Dropout Behaviour of Children: The Case of West Bengal

2020 ◽  
Vol 14 (2) ◽  
pp. 275-289
Author(s):  
Amita Majumder ◽  
Chayanika Mitra
Keyword(s):  
Parental Education ◽  
West Bengal ◽  
Multinomial Logit Model ◽  
National Sample ◽  
Probit Analysis ◽  
Sample Survey ◽  
Dropping Out ◽  
Education Expenditure ◽  
Data Set ◽  
Children’S Perspectives

This article examines the dropout behaviour of students below class 10 level (maximum age of 16 years) from two different perspectives. First, from the parents’ perspective, we identify the major characteristics of a household that forces the child to dropout from school, using a Probit analysis. Second, from the child’s perspective, we try to relate the reasons for dropping out (as specified by the child) with the background of the household the child belongs to and the school infrastructure provided to him/her, through a multinomial logit model. The data set used is the 71st round (January 2014 to June 2014) data on education expenditure and is provided by the National Sample Survey Office (NSSO). The analysis is done for the state of West Bengal, India, separately for boys and girls. It shows the significance of parental education and economic factors in children’s dropout behaviour, which is in line with the observations in existing literature. Additionally, this article offers children’s perspectives on such behaviour from across genders and economic classes.

Gender Bias in Education Expenditure among Religious and Social Groups: A Case Study for Below Class 10 Level in West Bengal

2021 ◽  
pp. 097674792110464
Author(s):  
Chayanika Mitra
Keyword(s):  
Gender Bias ◽  
West Bengal ◽  
Social Groups ◽  
National Sample ◽  
Sample Survey ◽  
Education Expenditure ◽  
Individual Level ◽  
Expenditure Data ◽  
The Social

This article attempts to capture gender bias in education expenditure among the religious (Hindu, Muslim and others) and the social groups (SC, ST and General) in West Bengal. Oaxaca–Blinder decomposition technique is used to obtain gender bias for a specific demographic group. Further, an attempt has been made to identify the religious or social groups with the acute problem of gender bias. In this work, 71st round (January–June 2014) education expenditure data (individual level) provided by NSSO (National Sample Survey Office) is used. JEL: I24, R1, C55

Does Education Produce Identical Labour Market Outcomes for All? A Study on India

2020 ◽  
Vol 14 (3) ◽  
pp. 309-331
Author(s):  
Anjan Ray Chaudhury ◽  
Madhabendra Sinha
Keyword(s):  
Labour Market ◽  
Occupational Status ◽  
Probit Model ◽  
National Sample ◽  
Sample Survey ◽  
Market Outcomes ◽  
Data Set ◽  
Multinomial Probit Model ◽  
And Gender ◽  
Gender Groups

According to the neoclassical economists, discrimination exists in the labour market if employers treat two equally qualified and skilled persons differently based on gender, race, age, disability, religion, caste, etc. In this article, we attempt to look at discrimination in the Indian labour market by applying the multinomial probit model of regression to the National Sample Survey Office data set. By taking years of schooling (as an indicator of skill and ability) as an independent variable in the model, we find that identically educated persons from different caste and gender groups are not equally likely to achieve similar occupational status, indicating the existence of discrimination in the Indian labour market. JEL Classifications: I31, C31

scholarly journals Education among Scheduled Caste Population in India

2019 ◽  
Vol 51 (3) ◽  
pp. 393
Author(s):  
Harihar Sahoo ◽  
Sumana Acharya
Keyword(s):  
Higher Education ◽  
National Sample ◽  
Gender Disparity ◽  
Sample Survey ◽  
Educational Institutions ◽  
Dropping Out ◽  
State Governments ◽  
The Social ◽  
Scheduled Castes ◽  
Drop Outs

Lack of education among the scheduled castes (SC) population in India may be the main reason for remaining at the lower end of the social structure. Therefore, this study attempts to explore the changing trends in literacy among the SC to find out the determinants of higher education and to explore the major reasons for never enrolling or discontinuing/dropping out from educational institutions among the SC population in India. Using the data from the Census of India and also from National Sample Survey and employing both bivariate and multivariate analysis, the results reveal that though there is an increasing trend in the literacy rate among the SC population, but the rates remain quite below the national average. Gender disparity in literacy is quite evident. The low level of higher education mainly due to reasons like failing in examinations, heavy drop-outs and stagnation caused by their poor socio-economic background. Despite various efforts by the central and state governments to eradicate differences in educational attainment among the social groups through several constitutional steps from time to time there still remain gaps to be bridged.

Gender bias in household education expenditure: the case of West Bengal

2016 ◽  
Vol 9 (2) ◽  
pp. 129-150
Author(s):  
Amita Majumder ◽  
Chayanika Mitra
Keyword(s):  
Gender Bias ◽  
Selection Bias ◽  
Female Student ◽  
West Bengal ◽  
Male Student ◽  
Sample Survey ◽  
Education Expenditure ◽  
Content Type ◽  
Engel Curve ◽  
Step Procedure

Purpose This paper aims to detect gender bias in education expenditure on “students”, who are children and young adults, in a household in the rural and the urban sectors of West Bengal. Outlay equivalent ratios have been calculated using the Engel curve approach, where the budget share function is log quadratic in income, to identify items relating exclusively to education of school/college going students. Heckman’s (1979) two-step procedure is used for estimation to address selection bias The 68th round (July 2011 to June 2012) household level consumption expenditure survey data of the National Sample Survey Organisation have been used for the analysis. Design/methodology/approach Engel curve approach is used to capture parental preference for student’s welfare and to find the existence of male student favouritism in the field of education. In case of exclusive adult goods, the addition of a student will reduce the resource allocated for adult goods leading to negative income effect. If a household favours males over females, then that household is likely to sacrifice more for a male student’s education than that for a female student. To address selection bias, Heckman’s two-step procedure has been used. Findings The authors find that not all education items relate exclusively to students of a household. Expenditure on books is not exclusively for students, whereas other educational items, such as stationary and photocopy charges, tuition fees and private coaching fees, are found to be students’ items only. Transport cost is found to be an adult good. Further, we find evidence of pro male bias in expenditure on educational items, and the extent of gender bias is more in the urban sectors compared to the rural sectors in West Bengal. Originality/value The objective of this paper is to identify the educational items exclusively for “students” and to test the difference in the allocation of resources in education, with respect to these items, between a male student and a female student for both sectors in West Bengal, using the outlay equivalent ratios.

