Major Indian States Research Articles

An Economic Analysis on Indian Scenario of Coconut Production: Trends and Prospects

The purpose of this study is to examine the coconut sector’s growth performance and instability in the Indian context. Since India is the world’s biggest producer of coconuts (22.96 billion nuts), Kerala, Tamil Nadu, Karnataka, and Andhra Pradesh are the states in the country where coconut trees are widely farmed and produced in huge quantities. These states account for over 90 per cent of overall production in the country and contribute around 89 percent of the total land for coconut farming. Area, production, and yield of coconut were collected from CDB based on secondary data from 1985-86 to 2020-21. The study period was divided into pre-TMC (1985-86 to 2000-01) and post-TMC (2001-02 to 2020-21). The study examines growth patterns using the compound growth rate, measures instability using the Coppock’s instability index, and investigates the role of area and yield on production using decomposition analysis. The results revealed that growth of area, production and productivity for major states in India was positive and statistically significant during the period II (post-TMC period) than the period I (pre-TMC period) except area under Kerala (-1.23%). Tamil Nadu and Karnataka reported a high level of instability in coconut production and its productivity during period II. Decomposition analysis shows that the area effect and yield effect play a crucial role in the total change of coconut production among the selected states. But area effect has negative in Kerala, which depicts that area expansion in coconut cultivation is merely nominal for other crops in the state. Hence, greater attention needs to be given to the states where to attract and encourage many new farmers into coconut cultivation by accessing modern technology, quality inputs, marketing and credit facilities under TMC by support of government, CBD and stakeholder.

Public Finance Management in India in the Time of COVID-19 Pandemic

Due to the COVID-19 pandemic, public finance management (PFM) in the FY 2020–2021 and 2021–2022 have become extremely challenging. The economic contraction has created pressures on PFM in India in terms of lower revenue mobilisation and higher expenditure needs. Both the union and state governments are facing dual problem of arresting economic contraction and managing public finance with limited resources. The present article analyses public finance management of the union as well as 16 major Indian states during the time of COVID-19 pandemic. For comparison, we have also analysed pre-COVID public finance monthly data of state governments. The shock to PFM came from both the revenue as well as expenditure side. Apart from aggregate analysis of state finances of 16 major states, we present state-wise analysis to highlight measures adopted by states to deal with the unprecedented fiscal crisis. JEL Codes: H20, H61, H62, H63

RURAL- URBAN DIFFERENCES IN HEALTH OUTCOMES IN INDIA: AN INTER STATE ANALYSIS

The present paper provides an overview of rural- urban differences in health outcomes. The study explained the relevance of rural urban variations and deal with the determinants of rural - urban health variation. It tried attempting to examine the rural-urban Differentials across the major states of India. To investigate the rural -urban Differentials for this purpose, Twenty States have been considered. This analysis has been restricted only within child health, therefore only IMR has been taken into account. The study deals with the rural - urban trend in IMR and made a composite index of Health Determinants on the basis of health outcomes variables, by using the principal component analysis for major twenty states of India. It is quite evident that in case of IMAL, there exists much difference between the rural and urban areas in almost all the states. The states which have done well in urban areas have also performed well in rural areas. For the southern states namely Kerala, Karnataka, Tamil Nadu and Andhra Pradesh have really done well in IMHC, Goa’s performance in this index is also very commendable. As usual, EAG states lag behind the other states in IMHC in both rural and urban areas. KEYWORDS: Rural Urban Health, IMR and Rural Urban variation in Socio-economic variables of health outcome.

The Growth Volatility Relationship: A Spatial Panel Analysis of the States of India

The impressive growth rate of the Indian economy and the subsequent signs of slowdown in the last few years have warranted the need to revisit the issue of determinants of growth. While most of the studies on economic growth in India focus on the demand and supply factors, which determine the growth rate, volatility as a major determinant of long-run growth (Kydland & Prescott, 1982, Econometrica: Journal of the Econometric Society, 1345–1370) has been ignored by most researchers. The present study attempts to fill the gap using data from 17 major states of India in a spatial panel data framework for the period 1995–2015. The results of empirical analysis clearly reveal that a significant and inverse relationship exists between volatility and growth in India. Also, the significant spatial effects in the growth regressions, highlight the importance of the role played by spillovers from adjoining areas, in the growth process. The results clearly highlight the important role that countercyclical policies can play in improving the growth rate of India.

