000242328 001__ 242328
000242328 005__ 20180123004714.0
000242328 037__ $$a1055-2016-86000
000242328 041__ $$aen_US
000242328 084__ $$aD10
000242328 084__ $$aQ18
000242328 084__ $$aI32
000242328 084__ $$aO55
000242328 245__ $$aHousehold resilience to food insecurity: evidence from Tanzania and Uganda
000242328 260__ $$c2016-06
000242328 269__ $$a2016-06
000242328 270__ $$mmarco.derrico@fao.org$$pd'Errico,   Marco
000242328 270__ $$mrebecca.pietrelli@fao.org$$pPietrelli,   Rebecca
000242328 270__ $$mdonato.romano@unifi.it$$pRomano,   Donato
000242328 300__ $$a27
000242328 336__ $$aConference Paper/ Presentation
000242328 520__ $$aResilience has become one of the keywords in the recent scholarly and policy debates on food security. However, household resilience to food insecurity is unobservable. Therefore, the two key issues in empirical research are (i) estimating a proxy index of household resilience on the basis of observable variables and (ii) assessing whether this index is a good indicator of the construct it intends to measure, i.e. household resilience. This paper contributes to this literature providing evidence based on two case studies: Tanzania and Uganda.
Specifically, the paper: (i) proposes a method to estimate a resilience index and analyses what are the most important components of household resilience, (ii) tests whether the household resilience index is a good predictor of future food security status and food security recovery capacity after a shock, and (iii) explores how idiosyncratic and covariate shocks affects resilience and household food security.
The analysis shows that: (i) in both countries adaptive capacity is the most important dimension contributing to household resilience, (ii) the resilience index positively influences future household food security status, decreases the probability of suffering a food security loss should a shock occur and speeds up the recovery after the loss occurrence, and (iii) shocks do not seem to have any statistically significant impact, though this likely reflects the poor quality of data on idiosyncratic and systemic shocks.
000242328 542__ $$fLicense granted by Davide Viaggi (davide.viaggi@unibo.it) on 2016-07-23T12:44:59Z (GMT):

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000242328 650__ $$aFood Security and Poverty
000242328 6531_ $$aResilience
000242328 6531_ $$afood security
000242328 6531_ $$astructural equation model
000242328 6531_ $$apanel data
000242328 700__ $$ad'Errico, Marco
000242328 700__ $$aPietrelli, Rebecca
000242328 700__ $$aRomano, Donato
000242328 773__ $$d2016
000242328 8564_ $$s1366294$$uhttp://ageconsearch.umn.edu/record/242328/files/AIEAA_2016_D_errico_Romano_Pietrelli.pdf
000242328 887__ $$ahttp://purl.umn.edu/242328
000242328 909CO $$ooai:ageconsearch.umn.edu:242328$$pGLOBAL_SET
000242328 912__ $$nSubmitted by Davide Viaggi (davide.viaggi@unibo.it) on 2016-07-23T12:49:31Z
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  Previous issue date: 2016-06
000242328 982__ $$gItalian Association of Agricultural and Applied Economics>Congress Papers>2016 Fifth AIEAA Congress, June 16-17, 2016, Bologna, Italy
000242328 980__ $$a1055