# **1. Introduction**

The COVID-19 pandemic exposed limitations to economic measurement. Across the world, governments enacted lockdowns and other containment measures to mitigate the public health crisis, with strong implications for economic activity. Rational policy making requires evaluating economic impacts and assessing the economic situation in real-time. However, in many countries, traditional indicators of economic activity do not provide that. First, national accounts estimates are available with substantial lags and often only at the national level. In addition, national accounts estimates in many countries, including in Bangladesh, are only available at annual but not quarterly frequency. Second, data collection through surveys, which are fundamental for the traditional estimation of gross value added, became more difficult during the pandemic due to severe containment measures. In Bangladesh, for example, it took more than a year to finalize the gross value-added estimates for fiscal year 2020 (FY2020) (from July 2019 to June 2020). In such a situation, high-frequency indicators of economic activity can provide crucial insights.

Many new approaches to tracking economic activity have been introduced since the outbreak of the COVID-19 pandemic. For example, high-frequency indicators measuring mobility based on phone locations provided by Google and Facebook have been used to assess the economic situation in real-time (Spelta and Pagnottoni 2021). Beyer, Franco-Bedoya, and Galdo (2021) use daily electricity consumption and monthly nighttime light intensity to analyze subnational economic activity during the pandemic in India. Few comparable indicators for tracking the economy in real-time are available in Bangladesh.

In this paper, we establish daily electricity consumption as a useful indicator for tracking economic fluctuations in Bangladesh. First, we confirm a meaningful relationship between electricity consumption and short-term economic fluctuations. Second, we estimate a daily electricity consumption model that explains over 90 percent of the daily variation in electricity consumption. Deviations of actual electricity consumption from the model prediction can then be interpreted as a real-time indicator of economic activity and can be used to assess economic shocks. We provide this measure not just at the national level, but also for the country’s eight divisions separately. Using this measure, we show that electricity consumption in Dhaka fell over 40 percent compared with normal during the first lockdown in April 2020 and remained below normal until early 2021. In stark contrast, the later lockdowns had smaller impacts, suggesting strong adaptation to the COVID-19 containment measures.

The layout of the paper proceeds as follows. Section 2 reviews related literature. Section 3 describes the data sources. Section 4 presents stylized facts on electricity consumption in Bangladesh. Section 5 analyzes the relationship between electricity consumption and economic activity in Bangladesh. Section 6 estimates a daily electricity consumption model. Section 7 analyzes deviations from the model during COVID-19 in Dhaka. Section 8 concludes.

2