Assessing socioeconomic inequalities in cognitive impairment among older adults: a study based on a cross-sectional survey in India

BackgroundThe rapidly aging population is a major concern for countries, especially where cognitive health in older age is poor. The study examined the socioeconomic and health-related factors associated with cognitive impairment among older adults and the contribution of those factors to the concentration of low cognitive functioning among older adults from economically poor households.MethodsData this study were derived from the “Building Knowledge Base on Population Ageing in India” (BKPAI) survey, which was carried out in seven major states of India. The effective sample size for the analysis was 9176 older adults aged 60 years and above. Results from descriptive and bivariate analysis were reported in the initial stage. Multivariable logistic regression analysis was conducted to explore the associations. Additionally, the concentration index and concentration curve were used to measure socioeconomic inequality in cognitive impairment among older adults. Wagstaff decomposition was employed to explore the key contributors in the concentration index.ResultsNearly 60% of older adults suffered from cognitive impairment in the study. The likelihood of cognitive impairment were higher among older adults with a low level of self-perceived income sufficiency [coefficient: 0.29; confidence interval (CI): 0.07- 0.52] compared to older adults with higher levels of perceived income status. Older adults with more than 10 years of schooling were less likely to be cognitively impaired [coefficient: -1.27; CI: − 1.50- -1.04] in comparison to those with no education. Cognitive impairment was concentrated among older adults from households with the lowest wealth quintile (concentration index (CCI): − 0.10: p < 0.05). Educational status explained 44.6% of socioeconomic inequality, followed by 31.8% by wealth status and 11.5% by psychological health. Apart from these factors, difficulty in instrumental activities of daily living (3.7%), caste (3.7%), and perceived income sufficiency to fulfil basic needs (3.0%) explained socioeconomic inequality in cognitive impairment among older adults.ConclusionsFindings suggest that older adults with lower perceived income, lower levels of education, poor physical and mental health, and poor physical and social resources were more likely to be cognitively impaired. Education, wealth and psychological health are major contributors in socioeconomic inequality in late-life cognitive impairment, which may be target areas in future policy formulation to reduce the inequality in cognitive impairment in older Indian adults.

What should government prioritize for the upliftment of the poor in India: access to credit or economic growth?

ABSTRACT The present work provides a comprehensive analysis of the effect of two prominent channels of financial-sector development (FSD)—economic growth and access to credit—on the poor in India. Employing panel data analysis for a sample of 15 major Indian states for the period 1999–2000 to 2011–2012, we provide empirical evidence for the effect of the two channels of FSD on poverty ratio, poverty gap ratio, and squared poverty gap in India. The results indicate that while access to credit and growth have reduced poverty and poverty gap in India, it has disproportionately benefitted the population living closer to the poverty line resulting in increased inequality among the poor. Further, while bank credit has a greater beneficial effect on the poor, it also has a greater detrimental effect on the poorest of the poor. The robustness check confirms the validity of the obtained results.

Determinants of patients' delay with disability in the diagnosed leprosy cases in the three major states of India: A case-control study.

