Gross State Domestic Product Research Articles

Effect of police expenditure on crime rate in India

Purpose This study aims to examine the relationship between law enforcement expenditures, economic indicators and various crime rates in India using data from the National Crime Records Bureau (NCRB) spanning from 2001 to 2021. Design/methodology/approach The study uses data sourced from the NCRB covering violent crimes, property crimes, economic crimes and total crimes under the Indian Penal Code across 27 states and 2 union territories in India. Crime rates per 100,000 people are calculated using projected population figures from the 2001 and 2011 censuses, adjusting for census periods and growth rates. Economic variables such as per capita real gross state domestic product (GSDP) and total police expenditure are obtained from state government sources, adjusted to constant prices. Pooled ordinary least squares analysis is conducted to explore the relationships between crime rates, conviction rate, economic factors and police expenditure over the three-time points: 2001, 2011 and 2021. Findings The study reveals a complex relationship between police expenditure and crime rates across different categories in India. Increased police expenditure is positively associated with higher reporting rates for violent and economic crimes, suggesting that enhanced law enforcement resources may improve crime detection and reporting. However, contrary to some expectations, higher police spending does not necessarily lead to a reduction in overall crime rates. Economic prosperity, measured by per capita GSDP, is found to reduce violent crime rates but is associated with an increase in property and economic crimes, likely due to the greater opportunities for such crimes in wealthier regions. Research limitations/implications The study’s reliance on state-level aggregate data and NCRB crime statistics, which are based on reported incidents, might not fully capture the true extent of criminal activity, particularly in regions with underreporting issues. In addition, the use of projected population data beyond 2001 and 2011 introduces some uncertainty into the analysis. Future research should explore district-level data to better understand regional variations in crime and incorporate social, cultural and innovative policing strategies to provide a more comprehensive analysis. Practical implications Policymakers should recognize the nuanced impacts of police expenditure and economic prosperity on crime rates. While increased law enforcement resources may enhance crime reporting, they do not guarantee a reduction in overall crime rates. Economic growth, while beneficial in reducing violent crimes, may inadvertently increase property and economic crimes due to greater opportunities for criminal activity. These insights suggest the need for targeted interventions that consider both economic factors and law enforcement strategies in crime prevention efforts. Originality/value This study contributes to the ongoing debate about the effectiveness of police expenditure in reducing crime by highlighting its limited impact on overall crime rates in India. The findings underscore the importance of understanding the diverse effects of economic prosperity on different crime types, offering valuable insights for policymakers aiming to design evidence-based crime prevention strategies that account for socioeconomic disparities and regional contexts.

Migration for Business: A Case Study of Goa

As the government eases out of economic activities and its role as an employer declines over time, there is a growing focus on attracting business and entrepreneurship and creating a conducive environment for their growth. Goa witnesses high rates of in-migration from the rest of India. However, census data reveal that of the total migration to Goa, only 2.7% of it is for business. This study uses census data to analyse the relative importance of population, distance, literacy and gross state domestic product (GSDP) in the volume and direction of migration flows through a gravity model analysis. In the case of population, it is observed that a high population at the source state means a higher degree of outmigration. This may be due to greater competition for scarce resources and lower costs of setting up business in the destination. The highest numbers of business migrants are from the neighbouring states of Maharashtra and Karnataka, which indicates that distance may be a deterrent to mobility, especially among women migrants. Educational attainment is not a very important determinant of migration for business. Similarly, economic growth does not seem to deter outmigration, indicating that better opportunities and cost-minimization at the destination may spur migration in spite of high economic growth in the home state. From the field study, it is observed that the majority of the businesspersons are Hindu males from the general caste. While economic factors serve as important push and pull factors, social factors are an important pull factor and determine the ease of settlement in the host state. They come to Goa for the long term and intend to settle here. They own land and housing. Though many are small businesses, through their consumption and investment activities, they play an important role in promoting growth in the state. The process of migration is self-sustaining as many bring their family members, relatives and neighbours and help settle them in business in related fields.

