The Singapore Economic Review

This paper examines the evolution of inequality, poverty and welfare in the South Caucasian Asian states, using an aggregate index based on consumer durables available to the households. Instead of using principal components analysis to aggregate asset indicators into an overall asset index, we propose an ordinal approach to using data on assets, when estimating the wealth of a household (or individual). Using three different approaches (the concept of order of acquisition of durable goods, item response theory and correspondence analysis), we first derive the order of importance of the different assets. Then, we compute indices introduced recently to measure inequality, poverty and achievement, when only ordinal variables are available. Our empirical analysis, based on data collected by the Caucasus Barometer and covering the three states in South Caucasus shows that there exists such an order, that it does not really depend on the statistical approach adopted and that it was very similar in 2009 and 2013. Our results show that among the three countries analyzed, Armenia had the lowest degree of inequality in asset ownership and Georgia the highest. Whatever the approach or index used, ordinal inequality, increased in Armenia and Azerbaijan between 2009 and 2013, but slightly decreased during that period in Georgia. It also appears that poverty decreased in all three countries during this period. There was also important growth, when measuring the latter via the welfare index recently introduced by (), assuming their parameter $\alpha \to 1$.

A society is composed of different socio-economic groups. At a given time, individuals in the society can be classified into different such groups. With the change of time, individuals can move across different groups. Social mobility is viewed as an aggregation of such individual movements across different socio-economic groups. We develop a simple analytic framework to discuss the issue of social mobility, and derive a class of measures for social mobility. A prominent member of this class is the Bartholomew measure that has often been used in applied work. We apply our framework and the theoretical results to the Chinese society by investigating its income mobility for the period between 1989 and 2011. We find an increasing trend in income mobility in 1990s and a drop in the middle and the late of 2000s. By decomposing total mobility into subgroups and into movements, we find that the lowest income group and one/two-step moves make the largest contribution in total mobility.

The decline in the share of labor income — an indicator of functional income distribution — has contributed to rising income inequality world-wide. Despite a growing literature, little is known about the effects of globalization on the labor share or inequality in Asia where some of the economies are most globalized. Applying fixed-effect regressions to panel data from 29 Asian economies over the period from 1980 to 2014, we focus on the impacts of globalization on the labor share in Asia where globalization is measured by trade openness and FDI. The modeling results show that trade openness is a significant determinant of the labor share. More specifically, the impact of export is significantly negative and the impact of import is positive. In terms of FDI, the coefficient of the inward FDI is significantly positive and that of the outward FDI is significantly negative in developing countries only.

This paper represents an early attempt to investigate the growth and distributional effects of Fintech development, using household survey data from China. China’s rapid expansion of Fintech in the past decade has significantly improved the accessibility and affordability of financial services, particularly for formerly financially excluded population groups. Linking the index of digital financial inclusion with China Family Panel Studies (CFPS) data, we find that Fintech development is positively correlated with household income, and the positive effect is larger for rural households than the urban counterpart, suggesting that Fintech development has helped narrow the urban–rural income gap. Moreover, the poor gain more than the rich from Fintech development in rural China, indicating its benign distributive impacts within rural China.

This paper attempts to explain why China performed better than India in reducing poverty. As two of the most populous countries in the world, China and India have both experienced fast economic growth and high inequality in the past four decades. Conversely, China adopted a more export-oriented development strategy, resulting in faster industrialization or urbanization and deeper globalization, than India. Consequently, to conduct the comparative study, we first decompose poverty changes into a growth and an inequality components, assessing the relative importance of growth versus distributional changes on poverty in China and India. Then, Chinese data are used to estimate the impacts of industrialization, urbanization and globalization on poverty reduction in rural China. The major conclusion of this comparative study is that developing countries must prioritize employment generation in secondary and tertiary industries through industrialization and globalization in order to absorb surplus agricultural labor, helping reduce poverty in the rural areas.