Female employment in India: determinants of choice of sector of activity

2019 ◽  
Vol 46 (3) ◽  
pp. 748-759
Author(s):  
Sandhya Mahapatro
Keyword(s):  
Labour Market ◽  
Labour Force ◽  
Multinomial Logit Model ◽  
National Sample ◽  
Female Employment ◽  
Sample Survey ◽  
Socioeconomic Condition ◽  
Content Type ◽  
Unpaid Labour ◽  
Formal Employment

Purpose The purpose of this paper is to examine whether the choice of employment sector for women is driven by the structure of the labour market or determined by the household socioeconomic condition. Design/methodology/approach Data for the study were drawn from the National Sample Survey 68th round (2011–2012). The sector of employment was assessed through females’ participation as an unpaid labour, employer/own account worker, informal wage worker, formal wage worker and unemployed. A multinomial logit model was used to examine the factors that determine the sector of employment. Findings Although education increases formal employment among women, most of them are unemployed or entering into informal employment. It indicates that the labour market has not been able to integrate educated women into formal employment. Research limitations/implications Increase in female education accompanied by a slow growth of employment creates the challenge to accommodate the educated and skilled women in formal employment. Originality/value This study examines the factors determining the sectoral participation of employment to assess the responses of the current labour market for the females, especially educated females who have not been adequately addressed. The findings of the study have significant implications for formulating appropriate labour market policies for the educated female labour force.

The Impact of Green Labels on U.S. Hotel Net Operating Income: Operating Statements Analyses

2019 ◽  
Vol 11 (1) ◽  
pp. 156-173
Author(s):  
Spenser Robinson ◽  
A.J. Singh
Keyword(s):  
Environmental Design ◽  
Green Buildings ◽  
Small Sample ◽  
Sample Survey ◽  
Data Set ◽  
Operating Income ◽  
Energy Star ◽  
The Impact ◽  
Industry Professionals

This paper shows Leadership in Energy and Environmental Design (LEED) certified hospitality properties exhibit increased expenses and earn lower net operating income (NOI) than non-certified buildings. ENERGY STAR certified properties demonstrate lower overall expenses than non-certified buildings with statistically neutral NOI effects. Using a custom sample of all green buildings and their competitive data set as of 2013 provided by Smith Travel Research (STR), the paper documents potential reasons for this result including increased operational expenses, potential confusion with certified and registered LEED projects in the data, and qualitative input. The qualitative input comes from a small sample survey of five industry professionals. The paper provides one of the only analyses on operating efficiencies with LEED and ENERGY STAR hospitality properties.

INFLUENCE OF WEATHER ON TEMPORARY AND PERMANENT MIGRATION IN RURAL INDIA

2013 ◽  
Vol 04 (02) ◽  
pp. 1350007 ◽  
Author(s):  
K. S. KAVI KUMAR ◽  
BRINDA VISWANATHAN
Keyword(s):  
National Sample ◽  
Sample Survey ◽  
Urban Migration ◽  
Temporary Migration ◽  
Urban Migrants ◽  
Wide Range ◽  
Permanent Migration ◽  
Sample Survey Data ◽  
Almost All ◽  
Temporary Migrants

While a wide range of factors influence rural–rural and rural–urban migration in developing countries, there is significant interest in analyzing the role of agricultural distress and growing inter-regional differences in fueling such movement. This strand of research acquires importance in the context of climate change adaptation. In the Indian context, this analysis gets further complicated due to the significant presence of temporary migration. This paper analyzes how weather and its variability affects both temporary and permanent migration in India using National Sample Survey data for the year 2007–2008. The paper finds that almost all of the rural–urban migrants are permanent. Only temperature plays a role in permanent migration. In contrast, many temporary migrants are rural–rural and both temperature and rainfall explain temporary migration.

The Cost of Being ‘Backward’ in India: Socio-religious Discrimination in the Labour Market

2021 ◽  
pp. 097370302110296
Author(s):  
Soumyajit Chakraborty ◽  
Alok K. Bohara
Keyword(s):  
Labour Market ◽  
Economic Cost ◽  
National Sample ◽  
Sample Survey ◽  
Religious Discrimination ◽  
Capital Endowment ◽  
Scheduled Castes ◽  
Sample Survey Data ◽  
The Cost ◽  
Human Capital Endowment

Being from backward castes, classes and Muslims in India has an economic cost associated with the nature of institutional discrimination. Using the 2011–2012 National Sample Survey data, this study identifies that caste and religion still rule the modern Indian labour market. We find that discrimination is evident in the socio-religious earnings gaps. While the parametric decompositions suggest that most of these gaps are due to differential human capital endowment, the nonparametric method almost evenly attributes inequality to discrimination and endowment. The results presented in this study suggest that discrimination against Scheduled Castes and Scheduled Tribes, Muslims and Other Backward Classes should be included in policy designs to promote equity in the Indian labour market.

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