Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this study, we explore the critical demand drivers of electricity consumption in Thailand based on monthly data from 2002 to 2020. Using Autoregressive Distributed Lag (ARDL), cross-quantile correlation (CQC), Generalized Method of Moments (GMM), and Granger-causality-in-quantile approaches, we find that industrial production and oil production positively contribute to next month's aggregate and provincial energy consumption in Thailand, both in the short and long run. We also find that industrial production positively affects current electricity consumption, whereas electricity prices negatively affect current electricity consumption. Oil production, however, has no effect on current electricity consumption. Moreover, the CQC analysis finds evidence of cross-predictability running from industrial production and electricity prices to next month's electricity consumption at the extreme and median quantiles of the distribution. Further, industrial production, electricity prices, and oil production Granger-cause energy consumption at the extreme and median quantiles of the distribution. Nevertheless, we show that the Thai government's energy policies are ineffective for reducing electricity consumption. Our findings have crucial policy implications for the electricity market efficient allocation and its reform.