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The effects of inequality on total factor productivity across districts in South Africa: a spatial econometric analysis.

ABSTRACT: This study builds on the fundamentals of the new economic geography and the skill-biased technological change argument, to empirically investigate whether increasing income/earning inequality enhances total factor productivity in South Africa. In so doing, panel data of district-municipalities and spatial econometric techniques are used for the period between 1995 and 2015, to gain a better understanding of the role of location and distance in the effects of income inequality on total factor productivity. The results from the analysis and empirical estimations indicate that: (1) there is strong support for the existence of positive spatial interactions in the effects of income inequality on total factor productivity; (2) the estimated direct effect of income inequality on TFP in local district-municipalities is negative and statistically significant, while the indirect effect is positive and statistically significant as well. These findings suggest that district-municipalities with moderate levels of inequality and high economic opportunities, attract more businesses, investments and important stocks of skilled labour from district-municipalities with high inequality. Furthermore, the finding of negative effects supports previous research suggesting that high levels of inequality set the stage for the adoption of distortionary policies which adversely influence the investment climate and produce political instability, thereby stifling the level of productivity and growth.

SUBMITTER: Espoir DK

PROVIDER: S-EPMC7228445 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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The effects of inequality on total factor productivity across districts in South Africa: a spatial econometric analysis.

Espoir Delphin Kamanda DK Ngepah Nicholas N

GeoJournal 20200515 6

This study builds on the fundamentals of the new economic geography and the skill-biased technological change argument, to empirically investigate whether increasing income/earning inequality enhances total factor productivity in South Africa. In so doing, panel data of district-municipalities and spatial econometric techniques are used for the period between 1995 and 2015, to gain a better understanding of the role of location and distance in the effects of income inequality on total factor pro ...[more]

PMID: 32427181

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Project description:BackgroundThe linkage between the socio-economic inequality and HIV outcomes was analysed using data from a population-based household survey that employed multistage-stratified sampling. The goal is to help refocus attention on how HIV is linked to inequalities.MethodsA socio-economic index (SEI) score, derived using Multiple Correspondence Analysis of measures of ownership of durable assets, was used to generate three SEI groups: Low (poorest), Middle, and Upper (no so poor). Distribution of HIV outcomes (i.e. HIV prevalence, access to HIV/AIDS information, level of stigma towards HIV/AIDS, perceived HIV risk and sexual behaviour) across the SEI groups, and other background characteristics was assessed using weighted data. Univariate and multivariate logistic regression was used to assess the covariates of the HIV outcomes across the socio-economic groups. The study sample include 14,384 adults 15 years and older.ResultsMore women (57.5%) than men (42.3%) were found in the poor SEI [P<0.001]. HIV prevalence was highest among the poor (20.8%) followed by those in the middle (15.9%) and those in the upper SEI (4.6%) [P<0.001]. It was also highest among women compared to men (19.7% versus 11.4% respectively) and among black Africans (20.2%) compared to other races [P<0.001]. Individuals in the upper SEI reported higher frequency of HIV testing (59.3%) compared to the low SEI (47.7%) [P< 0.001]. Only 20.5% of those in poor SEI had "good access to HIV/AIDS information" compared to 79.5% in the upper SEI (P<0.001). A higher percentage of the poor had a stigmatizing attitude towards HIV/AIDS (45.6%) compared to those in the upper SEI (34.8%) [P< 0.001]. There was a high personal HIV risk perception among the poor (40.0%) and it declined significantly to 10.9% in the upper SEI.ConclusionsOur findings underline the disproportionate burden of HIV disease and HIV fear among the poor and vulnerable in South Africa. The poor are further disadvantaged by lack of access to HIV information and HIV/AIDS services such as testing for HIV infection. There is a compelling urgency for the national HIV/AIDS response to maximizing program focus for the poor particularly women.

Project description:The development of information technology has created conducive conditions for the digital economy. The digital economy is regarded as a critical pathway for transforming traditional economic models. Green total factor productivity serves as an indicator for assessing the quality of economic development. During pivotal periods of economic transition, the digital economy and green total factor productivity have emerged as two prominent themes for achieving sustainable economic development. But the impact of digital economy on green total factor productivity is less discussed. Innovation environment refers to a confluence of conditions shaped by factors such as talent, funding, cultural atmosphere and government policies, all of which collectively support innovative activities within a region. The institutional environment encompasses the aggregate of economic, political, social, and legal rules. Currently, there is little discussion on bringing innovation environment and institutional environment into the impact of digital economy on green total factor productivity. To fill the research gap, this paper adopts the Slack based measure-Directional distance function model and Malmquist-Luenberger productivity index to measure green total factor productivity in each region based on the panel data collected from 30 provinces in China from 2004 to 2019. Generalized Method of Moments method is constructed to carry out an empirical study on the impact of digital economy on green total factor productivity. This paper constructs a panel threshold model with innovation environment and institutional environment as threshold variables. In further analysis, this paper employs panel quantile regression for the empirical analysis of the impact of the digital economy on green total factor productivity. Further analysis elucidates the evident disparities in the influence of the digital economy on green total factor productivity at various levels. The research results can provide a guide for discussing the green value of the digital economy and its role in fostering the development of a green economy.

Dataset Information

The effects of inequality on total factor productivity across districts in South Africa: a spatial econometric analysis.

Publications

The effects of inequality on total factor productivity across districts in South Africa: a spatial econometric analysis.

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