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Lotteries have gained immense popularity for enhancing fiscal resources for social intervention programs such as education. However, the fiscal significance of lotteries for accomplishing educational equity across the American states has been empirically challenged. Much of the literature on lotteries suggests that financial reliance on state operated lotteries for educational embellishment may actually hinder the process of educational egalitarianism. Through pooled time series regression analysis, this project intends to demonstrate that states earmarking lottery dollars for education are receiving fewer fiscal allocations for education from the federal government than states opting to by-pass adoption of a lottery for education. The data for this project will include fourteen variables over a twentyyear period covering all fifty states.

The purpose of this paper is to construct a robust macroeconomic performance (MEP) index of the State economies of an emerging market economy, i.e. India.

Two variants of data envelopment analysis (DEA) models – radial and non‐radial – are proposed to construct the macroeconomic policy performance of 22 Indian State economies in the post‐economic reforms era covering the period: 1994‐1995 to 2001‐2002, using three macroeconomic indicators: growth in gross state domestic product, price stability, and fiscal deficit.

The authors' three broad empirical findings are: first, the radial and non‐radial DEA models yield significantly different rankings of State economies in terms of their MEP index scores; second, as against the use of only growth in gross state domestic product and price stability for MEP measure, the inclusion of fiscal deficit as an additional indicator yields a noticeable improvement not only in the State MEP index scores, but also in their rankings, thus providing the evidence of relatively successful attempt by the Indian States in reducing fiscal deficit, in general, and legislating FRBM bill, in particular; and third, a positive significant correlation between foreign direct investment (FDI) and MEP indicates that a State's overall macroeconomic policy performance does matter to attract FDI.

Since the DEA models employed in this study ignore the possibility of asymmetric shocks, the MEP results might be questioned in this deterministic setting. However, the study period has been smooth and has not been subject to any major changes in the State economic policies. Therefore, the MEP results might not be susceptible such changes. However, further research is desired on examining the macroeconomic policy performance behavior of Indian States using bootstrapping DEA.

None of the past Indian studies were able to give a comprehensive picture concerning the MEP behavior of Indian State economies, since the methodologies adopted in those studies were not suitable to take into consideration all the macro indicators at a time. Therefore, this present study is considered the first of its kind in assessing the MEP index of the Indian State economies by simultaneously considering all the macro indicators.

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 assertions of the government that poverty eradication and social development generally are the main challenges and that it is fully committed to address these issues have continued over time. But how genuine this claim is a matter of great concern. So, this chapter may be an attempt to analyze patterns in social sector expenditure on education (SSEE) and its impact on Human Development Index (HDI) among different states in India. The combined social sector expenditures (SSE) of Centre and States, which provide the best picture of India’s commitment towards the social sector in education, may be assessed. There are diverse ways of inspecting the trends in expenditures. Firstly, to look at SSE as a proportion of gross state domestic product (GSDP), secondly is to calculate SSE as percentage of aggregate budget expenditure, thirdly is to look at the real per capita expenditure (PCE) (at constant prices) for the social sector in the case of the states. This chapter looks at the trends in SSEE, considering all the alternative ways and the impact of SSEE on HDI. The result of the study shows that there is a positive relationship between SSEE and HDI. SSEE may lead to increases in gross enrolment ratio (GER) and literacy rate (LR). An increase in GER and LR may help in increasing the HDI.

Although India is seen as a key player in the global economy, it is still below its potential level of growth. In this age of globalism, integration with the global economy through trade and foreign investments fosters domestic growth. For India, although this integration has strengthened over the years, there are certain gaps that remain to be addressed. Though numerous studies in the literature have tried to find answers to these questions, an important aspect that has not been considered by these studies relates to India’s federal structure and the role of states in determining the aggregate economic outcome. As Foreign Direct Investment (FDI) inflows to India are concentrated in a few states, this paper aims to provide an assessment of the reasons behind this trend.

This paper aims to investigate the reasons behind the interstate differences with respect to FDI inflows in India. The analytical work undertaken for this paper is based on secondary data, collected and collated from various sources. The approach adopted for this paper includes a heat graph analysis to examine whether there is a clear pattern in terms of the state-specific factors for high FDI states versus the low FDI states. This data analysis is followed by an econometric estimation to gauge the impact of state-specific factors in determining the FDI inflows.

As per the secondary data–driven heat graph and econometric analysis, factors like industrial output, social sector expenditure, judicial quality, connectivity indicators, labor cost and availability of credit, act as differentiators between high and low FDI-receiving states. It then becomes imperative to bridge the gap between the two sets of states in terms of these specific factors. Implementation and success of policy interventions can only be derived at the state level and therefore needs more decentralized approach.

This paper tries to identify the reasons that are responsible for FDI inflows being concentrated in a few Indian states. This involves a comprehensive analysis of several variables to understand whether there is a clear pattern where high-FDI states are also in a better position with respect to these attributes. This effort to factor in the federal aspect of a macroeconomic indicator like FDI provides new dynamic to this area of work.

