In this paper data from the Indian National Sample Survey Office (NSSO) for the year 2011-12 is used to examine the relationship between educational attainment and labour market participation of men and women. Educational variables have been gender disaggregated to see the effect of labour market returns. Estimates of the returns to education in wage employment in India by gender and location (rural–urban) are provided. The analysis in this paper shows that women’s education has a U-shaped relationship with paid work participation but men’s education has a linear negative relation. Education levels higher than compulsory secondary schooling correlate with an increase in propensity to take part in paid work among women. This is because the returns to education are insignificant and low for lower levels of education. The returns increase significantly along with the increase in educational levels. However, women have a significant lower rate of return for each year of education as compared to men in rural and urban labour markets. This suggests that women suffer high levels of wage discrimination in the labour market in the year 2011-12. This may be the reason behind the stated decline in female work force participation (FWFP) during the year 2011-12. Our findings suggest that, to increase the numbers of women in the work force, and wage employment; measures are needed to educate women beyond secondary level.
In the economics of education literature, an important explanation of the gender gap in education is that the labour market rewards women’s education less well than men’s, especially in developing countries (Kingdon, 1998). Our paper examines this argument to explain the declining work participation of women in India in the year 2011-12. Our aim is to study female work participation through the interlinkages between education and employment.
The data used for analysis in this paper were collected as part of the all India quinquennial survey on Employment-Unemployment by National Sample Survey Office (NSSO). NSSO employs three different methods of determining the activity status of the persons. The first method identifies the Usual Principal Activity Status (called ‘Usual Principal Status’, UPS) of a person by using a reference period of 365 days preceding the date of survey. A person is considered as being in the Work Force if he/she is gainfully employed for a major part of the preceding 365 days. The second method considers a reference period of one week (current weekly status) and the third method considers each day of the week (current daily status). Our study is based on current weekly status.
Methodology used in the study is as follows: for modelling the choice of work force participation we have adopted the standard model from the neo-classical theory of labour supply. The choice between participation in paid work or not is modelled as a binary probit. The standard Mincerian semi-logarithmic earnings function is used to model earnings, with modifications to take account of the possibility of endogenous sample selection using the familiar two step Heckman procedure. The analysis uses a sample of persons aged 25-59 years old. Separate sub-group regressions have been performed for married women.
The novelty of our study lies in the result, which deviates from established literature regarding the reasons of decline in female labour force participation. Our results show that the lower returns to education in the labour market discourages women workers from participating, whereas literature states that an increase in educational enrolment has caused the decline (Chowdhury 2009, Neff et al. 2012). Education has a strongly significant relationship with wages of both males and females in rural and urban labour market. However, females have a significant lower rate of return for each year of education as compared to men in rural and urban labour markets. Our results are divergent from the established literature about the reason for declining female labour force participation in rural and urban India for the year 2011-12. From the analysis in our paper we may suggest that policies to encourage education beyond secondary levels for females will enhance their paid work participation. Removal of discrimination against females in the labour market may increase the returns to education. This will provide a fillip in work participation for females. Women’s employment is a critical factor in their progression towards economic independence and is also considered as an indicator of their overall status in society (Mammen and Paxson 2008).
Work force participation is defined as the number of persons employed per thousand persons.
