac.za/media/shared/61/WP/wp_2025_29.zp270944.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202529

Access Statistics for this paper

More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rangan Gupta ().