scholarly journals Low Female Labor Force Participation in Pakistan: Causes and Factors

2018 ◽  
Vol III (III) ◽  
pp. 237-264
Author(s):  
Zubaria Andlib ◽  
Aliya H Khan

Pakistan has the lowest Female Labour Force Participation (FLFP) rate in the South Asian region. The study has used the latest round of Labor Force Survey 2014-15 and analyzed the individual and household factors that are associated with low FLFP in Pakistan. This study finds that there is less probability for urban women to take part in labor force activities. At national and regional level higher secondary and above levels of education have positive and significant relationship with FLFP whereas the situation is different for the four provinces of Pakistan. In case of Punjab province graduation and above levels of education are positively affiliated with FLFP, in Sind province higher secondary and above levels of education are positively associated with FLFP, in KPK province, matric and above levels of education are positively influencing FLFP decisions and in Baluchistan province primary and above levels of education are positively influencing women's decisions to participate in labor force activities. Women living in joint family systems, non-migrated, recipient of technical or vocational trainings are also more likely to participate in labor force activities. The study provides useful insights for policy makers to formulate appropriate policies to increase FLFP rate in Pakistan.

Author(s):  
Mbonigaba Celestin

The study evaluates the determinants of female labour force participation in Rwanda. The specific objectives were to establish the determinants of female labour choice to working in different sectors in Rwanda, and investigate the factors which affect female labour force participation in Rwanda. To be able to respond to the research questions and objectives, the Rwanda labor force survey data of year 2018 data collected by National institute of statistics of Rwanda (NISR) was used.  As this study, use national coverage data with a representative sample of 8936 households in the second round of august 2018, while the sample size in the first round of February 2018 was 8924 households. The validity and representatively of the sample was done and tested by NISR (2018).  The documentation on administrative data was done to compare and triangulation of results from the survey. The documents targets were available annual reports that talk about female labor force participation rate in 2018. The data analysis was done by descriptive statistical method to analyze data into quantitative by showing frequency, percentages and cumulative percent, the cross tabulation was used to show the relationship between dependent and independent variables, and finally logistic regression models was used to predict the odds ratios and probability of being employed and access the main determinant of female labor force market outcome in Rwanda. The study findings were summarized in accordance with the research objectives. The survey respondent’s female in employment ages includes 40.1% of female from urban and 59.9% female in employment age are from rural areas. Among which almost 40.8% of female surveyed were married with one husband. It is evidenced that many females are single not yet married (34.5%). The findings show that to analyse the socioeconomic and demographic factors determining the factors of female employment in public institutions and the choice of employment using labor force survey data collected by NISR in the year of 2018. The multinomial and binary models provided almost the same trends in explaining the determinants of female employment in Rwanda, explained by near similar coefficients and odd ratios either in magnitude and sings. This technique helped to examine probable determinants of female employment and the estimation of these probabilities of being employed or being government employee. Hence, the findings of this study help us to confirm that the problem of the study was solved, research objectives were achieved, and research questions were answered where we confirmed that there are different determinants of female labour force participation in Rwanda. Government should develop the Soft skills which are important for both men and women, women may benefit more from soft skills training to foster self-esteem, decision-making, negotiation skills, and perseverance, for example. Acknowledging women’s time constraints, provide flexible schedules and various time options for participation in services (e.g., mornings, evenings, and weekends).


Author(s):  
Prakash Kengnal ◽  
Asha Bullappa

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.


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