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Purpose: This study aims to examine the association between productivity growth and job reallocation in terms of job creation and job destruction. It also finds this productivity employment relationship for heterogeneous labor market institutions of the Indian states. Design/methodology/approach: The paper uses longitudinal data of the Annual Survey of Industries of Indian manufacturing from 2009–2010 to 2015–2016 and employs fixed-effect multinomial logistic regression. Findings: The paper finds a mixed result of total factor productivity (TFP) increase on employment. An increase in TFP is positively associated with employment by reducing the probability of destroying jobs, while adversely associated with employment by reducing the probability of creating jobs. The negative association of the increase in TFP on employment is more in the Indian states with strict labor regulations. Research limitations/implications: The relationship between TFP and employment can be endogenous. TFP is calculated as output changes that are not explained by inputs, capital and labor. So, job creation/destruction may affect TFP by changing the composition of employment and/or returns on labor/capital. In addition, this study is only restricted to Indian organized manufacturing. Practical implications: The results from this study help deeply understand the Indian labor market. In particular, it provides valuable insights into the "jobless growth" in Indian manufacturing and the recent changes in labor laws. Social implications: The findings from this study provide useful information to enhance the robust growth of productive jobs and efficient reallocation of labor. Originality/value: Unlike most papers, which analyzed the relationship between productivity growth and net employment changes, the present paper finds the relationship between improvement in productivity and job reallocation in terms of simultaneous creation of new jobs and destruction of existing jobs. In addition, the paper links this relationship with the existing heterogeneous labor laws of the Indian states. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the interrelation between two important dimensions of gender segregation: education and occupation. It further investigates the gender wage gap. Design/methodology/approach: The author uses a three-way additive decomposition of the mutual information index – an index based on the concept of entropy. A non-parametric wage decomposition method that uses matching comparisons is used for measuring the wage gap. Findings: The results show that the extent of gender segregation in India is higher in urban areas than that in rural areas. Most of the observed segregation in rural labour markets originates from educational outcomes, whereas in urban markets it is due to occupational profile of individuals. The findings of the wage decomposition analysis suggest that education in rural areas also explains a sizeable part of the gender wage differential. Nevertheless, a large share of the wage gap remains unexplained in both rural and urban areas. Originality/value: While much research has looked at occupational segregation, less attention has been paid to educational segregation. The paper uses a unique approach to understand the joint effect of occupation and education in explaining gender segregation. [ABSTRACT FROM AUTHOR]