Climate Resilience Pathways of Rural Households. Evidence from Ethiopia

Asfaw, Solomon; Maggio, Giuseppe; Palma, A.

doi:10.2139/ssrn.3268107

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…Many focus on modeling metrics of household consumption (Asfaw et al, 2017;Alfani et al, 2015), but omit the initial investigation into how the specific shock(s) have an effect on household consumption. Testing for the precise form of climate variability that is hazardous to consumption is analytically impossible, because consumption has no direct climate sensitivity.…”

Section: Proxy and Aggregated Metricsmentioning

confidence: 99%

Measuring climate resilience by linking shocks to development outcomes

Barrett

Brooks²,

Quadrianto

et al. 2019

Climate and Development

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Adaptation finance addresses the effects of climate variability and change on development and physical insecurity. Yet, adaptation has proven difficult to systematically measure and assess, resulting in a lack of coherent and comparable evidence to learn about good adaptation practice. Measurement has become even more challenging since the integration of resilience into policy framings. Measuring climate resilience requires evidence of resistance to, and recovery from, shocks and stresses. But resilience of what, to what seldom guides the design of assessments. Researchers tend to use proxy indicators and aggregated units of analysis that cloud the relationships under study, and crucially, leave unclear the interactions between climate and development. This viewpoint documents these common barriers to progress in the field. It then outlines two methods for practitioners and researchers to link climate shocks and stresses to climate-sensitive development outcomes as a key first step to research and evaluation design. Both methods enable prediction of expected levels of development outcomes, given the extent of climate shocks and stresses, which is then comparable with actual levels achieved under climate resilience interventions. The product is standardized and comparable metrics to learn about the performance of climate adaptation policymaking and resilient development programming.

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Section: Proxy and Aggregated Metricsmentioning

confidence: 99%

Measuring climate resilience by linking shocks to development outcomes

Barrett

Brooks²,

Quadrianto

et al. 2019

Climate and Development

View full text Add to dashboard Cite

show abstract

“…A study by Asfaw et al. (2018) assessed the climate resilience pathways of rural households using panel data collected from selected rural areas of Ethiopia, showing determinants of rural households’ resilience through comparing households’ welfare between the pre‐ and post‐2011 drought shock. Tesso et al.…”

Section: Introductionmentioning

confidence: 99%

Impact of climate smart agriculture on households’ resilience and vulnerability: An example from Central Rift Valley, Ethiopia

et al. 2023

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Climate change is causing serious challenges for smallholder farm households, especially in sub-Saharan Africa. The overarching objectives of this study are as follows: (i) to estimate household resilience and vulnerability indices, (ii) identify factors that explain these indices and (iii) to examine the impact of climate-smart agriculture (CSA) on households' resilience and vulnerability, and (iv) to identify which CSA package performs better in enhancing resilience and reducing vulnerability. For this study, 278 farm households from 4 districts and 8 kebeles from the Central Rift Valley (CRV) of Ethiopia were randomly selected using a threestage proportional to size sampling procedure. Cross-sectional data applying a structured and pretested survey questionnaire was collected for 2020/21 production season. Household resilience and vulnerability indices were estimated using resilience index and measurement analysis and indicators approaches, respectively. Multinomial endogenous switching regression was used to estimate the average treatment effects (ATEs) of the adoption of CSA practices on households' resilience and vulnerability. The results show that livestock holding, land size, level of education, and state of food consumption are major explaining factors of resilience, whereas educational level of households, livestock holding, and access to credit are found to be major factors explaining vulnerability. The estimated ATEs indicate that households which adopted more diversified combinations of CSA packages were more resilient and less vulnerable than non-adopter households. The impacts of soil fertility management and conservation agriculture practices have better performance in improving resilience, whereas conservation agriculture and small-scale irrigation performed better in reducing the vulnerability of rural households in CRV. Boosting resilience and reducing vulnerability, hence, requires scaling up CSA among smallholder farmers by diversifying and raising farm households' income, educational status, and livestock holding.

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