Changing educational inequalities in india in the context of affirmative action

Indian society suffers from substantial inequalities in education, employment, and income based on caste and ethnicity. Compensatory or positive discrimination policies reserve 15% of the seats in institutions of higher education and state and central government jobs for people of the lowest caste, the Scheduled Caste; 7.5% of the seats are reserved for the Scheduled Tribe. These programs have been strengthened by improved enforcement and increased funding in the 1990s. This positive discrimination has also generated popular backlash and on-the-ground sabotage of the programs. This paper examines the changes in educational attainment between various social groups for a period of nearly 20 years to see whether educational inequalities have declined over time. We use data from a large national sample survey of over 100,000 households for each of the four survey years--1983, 1987-1988, 1993-1994, and 1999-2000--and focus on the educational attainment of children and young adults aged 6-29. Our results show a declining gap between dalits, adivasis, and others in the odds of completing primary school. Such improvement is not seen for Muslims, a minority group that does not benefit from affirmative action. We find little improvement in inequality at the college level. Further, we do not find evidence that upper-income groups, the so-called creamy layer of dalits and adivasis, disproportionately benefit from the affirmative action programs at the expense of their lower-income counterparts.     

Technological innovation and inequality in health

The effect of education on health has been increasing over the past several decades. We hypothesize that this increasing disparity is related to health-related technical progress: more-educated people are the first to take advantage of technological advances that improve health. We test this hypothesis using data on disease-specific mortality rates for 1980 and 1990, and cancer registry data for 1973–1993. We estimate education gradients in mortality using compulsory schooling as a measure of education. We then relate these gradients to two measures of health-related innovation: the number of active drug ingredients available to treat a disease, and the rate of change in mortality from that disease. We find that more-educated individuals have a greater survival advantage in those diseases for which there has been more health-related technological progress.     

Demographic Differentials and Demographic Integration of Turkish and Kurdish Populations in Turkey

The objectives of the study are threefold: (1) to provide estimates of the total populations and spatial distributions of different language groups in Turkey, (2) to test whether the commonly held belief that Turkish-speaking and Kurdish-speaking populations are “actors” of different demographic regimes is true, and (3) to assess whether a process of integration, in the form of intermarriage of Turks and Kurds is under way in Turkey. Data come mainly from the 2003 Turkish Demographic and Health Survey (TDHS-2003). Based on the assumption that the mother tongue composition of women is also representative of that of the whole population, the results of the TDHS-2003 imply that of the population of Turkey, 83% are Turkish-speaking, 14% are Kurdish-speaking, 2% are Arabic-speaking and the remaining 1% belong to other language groups. Results show that despite intensive internal migration movements in the last 50 years, strong demographic differentials exist between Turkish and Kurdish-speaking populations, and that the convergence of the two groups does not appear to be a process under way. Turks and Kurds do indeed appear to be actors of different demographic regimes, at different stages of demographic and health transition processes.     

Social vulnerability and migration in the wake of disaster: the case of Hurricanes Katrina and Rita

This study explores the relationship between place-based social vulnerability and post-disaster migration in the U.S. Gulf Coast region following Hurricanes Katrina and Rita. Using county-level data from the U.S. Census Bureau, we develop a regional index of social vulnerability and examine how its various dimensions are related to migration patterns in the wake of the storms. Our results show that places characterized by greater proportions of disadvantaged populations, housing damage, and, to a lesser degree, more densely built environments were significantly more likely to experience outmigration following the hurricanes. Our results also show that these relationships were not spatially random, but rather exhibited significant geographic clustering. We conclude with a discussion of the implications of these findings for future research and public policy.     

The Influence of Acculturation on Breastfeeding Initiation and Duration for Mexican-Americans

This paper uses data from the Fragile Families and Child Wellbeing Study to test the hypotheses that (1) similar to other positive pre- and post-natal outcomes, Mexican immigrant mothers are more likely to breastfeed, and to breastfeed longer, than white or Mexican-American mothers; and (2) acculturation accounts for the ethnic/nativity differential in breastfeeding initiation and duration. The results support both hypotheses. Mexican immigrants to the U.S. are much more likely than whites to breastfeed, and to breastfeed longer. Mexican-American mothers, after controlling for background characteristics, have similar initiation and duration to whites. Using expanded acculturation measures developed for this paper, acculturation accounts for some of the difference between whites and Mexican immigrants in breastfeeding initiation, and much of the difference for breastfeeding duration. The results suggest that low levels of acculturation operate to protect Mexican immigrants from choosing to formula-feed, which gives their babies many health advantages, and may be associated with better health outcomes across the life course. The results also suggest that successive generations of Mexican immigrants may abandon breastfeeding, which is deleterious for their infants.     

Ethnic Classification in Global Perspective: A Cross-National Survey of the 2000 Census Round

Academic interest in official systems of racial and ethnic classification has grown in recent years, but most research on such census categories has been limited to small case studies or regional surveys. In contrast, this article analyzes a uniquely global data set compiled by the United Nations Statistical Division to survey the approaches to ethnic enumeration taken in 141 countries. The motives for this analysis combine theoretical, applied, and policy objectives. I find that 63% of the national censuses studied incorporate some form of ethnic enumeration, but their question and answer formats vary along several dimensions that betray diverse conceptualizations of ethnicity (for example, as “race” or “nationality”). Moreover, these formats follow notably regional patterns. Nonetheless, the variety of approaches can be grouped into a basic taxonomy of ethnic classification approaches, suggesting greater commonality in worldwide manifestations of the ethnicity concept than some have recognized.

Providing Spatial Data for Secondary Analysis: Issues and Current Practices Relating to Confidentiality

Spatially explicit data pose a series of opportunities and challenges for all the actors involved in providing data for long-term preservation and secondary analysis—the data producer, the data archive, and the data user. We report on opportunities and challenges for each of the three players, and then turn to a summary of current thinking about how best to prepare, archive, disseminate, and make use of social science data that have spatially explicit identification. The core issue that runs through the paper is the risk of the disclosure of the identity of respondents. If we know where they live, where they work, or where they own property, it is possible to find out who they are. Those involved in collecting, archiving, and using data need to be aware of the risks of disclosure and become familiar with best practices to avoid disclosures that will be harmful to respondents.

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

Pooling designs associated with unitary space and ratio efficiency comparison

Let mathbbF^(2n+d)_q²mathbb{F}^{(2nu+delta)}_{q^{2}} be a (2ν+δ)-dimensional unitary space of mathbbF_q²mathbb{F}_{q^{2}} , where δ=0 or 1. In this paper we construct a family of inclusion matrices associated with subspaces of mathbbF^(2n+d)_q²mathbb{F}^{(2nu+delta)}_{q^{2}} , and exhibit its disjunct property. Moreover, we compare the ratio efficiency of this construction with others, and find it smaller under some conditions.