Asymmetric impacts of Chinese climate policy uncertainty on Chinese asset prices
Najaf Iqbal,
Elie Bouri,
Syed Jawad Hussain Shahzad and
Naif Alsagr
Energy Economics, 2024, vol. 133, issue C
Abstract:
Uncertainty is important for pricing financial assets, and the academic literature is full of evidence of how various types of financial, economic, and geopolitical uncertainties affect assets and financial markets. However, the academic literature is very limited about the impact of Chinese climate policy uncertainty on the market of Chinese carbon emission allowances, Chinese environment, social and governance (ESG) stocks, Chinese clean energy stocks, and Chinese gas and oil stocks. In this study, we contribute to this line of research by examining the asymmetric impacts of the daily Chinese climate policy uncertainty, recently proposed by Ma et al. (2023), on the prices of these Chinese assets using the nonlinear autoregressive distributed lag (NARDL) framework. The results show that an increase in Chinese climate policy uncertainty significantly decreases (increases) carbon emission allowance prices (ESG index), in the long run. There is no asymmetric cointegration between Chinese climate policy uncertainty and the oil and gas stock index whereas the effect is insignificant for the clean energy stock index. In the short term, overall stock market conditions and own previous values of the indices drive the prices of energy related assets. These findings offer investors, traders, and policymakers in China important information useful for making more refined investment decisions and policy formulations under the effect of Chinese climate policy uncertainty.
Keywords: Carbon emission allowance; Chinese assets; Clean and brown energy stocks; Daily Chinese climate policy uncertainty; ESG stocks; NARDL framework (search for similar items in EconPapers)
JEL-codes: G14 G15 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:133:y:2024:i:c:s0140988324002263
DOI: 10.1016/j.eneco.2024.107518
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