Economics & Sociology

ISSN: 2071-789X eISSN: 2306-3459 DOI: 10.14254/2071-789X
Index PUBMS: f5512f57-a601-11e7-8f0e-080027f4daa0
Article information
Title: Still ‘few, slow and low’? On the female dimension of technology, labour markets and economic activity: Evidence for the period of 1990-2017
Issue: Vol. 12, No 1, 2019
Published date: 03-2019 (print) / 03-2019 (online)
Journal: Economics & Sociology
ISSN: 2071-789X, eISSN: 2306-3459
Authors: Ewa Lechman
Gdansk University of Technology
Keywords: ICT, female labour, women, developing countries
DOI: 10.14254/2071-789X.2019/12-1/1
Index PUBMS: b38fc8e5-5d44-11e9-8b68-fa163e6feac6
Language: English
Pages: 11-38 (28)
JEL classification: O30, O40
This research is part of Project no.2015/19/B/HS4/03220 financed by the National Science Centre, Poland.

The known in empirical economics question ‘Why so Few? Why so Slow? Why so Low?’ refers here to the persistently small number of women involved in innovative activities, the slowness of change in the inequalities between women and men in these fields, and women’s continuing lower rank in business and academic positions. In developing countries, women`s labour and entrepreneurial activity remains an ‘untapped resource’ for economic growth. In recent years, the rising proportion of women participating in the labour market has drawn the attention of many scholars. This positive change towards mobilising previously unused human resources is perceived as one of the positive externalities enhanced by the seemingly boundless flow of information and communication technology. This research examines, from a macroperspective, the association between economic deployment of ICT, women`s labour market participation, and economic growth in 64 developing countries between 1990 and 2017. We rely on the macrodata extracted from the World Bank Development Indicators (2018), the World Bank Enterprise Survey, the World Development Reports and the World Telecommunication/ICT Indicators Database (2018). Our methodological framework, in addition to standard descriptive statistics, combines time trends, graphical non-parametric analysis and panel vector-autoregressive models.


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