WageIndicator Foundation - Kabina, T., Varkkey, B., Korde, R., & Bizik, P. (2015). WageIndex Report India: WageIndicator Foundation, Amsterdam; CELSI, Bratislava; Monster India, IIMA, Paycheck India, Ahmedabad.
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ABSTRACT
The analysis presented in this report is based on the WageIndicator dataset covering the period of 2 years and 9 months, from January 2013 to September 2015. This report provides a comparison of wage and working conditions figures for three periods: calendar year 2013, calendar year 2014 and the first three quarters of 2015 (January – September 2015). The wage analysis is based on data collected from the Paycheck.in, Salary Calculator and Monster Salary Index from the aforementioned periods. The sample used for the analysis consists of 31,193 respondents, approximately 86.50% of which are men and the remaining 13.50% are women. The sample contains only employees; wages of self-employed people are excluded. Employees from different age groups, varied industries, and various hierarchical positions in their respective occupations are included in the sample.
WageIndicator and Paycheck India regularly survey and evaluate the Indian labour market. Being an online volunteer survey, the data is biased towards those people who have access to the internet and are inclined to complete the questionnaire. Because of this limitation, the data captures only the organized sector in India.
The data from the Indian labour market analyzed in this report is classified into eight different sectors: Legal and market consultancy, business activities; Information and communication technology (ICT); Health care, caring services, social work; Education, research; Financial services, banking, insurance; Transport, logistics, communication; Construction and technical consultancy; Manufacturing. As the analyzed data comes from online surveys, it has some specific characteristics, such as the sectoral structure of collected observations: the majority of observations come from these three sectors: Financial services, banking, insurance (23%), Manufacturing (21%), and ICT (19%).