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With referenc to India.

I exploit a natural experiment in Indian schools to study how being integrated with poor students affects the social behaviors and academic outcomes of rich students. Using administrative data, lab and field experiments to measure outcomes, I find that having poor classmates makes rich students (i) more prosocial, generous, and egalitarian; and (ii) less likely to discriminate against poor students, and more willing to socialize with them. These effects are driven by personal interactions between rich and poor students. In contrast, I find mixed but overall modest impacts on rich students’ academic achievement.

Study conducted among the children living in urban slums of twin cities of Hyderabad and Secunderabad, Andhra Pradesh, India.

The rural poor in developing countries, once economically isolated, are increasingly being connected to outside markets. Whether these new connections crowd out or encourage educational investment is a central question. We examine the effects on educational choices of 115,000 new roads built under India’s flagship road construction program. We find that children stay in school longer and perform better on standardized exams. Heterogeneity in treatment effects supports a standard human capital investment model: enrollment increases most when nearby labor markets offer high returns to education and least when they imply high opportunity costs of schooling.

Conventional models of clientelism often assume poor voters have little or no choice over which local broker to turn to for help. Yet communities in many clientelistic settings are marked by multiple brokers who compete for a following. Such competition makes client choices, and the preferences guiding such choices, pivotal in fueling broker support. We examine client preferences for a pervasive broker—slum leaders—in the context of urban India. To identify resident preferences for slum leaders, we conducted an ethnographically informed conjoint survey experiment with 2,199 residents across 110 slums in two Indian cities. Contra standard emphases on shared ethnicity, we find residents place heaviest weight on a broker's capability to make claims on the state. A survey of 629 slum leaders finds client-preferred traits distinguish brokers from residents. In highlighting processes of broker selection, and the client preferences that undergird them, we underscore the centrality of clients in shaping local brokerage environments.

Background Undernutrition among under five children in India is a major public health problem. Despite India’s growth in the economy, the child mortality rate due to undernutrition is still high in both urban and rural areas. Studies that focus on urban slums are scarce. Hence the present study was carried out to assess the prevalence and determinants of undernutrition in children under five in Maharashtra, India. Methods A community-based cross-sectional study was conducted in 16 randomly selected clusters in two districts of Maharashtra state, India. Data were collected through house to house survey by interviewing mothers of under five children. Total 2929 mothers and their 3671 under five children were covered. Multivariate logistic regression analysis was carried out to identify the determinants of child nutritional status seperately in urban and rural areas. Results The mean age of the children was 2.38 years (±SD 1.36) and mean age of mothers was 24.25 years (± SD 6.37). Overall prevalence of stunting among children under five was 45.9%, wasting was 17.1 and 35.4% children were underweight. Prevalence of wasting, stunting and underweight were more seen in an urban slum than a rural area. In the rural areas exclusive breast feeding ( p  < 0.001) and acute diarrhea ( p  = 0.001) were associated with wasting, children with birth order 2 or less than 2 were associated with stunting and exclusive breast feeding ( p  < 0.05) and low maternal education were associated with underweight. Whereas in the urban slums exclusive breast feeding ( p  < 0.05) was associated with wasting, sex of the child ( p  < 0.05) and type of family ( p  < 0.05) were associated with stunting,and low income of the family ( p  < 0.05) was associated with underweight. Conclusions Factors like sex of the child, birth order,exclusive breast feeding,economic status of the family, type of family,acute diarrhea and maternal education have influence on nutritional status of the child. Improvement of maternal education will improve the nutritional status of the child. Strategies are needed to improve the economic status of the community. Trial registration Trial registration number: CTRI/2017/12/010881 ; Registration date:14/12/2017. Retrospectively registered.

Background Mobile Health (mHealth) is becoming an important tool to improve health outcomes in maternal, newborn and child health (MNCH). Studies of mHealth interventions, have demonstrated their effectiveness in improving uptake of recommended maternal services such as antenatal visits. However, evidence of impact on maternal health outcomes is still limited. Methods A pseudo-randomized controlled trial (single blind) was conducted to assess the impact of a voice-message based maternal intervention on maternal health knowledge, attitudes, practices and outcomes over time: Pregnancy (baseline/Time 1); Post-partum (Time 2) and when the infant turned one year old (Time 3). Women assigned to the mMitra intervention arm received gestational age- and stage-based educational voice messages via mobile phone in Hindi and Marathi, while those assigned to the control group did not. Both groups received standard care. Results Two thousand sixteen women were enrolled. Interviews were conducted with 1516 women in the intervention group and 500 women in the control group at baseline and post-partum. The intervention group performed significantly better than controls on four maternal health practice indicators: receiving the tetanus toxoid injection (OR: 1.6, 95% Confidence Interval (CI): 1.05–2.4, p  = 0.028), consulting a doctor if spotting or bleeding (OR: 1.72, 95%CI: 1.07–2.75, p  = 0.025), saving money for delivery expenses (OR: 1.79, 95%CI: 1.38–2.33, p  = 0.0001), and delivering in hospital (OR: 2.5, 95%CI: 1.49–4.35, p  = 0.001). The control group performed significantly better than the intervention group on two practice indicators: resting regularly during pregnancy (OR: 0.7, 95%CI: 0.54–0.88, p  = 0.002) and having at-home deliveries attended by a skilled birth attendant (OR: 0.46, 95%CI: 0.23–0.91, p  = 0.027). Both groups’ knowledge improved from Time 1 to Time 2. Only one knowledge indicator, on seeking medical care during pregnancy, was statistically increased in the intervention group compared to controls. Anemia status at or near the time of delivery was unable to be assessed due to missing data from maternal health cards. Conclusions This study provides evidence that in low-resource settings, mobile voice messages providing tailored and timed information about pregnancy can positively impact maternal health care practices proven to improve maternal health outcomes. Additional research is needed to assess whether voice messaging can motivate behavior change better than text messaging, particularly in low literacy settings. Trial registration The mMitra impact evaluation is registered with ISRCTN under Registration # 88968111, assigned on 6 September 2018 (See https://www.isrctn.com/ISRCTN88968111 ).

