Predicting GDP Growth Using Night-time Light Emissions
Learn how to predict changes in GDP using changes in night-time light emissions. Discover the relationship between night-time light and GDP growth, with a focus on utilizing satellite data in remote areas to infer GDP trends. Step-by-step guidance on creating new variables, coding in R, and interpreting the estimated equation.
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DSS by Llaudet and Imai Chapter 4: Predicting Outcomes using Linear Regression Craig R. Parsons 1
The data: Night-time Light Emissions (satellite data) Two sets of variables: 1) GDP and 2) Night-time light measures Years of data? 1992-3 and 2005-6 Units of data: GDP (in trillions of LCU, local currency units, e.g. if Japan, data is in trillions of yen) Units of data: Night-time light (on a scale 0 to 63, 63 being most bright) Names of datafile: countries.csv How many cross-sections ? 170 (countries) 2
4.5 PREDICTING GDP GROWTH USING NIGHT-TIME LIGHT EMISSIONS Let's figure out how to fit a model to predict changes in GDP using changes in night-time light emissions. As mentioned earlier, being able to predict GDP growth using night-time light emissions would be quite useful. In remote areas of the world, where measuring GDP is difficult, measures of night-time light emissions are readily available through satellite imagery. 3
We want to find the relationship between a change in night-time lights and change in GDP If we KNOW that night-time light went up by, for example, 10%, how did GDP goes up ( on average .)? For some remote counties or area, we may have night-time light data from satellites) but may not have GDP data. So, we can predict or infer GDP, from the increased night-light data. 4
Interpretation continued (gdp_change hat is the predicted change) 10
Show Nigerias partial state GSP data https://www.nigerianstat.gov.ng/pdfuploads/State_Nominal_GDP_20 13_-_2017.cdr_(MAY_2019).pdf 11
4.6 MEASURING HOW WELL THE MODEL FITS THE DATA WITH THE COEFFICIENT OF DETERMINATION, R2 12
