Does infrastructure development help African countries boost their currently weak industrial structure to meet with pressing needs of their growing population? Answering this question which is also the ambition of SDG 9 requires taking into account rising global uncertainty which provokes a ‘wait-and-see’ behaviour in production and consumption expenditures. To this end, the new World Uncertainty Index and data on 43 African countries from 2003 to 2018 are used. The two-step system generalised method of moments modelling framework was recruited for regression analysis. Results show that while infrastructure development boost industrialisation in Africa, global economic policy uncertainty and risk of uncertainty undermine these benefits after a given uncertainty threshold. The positive net effects were apparent up to respective global uncertainty and uncertainty volatility thresholds where these effects are nullified. When disaggregated proxies of infrastructure are used, similar results are obtained with transport and electricity. Practical policy implications are discussed. JEL Codes: C23, D8, H54, O14, O55
Considering the growing importance of Information and Communication Technology (ICT) infrastructure, consumption of energy, and environmental sustainability in the context of globalisation, it is imperative to comprehend how these factors are related to one another and to make implications about the most effective ways to protect the environment. In this regards, present study aims to examine how ICT infrastructure and energy consumption affects environmental sustainability in Asian Emerging Economies spanning 1990–2022 by employing different advanced panel econometric techniques. The findings reveal that ICT infrastructure deteriorates environmental sustainability by exacerbating CO2 discharge in long run, while in short run, it lowers CO2 discharge. But energy consumption impairs environmental sustainability by exacerbating CO2 discharge both in short run and long run. The study highlights a causal link between ICT infrastructure and energy consumption and CO2 emissions, urging policymakers to prioritise clean energy, high-quality ICT, and innovation.
This study tries to investigate the cross-country variations in infrastructure development among different sets of countries with varying institutional rankings, over time, by building five infrastructure indices. Along with building the total/composite infrastructure index, four other (energy, ICT, finance and transport) sub-indices are also built in this study. The strength of our study lies in the fact that we not only find variations in the total infrastructure development but also within the sub-indices. We have introduced the role of country-specific Institutional quality and inflow of FDI empirically in this regard to determine the cross-country variance in infrastructure development. The core hypothesis of our study is that countries that receive a good amount of FDI inflows will have impressive infrastructure development provided the country-specific institutional quality is high. On the contrary, countries with low institutional indexes may not have a positive association between FDI inflows and infrastructure development. However, there are exceptions. For example, institutionally strong countries like Ireland and Belgium should invest more funds to boost their financial infrastructure sector. On the other hand, another institutionally strong country like Norway should develop its transport infrastructure. In this study, we are mainly interested in the joint impact of FDI inflows with the institutional variable on infrastructure development that has been largely neglected in the empirical literature. Using two-dimensional panel data for FDI inflows for 39 countries over the period 2000–20, we find that the conditional effects are positive and significant. From the policy point of view, we identify the possible areas of the infrastructure of a country that needs capital to be invested and at the same time identify some of the countries that need to improve their institutional quality that will eventually lead to improvement in the infrastructure development. The results of our study are robust to different institutional measures and infrastructure indices.
This study uses annual data from 1984 to 2019 for the Côte d’Ivoire to estimate the effects of public infrastructure spending, institutions, institutional shocks and their multiplicative effect on economic growth. We construct three institutional indices and interaction variables to estimate linear and nonlinear AutoRegressive Distributed lag models (ARDL). The results reveal symmetric effects of institutional shocks to democracy and regulation and conflict prevention and asymmetric effects of institutional shocks to investment promotion and the economy. The institutional index for the conflict prevention dimension is favourable to economic growth, while the other institutional dimensions remain insignificant. The institutional index of democracy and regulation amplifies the positive effects of public spending on infrastructure on per capita income in the long term. The institutional indices of investment and economic promotion and conflict prevention reduce the positive effect of public infrastructure spending on per capita income. Public debt and domestic savings have effects on per capita income. These results imply that improving institutions, particularly those promoting investment and the economy, is crucial to amplifying the benefits of public infrastructure investment in Côte d’Ivoire.
This study aims to investigate the influence of the capital structure (measured by book leverage) of a company on its financial performance using the top 100 non-finance firms listed in the National Stock Exchange (NSE) from 2010–11 to 2021–22. This study has used the random-effect panel regression model to determine the relationship between capital structure and firm performance. The main source of data is the Capitaline database. Capital structure has been measured through book leverage (BLEV) and long-term debt to total assets ratio (LTDTA), whereas firm performance has been measured through Tobin’s Q and ROA. A sample of 147 NSE-listed companies belonging to different industries has been chosen for this study. The study has been validated by using a two-stage difference-generalised method of moments (GMM) model. The study has shown that capital structure has a significant adverse influence on firm performance after controlling for the effects of asset tangibility and firm size. However, the findings reveal that turnover representing the firm size and asset tangibility bears no association with firm performance. The results endorse the usefulness of agency cost theory in the case of NSE-listed companies in India. The empirical results are validated using a dynamic panel-data approach, with two-stage difference GMM, and remain robust. Theoretically, this study extends the existing literature on capital structure by offering new evidence from a developing and prospective market like India. In practical terms, the findings of this study would help the stock exchange regulators and other regulatory bodies in the proper management of debt, as it could influence firm performance. The outcome of the study shows the relevance of the agency cost theory of capital structure and the influence of capital structure on financial performance.