Skin lesions are the most common early symptoms of leprosy, often ignored by patients at an early stage and misdiagnosed as other dermatological diseases by healthcare personnel, leading to delay in diagnosis and treatment of leprosy precipitating permanent neurological deficit, deformities and serious disabilities. The objective is to evaluate the duration of delay and factors responsible for the delay in reporting of patients, among the newly detected leprosy cases (Grade 1 and Grade 2 disability patients). A case-control study was conducted during 2014-2016 in three major states of India (Delhi, Gujarat and West Bengal) in 140 randomly recruited newly registered adult leprosy patients (aged 18 years and above) with Grade 2/1 disabilities (cases) and 140 Grade 0 disability patients (controls) in each of these Indian states. It is established that the major contributors for the delay in the early diagnosis of leprosy have been patient-related factors. The median patient delay in the three states of Delhi, Gujarat and West Bengal were five months (0.7-1.8), 2.8 months (2-14) and 12 months (2-24), respectively. The study design is case-control and has an inbuilt reporting bias due to the retrospective nature of data collection but the data collection was carried with caution to reduce the recall bias. As the study is carried out in three states, generalisation of interpretation was cautiously executed. The matching ratio of cases and controls was 1:1 in this study, but we could not increase the controls due to operational feasibility during the conduct of the study. Patient delay is a crucial factor responsible for the disability among new leprosy cases. A higher patient delay in these three states reflects that the community is not aware about the signs and symptoms of leprosy. Reducing patient delay is very important for reducing disabilities in the newly diagnosed cases.

Prevalence and risk factors of fall-related injury among older adults in India: evidence from a cross-sectional observational study

BackgroundFalls and related injuries in older ages have become a major public health problem. This study aims to identify the prevalence of self-reported fall-related injury and to describe risk factors associated with fall-related injury among older adults in India.MethodThe study used data from the "Building Knowledge Base on Population Ageing in India" (BKPAI), which was carried out in seven major states in India (2011). Bivariate and multivariable logistic regression analyses were conducted to examine the prevalence and risk factors of fall-related injury among older people.ResultsThe study found that 3.6% of older adults had a fall-related injury. Older adults with walk difficulty had a significantly higher likelihood of reporting fall-related injuries in comparison to their counterparts [adjusted odds ratio (AOR):1.80; confidence interval (CI): 1.38–2.36]. Older adults who consumed alcohol had significantly higher odds of reporting fall-related injuries than those who did not consume alcohol [AOR: 1.97; CI: 1.31–2.97]. Poor self-rated health was another risk factor for fall-related injury [AOR: 1.24; CI: 1.05–1.61]. Further, older adults with dementia were 2.15 times significantly more likely to report fall-related injuries than older adults with no dementia [AOR: 2.15; CI: 1.03–5.05]. Also, older women compared to men were 98% significantly more likely to report fall-related injury [AOR: 1.98; CI: 1.43–2.75]. The odds of reporting fall-related injury was significantly higher among those who had a secondary level education compared to those with no education [AOR: 1.44; CI: 1.01–2.06].ConclusionsWalking disabilities, alcohol consumption, poor self-rated health, dementia, and female gender were found to be the risk factors for fall-related injury among older adults. The results highlight the importance of improving physical as well as mental health of older individuals including dementia in terms of reducing the risk of experiencing fall-related injury.

Determinants of Financial Inclusion of Rural Agricultural Households in India

Using nationally representative survey data from 21,648 rural agricultural households, the current study investigates the financial inclusion level among distinct social groups across the major Indian States. The results show that 18.49 per cent of rural agricultural households have no access to formal institutions. Rural agriculture households are more financially included from the banks (78.37 per cent) compared to the post offices (15.39 per cent). Findings further exhibit the low level of financial inclusion and prevailing inequality for financial access among socially disadvantaged groups. Open category agricultural households show a relatively high financial inclusion level compared to socially disadvantaged groups. A logistic regression model is applied to examine the factors influencing the degree of financial inclusion of rural agricultural households, which reveals some interesting facts. The level of financial inclusion from banks and post offices increases with education level, size of landholdings, age, and households belonging to the open category, among others. Further, the chances are high for financial inclusion of men, while the presence of post office increases the probability of financial inclusion of women.

