Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/204379 
Authors: 
Year of Publication: 
2014
Series/Report no.: 
IFRO Working Paper No. 2014/11
Publisher: 
University of Copenhagen, Department of Food and Resource Economics (IFRO), Copenhagen
Abstract: 
This study investigates the effect of drought on economic activity globally using remote sensing data. In particular, predicted variation in greenness is correlated with changes in the density of artificial light observed at night on a grid of 0.25 degree latitude-longitude pixels. I define drought as greenness estimated by lagged variation in monthly rainfall and temperature. This definition of drought performs well in identifying self-reported drought events since 2000 compared with measures of drought that do not take greenness into account, and the subsequent analysis indicates that predicted variation in greenness is positively associated with year-on-year changes in luminosity: If a unit of observation experiences a predicted variation in greenness that lies 1 standard deviation below the global mean, on average 1.5 - 2.5 light pixels out of 900 are extinguished that year. Finally, an attempt is made to estimate the global cost of drought.
Subjects: 
Drought
Greenness
NDVI
Growth
Luminosity
Lights at night
Remote sensing
JEL: 
O11
O13
O49
R11
R12
Q54
Q55
Document Type: 
Working Paper

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