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Record W4211018443 · doi:10.1093/heapol/czac014

The impact of unconditional cash transfers on morbidity and health-seeking behaviour in Africa: evidence from Ghana, Malawi, Zambia and Zimbabwe

2022· article· en· W4211018443 on OpenAlexfundno aff
Jacob Novignon, Leah Prencipe, Adria Molotsky, Elsa Valli, Richard de Groot, Clement Adamba, Tia Palermo

Bibliographic record

VenueHealth Policy and Planning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
FundersNational Institute of Mental HealthKfW EntwicklungsbankEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEuropean CommissionUniversity of GhanaU.S. Department of Health and Human ServicesUnited States Agency for International DevelopmentCanadian International Development AgencyIrish AidStyrelsen för Internationellt UtvecklingssamarbeteUNICEFMedical Research CouncilFoundation for Appalachian Ohio
KeywordsCash transfersContext (archaeology)Conditional cash transferCashImpact evaluationLatin AmericansDeveloping countryConsumption (sociology)Environmental healthFood securityChild mortalityBusinessPublic economicsEconomicsGovernment (linguistics)SocioeconomicsEconomic growthGeographyMedicinePolitical sciencePovertyFinanceSociology

Abstract

fetched live from OpenAlex

Unconditional cash transfers have demonstrated widespread, positive impacts on consumption, food security, productive activities and schooling. However, the evidence to date on cash transfers and health-seeking behaviours and morbidity is not only mixed, but the evidence base is biased towards conditional programmes from Latin America and is more limited in the context of Africa. Given contextual and programmatic design differences between the regions, more evidence from Africa is warranted. We investigate the impact of unconditional cash transfers on morbidity and health-seeking behaviour using data from experimental and quasi-experimental study designs of five government cash transfer programs in Ghana, Malawi, Zambia and Zimbabwe. Programme impacts were estimated using difference-in-differences models with longitudinal data. The results indicate positive programme impacts on health seeking when ill and on health expenditures. Our findings suggest that while unconditional cash transfers can improve health seeking when ill, morbidity impacts were mixed. More research is needed on longer-term impacts, mechanisms of impact and moderating factors. Additionally, taken together with existing evidence, our findings suggest that when summarizing the impacts of cash transfers on health, findings from conditional and unconditional programmes should be disaggregated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.106
GPT teacher head0.420
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2022
Admission routes1
Has abstractyes

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