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

Tutan Ahmed
Additional contact information
Tutan Ahmed: Vinod Gupta School of Management

Australian Journal of Labour Economics (AJLE), 2018, vol. 21, issue 3, 253-268

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.

Keywords: labour market; India; job forecasting; multiple data sources; Hadoop; machine learning (search for similar items in EconPapers)
JEL-codes: C81 C83 C88 J2 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://ftprepec.drivehq.com/ozl/journl/downloads/AJLE213ahmed.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ozl:journl:v:21:y:2018:i:3:p:253-268

Access Statistics for this article

More articles in Australian Journal of Labour Economics (AJLE) from Bankwest Curtin Economics Centre (BCEC), Curtin Business School Contact information at EDIRC.
Bibliographic data for series maintained by Sandie Rawnsley ().