Trends and Growth Patterns in Public Expenditure on Education: An Analytical Study in Telangana

As India's economy flourishes, the way the country allocates its resources is becoming increasingly crucial. One vital aspect is public spending on education, which is essential for nurturing human capital and driving economic growth. This study examines the trends and growth rates of public expenditure on education in Telangana from 2014 to 2021, shedding light on the financial priorities and efficiency of educational funding. The analysis reveals a mixed bag of trends and growth rates. While some states have made significant strides in increasing their educational expenditure, others have seen a decline. The data shows that the total budget allocation for education has grown steadily over the years, with some fluctuations. However, the percentage of expenditure relative to Gross State Domestic Product (GSDP) has been declining in many states. To better understand the relationship between total budget allocation and educational spending, regression analysis was employed. The results indicate a positive correlation between the two variables, suggesting that an increase in overall budget allocation is linked to increased spending on education. However, the relationship is not straightforward, with some states exhibiting high levels of expenditure despite lower budgets. The findings of this study have significant implications for policymakers and educators. They highlight the need for a more nuanced approach to educational funding, one that takes into account the diverse needs and priorities of different states. It also underscores the importance of monitoring and evaluating the effectiveness of educational programs and policies to ensure that resources are being used efficiently. In other words, India's policymakers must adopt a more targeted approach to educational funding, recognizing that every state has unique challenges and opportunities. By doing so, they can ensure that limited resources are allocated effectively to address the most pressing educational needs and drive long-term economic growth.

Impact of Public Expenditure on Education in Chhattisgarh

This paper objective to investigate the correlation between public spending on education and the growth of the state of Chhattisgarh. Time-series data spanning from 2000 to 2021 was utilised. Public expenditure has several effects in economy. It can increase economic growth. It can increase social welfare. It is directly expected education is helps Positive Social change of citizen. The result shows that total public expenditure and Education expenditure is highly and statistically significant on economic growth indicator such as GER and DOR in primary level in Chhattisgarh.Public expenditure helps in achieving equitable distribution income and promote growth and welfare. The findings indicate that total public spending and education spending have a statistically significant and positive impact on economic growth indicators like the state's Gross Enrollment Ratio (GER) and the percentage of primary school dropout children (DOR) at the primary level. Education is directly expected to contribute to citizens' positive social transformation. The study's findings show that public spending on education and economic growth are correlated over the long term. Over time, there is a found unidirectional causal relationship between public education spending and Gross State Domestic Product (GSDP).

Renewable Energy and Economic Growth: Evidence from India

This article examines the nexus between economic growth and two renewable energy sources, namely wind and solar, to separate out the contrast between these two sources, for India deploying system generalised method of moments and vector error correction method suitable to capture the dynamic nature of panel data. Unlike most of the earlier studies, it takes into account cross-sectional dependence and addresses the issue of endogeneity. India has been chosen because despite India being one of the largest producers of renewable energy globally; the nexus is under-studied. This article finds the installation of solar energy capacity positively influences the Gross State Domestic Product (GSDP) growth. Moreover, there is a bi-directional positive relation between the installation of wind energy capacity and GSDP growth. Hence the adoption of renewable energy is helping the states to grow faster. However, the study found not much difference in the nature of the nexus between solar energy growth and wind energy growth for India. JEL Codes: O13, P28, P44, Q56

Does growth of Gross State Domestic Product can manage unemployment in India? A State-level Analysis

Unemployment and Gross State Domestic Product (GSDP) is a complex and critical aspect of economic research, with a particular focus on the impact of GSDP on unemployment from 2017 to 2022. In summary, this research paper examines the intricate interplay between these two variables, aiming to understand how changes in GSDP impact unemployment rates in different states of India and growth of the said variables. Growth rate of the variables has been calculated using year over year growth rate (YOY), compound annual growth rate (CAGR), and relationship between the variables find out using correlation and Granger causality test. It investigates the potential causal links, cyclical patterns, and policy implications, shedding light on the dynamic nature of employment and economic growth at the state level. The findings of the study suggest that growth of the variables are fluctuative in nature and there is a negative relationship between GSDP and unemployment rate in the states as well as there is a existence of unidirectional or bidirectional causality.

RESEARCH AND PUBLICATION CULTURE OF HIGHER EDUCATION INSTITUTIONS IN ODISHA

The objectives of the paper is to analyse research outputs, self financing courses, research initiatives and inclusive education in Odisha. The study highlights on Government investment in in research activities and Researchers who lead them with the expectations that the country benefits in the long term from increased productivity and enhance social development.The total expenditure on higher education by Odisha State government is approximately Rs.1, 200 Crore which represents 0.5% of its Gross State Domestic Product (GSDP). This includes plan and non-plan for revenue and capital expenditure. The state’s annual per capita expenditure on higher education for its 18-23-year-old population is about Rs. 2,700 (EY, 2015). Studies have highlighted the value of continuity of sound leadership in enhancing institutional strength. All HEIs have Student Placement Cells but not all are equally functional. Cells are headed on a part-time basis by a member of the faculty who is a full-time teacher of a discipline, fitting in the management of the cell.Skills development, much sought after by employers, was supported by some colleges through well-planned co-curricular activities and processes. Experience with interactive sessions outside the regular classroom environment increases the flexibility and ease with which graduates can adapt to new environments. KEY WORDS: Culture, Journals, Patients, Publications, Research Policies

