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This paper investigates whether electricity consumption is a useful indicator for tracking economic fluctuations in Bangladesh. It presents monthly data on national electricity consumption since 1993 and daily consumption data since February 2010 for the country’s eight divisions. National electricity consumption is strongly correlated with other high-frequency indicators of economic activity, and it has declined during natural disasters and the COVID-19 lockdowns. The paper estimates an electricity consumption model that explains over 90 percent of the variation in daily consumption based on the trend, seasonality, within-week variation, holidays, Ramadan, and temperature. Deviations from the model prediction can act as in indicator of economic fluctuations. For example, during the first COVID-19 lockdown in April 2020, electricity consumption in Dhaka fell over 40 percent compared with normal and remained below the normal level until early 2021. The later lockdowns, in contrast, had only small additional impacts, in line with less stringent containment measures and more effective adaptation.

The COVID-19 pandemic has disrupted economic activity in India. Adjusting policies to contain trans- mission while mitigating the economic impact requires an assessment of the economic situation in near real-time and at high spatial granularity. This paper shows that daily electricity consumption and monthly nighttime light intensity can proxy for economic activity in India. Energy consumption is compared with the predictions of a consumption model that explains 90 percent of the variation in normal times. Energy consumption declined strongly after a national lockdown was implemented on March 25, 2020 and remained a quarter below normal levels throughout April. It recovered somewhat subsequently, but electricity consumption was on average still 13.5 percent lower than normal in May. Not all states and union territories have been affected equally. While electricity consumption halved in some, others were not affected at all. Part of the heterogeneity is explained by the prevalence of manufacturing and return migration. At the district level, higher COVID-19 infection rates were associated with larger declines in nighttime light intensity in April. Together, daily electricity consumption and nighttime light intensity allow monitoring economic activity in near real-time and high spatial granularity.