GDP per capita and household survey means present conflicting pictures of the rate of economic development in emerging countries. One of the areas in which the national accounts–household surveys debate is key is the measurement of developing world poverty. We propose a data-driven method to assess the relative quality of GDP per capita and survey means by comparing them to the evolution of satellite-recorded nighttime lights. Our main assumption, which is robust to a variety of specification checks, is that the measurement error in nighttime lights is unrelated to the measurement errors in either national accounts or survey means. We obtain estimates of weights on national accounts and survey means in an optimal proxy for true income; these weights are very large for national accounts and very modest for survey means. We conclusively reject the null hypothesis that the optimal weight on surveys is greater than the optimal weight on national accounts, and we generally fail to reject the null hypothesis that the optimal weight on surveys is zero. Additionally, we provide evidence that national accounts are good indicators of desirable outcomes for the poor (such as longer life expectancy, better education and access to safe water), and we show that surveys appear to perform worse in developing countries that are richer and that are growing faster. Therefore, we interpret our results as providing support for estimates of world poverty that are based on national accounts.

Accumulation of human capital is indispensable to spur economic growth. If students fail to acquire needed skills, not only will they have a hard time finding high-wage employment in the future but the development of the economies in which they work may also stagnate owing to a shortage of human capital. The overall goal of this study is to try to understand if China is ready in terms of the education of its labour force to progress from middle-income to high-income country status. To achieve this goal, we seek to understand the share of the labour force that has attained at least some upper secondary schooling (upper secondary attainment) and to benchmark these educational attainment rates against the rates of the labour forces in other countries (e.g. high-income/OECD countries; a subset of G20 middle-income/BRICS countries). Using the sixth population census data, we are able to show that China's human capital is shockingly poor. In 2010, only 24 per cent of China's entire labour force (individuals aged 25–64) had ever attended upper secondary school. This rate is less than one-third of the average upper secondary attainment rate in OECD countries. China's overall upper secondary attainment rate and the attainment rate of its youngest workers (aged 25–34) is also the lowest of all the BRICS countries (with the exception of India for which data were not available). Our analysis also demonstrates that the statistics on upper secondary education reported by the Ministry of Education (MoE) are overestimated. In the paper, we document when MoE and census-based statistics diverge, and raise three possible policy-based reasons why officials may have begun to have an incentive to misreport in the mid-2000s. 人力资本积累是促进经济发展至关重要的因素。如果劳动力的人力资本不足, 不仅难以找到高收入的工作, 国家经济发展也会因此停滞。本研究的主要目的是通过衡量和比较中国和其他国家 (经合组织成员国等高收入国家以及二十国集团和金砖四国等中等收入国家) 劳动力的中等教育水平 (包含高中和职高), 来了解中国目前的劳动力教育水平是否能够支持中国经济从中等收入向高等收入迈进。我们利用第六次人口普查数据分析显示中国的人力资本水平极低。 2010 年中国只有24%的劳动力 (25 到 64 岁人口) 上过高中或职高, 不足经合组织成员国的三分之一。中国总体劳动力中上过高中或职高的比例和相对年轻的劳动力 (25 到 34 岁人口) 中上过高中或职高的比例也是在金砖四国当中最低的 (因数据缺失该比较不含印度)。我们的分析也指明中国教育部过高估计了劳动力中等教育的普及程度。本文也探索了人口普查数据和教育部统计数据之间出现差异的时间截点以及出现这种对劳动力教育程度过高估计的原因。

The study examines the relationship between growth–inequality–poverty (GIP) triangle and crime rate under the premises of inverted U-shaped Kuznets curve and pro-poor growth scenario in a panel of 16 diversified countries, over a period of 1990–2014. The study employed panel Generalized Method of Moments (GMM) estimator for robust inferences. The results show that there is (i) no/flat relationship between per capita income and crime rate; (ii) U-shaped relationship between poverty headcount and per capita income and (iii) inverted U-shaped relationship between income inequality and economic growth in a panel of selected countries. Income inequality and unemployment rate increases crime rate while trade openness supports to decrease crime rate. Crime rate substantially increases income inequality while health expenditures decrease poverty headcount ratio. Per capita income is influenced by high poverty incidence, whereas health expenditures and trade factor both amplify per capita income across countries. The results of pro-poor growth analysis show that though the crime rate decreases in the years 2000–2004 and 2010–2014, while the growth phase was anti-poor due to unequal distribution of income. Pro-poor education and health trickle down to the lower income strata group for the years 2010–2014, as education and health reforms considerably reduce crime rate during the time period.