Rural Transformation in Gujarat: An Empirical Assessment through Multidimensional Indicators

Rural transformation is one of the key social and economic changes that lead to the development of rural communities and the overall growth of any country. A country like India has diversity in terms of the availability of natural resources, work culture, race, and religion for each geographical state unit with its own pace of growth and development. Gujarat is one of the high-growth states in the country, with Gross State Domestic Product (GSDP) estimates of USD 253.64 billion in FY22 with a 7% YoY increase (India Brand Equity Foundation, n.d.). However, the rural population in Gujarat fell to 57.4% in 2011 from 62.6% in the 2001 census. This paper tries to assess the rural transformation in Gujarat with multidimensional indices like agriculture, consumption, employment, education, and urbanization that focus on rural transformation with the help of district-level microdata in the broader context of the high economic growth of Gujarat.

Role of Public Debt in Indian States in the Post-Reform Era

The substantial amount of existing literature investigating the debt–growth association for high-income countries shows that debt has a negative impact on economic growth or the existence of an inverted U-shaped relationship between these two variables on some occasions. Given the lack of literature involving developing economies in this space, our study entirely focuses on a developing country like India. The study examines the empirical relationship between public debt (internal) and state gross domestic product (SGDP) for India in the post-reform era. The panel data extend from the year 2000 till 2020. Our random error component model findings indicate a positive and significant impact of debt in enhancing the Indian SGDPs for the above-mentioned period. Results are also confirmed by using an alternative estimation technique, namely, fixed effect. Next, we address the issue of endogeneity by employing generalized method of moments. Our results continue to remain robust. Finally, the inclusion of other control variables does not alter our findings. JEL Codes: H63, H54, O50, C51

Estimating funds required for UHC within Indian States.

Universal Health Coverage (UHC) has been high on national and international agendas since its adoption as one of the Sustainable Development Goals (SDGs). Within India, there is a wide variation in the total amounts per capita spent by each state government (Government Health Expenditure or GHE) on healthcare. Bihar, with a GHE of 556 per capita (per annum), has the lowest state government spending, but there are many states in which governments spend more than four times that amount on a per capita basis. However, despite this, no state offers UHC to its residents. This failure to provide UHC could be because even the highest amounts spent by the state governments are too low for them to offer UHC or because the cost differences between states are very high. It is also possible, however, that a poor design of the government-owned health system and the degree of waste embedded within it could account for this. It is important to understand which of these factors is responsible because it then provides a clue as to what the best path to UHC might be in each state. One way to do that would be to arrive at one or more broad estimates of the amounts needed to finance UHC and to compare them with actual amounts being spent by the governments in each state. Older research provides two such estimates. In this paper, using secondary data, we add to them using four additional approaches so that we can build greater confidence in the estimation of amounts needed by each state to offer UHC to its residents. We refer to these as Outside-in, Actuarial, Normative, and Inside-Out. We find that, with the exception of the approach which assumes that the current design of the government health system is optimal and only needs added investment to offer UHC (the Inside-out approach), all the other approaches give a value of between 1302 and 2703 per capita for UHC, with 2000 per capita providing a reasonable point estimate. We also find no evidence to support the view that these estimates are likely to vary between states. These results suggest that several Indian states may have an inherent ability to offer UHC with government financing alone and that a high degree of waste and inefficiency in the manner in which government funds are currently being deployed may well be behind their apparent inability to do so already. Another implication of these results is that several states may also be further away from the goal of offering UHC than an initial analysis of their GHE as a proportion of their Gross State Domestic Product (GSDP), i.e., GHE/GSDP, may suggest. Of particular concern are the states of Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh, all of which have GHE/GSDP greater than 1%, but because their absolute levels of GHE are well below 2000, in order to reach UHC, they may need to more than triple their annual health budgets. The Christian Medical College Vellore supported the second author (Sudheer Kumar Shukla) through a grant from the Infosys Foundation. Neither of these two entities had any role in the study design, data collection, data analysis, interpretation, writing of the manuscript, or the decision to submit it for publication.

