The impact of fiscal policy on total factor productivity growth in a developing economy: evidence from Botswana

Timuno, Sayed O. M.; Eita, Joel Hinaunye

doi:10.1080/03796205.2022.2053298

Cited by 5 publications

(3 citation statements)

References 39 publications

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“…Similarly, education expenditure equally has a significant positive impact on TFP in SSA. This finding is in line with the studies of Filip, Olomola and Osinubi, Timuno and Alvi and Ahmed 9 12 19 21…”

Section: Discussionsupporting

confidence: 92%

“…A study by Fadiran and Akanbi 11 investigated the determinants of TFP growth in SSA from 1990 to 2011, the study confirmed market based institution rather than political institution and other determinants like research and development, human capital, infrastructure and financial development as the determinants of TFP. A study by Timuno 19 investigated the determinants of TFP in Botswana over the period of 1977–2014 using auto-regressive distributed lag bounds testing approach, the study identified economic diversification, openness to trade, human capital in education and inflation as the determinants of TFP in Botswana. A study by Akinlo 10 investigated the determinants of TFP in Nigeria over the periods of 1970–2009 using error correction model, impulse-response functions and variance decompositions.…”

Section: Literature Reviewmentioning

confidence: 99%

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

2023

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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%, respectivelyConclusionsMore 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.

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Section: Discussionsupporting

confidence: 92%

Section: Literature Reviewmentioning

confidence: 99%

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

2023

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“…al, 2007;Xu, et. al.2020;Fadiran & Akanbi, 2017;Rasheed, 2010;Habib, Abbas, & Noman;2019;Timuno, 2017;Odior, 2013;Olomola & Osinubi, 2018). Given the large variety of the variables that determine total factor productivity, in this study those variables that are commonly touched in the majority of the above theoretical and empirical studies, and are relevant within the context of my study are identified.…”

Section: Total Factor Productivity (Tfp) Measurement and Estimationmentioning

confidence: 94%

Determinants of Total Factor Productivity of Large and Medium-scale Manufacturing Industries in Ethiopia: Time Series Analysis

Gidey

2022

J. Afri. Devt. Stud

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contribution of the manufacturing sector to overall GDP has not only been below the planned target, but it has also remained low relative to the mean performance of the Sub-Saharan Africa (SSA) countries. In the second growth and transformation plan (GTP-II) manufacturing industry is projected to grow by an average annual growth rate of 21.9% and its share in the overall GDP was projected to increase from less than 5% in 2014/15 to 8% by 2019/2020. But, still, the share of this sector in overall GDP in 20018 was poor, accounting for about 6 % (NBE, 2018). This figure is still lower than the sub-Saharan Africa average of nearly 10% (Signe, 2018). Further, the share of manufactured exports in total exports remained less than 13% (Arkebe, 2018). This seems unanticipated, given the emphasis placed by the Ethiopian government to achieve structural transformation through industrial policy.For many decades, economists have debated on the sources of total factor productivity (TFP) productivity in the manufacturing sector. The endogenous theorists such as Romer, 1990;Todaro & Smith, 2012 and other scholars identified many factors that determine the performance of the manufacturing sector productivity in developing countries (NPC, 2018). The theoretical and empirical literature clearly shows that the factors that affect the Total Factor Productivity and output of the manufacturing sector vary from country to country (Ilyas et.al, 2010). But in general, the common determinants of TFP examined in the empirical literature includes variables such as trade openness, macroeconomic stability (inflation rate), human capital, financial sector development (credit to the private sector), governance, economic growth, infrastructure, and research and development, FDI, lending rate, institutions among others (

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Valued added taxation and industrial sector productivity: a granger causality approach

Omodero

Eriabie

2022

Cogent Business & Management

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The impact of fiscal policy on total factor productivity growth in a developing economy: evidence from Botswana

Cited by 5 publications

References 39 publications

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

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

Determinants of Total Factor Productivity of Large and Medium-scale Manufacturing Industries in Ethiopia: Time Series Analysis

Valued added taxation and industrial sector productivity: a granger causality approach

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