Emerging Challenges in Rural Non-Farm Sector and Inequality in Rural India

Purpose: This paper highlights the changing patterns of income diversification and the effects of various socio-economic factors influencing the non-farm (NF) income of rural households in India. The study also explores the inequality effects of the non-farm earnings of the households by using the Fields inequality decomposition. Method: The study compares and evaluates the determinants and trends of inequality in 2004-2005 and 2011-2012 in the NF sector. It uses nationally representative data from two rounds of the Indian Household Development Survey (IHDS), which includes a panel of 36,278 households at all levels in India. The Censored Least Absolute Deviation (CLAD) model is used to estimate household determinants for non-farm income. The Fields decomposition decomposes total income inequality by considering the socio-economic factors. Results: The study finds that variations in non-farm earnings have increased. Field's Income Inequality Decomposition estimates show that income inequalities between households are significantly high due to factors such as education, level of the household head, land ownership, and population density, but also appear to be declining in 2011-12. Also, the earning gaps based on gender, age, and geographical zones have increased. Implications: Overall, the non-farm income during the studied period was observed to be biased towards the better-off households. However, it opened up opportunities for underprivileged households as well. The non-farm sector has huge potential in augmenting incomes for unprivileged rural households. Therefore, the government should pay attention to this sector as a means of reducing income inequality and alleviating poverty.

865The dynamics of SES-related health inequality across the lifecycle and the role of selective mortality

Background The positive cross-sectional association between health and SES often strengthens at younger ages before peaking at middle ages and then weakening at older ages. Selective mortality is a possible reason for the weakening relationship at older ages but current evidence for this is limited. Methods This paper uncovers the changing nature of the inter-dependence between SES and health over the lifecycle by further developing and applying longitudinal inequality decomposition techniques which account for mortality. We examine changes in SES-related health inequality for rolling age cohorts by gender for Australia (using the Household, Income and Labour Dynamics in Australia (HILDA) survey) and the United Kingdom (using the Understanding Society survey). Results We find for young men in both countries that the simultaneous co-movement in both health and income plays the major role in increasing health inequalities. At middle ages the poor start to lose health more quickly than the rich but at older ages selective mortality plays the major role with the poor more likely to die than the rich which also has an indirect effect of making morbidity losses seem less concentrated among the poor. Conclusions Selective mortality plays a major role in weakening the relationship between SES and health at older ages. Past studies have missed identifying the full effect of selective mortality. Key messages SES-related health inequalities accumulate throughout the lifecycle, even in older ages.

Income Inequalities among Earners Engaged in Selected Occupations and Professions in Pakistan

The current study investigates income inequalitiesamong earners engaged in different occupationsand professions in Pakistan using HIES data for 2010-11 and2015-16, focusing on their yearly income. Income equation anddifferences of income between subgroups of the population areestimated by using the OLS method. The generalized Entropy(GE) Class method is employed to evaluate the contribution ofdifferent subgroups of household characteristics and differentincome sources in overall inequality. The regression-baseddecomposition method is used to assess decompose changes inincome inequality by various socio-economic factors. OLSestimates conclude that all variables play a significant role inexplaining the differences in income. All indices of GE methodindicate that inequality within the group is a greater problemthan inequality experiences between groups. The decompositionmethod shows a positive sign of inequality decomposition for mosthousehold characteristics and income sources which depicts thatthese determinants have greatly contributed to overall incomeinequality.

Increased inequalities of per capita CO2 emissions in China

Designing inter-regional and inter-provincial responsibility-sharing mechanisms for climate change mitigation requires the knowledge of carbon distributions. This study is the first to use a two-sector (i.e., productive and household sectors) inequality decomposition approach to examine the regional, provincial, and national inequalities of per capita CO2 emissions (CPC) in China, as well as their determinants. We show that the CPC inequality index in China increased from 1.1364 in 2000 to 2.3688 in 2017, with the productive sector accounting for 91.42% of this expansion and households responsible for the rest. The production-side per capita output level, energy efficiency, energy structure, and industrial structure explain 69.01%, 12.81%, 5.57%, and 4.03% of these inequalities, respectively. Further, the household per capita energy consumption and energy structure explain only 8.12% and 0.46%, respectively. Therefore, future responsibility-sharing mechanisms for climate mitigation need to be formulated taking mainly the productive sector into account.

International Remittances, Domestic Remittances, and Income Inequality in the Dominican Republic

Inequality decomposition techniques are used to analyze the different impacts of domestic and international remittances on household income inequality in the Dominican Republic. This analysis highlights the importance of the distinction between domestic and international remittances as drivers of inequality as well as the importance of identifying and quantifying the determinants of remittances and their subsequent impact on inequality. Domestic remittances are found to be more equalizing than international remittances. Education leads to lower domestic remittances and higher international remittances, reflecting the role of education in promoting international versus domestic migration. Schooling increases inequality through domestic remittances and decreases inequality through international remittances.

The Effect of Income Inequality on Happiness Inequality in India: A Recentered Influence Function Regression Estimation and Life Satisfaction Inequality Decomposition

It is now an accepted stylised fact that increase in happiness level in any country is not commensurate with growth in income, a puzzle known as Easterlin Paradox. This paper analyses the income-happiness relationship in India and tries to explain the flat happiness response to income change in terms of rising income inequality. Income growth propels inequality and so also inequality in well-being. Empirically the effects of income inequality, absolute income, relative income, rank position and social capital indices are analysed using World Value Survey data for 12 states of India over 24 years from 1990 to 2014. As the variation in the 10-point scale measure of life satisfaction level is narrow, an recentered influence function (RIF) regression of variance and Gini of life satisfaction are estimated. The life satisfaction inequality is decomposed into composition and coefficients effects using Blinder–Oaxaca (B–O) decomposition method. The estimated RIF coefficients reveal significant effects on life satisfaction inequality of various income measures and social capital indices. The B–O decomposition shows that the functional relationship between material aspirations and life satisfaction, contribute significantly to rising life satisfaction inequality relative to changes over time in happiness influencing factors. Reducing income inequality and improving trust, sociability, health, education and employment over time and space could reduce life satisfaction inequality and improve happiness level in India.

Research on Property Income Inequality Effect of Fiscal Finance

“Creating conditions for more people to have property income” has become a national policy after the 17th National Congress of the Communist Party of China. Based on the micro survey data from Chinese Family Panel Studies (CFPS) in 2010, 2012, 2014, 2016 and the macro panel data at the provincial level, a logarithmic linear equation was built to estimate the impact of micro and macro factors on property income. Furthermore, the contribution of fiscal expenditure and financial development on property income equality can be recognized using the regression-based inequality decomposition method. This research revealed that fiscal expenditure improves residents’ property income and slightly reduces the inequality of property income distribution. With respect to financial development, it improves residents’ property income but aggravates the inequality of property income distribution. However, there is a significant difference between the different regions. In eastern and central regions, inequality of property income distribution greatly benefits from fiscal expenditure, while in northwest regions, fiscal expenditure makes property income inequality even worse. Therefore, the focus of financial sustainable development is to reduce property income inequality through the establishment of an effective government and the improvement of the rule of laws.