The spatial distribution of population within a country is far from being homogenous. All countries are characterized by core areas, with high levels of income and wealth, and peripheral regions, often specialized in low value added sectors. One of the possible explanations for these patterns is the fact that places are inherently different in terms of productivity; core urban are frequently characterized by the presence of some natural advantages (i.e. first nature advantages: large and deep harbors or the location at the center of large plains with a highly productive agriculture) that eventually evolved in agglomeration economies (i.e. second nature). However, the distribution of population is also subject to (non-economic) historical shocks that can have long lasting effects (Rosenthal and Ross, 2015; Schumann, 2014). A possible consequence is that the distribution of population is mislocated, that is not optimally allocated across areas, and some high-(low)productivity sites end up to be suboptimally under-(over) populated. Spatial mislocation might also have negative effects on the aggregate growth of a country (Hsieh and Moretti, 2015). The aim of this paper is to analyze the causes and the effects of the mislocation of population in Italy. Our work relates to the growing literature on the consequences of historical shocks on city development and growth (see, for example, Bleakley and Lin (2012), Jedwab and Moradi (2014), Michaels and Rauch (2016)) but differently from the cited studies, that focus on the path-persistence of population settlements, we do not exploit a natural or infrastructural original location advantage, but we refer to the consequences of predatory behaviors like in Nunn (2008) and Nunn and Puga (2012). We consider, in particular, the role of the attacks from the north-African pirates that coastal places (especially in the Southern-West coast) experienced in Italy over two different waves for a very long period of time (i.e. from VIII century with the fall of the Byzantine Empire as a naval power to early XIX century when northern Africa, Tunis in particular, fell under the French influence). Due to the fear of being attacked, coastal places lost their attractiveness for residents who moved towards inner locations, far from the costs and difficult to assault because positioned on mountainous and rugged territories. As a result, these low productivity territories ended up in being relatively overpopulated. These findings are robust to alternative definitions of the security features of the havens and using different measures for the likelihood of being targeted by pirates. More importantly, our results are obtained by using a very detailed set of geographical fixed effects and by controlling for subsoil characteristics, which take into account the productivity features of each location. We also show that the concentration of population over the space was very different before the VIII century: Roman cities were not located in places that ensured protection from the pirates, as there were no raids before the VIII century. The effects of pirates’ attack on the distribution of Italy’s population are shown to persist overtime, a feature highlighted in the literature on population changes over space (Rosenthal and Ross, 2015). The impact measured for 1871 (the first year for which a complete census of Italian cities is available) is still evident, tough its magnitude is reduced by a half, in the 1951 distribution of population. The effect persisted notwithstanding two world wars, the exceptional wave of outward migration from the end of the XIX century and the twenties of the XX century. The impact ceases to exist after 1981, wiped away by the massive south-to-north and rural-to-urban migration, which went hand in hands with the Italian industrialization process up to middle 1970s. We then analyze the consequences of spatial mislocation of population induced by the pirate attacks on a number of economic outcomes. Due to the data constraint, all estimates refer to post-WWII censuses when measured mislocation was quantitatively smaller than the one registered 80 years before. This notwithstanding, we find that overpopulation derived by pirates’ attacks in areas less suitable for economic activities determined a slower accumulation of human capital and an over specialization in subsistence agriculture; in the period 1951-1981, escaping from the wrong places also determined a sizable and persistent increase in the aging index with possible long-run consequences on the future development of those areas.
The trends of decline in TFR varied widely across EU countries. Exploiting individual data from the longitudinal EU-SILC dataset from 2005 to 2013, this study investigates the cross-country short- run effect of job instability on the couple's choice of having one (more) child. In order to account for the unobserved heterogeneity and potential presence of endogeneity, I estimate a Two Stage Least Square Model (2SLS) in first differences and under sequential moment restriction. Thus, grouping European countries into six different welfare regimes, I can estimate the heterogeneous effects of instability in the labour market on childbearing among different institutional settings of European welfare. The principal result is that the cross-country average effect of job instability on couples' fertility decisions is not statistical relevant because of the huge country-specific fixed effects, even if having a temporary job for women encourages childbearing, in average. When I analyse these impacts distinguishing between welfare regimes, the institutional structure and linked social active policies reveal a varying family behaviour in fertility choices. In low-fertility countries, however, it is confirmed that the impact of parents' successful labour market integration might be ambiguous and it might due to the scarcity of child care options and/or cultural norms.
It is a well-known fact that boys tend to lag behind girls in terms of socio-emotional development and maturity (Silverman, 2003; Else-Quest et al., 2006) and perform worse than girls on many non-cognitive dimensions (Beamen et al., 2006; Gilliam, 2005; Ready et al., 2005; Bertrand and Pan, 2013). There is growing literature that suggests that these long-standing behavioral and developmental differences between boys and girls might explain gender differences in academic achievement and the female advantage in college attendance (Goldin et al., 2006; Becker et al., 2010; Cornwell et al., 2013). Boys' early difficulties in school have been shown to explain a substantial share of the female advantage in college enrolment (Jacob, 2002). Some psychologists have suggested that as the early school years become more “academic” in nature - reflecting a shift away from play-centered learning to an increasing emphasis on test-taking and the development of literacy and math skills, children who are not developmentally ready are likely to struggle when placed in such an academically-oriented and demanding classroom setting (Sax, 2007). This factor is likely to be particularly salient for boys given their relatively slower maturation and emotional development.