Financial Inclusion through Self Help Groups – An Economic Catalyst to transform Rural India

This study attempted to create a comprehensive measure of Financial Inclusion (FI) with specific focus on SHGs among 33 major states in India from the period of 2016 to 2020. Principal Component Analysis was employed to track the status of inclusion in Indian financial sector. The link between FI and development indicators like agricultural and industrial growth, access to basic education was explored through Ordered Probit Random effect model using panel data. Results indicated that majority of Eastern and North Eastern states have poor FI, in addition Financial Inclusion Index (FII) showed a positive relation with agricultural growth

Technical efficiency of financial inclusion and human development: Insights from the Indian states

AbstractFinancial inclusion programs are used as a major economic development tool in emerging economies. Human development is the major determinant of financial inclusion, creating opportunities for people to better access financial services. The study's major aim is to examine the technical efficiency of financial inclusion of Indian states by Data Envelopment Analysis using human development as input. To achieve this objective, a 3‐dimensional Financial Inclusion Index (FII) is constructed for 28 major Indian states from 2010 to 2017. Empirical findings suggest most Indian states are under low and medium financial inclusion, and states with better human development have better FII status. Crucially, technical efficiency results reveal states with better human development perform better in terms of FII. The inconsistency in FII and human development ranks is majorly found in North‐eastern and high‐income Indian states. Therefore, policymakers in India should focus on promoting human development in low Human Development Index states.

A machine learning framework to quantify and assess the impact of COVID-19 on the power sector: An Indian context

As the COVID-19 continues to disrupt the global norms, there is the requirement of modeling frameworks to accurately assess and quantify the impact of the pandemic on the electricity sector and its emissions. In this study, we devise machine learning models to estimate the pandemic induced reduction in electricity consumption based on weather, econometrics, and social-distancing parameters for seven major Indian states. As per our baseline electricity consumption model, we find that the electricity consumption dropped by 15–33% in 2020 (March-May) during the complete lockdown phase, followed by 6–13% (June-August) during the unlock phases and gradually reached the norms by September 2020. As a result, the net CO2 emissions from power generation in 2020 dropped by 7% and 5% compared to 2018 and 2019 respectively. Amidst the ongoing second wave since mid-April 2021, we projected the electricity consumption across states from May-August by accounting for two scenarios. Under the reference and worst-case scenarios, the electricity consumption approximates 106% and 96% of the non-pandemic situation, respectively. The modeling framework developed in this study is purely data-orientated, cross-deployable across spatio-temporal scales and can serve as a valuable tool to inform current and future energy policies amidst and post COVID-19.

The prevalence and risk factors of hypertension among adult population of four major states in India: An exploratory study

Hypertension is one of the major non-communicable lifestyle disorders which has taken the form of modern-day epidemic affecting almost two times in 2019 than in 1990. Hypertension is also a major important risk factor for the occurrence of ischemic heart diseases and stroke in later life which stands to be the most important cause of morbidity and mortality according to the Global Burden of Disease studies. The incidence of hypertension in an individual depends on multiple inter related and unrelated factors which leads to the structural changes of the blood vessels and increases the turbulence of flow of blood and in the end leads to hypertension. Though there have been a number of studies done to find out the associations of different risk factors with the incidence of hypertension, they were focused upon the affect of those risk factors as a whole and not on specific adult age group. This study tried to shed some light on the different risk factors which specifically affect the men and women in reproductive age 30 years and more and give recommendations about factors on which special attention is needed to be given to prevent them. The National Family Health Survey 4 (NFHS-4) was conducted countrywide in 2015-16 among men and women of 15-54 years and 15-49 years respectively. The unit level data was used in this study to find prevalence of hypertension of men (30-54 age group) and women 30-49 age years for the four major states of Delhi (North), Odisha (East), Kerala (South), Maharashtra (West) and also analysed association with various socio demographic and others related variables using standard statistical tools of SPSS 23 and MS EXCEL.The most important factors leading to occurrence of hypertension in an individual of 30 years or more were found to be age, smoking and alcoholism, diabetes and unhealthy diet. But some socio and economic factors having an indirect association with prevention of hypertension were found to be female literacy and insurance coverage. The health seeking behaviour of hypertensives and the screening of people for hypertension were also not found up to the mark. Hypertension is preventable and treatable by proper lifestyle modification and medication. The screening of the adult population of 30 years and more needs to be strengthened, advocacy against smoking and alcoholism, stress management, and penetration of health insurance coverage needs to be increased.

