nighttime lights

Regional Inequality from Outer Space: Predicting GDP from Nighttime Lights and Building Inequality Indices in Python

A comprehensive, beginner-friendly Python replication of Lessmann and Seidel (2017) — turning satellite nighttime lights into predicted regional GDP, building five population-weighted inequality indices from scratch, exploring the cross-country dynamics of regional inequality, and estimating the regional Kuznets curve, its determinants, and a Conley spatial-HAC robustness check with PyFixest.

Bayesian average of classical estimates for panel data: Can the puzzle of the shape of the regional Kuznets curve be solved?

We study the robust determinants of regional inequality using a Bayesian average of classical estimates for panel data.

Harmonized luminosity and economic activity across provinces in China: Cross-sectional differences, regional time series, and inequality dynamics

This study explores income-luminosity dynamics in China, highlighting VIIRS's superiority over DMSP in predictive accuracy over time.

Exploring Economic Activity from Outer Space: A Python Notebook for Processing and Analyzing Satellite Nighttime Lights

This paper introduces a user-friendly geocomputational notebook that illustrates how to process and analyze satellite NTL images.

Can higher-quality nighttime lights predict sectoral GDP across subnational regions? Urban and rural luminosity across provinces in Türkiye

This study explores the potential of higher-quality nighttime light (NTL) data to predict economic activity across various sectors within regions.