Employment growth/ skill requirement estimation in India: a non-traditional approach

Main Article Content

Tutan Ahmed https://orcid.org/0000-0003-4858-065X

Keywords

labour market, India, job forecasting, multiple data sources, Hadoop, machine learning

Abstract

There is a remarkable lack of regular labour market data in the context of a developing country such as India. Given the lack of regular labour market surveys, a lack of labour market data in the informal sector and the geographical vastness of the country, it is almost impossible to obtain labour market data regionally and regularly. Consequently, there is barely any possibility of obtaining job market forecasts. With the emphasis on skill development initiatives in India, the need for linking skill development initiatives with the labour market is felt quite prominently. Within this context, an initiative has been undertaken in India to develop a job growth and skill requirement forecasting model. It is a data-driven model to be designed with multiple sets of data such as job advertisements in websites, proxy data at the district level, and Government Survey data. Machine learning techniques will be used for prediction of job growth and skill requirement growth. This job forecasting model is likely to be cost-effective, easily replicated across districts and a tool for providing the forecasts for job growth and skill requirement growth regularly and comprehensively.


JEL Codes: J2, C81, C83, C88

Abstract 170 | PDF Downloads 51

Similar Articles

1-10 of 142

You may also start an advanced similarity search for this article.