2020
DOI: 10.1016/j.wdp.2020.100177
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Which aid targets poor at the sub-national level?

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Cited by 11 publications
(10 citation statements)
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“…The estimated results from the latter are presented in the appendix . Deviations from the SSA average are in line with the argument that aid will go to countries with the most need ( Dipendra, 2020 , Lahiri and Raimondos-Møller, 1997 ). These rainfall indicators assume that donors would respond to huge deviations from either rainfall deviations from the country’s own average rainfall or that of the SSA average.…”
Section: Data Sample Period and Descriptive Statisticssupporting
confidence: 75%
“…The estimated results from the latter are presented in the appendix . Deviations from the SSA average are in line with the argument that aid will go to countries with the most need ( Dipendra, 2020 , Lahiri and Raimondos-Møller, 1997 ). These rainfall indicators assume that donors would respond to huge deviations from either rainfall deviations from the country’s own average rainfall or that of the SSA average.…”
Section: Data Sample Period and Descriptive Statisticssupporting
confidence: 75%
“…Although the study of the observed variables shows similar results to previous findings of sub-national adaptation finance, it also reveals noteworthy distinctions and some unexpected findings. First, as reported in other contexts (see Barnett, 2014;Dipendra, 2020), physical vulnerability influences the allocation of adaptation aid; however, data suggest a positive bias towards jurisdictions where rainfall is historically intense. Episodes of flooding in the coastal lowlands and mountain riverine floods on the Andes mountains are frequent and often associated with urban development, deforestation and other land use change as well as poor flood risk management (Burgos Choez et al, 2019; Pinos & Timbe, 2020; Sierra et al, 2021).…”
Section: Discussionmentioning
confidence: 69%
“…The paper also speaks to the broader literature on aid targeting (Briggs 2014;Jablonski 2014;Öhler and Nunnenkamp 2014;Nunnenkamp et al 2016;Briggs 2017;Öhler et al 2019;Dipendra 2020;Wayoro and Ndikumana 2020)-especially the subset of that literature that employs highly disaggregated local data on project placement alongside covariates measured at the micro-level (Chhibber and Jensenius 2016;Carlitz 2017;Hoffmann et al 2017;Briggs 2018a,b;Ejdemyr et al 2018;Murray 2020;Brierley 2021). While our study joins these others in leveraging highly disaggregated data, the degree of disaggregation offered by our point-level empirical approach (described below) goes well beyond that of other research.…”
Section: Introductionmentioning
confidence: 98%