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The financial system plays an essential role in facilitating the intermediation process for economic growth. Policymakers stress on achieving a well-developed and regulated financial system to achieve economic development and resiliency. Using data from the State of Qatar, this paper aims to examine the impact of financial development indicator on economic growth; the impact of financial development indicator on hydrocarbon and nonhydrocarbon sector; the impact of Islamic banking on hydrocarbon and nonhydrocarbon economic growth.

The research uses quarterly data from 2007 to 2019 and adopts autoregressive distributed lag cointegration techniques to test the long- and short-run dynamic relationship between various measures of financial development and economic growth.

The results present evidence of long-term cointegration between overall financial development indicator and economic growth. Furthermore, the authors document the existence of long-term relationship between financial development and nonhydrocarbon sector. However, there is a lack of evidence on the long-run relationship between financial development and the hydrocarbon sector. Notwithstanding, Islamic banking contributes to overall economic development, as well as to the nonhydrocarbon sector.

This paper offers policymakers with insights to evaluate measures to diversify the economy. It also assists decision-makers in promoting Islamic finance, particularly to the banking sector as a vital contributor to economic growth.

To the best of the author’s knowledge, this paper is the first to evaluate financial development and economic growth for the case of Qatar in light of recent developments in Islamic finance.

The literature on sustainable development reveals that the financial sector and the real sector should maintain a coherent association in the long run. Thus, like that in a country-level significance, the relevance of the investigations of the interrelationships between the financial sector’s development and the growth and development of the states within a country is also required to be done. This chapter tries to examine the interrelationships between two sets of variables, bank credit and state output, and bank credit and human development, for the pre-reform and post-reform periods. Using the appropriate time series econometric analysis, the study finds no long-run relationships between credit and NSDP during the pre-reform period but it has observed a number of states where such stable relations hold during the post-reform period. Again, there are mixed results between the two in the Granger causality analysis during both the periods. There are the states like AP, Bihar, Karnataka, Kerala and WB where developments in the financial sector influence the growth of the real sector, while the reverse causality, that is, from the real sector to the financial sectors works in case of Assam, Haryana, MP and Maharashtra. Bidirectional causality between the two is observed in the states like TN, WB, etc. Further, the study finds very small number of states where credit and human development are interlinked in the long run. However, in the short run, the financial sector makes influences to the human development in case of the states like Bihar, Odisha and TN.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.

There is a rich literature which states that India did not suffer much from the impacts of the US financial crisis, but there is a school of thought which believes that the idea of India being insulated or decoupled from the contagion on account of limited integration into the world economy has been proved to be wrong. What is interesting is the focus has always been on the services sector and not on the manufacturing sector in India. In this background, this chapter tries to understand whether manufacturing sectors' productivity growth was one of the reasons that the crisis worsened in India or was it because of the crisis that India's manufacturing sector went into a deep recession. To look into the causality issue, the author estimates the productivity loss index (PLI) for the Indian industries during the period between July 2007 and July 2010 by estimating the fall in growth percentages in consecutive months for a total of 9,000 manufacturing, mining, and electricity industries. The data at monthly level have been retrieved from the Centre for Monitoring Indian Economy (CMIE) Prowess database. Based on the causality results, the chapter shows that it was because of the subprime crisis that India's manufacturing sector went into a deep recession. Using a probit model, the chapter also estimates the probability of the US subprime crisis being responsible for the productivity loss in India's manufacturing sector during the above-mentioned period.

This research aims to explain the effect of financial indicators and economic growth on human capital in low-income countries.

We gathered balanced panel data from 1980 to 2016 over a sample of 12 low-income countries categorized by World Development Indicators. The data stationary properties were analyzed by unit root test while the existence of a long-run relationship among the variables was confirmed by cointegration test. We performed Hausman test to differentiate between the fixed effect and random effect model. The sensitivity analysis confirmed the robustness of the results.

Our findings indicated that broad money supply and private sector credit has a positive and significant impact on human capital. Interestingly, bank credit showed a negative and significant effect on human capital. We also found a significant positive relationship between human capital and economic growth in the study sample.

This is a preliminary study using financial development and human capital in low-income countries with panel econometric techniques as an analysis tool. Overall, we suggest a policy to focus on the financial sector development and economic growth to produce sustainable human capital.

The financial system of an economy, especially banking, facilitates efficient allocation of resources from savers to borrowers for productive investments, and thus promotes economic growth. State-wise bank credit in India shows a growing divergence, despite the aim of central planning to reach a degree of convergence in macroeconomic performance over time. This chapter analyzes how diverging bank credit affects macroeconomic performances of the Indian states, through an alternative approach of composite indicators-based rankings of states adopting the methodology of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) that is used in operations research or more specifically MCDM (multiple criteria decision-making). A composite indicator of the states’ annual macroeconomic performances has been constructed taking indicators of output growth, per capita state domestic product, inflation, and fiscal indicators for years 2006–2018. States are ranked by both macroeconomic performance and bank credit to states, and the correlation between the two indicators, known in the literature to be interlinked,is studied here to understand how the availability of credit or lack of it has influenced State level macroeconomic development in India. The results thus show that wealthier and better performing states continue to attract the larger chunk of bank credit, while weaker states have not been able to catch up. An important policy implication would be to place even more emphasis on higher levels of credit growth for weaker states, particularly infrastructure credit, to achieve a degree of income convergence throughout the Indian economy.

