Inequality in the Labor Market: Lower Perceived Returns Among - PDF document

Inequality in the Labor Market: Lower Perceived Returns Among Marginalized Youths and Girls Manjistha Banerji and Ashwini Deshpande 1 To be presented at XXVIII IUSSP International Population Conference in Session “Children, Youth and the Labor Market” On Friday 3 rd November, 2017 1 The authors would like to thank Dr. WilimaWadhwa, Director, ASER Centre for her helpful comments and suggestions. Usual disclaimers apply.

Abstract In this paper, rather than examining actual wages in the labor market, we look at perceived returns in the labor market among adolescents and their parents. The rationale for carrying out this examination is two folds- previous research has established that lower subjective expectations of labor market returns among parents affects educational investment. Likewise, subjective expectations of children about labor market returns are likely to affect their commitment to their education in terms of effort and time spent. Gender and caste have long been the major axis of discrimination in India. In the labor market, it manifests itself in terms of lower wages for women and persons from marginalized communities. We, therefore, ask if perceived labor market returns among adolescents and their parents vary by caste and gender. We use a unique dataset on adolescents that has been recently collected (2013) by ASER Centre, the research and assessment wing of Pratham Education Foundation for our analysis. Results confirm that girls have lower expected earnings than boys. Caste differences appear more rigid in Bihar.

Section I Introduction Gender and caste have long been the major axis of discrimination in India. In the labor market, it manifests itself in terms of lower wages for women and persons from marginalized castes/tribal communities. In this paper, rather than examining actual wages in the labor market, we examine if perceived labor market returns vary by gender and caste among adolescents and their parents. The rationale for carrying out this examination is two folds- previous research (Maertens, 2010) has established that lower subjective expectations of labor market returns among parents affects educational investment. The same rationale suggests that subjective expectations of children about labor market returns are likely to affect their commitment to education in terms of effort and time spent. In other words, lower subjective expectations among parents and children are likely to translate into lower educational investment and vice- versa. Furthermore, answers to the question has policy implications. If adolescents of identical intrinsic ability have different expectations of labor market returns that is based on their gender and caste as do their parents, a vigorous enforcement of civil rights and affirmative action is warranted. On the other hand, if differences in labor market expectations among adolescents are solely due to their intrinsic abilities, then policy recommendation would be to focus on fostering skills through skill development programs (Carneiro, Heckman, & Masterov, 2004). Explorations about expected returns along lines of gender and caste adds another layer to our understanding of systemic biases in the functioning of the labor market and adolescents in India. The paper uses cognition as a measure of an adolescent ’s intrinsic ability. Therein lies the uniqueness of the paper. It brings into the discussion on expected earnings test scores as a measure of an adolescent’s cognitive ability. It is also unique in that it focuses on adolescents in the age group of 11- 16 years who are likely to join the labor force in few years. Previous discussion of subjective expectations in India did not include any measure to capture cognitive ability and did not focus exclusively on adolescents. To set up the analytical context, Section II surveys the literature on cognitive skills as a predictor of labor market outcomes. It then surveys the state of education keeping in focus the age group under consideration and labor market returns in India. Section III presents the research questions and hypotheses, discusses the data and methods. Results are analyzed in Section IV. Section V concludes.

Section II Cognitive skills as a predictor of labor market outcomes Higher cognitive ability is systematically correlated with individual preferences and choices that favour economic success (Burks et al, 2009). Persons with higher test scores have higher earnings (Attanasio and Kaufmann, 2010). Better literacy and numeracy skills increase the likelihood of positive labor market outcomes- wages and employment (Chesters, Ryan and Sinning, 2013)-because basic skills acquired in early childhood and school years, particularly literacy and numeracy, are the necessary foundation for developing higher order skills that contribute to a productive workforce (Treasurer of the Commonwealth of Australia, 2010). Lee and Newhouse (2008) utilize data for up to 315 tested cohorts in 67 countries to establish that both education quality, as measured by performance on international assessments and average educational attainment are important determinants of youth outcomes in labor markets. Higher scores in tests like PISA and TIMSS also correlate with a larger share of youth working in wage and salaried employment, outside the agricultural sector and to some extent in higher status occupation. The effects of test scores for most outcomes continue to hold true even after keeping educational attainment constant or when the focus is on low and middle income countries; suggesting that the correlations between test scores and youth employment outcomes are not driven solely by differences in educational attainment, or broad contrasts between the labor markets of high-income and low-income countries. More broadly, cognitive skills of the population are powerfully related to individual earnings, distribution of income, and economic growth (Hanushek and Woessmann, 2008). Further, the earlier in childhood children develop cognitive and social skills, the better are the long-term impacts on their skills and labor market outcomes (Rose, 2005). Data from the National Education Longitudinal Study of 1988 indicates that students who made relatively large test score gains during high school had larger earnings 7 years after high school compared to students whose scores improved little. In other words, test score gains during high school predict subsequent employment status and earnings. There is, however, a gender differential- test score gains increase female earnings by both increasing the likelihood of employment and by increasing earnings once employed. For men, on the other hand, test score gains are not significantly related to employment status or earnings, except for those men who have low initial test scores. It follows from the above discussion then that

given the association between cognitive skills and labor market outcomes, adolescents and their parents are likely to factor it in their labor market expectations. Universal enrolment, but “low” quality is an issue The most notable achievement in recent years in the provision of education in India is near universal enrolment as indicated in the ASER surveys over the years (2005- 2016). However, there are numerous quality concerns- poor attendance and high drop out among adolescents, and low learning levels, and that these outcomes vary by background characteristics as gender and caste. In the context of the paper, these deficiencies of the educational system highlight that it is not a system geared to maximizing the educational potentialities of its students, particularly girls and children from marginalized castes. Unlike in developed countries where enrolment is synonymous with attendance, in rural India attendance is far from universal (Deshpande and Banerji, 2017; Bhattacharjea, Banerji and Wadhwa, 2011). Nationally, about 25% children were found to be absent when a team as part of the annual ASER (Annual Status of Education Report) 2016 survey visited the village school. Data from Wave I of IHDS confirm the findings (Desai et al, 2010). Nationally, 20% of children were absent for 6+ days in the month preceding the survey, with as many as 26% children in “less developed villages” reporting an absenteeism in the above reporting period. Second, drop out remains a huge concern, particularly in the adolescent age group and among girls. As per ASER 2016, the percent drop out in the age group 15- 16 years is 13.5% and in the age group 11- 14 years is 3.5%. Discontinuation rates computed for men and women (17+) using IHDS- Wave I suggests that around 50% men dropped out between grades 5 & 10. The corresponding rate for women is 57%. Likewise, discontinuation rates are highest among Adivasis (Scheduled Tribes), followed by Dalits (Scheduled Castes) and lowest among high caste Hindus. There are regional differences- states as Madhya Pradesh, Chhattisgarh and Rajasthan have higher dropouts than other states. Beyond attendance and dropouts, the most important concern that has occupied center stage in the discussion on quality of education in India is poor learning outcomes as highlighted in the annual ASER surveys. As per ASER 2016, only 26% of children in Class V and 43% of children in Class VIII could solve a three- by one digit division (with a remainder) problem. Comparisons over time suggest that learning levels have deteriorated or at best have remained stable. In the above example, percent of Class V children who could solve the division problem was 36.2% in 2010 and it declined to 26.1% in 2014. The corresponding percentages for Class VIII are 68.4% and 43.3% respectively.