Infrastructure, Human Capital Development and Economic Growth in Transitional Countries

Abstract

<jats:p>This study investigated the impact of infrastructure and human capital development on economic growth in transitional economies. It also explored whether the interaction between infrastructural and human capital development enhanced economic growth in the transitional economies. Although the literature is awash with studies which investigated the separate impact of infrastructure and human capital development on economic growth, no study that the author is aware of has so far explored whether the interaction between infrastructure and human capital development enhances economic growth. The study mainly used a dynamic panel generalised methods of moments (GMM) approach by Arellano and Bond (1995), a framework that takes into account the dynamic nature of economic growth data and addresses the endogeneity issues normally associated with economic growth regression functions. Panel data analysis approaches such as pooled ordinary least squares (OLS), and fixed and random effects were used for comparison purposes and robustness tests. According to the dynamic GMM framework, the interaction between infrastructure and human capital development improved economic growth in transitional economies, in line with theoretical and empirical predictions. Random effects and pooled OLS show that the interaction between infrastructural and human capital development had a deleterious effect on economic growth, whilst according to the fixed effects approach, the interaction between these two variables had an insignificant positive influence on economic growth in transitional economies. Considering that the results from a dy34 Kunofiwa Tsaurai, Adam Ndou namic panel GMM are considered to be more accurate due to the approach’s ability to address the endogeneity problem and the dynamic nature of economic growth data, the current study recommends that transitional economies should implement policies that improve human capital development in order to enhance infrastructural development’s ability to influence economic growth. Future studies should investigate not just one (human capital development), but all the conditional factors which must be in place before economic growth advantages triggered by infrastructure development are realised.</jats:p>

Analysis of Funds for Community Empowerment Programs for Economic Development

“…The role of Prodamas in socio-economic matters is also not important & through the existence of savings and loan funds per RT so as to stimulate the growth of micro business which can encourage the community to become more financially independent. These results indicate that in accordance with previous research conducted by (Tsaurai & Ndou, 2019) and (Javid, 2019) who empirically stated that the development of infrastructure in a region can encourage economic growth.…”

“…These results are consistent with the results of the study Awandari & Indrajaya (2016); Putri (2014); and Kusuma & Muhtadi (2019). Tsaurai & Ndou (2019) found that the interaction between infrastructure and human resource development can increase economic growth. Masrija (2018) states that there is still no governance and lack of transparency in the implementation of the Community Empowerment Program.…”

The Corruption and Human Development to the Economic Growth of Oic Countries

“…In addition to the basic theory, there are many studies that discuss the impact of the Human Development Index on economic growth turns out that most of them mention the significant influence of Human Development Index on economic growth, starting from research conducted with a sample of one city by Kawulur Tsaurai and Ndou (2019). The results from all of them state one similar conclusion: the Human Development Index positively influences the economic growth as represented by Gross Domestic Product growth.…”

Information and Communication Technology and Electricity Consumption in Transitional Economies

“…The probabilities of the Jarque-Bera criterion equal to zero across all the variables studied, an indication that the data is not normally distributed (Odhiambo, 2008;Tsaurai and Ndou, 2019). Standard deviation values (>1000) show that electricity consumption and economic growth (GDPPC) data has abnormal values (Table 4).…”