In Search of the Determinants of Dairy Production in an Emerging Market

In view of the growing importance of the dairy sector, especially for the livelihood of the rural population and the increasing demand for milk by the Indian population, higher yield of milk animals and milk availability have become the focal point of attention. This study aims to identify the determinants of dairy production in India by examining the relationship of crossbreed and buffalo populations with the quantity of milk production across different Indian states. Fifteen major Indian states were included in this study and relevant secondary data from 2001 to 2019 was taken for analysis. The sources of statistical data are BAHS (GOI), Statistical abstract, NDDB website, etc. Coarse cereal, fodder crops, grazing land, artificial insemination and veterinary services have an influence on the total milk production of the Indian states, and the significance of these impacts were tested by pooled OLS regression analysis. Crossbreed cows, indigenous cows, buffalo and goat populations were tested with the Spearman’s rho correlation test, and these variables were also found to have a positive correlation with the quantity of total milk production (TMP). The study was further extended to compare the population strength of the crossbreed and buffalo, their growth rate and ultimately the status of average milk production across the major Indian states during the period 2001 to 2019. Uttar Pradesh, Rajasthan, Gujarat, Punjab and Andhra Pradesh were found to have healthy production of milk. However, Bihar and Rajasthan were found as promising states. States like Orissa, Kerala, Uttarakhand and West Bengal were found to have certain points of concern.

CHANGING PATTERN OF INTER-STATES IN-MIGRATION TO WEST BENGAL: CENSUS 2001-2011

This paper attempts to understand the pattern of the change of in-migration to West Bengal from different states of India. Inter-state migration flow to West Bengal is an old and essential phenomenon from the times of pre-independence periods. The total population of West Bengal in 2001 was about 80 million, and in 2011 the population increased to 91million persons. During the same period, it is observed that total in-migrants declined slightly from 2.45 million persons in 2001 to 2.38 million persons. The Study's objective is to examine the pattern of inter-state in-migration to West Bengal during 2001-2011 censuses and analyze the reasons and duration of stay of in-migration by the age-sex groups. The primary source of the Study is the census of India 2001 and 2011 (D2 &amp; D5 Tables) based on place of last residence (POLR). The analysis includes computation of rate, ratio, and the result are shown by graphs and maps using ArchMap10.3.1 software. Significant findings include changing the pattern of inter-state in-migration by POLR between North 24 Parganas and Kolkata, indicating a flow decline pattern. The top ten major states in India send enormous numbers of migrants (94.33% in 2001 and 94.30% in 2011), the working-age groups have quite diminished as in-migrants in the past ten years. Bihar and Jharkhand sent the most prominent migrants to West Bengal. The Study feels that to attract the migrants again back, West Bengal would require a new regional developmental strategy to regain its old status as one important destination for in-migrants.

Diversity in food consumption: Evidences from urban Kerala

Food is fundamental to human survival and it appears to be the first item of the family budget allocation of all irrespective of class to which they belong. Kerala ranks top among the major States of India in the MPCE on food in the post liberalized era. A perusal of NSS data exhibits that, MPCE of urban Kerala is ahead of the rural for the last few decades, however, a sharp decline is noted in the last decade (2001-2011). Along with an increase in MPCE on food, an increase in food diversity is being expected. The study probe into the extent of food diversity among different income strata of urban Kerala with the unit-level data from NSS 68 consumer expenditure survey. The findings indicate that the share of expenditure on cereal in total food expenditure is high in the low-income class and low in the high-income group. The state of Kerala has high food diversity across all income classes signals a better diet quality of people. It is revealed that food diversity is low in the high and low-income groups compared to middle-income group.

