TY - JOUR
T1 - Markov-switching dependence between artificial intelligence and carbon price
T2 - The role of policy uncertainty in the era of the 4th industrial revolution and the effect of COVID-19 pandemic
AU - Tiwari, Aviral Kumar
AU - Abakah, Emmanuel Joel Aikins
AU - Le, TN Lan
AU - Leyva-de la Hiz, Dante I.
N1 - Publisher Copyright:
© 2020
PY - 2021/2
Y1 - 2021/2
N2 - This paper investigates the dependence structure and dynamics between artificial intelligence (AI) and carbon prices in the era of the 4th industrial revolution. Using the NASDAQ AI price index as a measure of AI and the European Energy Exchange EU emissions trading system (i.e. certificate prices for CO2 emissions) as a measure of carbon prices, we employ time-varying Markov switching copula models from December 2017 to July 2020 that provide evidence of a time-varying Markov tail dependence structure and dynamics between AI and carbon prices. The result shows a negative dependence structure for the return series between AI and carbon prices. However, the relationship is asymmetric, indicating that there is a stronger tail dependence in the lower tails instead of the upper tails. The finding implies that AI is a favourable hedge against carbon prices, therefore indicating the diversification benefits of AI. To understand the issue in detail, we examine the effect of economic policy uncertainty, equity market volatility, and the recent COVID-19 pandemic; we find their negative effect on the dynamic dependence structure between AI and carbon prices at lower and higher quantiles. This evidence offers additional support for the safe-haven ability of AI for carbon prices.
AB - This paper investigates the dependence structure and dynamics between artificial intelligence (AI) and carbon prices in the era of the 4th industrial revolution. Using the NASDAQ AI price index as a measure of AI and the European Energy Exchange EU emissions trading system (i.e. certificate prices for CO2 emissions) as a measure of carbon prices, we employ time-varying Markov switching copula models from December 2017 to July 2020 that provide evidence of a time-varying Markov tail dependence structure and dynamics between AI and carbon prices. The result shows a negative dependence structure for the return series between AI and carbon prices. However, the relationship is asymmetric, indicating that there is a stronger tail dependence in the lower tails instead of the upper tails. The finding implies that AI is a favourable hedge against carbon prices, therefore indicating the diversification benefits of AI. To understand the issue in detail, we examine the effect of economic policy uncertainty, equity market volatility, and the recent COVID-19 pandemic; we find their negative effect on the dynamic dependence structure between AI and carbon prices at lower and higher quantiles. This evidence offers additional support for the safe-haven ability of AI for carbon prices.
KW - Artificial intelligence
KW - Carbon price
KW - Time-varying dependence
UR - http://www.scopus.com/inward/record.url?scp=85096160111&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2020.120434
DO - 10.1016/j.techfore.2020.120434
M3 - Article
AN - SCOPUS:85096160111
SN - 0040-1625
VL - 163
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 120434
ER -