In recent time, many studies have contributed to understanding how firms behave in the developing countries. However, collecting high-frequency firm data and a comprehensive sample frame remain pertinent in studying enterprise development in the low- and middle-income countries. This project aims to construct a longitudinal firm-level energy use database in monthly frequencies using administrative billing information from the power distributing companies operating in Dhaka city, Bangladesh. This unique database will comprise of all currently manufacturing enterprises in operations in Dhaka as long as they are customers of one of the two power utilities, allowing a population of about 10,000 manufacturers. The researchers will use this database to understand how Bangladeshi enterprises respond, manage their activities and possibly change their investment decisions during an exogenous shocks (such as COVID-19 pandemic).
This project will involve (a) merging the administrative dataset from the power distributing firms together and producing a longitudinal dataset using firms billing information to map their locations; (b) linking the longitudinal energy use data with spatial and temporal data including lockdown and zoning within Dhaka city; (c) exploring exits and entries of firms; and (d) collecting more detailed firm-level data through a survey to control for firms characteristics and estimating impact heterogeneity.
This project will contribute towards several policy issues that are important for a fast-growing low-middle income country such as Bangladesh. The project will characterise the nature of firm growth experiences at the enterprise level. Moreover, it will also use the data assembled to understand how the possible COVID-19 zoning affects firm behaviour and adaptation, including exiting from the market. The analysis will also contribute to assessing the efficacy of the zoning policies that the Bangladesh government is planning to impose.