Perhaps in response to these social developments, the practice of delaying children's school entry, also known as academic “redshirting” is becoming increasingly popular, particularly for boys from more advantaged families (Dobkin and Ferreira, 2010; Bassok and Reardon, 2013). As discussed in Dee and Sievertsen (2015), the hypothesized benefits of delaying school entry are two-fold. First, absolute maturity could matter for school success - that is, the returns to formal schooling could be higher for older children who are more ready developmentally (Vygotsky, 1978; Whitebread, 2011). Second, delaying school entry could confer a developmental advantage over younger peers that might lead to early successes that compound over time due to positive reinforcement or institutional practices (e.g. ability grouping).
In this paper, we examine the causal effect of delayed school entry on the development of cognitive and non-cognitive skills, focusing in particular on whether boys and girls respond differently to starting school later. This question is relevant for public policy debates over what is the optimal age that children should start school and whether raising the school starting age might be a potential lever in reducing gender disparities in educational outcomes. We use data from a rich longitudinal survey of Australian children that allows us to track the cognitive and non-cognitive development of children from age 6 to age 14. Following previous literature, we address the potential endogeneity of school starting age using an instrumental variables approach. Our instrument isolates plausibly exogenous variation in the age at which children start school due to naturally occurring variation in children's birth dates and large differences in state policies in Australia that determine when children are eligible to start formal schooling.
We find large gender differences in the effects of school starting age. In particular, boys who entered formal schooling later had significantly higher scores on standardized tests of literacy and numeracy at age 8. Strikingly, these effects show little evidence of fade-out. The positive effect of delaying school entry on boys' numeracy skills grows over time and is large and statistically significant at age 14. Our results indicate that a one month increase in school starting age leads to an increase in the numeracy scores of boys by 0.095 standard deviations at age 8 and 0.16 standard deviations at age 14. While the effects on boys' literacy skills are insignificant, the point estimates are consistently positive and of non-trivial magnitude from age 8 (0.07 standard deviations) to age 14 (0.06 standard deviations). By contrast, we do not find consistent evidence that girls' cognitive skills are systematically affected by school entrance age.
Turning to non-cognitive skills, we find similar gender differences in the effects of delayed school entry on parent-reported measures of non-cognitive skills from age 6 to age 12. A one month increase in school starting age reduces the incidence of socio-emotional and behavioral problem by 0.04 standard deviations between age 6 and age 12. However, these effects disappear at age 14. Most of the benefits of delayed school entry on non-cognitive skills for boys are due to the reduction in hyperactivity and emotional symptoms. Consistent with our findings for cognitive skills, there are no discernible effects of school starting age on girls' non-cognitive skills from age 6 to age 12.
Over the last century, the narrowing of gender differences in education and labor market outcomes has been impressive, up to a reversal of the gap in school attainment in many OECD countries. Despite that, gender stereotypical beliefs are pervasive and deeply-held in most societies. Women are believed to be worst than men in highly profitable fields as mathematics, engineering and technology, even controlling for measured ability. Stereotypes are overgeneralized and amplified representations of differences among groups, which are often based on empirical realities. Indeed, for instance, boys outperform girls in math by the age of 15 in most countries according with PISA data (Program for International Student Assessment). However, gender differences in math vary substantially across countries and increase dramatically throughout the educational career of students. Gaining a better understanding of the reasons behind the emergence of gap in math skills between males and females is of first-order importance to explain the enduring differences in performance and the underrepresentation of women in leadership position and among science, technology, engineering, and math (STEM) workforce. To the extent that gender stereotypes are internalized directly in the development of self-concept or influence investment choices, these cultural beliefs may have causal influence on life-outcomes of individuals, shaping educational and occupational careers.