Understanding the relationship between states' unemployment rates and gross domestic product

This research paper examines the factors that affect the unemployment rate in public sector states of America. The study is based on the relationship between states' unemployment rates and Gross Domestic Product (GDP). The research question is: What is the relationship between states' unemployment rates and GDP? The hypothesis is that states with high unemployment rates will have lower GDPs. The research design contains three studies and one theory for different authors in the literature review section relevant to this study. The unit of analysis is the states of America. The paper proposes a methodology that describes the measures of the study. The researcher used nominal-level data to measure states and scale to measure GDP, states' unemployment rate, and population. The study concludes that higher unemployment rates caused lower GDP in states of America. An interesting subject for future study is the effects of states' unemployment rates on the state's GDP.

Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis

The USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes. Data disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05. Standardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures. COVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises. Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

Air pollution attributed disease burden and economic growth in India: Estimating trends and inequality between states

Air pollution is one of the major contributors to the disease burden in India after malnutrition. We examined the relation, and state-wise disparities in air pollution attributed to disease burden (APADB) concerning gross state domestic product (GSDP) and growth in motor vehicles in India. We retrieved disability-adjusted life year (DALY) estimates for India due to air pollution from the Global Burden of Disease Studies, injuries, and Risk Factors Study (GBD). We examined the association between APADB with GSDP and the growth in the number of registered motor vehicles in India during the 2011 to 2019 period. Concentration indices and Lorenz curves were used to explore the variation in APADB across individual states. Except for a few states, APADB is inversely proportional to GSDP. Growth in motor vehicles was also negatively correlated with the APADB in n=19 states. The concentration index explained a 47% inequality in APADB between individual states and exhibited a decline (45%) during 2019 compared to 2011. The unevenness in APADB among Indian states is evident from the analysis as the states occupying the 6 th or 7 th decile and above in terms of GDP, urbanization and population contribute more than 60 per cent of the total APADB. The APADB is inversely correlated with GSDP for most of the states, and the negative correlations were conspicuous when APADB per 100,000 population was analysed. The concentration index and Lorenz revealed the presence of APADB inequality between states in terms of GSDP, population, urbanisation, and total factories. Not applicable.

Assessing interstate softwood roundwood trade in the southern United States: a gravity trade model approach

Intraregional trade of forest products is a critical component of regional and subregional timber markets in terms of supply chain planning and locating forest product manufacturing facilities. Based on a gravity trade model, we evaluated the various factors driving the interstate flows of softwood sawlog and roundwood pulpwood in the 13 southern US states: AL, AR, FL, GA, KY, LA, MS, NC, OK, SC, TN, TX, and VA. Biennial state-level panel data from 2011 to 2019 in 13 southern states were employed to estimate empirical sawlog and pulpwood trade models. The results suggest that state gross domestic product (GDP) of importing states, exporter and importer production, importer consumption, the distance between the trading partners, and the electronic logging device mandate are influential factors of softwood sawlog trade between the states. Similarly, state GDP, exporter pulpwood production, importer consumption, the distance between the trading partners, delivered timber prices, and pellet mill capacity in each state are found to be significant determinants of softwood pulpwood trade between the partners across the state borderlines. The findings provide forest managers and policy makers with additional insights on the growing bilateral timber trade dynamics in regional and subregional markets in the southern United States.

Linkage of Electricity with Agricultural Growth and Technology Factors: An Illustration of India’s Case

Understanding the relationship between electricity consumption and economic growth is crucial for formulating efficient energy policies for all sectors in general, and for agriculture in particular. To study this, an empirical examination of the long-run co-movement and the causal relationship between electricity consumption and real gross state domestic product (GSDP) from agriculture and its allied sectors is attempted. The agricultural sector involves the use of different input technologies that are further influenced by electricity consumption. To account for this technology-enabling effect of electricity, we further take up an analysis of the relationship between electricity consumption and agricultural technology factors: fertilizer consumption, the share of irrigation, area under cereal, and the extent of mechanization. We use both state (data from 17 states for the period 1993–2017 for the electricity–GSDP relationship) and country-level data (for the period 1980–2018 for the electricity–technology factors relationship) in the analysis. Since short-period time series datasets analysis may yield unreliable and inconsistent results, we employed modern heterogeneous panel co-integration and panel-based error correction model techniques for analyzing the energy–growth linkage. When the heterogeneous states effect is taken into account, the empirical results fully support a positive long-run co-integrated connection between GSDP and electricity consumption. We could detect both long-run and short-run unidirectional causality running from electricity consumption to agricultural growth. Further electricity consumption was also found to augment the use of technology factors in agriculture. This calls for implementing policies and strategies for achieving higher electricity use in agriculture and improved efficiency in its utilization simultaneously.