This study examines the moderating effect of institutional quality on the finance-growth nexus in South Africa from 1986 to 2015.

This study adopts unit root tests, cointegration test and autoregressive distributed lag (ARDL) model.

The findings reveal that institutional quality constitutes a drain to the growth benefits of financial development (FD) in South Africa in the short-run while FD and institutional quality converge to enhance growth process of the country in the long-run. Also, the threshold of institutional quality beyond which institution stimulates strong positive impact of finance on growth is estimated to be 6.42 on a 10-point scale.

This study, therefore, suggests that institutional quality matters in the way FD influences economic growth in South Africa. Hence, stakeholders are encouraged to trace and block lapses and loopholes in the institutional framework guiding financial system in South Africa so as to maximize growth benefits of FD.

This study contributes to the extant studies by introducing a country-specific analysis into the empirical examination of how institutional quality influences the impact of FD on economic growth. Also, this study deviates from other studies by determining the threshold of institutional quality beyond which FD stimulates strong positive effect on economic growth in South Africa

The purpose of this paper is to examine the relationship between financial development and economic growth in India using annual data from 1982 to 2012.

The stationarity properties are checked by ADF, DF-GLS, KPSS and Ng–Perron unit root tests. The long- and short-run dynamics are examined by using the autoregressive distributed lag (ARDL) approach to co-integration.

The co-integration test confirms a long-run relationship in financial development and economic growth for India. The analysis of ARDL test results reveals that both bank-based and market-based indicators of financial development have a positive impact on economic growth in India. Hence, the results support the supply-leading hypothesis and highlight the importance of financial development in economic growth. The findings also indicate that the Indian bank-centric financial sector has the potential for economic growth through credit transmission.

The present study recommends appropriate reforms in financial markets to attain sustainable economic growth. The findings are useful for policy-makers who want to maintain a parallel expansion of financial development and growth.

To date, there are hardly any studies that use both market-based and bank-based indicators as proxies of financial development and analyze their role in economic growth in India. So, the contribution of the paper is to fill this gap in literature.

The purpose of this paper is to examine the relationship between financial development and economic growth in Indian states using annual data from 1993 to 2012.

The stationarity properties are checked by Levin-Lin-Chu and Im-Pesaran-Shin panel unit root tests. The study employed the Pedroni’s panel co-integration test to examine the existence of long-run relationship and the coefficients of co-integration are examined by fully modified ordinary least squares. The short term and long-run causality is checked by panel granger causality.

The co-integration test confirms a long-run relationship between financial development and economic growth for Indian states. The results support the supply leading hypothesis and highlight the importance of financial development in economic growth in Indian states. The findings also indicate that bank-centric financial sector of India has the potential of economic growth through credit transmission.

The present study recommends for appropriate reforms in financial market to attain economic growth in India. The findings will be useful for India’s policymakers in order to maintain the parallel expansion of financial development and economic growth.

Till date, there is no study that includes all 28 states in analyzing the role of financial development in economic growth for Indian economy by applying latest econometric techniques. Further, the study uses gross domestic state product instead of net domestic state product as proxy for economic growth because of the presence of different depreciation rates.

The purpose of this paper is to explore the emissions of SO₂, NO₂ and SPM in India during 1991‐2003. The Environmental Kuznets' Curve (EKC) is applied to explore the relationship between economic development measured in terms of State Domestic Product (SDP) per capita and different air quality parameters for industrial and residential locations respectively. Several developmental factors contribute to change in emissions of these air quality parameters. These factors generally include the scale effect, composition effect and the pollution abatement effect.

The methodology has focused on testing the EKC hypothesis at state level in India, using cross‐section and time series data for 15 major states. The study has made use of fixed effect version of pooled data estimation technique.

The findings in the paper indicate only a directional inverted U‐shaped EKC relationship for both industrial and residential locations, without being significant statistically. Basically, some developmental factors such as population density, urbanization and policy variables are significant with expected signs in explaining the relationship for most of the cases. The calculated turning point of SDP per capita for different air quality parameters ranges between $163.46 and $408.66

The present study has been restricted to a shorter time period (i.e. 1991‐2003) because of the unavailability of continuous time series data. The study only includes 15 major Indian states and excludes other states due to lack of proper data sources.

The inclusion of several developmental variables (such as urbanization, infrastructure development, population density, policy) helps to detect whether the emissions of different air quality is mainly due to economic growth or other reasons.

The investigation in the paper allows determination of the level of SDP per capita, the emissions of different types of air quality will start to decrease in different Indian states.