The datasets and software code (in the form of STATA dofiles) relate to the publication in Applied Economics entitled: "Lights along the frontier: convergence of economic activity in the proximity of the Polish-German border, 1992-2012". The analysis dataset in STATA format is created by combining data coming from: 1) NOAA Version 4 DMSP-OLS Nighttime Lights Time Series (https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html); 2) Map data copyrighted OpenStreetMap (OSM) contributors and available from https://www.openstreetmap.org; 3) Administrative division of Poland, municipality level Shapefiles for 2018, PRG (http://www.gugik.gov.pl/pzgik/dane-bez-oplat/dane-z-panstwowego-rejestru-granic-i-powierzchni-jednostek-podzialow-terytorialnych-kraju-prg); 4) Map of the municipalities and districts of Germany as of 31.12.2013, VG250 and VG250-EW, © GeoBasis-DE / BKG 2013 (https://gdz.bkg.bund.de/); Geographical data (nighttime lights, municipality borders for Poland and Germany and OpenStreetMap data) have been imported into PostgreSQL database using PostGIS plugin using batch processing in Python. Nighttime intensities for municipalities were created by intersecting vector municipality borders and raster lights data for each avaliable year and satelite. Light totals and averages were calculated using calibrated pixel values using 2nd deg. polynominal intercalibration parameters from Elvidge et al., National Trends in Satellite Observed Lighting: 1992-2009. Bridge crossings were identified using contemporary map data and OSM. OSM data were used to calculate road travel times and distances using pgRouting in PostgreSQL. Data were exported into CSV using Python and imported and merged in Stata, creating the initial dataset.

The datasets and software code (in the form of STATA dofiles) relate to the publication in Applied Economics entitled: "Lights along the frontier: convergence of economic activity in the proximity of the Polish-German border, 1992-2012". The analysis dataset in STATA format is created by combining data coming from: 1) NOAA Version 4 DMSP-OLS Nighttime Lights Time Series (https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html); 2) Map data copyrighted OpenStreetMap (OSM) contributors and available from https://www.openstreetmap.org; 3) Administrative division of Poland, municipality level Shapefiles for 2018, PRG (http://www.gugik.gov.pl/pzgik/dane-bez-oplat/dane-z-panstwowego-rejestru-granic-i-powierzchni-jednostek-podzialow-terytorialnych-kraju-prg); 4) Map of the municipalities and districts of Germany as of 31.12.2013, VG250 and VG250-EW, © GeoBasis-DE / BKG 2013 (https://gdz.bkg.bund.de/); Geographical data (nighttime lights, municipality borders for Poland and Germany and OpenStreetMap data) have been imported into PostgreSQL database using PostGIS plugin using batch processing in Python. Nighttime intensities for municipalities were created by intersecting vector municipality borders and raster lights data for each avaliable year and satelite. Light totals and averages were calculated using calibrated pixel values using 2nd deg. polynominal intercalibration parameters from Elvidge et al., National Trends in Satellite Observed Lighting: 1992-2009. Bridge crossings were identified using contemporary map data and OSM. OSM data were used to calculate road travel times and distances using pgRouting in PostgreSQL. Data were exported into CSV using Python and imported and merged in Stata, creating the initial dataset.