Sustainable development: Does improvement in education and health of women improve female labour force participation rate?

2019 ◽  
Vol 28 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Olawumi Abeni Osundina
Keyword(s):  
Sustainable Development ◽  
Labour Force ◽  
Participation Rate ◽  
Labour Force Participation ◽  
Female Labour Force Participation ◽  
Labour Force Participation Rate ◽  
Female Labour ◽  
Education And Health

scholarly journals Fertility and socio-economic determinants: evidence from co-integration and multivariate Granger casualty tests

2016 ◽  
Vol 4 (1) ◽  
pp. 134
Author(s):  
Prakash Kengnal ◽  
Asha Bullappa
Keyword(s):  
Labour Force ◽  
National Income ◽  
Participation Rate ◽  
Labour Force Participation ◽  
Fertility Rate ◽  
Gross National Income ◽  
Female Labour Force Participation ◽  
Labour Force Participation Rate ◽  
Female Labour ◽  
Per Capita

Background: The empirical work on fertility determinants widely discusses the role of socio-economic factors like female labour force participation rate, urban population and per capita gross national income in determining fertility rates. The India’s high fertility rate began to decline gradually after late 1950s and continued to fall since then. India achieved almost 31 per cent decline in fertility rate from 1990 to 2012. The objective was to examine the relationship between fertility rate, urbanization, female labour force participation rate and per capita gross national income for India.Methods: This study covers the sample period from 1990-2012. Moreover, the direction of causality between fertility rate, urbanization, female labour force participation rate and per capita gross national income in India using Granger Causality test within the Vector Error-Correction Model (VECM) are examined.Results: As a summary of the empirical results, we found that fertility rate, urbanization, female labour force participation rate and per capita gross national income in India are co-integrated and there is unidirectional Granger Causality between the four variables in long and short-run.Conclusions: The growth in urban population, female labour force participation rate and per capita gross national income are responsible for the decrease in fertility rate in India.

scholarly journals Association of household income and female labour force participation rate in income generating activities in hill rural areas of Uttarakhand

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Prashant Kandari ◽  
Uma Bahuguna
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Labour Force ◽  
Participation Rate ◽  
Labour Force Participation ◽  
The State ◽  
Female Labour Force Participation ◽  
Labour Force Participation Rate ◽  
Female Labour ◽  
Income Generating Activities

As per 2011 Census, about 70 per cent of population in Uttarakhand state resides in rural areas and the ten hill districts out of total 13 districts of the State comprises 48.1 per cent of its entire population. Difficult terrain, lack of transport, lack of employment due to non availability of industrial sector along with small farm sizes and low farm incomes has fuelled large migration from these hill rural areas of the Uttarakhand to the urban regions across the country. The various studies reflect upon the importance of women in the economy of the hill areas as they share the burden of their families and their participation in employment and subsistence cum income generating activities mainly in the rural regions is much higher than the males. The importance of women further enhances amidst the severe problem of migration of males and mainly of the youths from these regions to the urban areas. The women are left back to work in most tough conditions further taking care of the domestic chores. The females labour force participation is higher in rural areas of the state, as per National Sample Survey Office, 68th Round, the female labour force participation rate in rural areas was 31.5 percent and 10.8 percent in urban areas of the state. In this context it is very important to understand the nature of female labour force participation i.e. , whether it is in non-income generating sector like agriculture or in purely income generating sector which mainly comprises of both i.e., agriculture and non-agriculture sector. The present study analyses this distribution of female labour force participation and depicts the association between the female labour force participation in income generating activities and the total household income.

‘Give Me Some Rail’: An Enquiry into Puzzle of Declining Female Labour Force Participation Rate

2020 ◽  
pp. 0258042X2097696
Author(s):  
Rajesh Gupta ◽  
Vibhav Bhamoriya
Keyword(s):  
Social Inclusion ◽  
Labour Force ◽  
Participation Rate ◽  
Labour Force Participation ◽  
Jel Classification ◽  
Female Labour Force Participation ◽  
Intermodal Transport ◽  
Indian States ◽  
Labour Force Participation Rate ◽  
Female Labour

Female labour force undeniably constitutes half of the human capital that drives the growth and development of emerging economies. Probing into determinants of female labour force participation decline has gathered momentum in recent past, but there has been no significant breakthrough in resolving the puzzle. Using World Bank’s database of female labour force participation rate of India and China, and the state-wise database for India, this article juxtaposes the intermodal transport trend to examine if the former can be explained by the latter. Decline of female labour force participation in India is a concern from both the demographic dividend aspect and the social inclusion aspect. Twenty-five years’ data of both China and India and 3 year’s data of 18 Indian states show this trend, and this article probes the mobility constraint as the reason behind this phenomenon. Results of this study indicate that lower rail-to-road ratio is exclusionary for women. The findings regarding gendering of mobility and employment would influence important policy towards planning intermodal transport and its share of total transport for a nation. JEL Classification: C25, J12, J16, J21, J22, J130, J220, I38, I180, R48

How does trade openness affect female labours?

2019 ◽  
Vol 41 (4) ◽  
pp. 375-390
Author(s):  
Jing-Ping Li ◽  
Zheng-Zheng Li ◽  
Ran Tao ◽  
Chi Wei Su
Keyword(s):  
Labour Force ◽  
Trade Openness ◽  
Participation Rate ◽  
Labour Force Participation ◽  
Threshold Value ◽  
Female Employment ◽  
Female Labour Force Participation ◽  
Labour Force Participation Rate ◽  
Female Labour ◽  
Content Type

Purpose The purpose of this paper is to investigate the non-linear threshold effects between trade openness and female labours to participate in the labour markets. Design/methodology/approach The authors consider data for nine Asian countries from 1990 to 2016 period and perform the panel threshold regression method. Findings Empirical results indicate that the threshold value is occurred. With the increase of trade openess, the female labour force participation rate shows a trend of rising first and then declining. Furthermore, exports also have an asymmetric threshold effect on female labour force participation, which is partly in accordance with the discrimination model (Becker, 1957). On the other hand, imports dependency will hinder female labour force participation regardless of a threshold effect. The authors obtain similar results when the authors consider the female employment rate as substitution. Practical implications Specifically, increased trade openness may contribute positively or negatively towards overall female labour force participation rate (FLFPR), attributed to the relative importance of these opposing effects. Thus, when the cost reduction effect, resulting from intensified competitive pressure and comparative advantages would enhance the participation rate, the technology channel operates in the opposite direction. Therefore, from the perspective of female employment, trade openness is not the more the better. Originality/value This study innovatively discusses the non-linear correlation between trade openness and FLFPR and distinguishes the different contributions from exports and imports. The advanced threshold regression model assumes the existence of threshold value from trade to female employment. Thereby, targeted policies for the government should be applied to promote active female in the labour market.

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