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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Autores principales:	Robalino, Juan, Sandoval, Catalina, Abarca, Alejandro
Formato:	Artículo
Lenguaje:	Inglés
Publicado:	2020
Materias:	FENOMENOS METEOROLOGICOS ESTIMACION CLIMA BIENESTAR SOCIAL ANALISIS ENCUESTAS POBREZA AGRICULTURA VULNERABILIDAD GUATEMALA
Acceso en línea:	https://repositorio.catie.ac.cr/handle/11554/9512

id	RepoCATIE9512
record_format	dspace
spelling	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
institution	Centro Agronómico Tropical de Investigación y Enseñanza
collection	Repositorio CATIE
language	Inglés
topic	FENOMENOS METEOROLOGICOS ESTIMACION CLIMA BIENESTAR SOCIAL ANALISIS ENCUESTAS POBREZA AGRICULTURA VULNERABILIDAD GUATEMALA
spellingShingle	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
_version_	1808116966996574208

Direct and Indirect Effects of Extreme Weather Events and Potential Estimation Biases

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