Working Paper: NBER ID: w29945
Authors: Katarzyna A. Bilicka; Andr Seidel
Abstract: To understand how global firm networks operate, we need consistent information on their activities, unbiased by their reporting choices. In this paper, we collect a novel dataset on the light that factories emit at night for a large sample of car manufacturing plants. We show that nightlight data can measure activity at such a granular level, using annual firm financial data and high-frequency data related to Covid-19 pandemic production shocks. We use this data to quantify the extent of misreported global operations of these car manufacturing firms and examine differences between sources of nightlight.
Keywords: nightlight data; remote sensing; firm activity; COVID-19; multinational corporations
JEL Codes: F23; H26; H32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| COVID-19 factory closures (L69) | nightlight emissions (Y50) |
| production activities (L23) | nightlight emissions (Y50) |
| nightlight emissions (Y50) | firm turnover (L14) |
| nightlight emissions (Y50) | firm activity (M13) |
| firm activity (M13) | financial disclosures accuracy (G38) |