Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases
The literature analyzing the effects of extreme weather events on social and economic outcomes has increased significantly in the last few years. Most of these analyses use either self-reported data about whether the storm affected the respondent or aggregated data such as precipitation at municipal...
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RepoCATIE95122021-12-22T19:09:50Z Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases Robalino, Juan Sandoval, Catalina Abarca, Alejandro FENOMENOS METEOROLOGICOS ESTIMACION CLIMA BIENESTAR SOCIAL ANALISIS ENCUESTAS POBREZA AGRICULTURA VULNERABILIDAD GUATEMALA The literature analyzing the effects of extreme weather events on social and economic outcomes has increased significantly in the last few years. Most of these analyses use either self-reported data about whether the storm affected the respondent or aggregated data such as precipitation at municipality level. We argue that these estimates might be biased due to the inclusion of households that are not directly affected but live close enough to be indirectly affected through economic or government assistance spillovers. Using data for Guatemala, we estimate separately the direct and indirect effects of Tropical Storm Stan on subjective economic well-being. We find that households that were directly affected by Stan are significantly more likely to report being poorer after the storm. We also find that the direct effects of the storm are similar in poor and less-poor agricultural municipalities. However, in non-agricultural municipalities, the effects are larger in less-poor municipalities. Reducing poverty rates might not be enough to address the problems related to climate shocks, which are expected to increase with climate change. We also find that households indirectly affected in non-poor municipalities reported being significantly worse off and households indirectly affected in poor municipalities reported being significantly better off. Given that shocks and responses to shocks will likely affect households that were not directly exposed, estimates of these effects are difficult to measure without simultaneously considering exposure data at both the household level and municipality level. 2020-08-25T00:16:13Z 2020-08-25T00:16:13Z 2015-11 Artículo https://repositorio.catie.ac.cr/handle/11554/9512 en Environment for Development (November 2015) info:eu-repo/semantics/openAccess application/pdf |
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Centro Agronómico Tropical de Investigación y Enseñanza |
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Repositorio CATIE |
language |
Inglés |
topic |
FENOMENOS METEOROLOGICOS ESTIMACION CLIMA BIENESTAR SOCIAL ANALISIS ENCUESTAS POBREZA AGRICULTURA VULNERABILIDAD GUATEMALA |
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FENOMENOS METEOROLOGICOS ESTIMACION CLIMA BIENESTAR SOCIAL ANALISIS ENCUESTAS POBREZA AGRICULTURA VULNERABILIDAD GUATEMALA Robalino, Juan Sandoval, Catalina Abarca, Alejandro Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases |
description |
The literature analyzing the effects of extreme weather events on social and economic outcomes has increased significantly in the last few years. Most of these analyses use either self-reported data about whether the storm affected the respondent or aggregated data such as precipitation at municipality level. We argue that these estimates might be biased due to the inclusion of households that are not directly affected but live close enough to be indirectly affected through economic or government assistance spillovers. Using data for Guatemala, we estimate separately the direct and indirect effects of Tropical Storm Stan on subjective economic well-being. We find that households that were directly affected by Stan are significantly more likely to report being poorer after the storm. We also find that the direct effects of the storm are similar in poor and less-poor agricultural municipalities. However, in non-agricultural municipalities, the effects are larger in less-poor municipalities. Reducing poverty rates might not be enough to address the problems related to climate shocks, which are expected to increase with climate change. We also find that households indirectly affected in non-poor municipalities reported being significantly worse off and households indirectly affected in poor municipalities reported being significantly better off. Given that shocks and responses to shocks will likely affect households that were not directly exposed, estimates of these effects are difficult to measure without simultaneously considering exposure data at both the household level and municipality level. |
format |
Artículo |
author |
Robalino, Juan Sandoval, Catalina Abarca, Alejandro |
author_facet |
Robalino, Juan Sandoval, Catalina Abarca, Alejandro |
author_sort |
Robalino, Juan |
title |
Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases |
title_short |
Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases |
title_full |
Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases |
title_fullStr |
Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases |
title_full_unstemmed |
Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases |
title_sort |
direct and indirect effects of extreme weather events and potential estimation biases |
publishDate |
2020 |
url |
https://repositorio.catie.ac.cr/handle/11554/9512 |
work_keys_str_mv |
AT robalinojuan directandindirecteffectsofextremeweathereventsandpotentialestimationbiases AT sandovalcatalina directandindirecteffectsofextremeweathereventsandpotentialestimationbiases AT abarcaalejandro directandindirecteffectsofextremeweathereventsandpotentialestimationbiases |
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1808116966996574208 |