Satis Devkota

Agricultural Productivity and Poverty Reduction in Nepal

This paper provides for the first time a clear quantitative link between agricultural productivity and poverty among rural households in Nepal. Using data from a nationwide Nepal Living Standard Survey 2004, we first estimate household‐specific productivity per worker under both Cobb–Douglas and translog production functions. Second, the paper identifies the determinants of productivity. Third, we explore a theoretical link between productivity and poverty using Sens poverty index and find empirically that productivity growth substantially helps poverty reduction. Finally, the integrated effects of changes in productivity determinants are found to be stronger than the outcomes of sectoral policies taken in isolation.

Socioeconomic gradients in early childhood health: evidence from Bangladesh and Nepal

BackgroundA large literature has developed researching the origins of socioeconomic gradients in child health in developed countries. Particularly, this research examines the age at which these gradient effects emerge and how they change across different stages of childhood. However, similar research on developing countries is limited.MethodsThis paper examines the socioeconomic gradients in early childhood health in two developing countries, Bangladesh and Nepal using the 2011 Demographic and Health Surveys. The paper separately studies two measures of household socioeconomic status: household wealth and maternal educational attainment. Two anthropometric measures of early childhood health, height-for-age and weight-for-age Z scores for 0–59 months of children, are used for our empirical exercise. The paper uses both non-parametric and multivariate ordinary least squares approaches to examine at what age socioeconomic disparities in health emerge, and investigates if these disparities increase with age in early childhood.ResultsThe paper provides significant evidence of age-specific socioeconomic gradients in early childhood health in both countries. Health disparities in household wealth exist in both countries. This disparity emerges in the first 11 months of life, and is particularly severe for children from the poorest quintile. On the other hand, while the emergence of maternal education gradients during the first 11 months is sensitive to the choice of childhood health measure, the study finds the children of mothers with higher education to enjoy significantly higher health outcomes in comparison to those with lower education. However, controlling for father’s education weakens the effects of maternal education on child health in both countries. Further, the paper does not find statistically significant evidence where socioeconomic gradients in health increase with age in early childhood.ConclusionsOur study concludes that socioeconomic disparities in health outcomes exist even in very early childhood in Bangladesh and Nepal. This has important implications for targeted policy interventions in the form of food security and nutrition supplement programs, free provision of health care, and maternal education in both countries.

What Factors Change Education Inequality in Nepal

Abstract We estimate indices of income-based inequality of education for Nepal using comprehensive survey data from 1996 and 2004. The 5% increase in the inequality that we obtain for those eight years is then decomposed into its contributing factors. Greater urbanization contributed substantially to the rise in education inequality. On the other hand, income significantly reduced education inequality because of a substantial increase in mean income during the eight years, and because of a fall in income inequality. This implies that an increase in the median income could reduce education disparity substantially.

How do income and education affect health inequality: evidence from four developing countries

Using household survey data from four countries ‒ Albania, Nepal, Tajikistan and Tanzania ‒ this article calculates income-related inequality in health care utilization. We measure health disparity separately for generally and chronically ill individuals by constructing two models: one for the probability of a visit to a physician and another for the number of visits. Following model-based measurements, we decompose inequality into two major parts: one accounted for by identity-related factors and another by socioeconomic and other factors such as education, geography and distance to a clinic. We propose a new method to quantify the effect of changes in income and education on health disparity. One of our important findings suggests that health disparity is pro-rich in all our sample countries. The pro-rich disparity is prevalent among generally ill as well as chronically ill patients, in both visit probability and visit frequency models. Health inequality seems primarily driven by income differences followed by nonidentity factors. Further, the principle of equal treatment for equal need is not fulfilled in any of our countries. Among policy implications, increasing average income and education in a way that also reduces disparity in income and education, respectively, will substantially shrink inequality in health care utilization.

Calculation and decomposition of income inequality in low- and middle-income countries: a survey data analysis

ABSTRACT This article estimates income inequality in a sample of four low- and middle-income (LMI) countries namely; Albania, Nepal, Tajikistan and Tanzania using the household survey data – Nepal Living Standard Measurement Survey Second. First, we estimate the income generation function for each country and calculate the income inequality using Gini index (GI). Second, we decompose the income Gini into the determinants of income generation functions. Based on the decomposition result, socio-economic factors are the most important determinants of income inequality followed by geographic factors. Demographic factors have the least effect on income inequality in all four countries. Third, we propose a new method to quantify the effect of change in each covariate of income generation function on income Gini. That allows us to quantify the effects of change in specific policy such as increase in investment in schooling or public health to specific group of the population in society on income inequality. A carefully chosen, integrated policy can significantly reduce inequality in all four countries under study.

How does education inequality respond to policy? A method and application to survey data from Albania and Nepal

Purpose - – The purpose of this paper is to measure inequality in education and examine how socioeconomic factors affect education inequality in Albania and Nepal. Design/methodology/approach - – Using large household survey data sets the authors calculate income-related inequality in education and decompose the inequality into factors that determine educational attainment. The decomposition procedure establishes the role played by two sets of factors: elasticities of education demand with respect to its determinants; and inequalities in those determinants. The paper then proposes a new mechanism to quantify the effects of policy simulations regarding income, urbanization, and distance to school on education inequality. Findings - – Both the countries show significant inequality in education. Educational attainment in Albania and Nepal is determined by socioeconomic, demographic and geographic factors of which three are particularly significant in affecting inequality – income, urbanization and distance to school. Research limitations/implications - – While schooling for most individuals is largely financed by public subsidy in the countries, attainment is also likely affected by the price of education services and cost of health care. Identification of those factors in the context of more comprehensive data will enable researchers in future to draw firmer conclusions. Practical implications - – The proposed method can help to identify cost-effective and sustainable policies to reduce socioeconomic inequality in education in developing countries. Social implications - – Reduction in education inequality can lead to higher income and better health which are instrumental in uplifting the poor in developing countries. Originality/value - – This is the first paper to measure education inequality using a concentration index and to propose a new mechanism to show the effect of simulated policies on education inequality.

Childhood Immunization and Access to Health Care: Evidence From Nepal.

This article examines the effect of access to health care center, in terms of travel time, on childhood immunization in Nepal using the 2004 and 2011 waves of the Nepal Living Standards Measurement Surveys. We employ probit and instrumental variable probit estimation methods to estimate the causal effect of travel time on the probability of immunization. Results indicate that travel time to the nearest health center displays a significant negative association with the probability of immunization (coefficient = −0.015, P < .05). Furthermore, the effect of travel time tends to be stronger in rural and distant areas of Nepal’s mountain and hill regions. The results suggest that policy interventions should increase the number of mobile clinics in rural villages and provide conditional cash transfer to incentivize immunization coverage at the household level. In addition, household income, parental education, ethnicity, and household location emerge as important determinants of immunization in Nepal.