TY  - JOUR
TI  - A Nonlinear Autoregressive Distributed Lag (NARDL) Approach for U.S. Climate Policy Uncertainty Index, Renewable Energy Consumption, and Oil Prices
AB  - This study aims to reveal the asymmetric relationship among climate policy uncertainty, oil prices, and renewable energy consumption for January 2000-March 2021 in the U.S. The long- and short-run dynamic impacts of oil prices and renewable energy consumption on climate policy uncertainty are mainly examined utilizing a nonlinear autoregressive distributed lag (NARDL) approach. The findings of the study depict that there exists an asymmetric cointegrating relationship between climate policy uncertainty, renewable energy consumption, and crude oil prices in the long run. Climate policy uncertainty is affected by both negative and positive variations in renewable energy consumption and oil prices in the long-run period. The presence of asymmetric relations is an indicator of the data is suitable for the NARDL model. The NARDL estimation results reveal that an increment in renewable energy consumption causes an increase in climate policy uncertainty while a decrease in renewable energy consumption also causes an increase in climate policy uncertainty in the long-run period. Further, an increase in oil prices causes an increase in climate policy uncertainty while a reduction in oil prices results in a decrease in the climate policy uncertainty for a long-run period.
AU  - Dinc Cavlak, Ozge
DO  - 10.26745/ahbvuibfd.1055390
PY  - 2022
JO  - Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi (Online)
VL  - 24
IS  - 2
SN  - 2667-405X
SP  - 757
EP  - 776
DB  - TRDizin
UR  - http://search/yayin/detay/1196269
ER  -