In this paper, I explore whether exposure to stereotypes can causally affect math achievements and track choice of boys and girls. I focus in particular on the influence of teachers’ gender stereotypes in affecting student performance, combining administrative data and original first-hand questionnaire on students and more than 1.400 teachers in Italy. I find that gender gap in math performance increases when students are assigned to teachers with higher bias (as measured using a computer- based tool developed in social psychology and called Implicit Association Test). The difference in the additional gap in math performance between boys and girls generated during middle school would be 34 percent smaller if teachers had one standard deviation lower implicit stereotypes. The effect is driven by students from disadvantaged backgrounds and by lower performance of females, while males are not affected by implicit stereotypes. Teacher bias has a substantial impact on own assessment of math ability, as measured by detailed information collected through an original student questionnaire. This paper shows that biased teachers activate negative self-stereotypes on female students only in maletyped domains (as math), while there is no effect on reading performance. Furthermore, I also provide evidence that teacher implicit bias is correlated with their high-school recommendation to students and it has an influence on the actual high-school track choice of pupils. The findings are consistent with a model of stereotype whereby ability-stigmatized groups underperform failing to achieve their potential. Teacher bias fosters low expectations about own math ability and underperformance of individuals vulnerable to the gender stereotype.
Recently, there has been a growing academic interest in the study of the household decision-making process. Intra-household differences in decision making represents a significant aspect of gender inequality. Moreover, the nature of gender relations of power in the households affects economic outcomes in multiple ways (Agarwal, 1997). As a general finding, it has been shown that the person who controls the income in the household directly affects decisions and outcomes, for instance in terms of child health, education and expenditures in goods and services (Lundberg et al. 1997; Phipps and Burton, 1998; Duflo, 2003).
Even though most authors agree that the way couples in the family organize personal and household money, follows an ‘earner-specific’ division among pooling and not-pooling household organization schemes there is, however, little agreement about which allocation system produces more equality. This paper aims to analyse gender differences in decision making in six different management systems. We focus on two relevant factors associated to household decision making, namely, distributive factors (DF) (i.e., income age and education differences as well as economic activity of partners) and social norms (by means of a variable that capture the difference in the ability to freely use resources within the family). In particular, we estimate the probability that women decide in different household management settings and the relationship among this probability, DF and social norms. We make use of an ordered probit model for different types of household decisions made within the family(namely everyday shopping, purchase of durable goods, borrowing, savings and taking important decisions) drawn from the special module on intra-household decision-making in the 2010 European Union Survey on Income and Living Conditions (EU-SILC). These outcomes are related to different aspects of decision making within the family, in fact we distinguish between executive and strategic decisions in order to capture the difference in decision making processes, theoretical models explaining them (i.e.: Unitary, Strategic and Collective models) and the resulting gender differences. Differently from other analyses (Pahl, 1989; Ponthieux, 2013), we identify six arrangements, depending also on how many household components have a personal income in the household. We, therefore, define “Full pooling system with 1 earner" (FP1); "Full pooling system with 2 earners" (FP2); "Partial Pooling system (two earners)" (PP); "Partial Dictator system (one earner)" (PD); "Full Dictator system (one earner)" (FD) and "Independent system (two earners)" (IM).
In general, results confirm an important difference between time consuming/executive decision (i.e. everyday shopping) where efficiency arguments hold (i.e. the income is either not significant or negative related to the probability to decide, except for the Full dictator system), and control/strategic decision (i.e. borrowing) where bargaining arguments hold (i.e. the higher income or education the more is the power). Income and education differences affect also the gender gap. In particular, our hypothesis is that if a power/bargaining works each partner use his/her power in order to reduce his/her gap. We find for executive decision that (i) the income difference has no effect for FP1 and IM2 (the difference in predicted probabilities is not statistically different from zero as in the unitary model); (ii) higher women’s income reduces gender gap in the FP2 where the effect of income on the probability that women decides is negative as in a pure collective model with introduction of household production; (iii) income increases gender difference in PD1 and FD1, where, especially for the last, the effect of income on the probability that women decide is positive. About education, we find that higher women’s education reduces gender gap in the FP1, FP2, PD1 and PP2, while it increases gender differences in FD1 and IM2.
For strategic decisions there are no differences among management systems since higher women’s income compared to men always reduce gender gap, as well as higher women’s education respect to men always reduces gender gap.
With regards to social norms we find that when the woman feels more free than the man within the couple, her power increases leading to an increase in gender gap for executive decisions and a decrease in gender gap for strategic ones.
These results could represent a useful advice for policies which aim to reduce gender gapin decision making: gender differences can be reduced by improving women’s education and income in household management systems where both partners work and they fully pooled their resources for executive decisions, and in all the declared management systems regarding strategic decisions.