Causal relationship between electricity consumption and economic growth in Assam, India

The aim of this study is to find the causal relationship between electricity consumption (EC) and economic growth in terms of Gross State Domestic Product (GSDP) in Assam considering the time period 1980-81 to 2018-19 with the help of Granger Causality Test. The stationarity of the series are tested through the Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests and reveal that both the series become stationary in first order differences but the result of Johansen Cointegration test indicates no cointegration between them. Applying Granger Causality test, no causal relationship is observed in either direction between EC and GSDP during the considered time period in Assam implying that energy conservation policies may not harm the economic growth in Assam.

Burden of COVID-19: DALY and productivity loss for Karnataka, India.

COVID-19 is a pandemic that is devastating the world right now quelling over 2.5 million people worldwide. Similarly, in India and its largest southern state Karnataka, the coronavirus is responsible for around 161,000 and 12,449 deaths, respectively. These numbers capture the havoc caused by this novel coronavirus, but fail to discern the complete picture. Broadly, this study aimed to study the mortality, morbidity, and the economic issues inflicted by the COVID-19 in the state of Karnataka. Specifically, the study used publically available epidemiological data to study both mortality and morbidity by means of disability-adjusted life years (DALYs). Furthermore, the study aimed at estimating the permanent losses to the state gross domestic product (SGDP) due to the pandemic. Publicly available epidemiological data are used from selected sources and DALYs are computed. The permanent loss to the SGDP is estimated using the human capital approach. The total DALYs for Karnataka are computed to be 22,506 of which 22,041 correspond to mortality and remaining correspond to morbidity. Financially, Karnataka lost around 208 years of productive years of lives costing around ₹590 million rupees to the SGDP. It is found that major burden of COVID-19 during study period is due to mortality. Morbidity accounts for around 2% of the total DALYs. Males are the most affected by the mortality and also the morbidity. With respect to loss in productivity, the losses due to premature mortality of COVID-19 amounted to ₹590 million.

Institutional Factors Driving Participation of Marginalized Section(s) in Livestock Extension Programs in Tamil Nadu

Livestock plays an important role in livelihood of small and marginal farmers with 5.47 per cent of state GDP (Gross domestic product) and one of the primary sources of employment to marginalized section(s) of rural Tamil Nadu. This study was undertaken to identify the factors driving participation of marginalized section(s) in livestock extension programs in Tamil Nadu. The study was conducted in Tamil Nadu from February 2020 to September 2021 at Tamil Nadu Veterinary and Animal Sciences University, India. Primary data was collected from the selected sample of 23 extension centres using structured questionnaire in google form and secondary data was collected from the Directorate of Extension Education, TANUVAS for the period of 2017 to 2019. Descriptive statistics (frequency, percentage, chi-square and Mann-Whitney U test) were used to analyze the data. The results revealed that better staff availability in the centre and higher proportion of off-campus programs significantly influenced the inclusiveness of marginalised sections in overall extension programmes. Furthermore, improving transport facilities through mobility innovations such as pooling of transport and hiring models during on-campus programmes may facilitate better participation / inclusion level of marginalised sections.

Contribution of economic and nutritional context to overweight/obesity dynamics in Indian women from 1998 to 2016: a multilevel analysis of national survey data

BackgroundOverweight/obesity increased dramatically among Indian women since 2000. We evaluated the independent contributions of economic and nutrition context to the changing distribution of overweight/obesity among women from 1998 to 2016...

Pattern of Development Spending and Its Impact on Human Development Index and Gross State Domestic Product in Low-income States in India

The paper empirically examines the pattern and impact of development spending (DS) on human development index (HDI) and gross state domestic product (GSDP) in the low-income states (LIS), for the period of 1993–94 to 2014–15 for seven LIS states. Further analysing the sectoral impact of DS, panel unit root test and co-integration test were performed to analyse stationarity and panel long-run association among DS, GSDP and HDI. The paper finds that the share of DS in recent years for LIS is higher than the major states (MS), implying emphasis on social sector development. It also highlights the lagging behind a few LIS such as Uttar Pradesh, Jharkhand and Rajasthan. The paper sheds light on the long-run co-integrating relationship among DS, HDI and GSDP. It finds that the DS has a significant and positive influence on GSDP but not on HDI in the long run. Sector-specific analysis suggests a long-run equilibrium relationship between DS and all three sectors of economy. Though the coefficient of DS did not emerge to be significant for the HDI indicator, sector-specific analysis suggests that increased health spending is associated with better health outcomes. Prioritising on education, health and skill development, and other DS will help in economic advancement. Proper implementation of schemes may bring change in HDI outcomes.