When working with worldwide data, it si often frustrating that data quality and availability is far from uniform across countries. Especially for developing countries, or those with large informal sectors or notable self-sustenance, we have a very imperfect idea of how much economic activity there is. Hence, looking at other indicators that GDP can give us interesting clues.
Xi Chen and William Nordhaus make the case for luminosity. By looking at how brightly various locations shine at night, it allows you to infer something about economic activity and the level of development. Also, it allows to say something about regional distribution of economic activity. Of course, this is not going to be perfect, especially for developed economies where data is of much better quality to start with.
The standard data set for international macroeconomics data is the Penn World Tables. It also grade grades to its data, telling us how reliable it is. Unfortunately, these grades are largely ignored in empirical work. Chen and Nordhaus ask whether they can increase the quality of output measured with their luminosity data and they claim this is only useful for those labeled D and E. Yet they do not advocate using luminosity data for countrywide analysis. Indeed, data collection methods will eventually improve and traditional data will move up in the quality ladder. Luminosity data is far from perfect, it is just that in some countries official data is even worse at the moment. Chen and Nordhaus are more confident with luminosity as a proxy for regional activity in some cases, even if measurement error is even larger there.