This paper aims to provide an up-to-date analysis of the productivity in the agricultural sector within the states and union territories of India. Despite agriculture’s diminishing role as a share of overall gross domestic product (GDP) in India, it plays a crucial role by providing a large proportion of jobs to the workforce. Recognising agriculture’s central role in the economy as well as the significant diversity between the states in terms of resources, this paper estimates the total factor productivity (TFP) for Indian crops at the state level from 2000 to 2010 using both the growth accounting and the Malmquist Index Data Envelopment Analysis methodologies. The results highlight the possibility of increasing production with existing technologies by focusing on efficient resource deployment and enhanced management techniques.

The paper utilizes both growth accounting and the Malmquist Index Data Envelopment Analysis methodologies to estimate the growth of TFP at the regional level at the sub-national level (for states and union territories).

The results highlight the wide variations in the performance of states with respect to growth in TFP for the period 2000-2010. At the regional level, the Western region experienced the largest TFP growth, while the Eastern region experienced the lowest. At the state level, Gujarat registered the highest TFP growth, while Bihar emerged as a laggard with the lowest growth in TFP.

The results highlight the possibility of increasing production with existing technologies by focusing on efficient resource deployment and enhanced management techniques.

Although most of the existing literature focuses on national level analysis for India, this paper provides an up-to-date analysis of the productivity in the agricultural sector within the states and union territories of India. Correspondingly, the results are more applicable for these sub-national economies and offer more relevant policy implications.

This paper aims to study the relationship between employment and tourism activities as well as economic variables for the 32 states of Mexico for the period 1999-2014.

To study the case of Mexico, the authors use panel data and cointegration panel data. They also use geographic information systems to observe changes over time between the variables, which is useful in the empirical evidence.

The main results obtained by the models are as following: domestic tourism is the variable with the greatest impact on the generation of direct employment in the tourism sector, a finding supported by both methodologies; economic growth (measured by state gross domestic product) also directly impacts the generation of employment; and the cointegration of the panels causes a long-term equilibrium among the states and some variables.

The model used leaves out other variables that may influence the performance of the tourist activity. In addition, given the availability of official and homogeneous information, it only covers what has been documented up to 2014.

The aim is to measure the impact of tourism on the variables at the state level, where the economic activities could be based on public policies, as well as the importance of tourism activities in generating employment. In this sense, the impact would be in channeling efforts to support the main economic activities and could serve as a starting point for the evaluation of programs to promote domestic tourism.

This paper reviews the relationship that exists between tourism activity and its effect on other variables, especially employment. It is the first time that these topics are studied for the Mexican economy.

The main aim of this study is to explore the role of multi-dimensional human capital on the economic growth of the Indian economy.

The study used the methodology given by World Bank, 2018) in calculating the human capital index (HCI). The HCI has been constructed at a regional level for all 28 Indian states and 8 Union Territories (UTs) for the period of 2015–2016. The study explored the linkages between HCI and per capita gross state domestic product (PGSDP). The study further employed OLS (Ordinary Least Square) for overall significance and Spearmen’s Rank correlation coefficient test for establishing the linkage between HCI and PGSDP.

The results indicate that quality education, expected year of schooling, and infant mortality rate play a significant role in the improvement of HCI which further impacts the productivity rate of the upcoming generation and the inclusive growth of the country. The findings show that Mizoram, Chandigarh and Kerala are better performing states while the Bihar and Uttar Pradesh are the worst performers. The results also show that there is a positive and statistically significant correlation between PGSDP and HCI and its components. Further, the results show that public expenditure on health and education has significant effect on HCI.

The results of this study would be useful for policymakers to identify the determinants and improve the position of Indian states in HCI. The results show that policymakers should focus on quality education and health to improve the productivity of future generation workers for sustainable and inclusive growth.

The study is the pioneering study to analyze the state-wise HCI in India using methods mentioned by the World Bank. Unlike previous studies, variables such as expected year of schooling, under-5 mortality rates and survival rates are constructed more pragmatically.

India launched Smart City Mission in 2015 with an objective of development of 100 smart cities with a completion deadline in 2019 that was extended till June 2023. Smart City Mission is an important mission in the backdrop that urban population in India is projected to be 67.55 crore in 2035 from 48.30 crore in 2020. Further, by 2035, the percentage of population in India at mid-year residing in ‘urban area’ will be 43.2% as per the United Nations – Habitat's World Cities Report 2022 and it will be just next to China's urban population in 2035 that is projected at 1.05 billion. A recent World Bank report (2022) estimated that India will need to invest US (United States) $840 billion over the next 15 years, i.e. US $55 billion per annum – into urban infrastructure if it has to effectively meet the needs of its fast-growing urban population.

This chapter focuses on financing of sustainable smart cities in India. This chapter summarises financing options explored by the government in the beginning, challenges faced in financing of Smart City Mission in India over a period due to various developments such as pandemic, delay in execution of projects under the Smart City Mission, among others. Finally, suggestions have been given for making financing means effective and sustainable. These suggestions are based on the gaps between the ‘financing means thought of’ in the beginning and ‘financing means actually applied’ while executing Smart City Mission in India. Financing part is worth exploring in the background that India had the fiscal deficit at 3.9% of Gross Domestic Product (GDP) in 2015–2016 and most recently, the country had the fiscal deficit at 6.71% of GDP in FY22. And the country also dealt with the pandemic like other economies and provided COVID-19 vaccine free of cost to all citizens. Insights are useful for any other economy with a similar sustainable and smart city mission while facing resource constraints.