Since 2010, China’s miraculous growth has come to a halt and has shown steady deceleration. To re-accelerate economic growth, stimulating domestic consumption is a crucial way with fighting poverty as the key step. This paper attempts to explore the impact of poverty on resident consumption in China over the last four decades. Based on provincial data, we first simulate income distribution at the individual level and provide moderate poverty profiles at the provincial level. The empirical analyses are then conducted to gauge the poverty impacts using the estimated poverty index. Results show that (1) moderate poverty has decreased sharply in China, with the best achievement in Beijing, Shanghai and Guangdong; (2) moderate poverty exerts a significantly negative impact on resident consumption; and (3) when poverty increases, resident consumption on household equipment decreases the most, while resident consumption on food, transportation, and telecommunication decreases the least.

Poverty is an interlacement of income distribution below a threshold value and inequality within that boundary. To unthread the fabric of poverty and understand the dimensions of impoverishment below and around the poverty line, a deeper examination of different facets of deprived and starving households is required. This paper attempts to provide an additional tool in monitoring poverty reduction by computing density ratio and decile density trends by applying Kernel density function for the consumer expenditure distribution from the 55th (), 61st (), 66th () and 68th () quinquennial rounds. The progressive Indian state Kerala has exhibited a higher density ratio with the poverty tail flattening when compared with the backward State Bihar. The ways and means to succeed in reaching the end of the sea of hardship in Bihar are explored keeping in view some of the most impressive achievements of Kerala, a developed Indian state.

We present cross-country evidence suggesting that agricultural credits have a positive impact on agricultural productivity. In particular, we find that doubling agricultural credits generates around 4–5% increase in agricultural productivity. We use two different agricultural production measures: (i) the agricultural component of GDP and (ii) agricultural labor productivity. Employing a combination of panel-data and instrumental-variable methods, we show that agricultural credits operate mostly on the agricultural component of GDP in developing countries and agricultural labor productivity in developed countries. This suggests that the nature of the relationship between agricultural finance and agricultural output changes along the development path. We conjecture that the development of the agricultural finance system generates entry into the agricultural labor market, which pushes up the agricultural component of GDP and keeps down agricultural labor productivity in developing countries; while, in developed countries, it leads to labor-augmenting increase in agricultural production. We argue that replacement of the informal credit channel with formal and advanced agricultural credit markets along the development path is the main force driving the labor market response.

The mismatch between a laborer’s abilities and the goals set forth by a training program is one of the most pressing concerns for a labor training program. This paper looks at the incentives for a laborer to enter a rural labor training program and demonstrates a clear method of analyzing the participation issues using instrumental regressions on the data collected from a case study a “poverty city” in the Zhejiang province, China. This paper shows that a pre-program wage drop may induce workers of a higher caliber to enter the training program and cause a “cream-skimming” effect on its outcome because of the S-shaped labor supply curve for the rural population who live in poverty. The result of the cream-skimming effect enhances the traditional view that a pre-program wage drop may reduce “opportunity cost” to enter a training program. This extension can be handy to revise future designs of rural labor training programs.

Similar to the hukou system in China, the household registration system () in Vietnam which represents the citizenship of its people has become a part of the Vietnamese society in the past 60 years. After the economic reform in 1986, the force of system has begun to wane; however, it still plays an essential role in everyday life of Vietnamese. Utilizing the new Household Registration Study (HRS) survey conducted by the World Bank in 2015, this paper employs Instrumental Variables (IV) to estimate the effect of citizenship (household registration status) on migrant workers in urban Vietnam. The main findings detect a pattern of discrimination against temporary residents in term of labor wages, which is different from the result of OLS estimation in the World Bank report.

Persistent socioeconomic inequalities in a society reduce the chances of employment for its weaker sections. In India, those most affected by inequality and discrimination are women, people of lower castes, rural households and illiterate people. This necessitates an analysis of the levels of discrimination and favoritism working against female, lower caste, rural and illiterate individuals in different manufacturing industries. This study presents an in-depth picture of employment in each industry with regard to the four variables selected — gender, caste, location and education. Fourth (2013–2014) and fifth (2015–2016) annual Employment and Unemployment Surveys have been used for the analysis.