Geospatial Assessment of Flood-Tolerant Rice Varieties to Guide Climate Adaptation Strategies in India

Rice is the most important food crop. With the largest rain-fed lowland area in the world, flooding is considered as the most important abiotic stress to rice production in India. With climate change, it is expected that the frequency and severity of the floods will increase over the years. These changes will have a severe impact on the rain-fed agriculture production and livelihoods of millions of farmers in the flood affected region. There are numerous flood risk adaptation and mitigation options available for rain-fed agriculture in India. Procuring, maintaining and distributing the newly developed submergence-tolerant rice variety called Swarna-Sub1 could play an important role in minimizing the effect of flood on rice production. This paper assesses the quantity and cost of a flood-tolerant rice seed variety- Swarna-Sub1, that would be required during the main cropping season of rice i.e., kharif at a district level for 17 major Indian states. The need for SS1 seeds for rice production was assessed by developing a geospatial framework using remote sensing to map the suitability of SS1, to help stakeholders prepare better in managing the flood risks. Results indicate that districts of Bihar, West Bengal and Uttar Pradesh will require the highest amount of SS1 seeds for flood adaptation strategies. The total estimated seed requirement for these 17 states would cost around 370 crores INR, less than 0.01 percent of Indian central government’s budget allocation for agriculture sector.

The impact of income on public health and education expenditure: Evidence from the Indian states

In this study, we examine the long‐run impact of state‐level per capita income on public education expenditure and public health expenditure in 17 major Indian states over the period 1993–2017. To test for the existence of a unit root, we have employed the Zivot–Andrews test and the Clemente–Montañes–Reyes test, which allows for an endogenous structural break in the data series. These tests indicate that all variables are nonstationary. Autoregressive distributed lag model with one structural break is applied to find the cointegration of variables and estimate the cointegrating equation. The bounds test reveals the presence of a long‐run relationship between public health expenditure and per capita income in 12 out of 17 states, between public education expenditure and per capita income in 15 out of 17 states. The result shows that per capita income affects the public health and education expenditure of states. We find elasticities of public health expenditure and public education expenditure vary across states and are small in magnitude (less than one for most of the states). Our results suggest that public health and education expenditures are necessary goods. Based on the results, we also draw policy implications from our findings.

ELDERLY DEPENDENCY IN INDIA: FINDINGS FROM CENSUS DATA

The changing demographic profile resulting in ageing of population has thrown many new challenges in the social, economic and political domains in India due to the huge number of aged population. The economic support to the older persons is very much dependent upon the earning ability of the adults. The study mainly focuses on the quantum of dependency burden and assesses the dependency burden in relation to the prevailing economic situation. The old age dependency ratio (OADR) in India estimated as ratio of population 60+ to that of 15-59 years is found to be 0.14 and the old age economic dependency ratio (OAEDR) is much higher at 0.23. Both OADR and OAEDR is highest in Kerala followed by Punjab and Haryana among the major states in India. Elderly dependency is high in most of the states and the economy is not prepared to bear the burden. The Economic Dependency ratio is almost three times the total dependency when we add the number of non workers 15-59 years in the dependent group and eliminate non workers 15-59 years from the economically active group in India. The unemployment rates are found to be quite high in states where the elderly dependency burden is higher. Increased longevity demands higher savings rates to cater to the needs of the old-old group. So the benefit of having a large working age population remains to be tapped through creating more employment opportunities.

Inter-linkage between the health status and socio-economic life of Indian Elderly: An exploration based on 71st Round of NSS data

Like many other countries in the world, India is also in the process of major age-related structural changes with an acceleration of growth in its elderly populations. The present study focused on economic independence andliving arrangements and about how such factors shape perceived health status among the elderly. On the basis of the unit level data from the NSS 71 st Round taken for the 18 major Indian states, an attempt was made in this analysis to establish the inter-linkage between the perceived health status and the financial self-dependence along with aspects of filial status and the factor of co-residence. “Self-reported health status” has been used as a response variable in the present study. The perception of “Poor” health status was significantly reported more by the economically dependent elderly as compared to their independent counterparts, irrespective of their place of residence. The study found that when the elderly are co-residing with their spouse, psychologically they remain more satisfied and on such occasions fifty percent or more of them expressed their health status to be either excellent or good. It has also been empirically found that whenever the elderly lack financial autonomy, they are increasingly found to reveal poor health status may be because of feeling mentally distressed and are having low self-esteem.