Evidence map›Paper›PMID 37130671›Full record

ArticleBMJ open2023

Health and total factor productivity nexus in selected sub-Saharan African countries: quadratic and threshold modelling.

Yetunde Oluranti Adegoke, Josue Mbonigaba, Gavin George

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Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yetunde Oluranti AdegokeSchool of Accounting, Economics and Finance, University of KwaZulu-Natal, Durban, South Africa ranty.tunde@yahoo.com.ORCID 0000-0003-4973-4198
Josue MbonigabaSchool of Accounting, Economics and Finance, University of KwaZulu-Natal, Durban, South Africa.
Gavin GeorgeHealth Economics and HIV and AIDS Research Division (HEARDS), University of KwaZulu-Natal, Durban, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe sub-Saharan African (SSA) countries have been recording a decline in total factor productivity (TFP) growth, inadequate health funding and poor health outcomes are regarded as problems that might have impeded productivity in the region. This study therefore aligns with Grossman's theory that better health could be instrumental to productivity growth. In this paper, we establish a predictive TFP model that accommodates the roles of health, which has been omitted in prior studies. To corroborate our findings we examine the threshold relationship between health and TFP.

methodsThe study employs the fixed and random effect model, panel two-stage least squares, static and dynamic panel threshold regression model on a balanced panel data of 25 selected SSA countries from 1995 to 2020 as the estimating technique for the linear relationship and the non-linear relationship between health and TFP.

resultsThe result of the analysis reveals a positive relationship between health expenditure and TFP, health expenditure per capita and TFP. Education and other non-health factors, like Information Communication Technology (ICT) and control of corruption equally have significant positive impact on TFP. The result further shows the existence of a threshold relationship between TFP and health at 3.5% level of public health expenditure. We also discover threshold relationship between TFP and some non-health variables like education and ICT at 2.56% and 21%, respectively

conclusionsMore importantly, the study confirms health as a determinant of TFP and also validates the existence of a non-linear relationship between TFP and health. Overall, improvements in health and its proxies have implications for TFP growth in SSA. Therefore, the increase in public health expenditure stipulated in this study should be passed into law for optimal productivity growth rate.

Indexed as

EfficiencyHealth ExpendituresAfrica South of the SaharaHumansPublic Healthhealth economicshealth policyhealth & safetyhuman resource managementorganisation of health servicesquality in health care

Identifiers

PMID37130671
PMCPMC10163443

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