Panchanan Das
Professor of Economics
University of Kolkata
(financial blog on behalf of GLARiUS Markets Intelligence – www.glarius.com) GLARiUS Platform
Professor of Economics
University of Kolkata
(financial blog on behalf of GLARiUS Markets Intelligence – www.glarius.com) GLARiUS Platform
The glass ceiling effect refers to a wider wage gap at the top of distribution, suggesting that temporary staff in high-income jobs are paid less than their permanent counterparts. The sticky floor appears when the gap widens at the bottom of the wage distribution. The relevance of glass ceiling or sticky floor hypothesis could be used to examine the wage penalty between workers in temporary and permanent employment across wage profile.
In India, employment has been generated mainly in the form of temporary employment of heterogeneous types during the high growth regime under economic liberalisation. Temporary workers do not enjoy social security benefits and they are getting wages according to the terms of the daily or periodic work contract. Temporary workers are casual workers and most of them have no written job contract, while permanent workers have written job contract for longer period. Permanent workers enjoy social security benefits and they get wage or salary payment on regular basis.
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The Kernel density estimates across the employment groups provide a rough idea about the existing wage penalty between workers in permanent and temporary employment. The density functions of daily wages for workers in temporary and permanent employment have been estimated by using an Epanechinov kernel estimator. As is shown by the shape of the estimated Kernel density function of log values of daily wages (Figure 1), the distribution of wage in permanent employment is significantly different from the wage distribution in temporary employment. The estimates reveal a larger proportion of the permanent workers to be in the higher wage levels. The two-sample Kolmogorov-Smirnov test is used to compare the observed cumulative distribution function for log values of daily wages with the normal distribution. The Kolmogorov-Smirnov Z-statistic is computed from the largest difference between the empirical and theoretical cumulative distribution functions. The test rejects the null hypothesis that the wages of the permanent and the temporary workers follow the same distribution at less than 1 percent level of significance (p-value = 0.001).
Figure 1 Kernel density function of log of daily wage
Workers’ education and skill have normally been treated as the major factors determining the status of employment of a person. But, in a transitional developing economy like India, higher level of education does not provide any guarantee for high status employment. There are some other factors, mostly relating to gender, social, political and other characteristics of a person that may determine the job status and the respective pay structure in the labour market.
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In India, the job distribution by education of permanent workers is not similar to that of the temporary workers. The proportion of higher hierarchy jobs is high among the permanent workers compared to the temporary workers. The incidence of low hierarchy jobs is high among permanent workers at education up to secondary level, but it is notably high at any education level among temporary workers.
We observe that the wage gap between temporary and permanent workers is wider in the upper tail of distribution supporting the glass ceiling hypothesis. Wage gap presents at every location of the wage distribution and the extent of the gap becomes wider as we move from bottom end to top end of the distribution. Wage gap increases with the level of workers’ education and it is extremely high in higher hierarchy jobs. The decomposition analysis suggests that the pay gap presents in the Indian labour market primarily because of discrimination measured by the coefficients effects.
The return to education at the upper tail is significantly higher than that at the lower tail of the wage distribution irrespective of the level of education. The wage gap presents among workers with differential technical know-how may be because of skill biased technological change during the post-liberalisation period.
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