| Pub. Date | : Apr, 2022 |
|---|---|
| Product Name | : The IUP Journal of Applied Economics |
| Product Type | : Article |
| Product Code | : IJAE20422 |
| Author Name | : Karuna Bohini*, C Hussain Yaganti** and Mini P Thomas*** |
| Availability | : YES |
| Subject/Domain | : Economics |
| Download Format | : PDF Format |
| No. of Pages | : 28 |
India's youth unemployment rose from 15.5% in 1991 to 23% in 2019. This period also witnessed a declining trend in India's youth to working-age population ratio from 33% to 27%. These statistics are aligned with the existing studies which postulate that if the working-age segment has a large proportion of youth in the age group of 15 to 24 years, it will lead to a high unemployment rate. Given such a context, this paper aims to examine and estimate the demographic, monetary and macroeconomic factors influencing India's rising youth unemployment, with the help of Autoregressive Distributed Lag (ARDL) approach to cointegration. This study also brings in a new dimension to the existing studies by providing an in-depth analysis of the role of millennials cohort, which entered the working-age segment in 1995, in contributing to India's rising youth unemployment. A disaggregated analysis of India's youth unemployment based on the criteria of education and gender has also been carried out.
Population shifts into specific age segments have implications on the economy and other demographic aspects. Demographic studies, including the demographic dividend theory, have propounded that when the population of a country is skewed towards a large working-age segment, savings in the economy grow for over a decade (Schultz, 2005). There are, however, certain prerequisites for the savings to grow and deliver the resultant dividend. Firstly, alongside a growing working-age population, there should be a declining dependent population trend, and secondly, there should be an increase in the Labor Force Participation Rate (LFPR) (Mason, 2005; and Bloom and Canning, 2011). This correlation established between age structure, labor statistics and economic growth garnered greater significance on unemployment in economic studies.