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This paper aims to suggest the preferred mode of financing for major sub-sectors of infrastructure: roads, seaports, telecommunication and energy by examining which mode of infrastructure financing – public, private or public–private partnership (PPP) – has the maximum positive impact on the overall GDP of India. The same exercise was carried out for the overall infrastructure sector by integrating data from all the four sub-sectors.

The structural vector autoregressive approach was used with the period of analysis taken from 1995 to 2014. The stationary properties of the variables were checked by the Phillips–Perron unit root.

The PPP mode of financing was found to make the maximum positive impact on the GDP of India. Considering the four sub-sectors individually, it was concluded that the private mode of financing in roads, energy and telecom sectors has the maximum positive impact on the GDP, while the PPP gives optimal benefit to the seaports sector.

Results will aid the Indian Government and policymakers to efficiently design and develop their economic policies accordingly.

The study is novel in a sense that it helps to address the lack of research into the area of infrastructure financing in India.

India is a developing nation where the marginal benefit of infrastructure development is tremendous. The purpose of this paper is to analyze the relationship between infrastructure development and poverty reduction for India using the yearly data from 1991 to 2015.

The authors use the principal component analysis to construct indices for four major sub-sectors, namely, transport, water and sanitation, telecommunications and energy, falling under the broad infrastructure sector and then using these sectorwise indices, the authors construct an overall index which represents infrastructure development. The authors provide evidence on the link between infrastructure development and poverty reduction by using the auto regressive distributed lag (ARDL) bound testing approach.

The ARDL test results suggest that infrastructure development and economic growth reduce poverty in both long run and short run. The causality test confirms that there is a positive and unidirectional causality running from infrastructure development to poverty reduction.

The study confirms that India’s Infrastructure development plays a vital role in reducing poverty and calls for the Indian Government to adopt economic policies which are aimed at developing and strengthening the infrastructure levels and bringing in more investment in the infrastructure sector in order to help the poor population by making them exposed to better opportunities of employment and income growth, thereby achieving the goal of poverty reduction.

This paper is a fresh and unique attempt of its kind to empirically investigate the causal relationship between infrastructure development and poverty reduction in India using modern econometric techniques.

The purpose of this paper is to investigate the relationship between infrastructure development, rural–urban income inequality and poverty for BRICS economies.

Pedroni’s panel co-integration test and panel dynamic ordinary least squares (PDOLS) have been used to carry out the analysis.

The empirical findings confirm a long-run relationship among infrastructure development, poverty and rural–urban inequality. The PDOLS results suggest that both infrastructure development and economic growth lead to poverty reduction in BRICS. However, rural–urban income inequality aggravates poverty in these nations. The paper advocates for adopting policies aimed at strengthening infrastructure and achieving economic growth to reduce the current levels of poverty prevailing in the BRICS nations.

Significant limitations exist in the literature in terms of not clearly defining the nature of relationship and interlinkages between infrastructure development, poverty and inequality, with regard to the BRICS nations. The available studies mainly focus on the relationship between infrastructure and growth, with the universal agreement being that these two are positively related. However, it is still not right to assume that economic growth attributable to infrastructure development will, therefore, subsequently lead to a reduction in inequality. This forms the basis for this study, that is, to critically examine the relationship between infrastructure development, inequality and poverty for BRICS nations.

The purpose of this study is to understand the specific reasons why developed countries could easily start implementing innovative alternative fuel vehicles (e.g. electric vehicles or EVs) while the implementation in developing countries looks so far-fetched, with respect to infrastructure and downstream activities, and suggest the steps that can be taken to effectively address these issues.

This research undertakes case study – Tesla (USA), Mahindra and Mahindra (India) and Tata Motors to bring out the problems being faced by manufacturers from developing countries vis-a-vis the developed countries. The consumers’ side has been adequately represented though an in-depth survey. An analysis is also carried out as to how Tesla has accrued competitive leverage by innovating and vertical integration of up as well as downstream systems.

EV infrastructure remains grossly inadequate in developing countries like India. Two key areas that remain significantly unexplored are the installation of charging stations at parking lots and at the housing clusters and lack of competitive leverage in the services, processes and other downstream systems due to limited research and development capabilities. The performance metrics of domestic EVs lag those of conventional vehicles as well as foreign competitors like Tesla. Range anxiety is ranked as number one in the major concerns among the potential mass buyers of electric vehicles in India.

The value of the paper lies in an in-depth analysis of the relationship between horizontal and vertical perspectives as well as the impact of the product eco-system innovation on both the upstream as well as downstream nodes in the supply chain. Whereas the consumer attitudes and perspectives on e-mobility are inferred from a survey, the impact analysis matrix is used for analyzing the competitive leverage of Tesla through several features in the upstream, downstream and servitization.