This paper is the first to examine the short term local economic impact of tropical cyclones by estimating the effects on monthly nightlight intensity. More specifically, for Guangdong Province in Southern China, we proxy monthly economic activity with remote sensing derived monthly night time light intensity and combine this with local measures of wind speed derived from a tropical cyclone wind field model. Our regression analysis reveals that there is only a significant (negative) impact in the month of the typhoon strike and nothing thereafter. Understanding that typhoons are inherently a short-term phenomenon has possible implications for studies using more aggregate data.
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Unlike our study they focus on a single event and only examine aggregate rather than local impacts.
For an example of the use of nightlights to examine the local economic impact of tropical cyclones using annual data see Elliott et al. (2015).
Unfortunately, given the normalization, the values can only be valued in relative terms.
We add 1 to all values so cells with zero values are not dropped.
For months when we use the average across different satellites, we also use the average of the number of cloud free days across satellites.
We also estimated each specification using 12 lags to investigate how the monthly coefficients changed over the period of one year (which is the usual data frequency used in studies of natural disasters). The main results did not change and are available from the authors upon request.
See, for instance, the discussion in Bier (2017).
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Thanks for funding support from Nankai University, Business School and the Collaborative Innovation Centre in Nankai.
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Del Valle, A., Elliott, R.J.R., Strobl, E. et al. The Short-Term Economic Impact of Tropical Cyclones: Satellite Evidence from Guangdong Province. EconDisCliCha 2, 225–235 (2018). https://doi.org/10.1007/s41885-018-0028-3