Impact of Digital Economy on Female Employment: Evidence from Turkey

ABSTRACT

This paper investigates impact of e-economic activities on female employment rates in Turkey over 1994–2016. The analysis unveils three major findings. First, 80.74% of variations in female employment are accounted by e-commerce and control variables. Second, Autoregressive Distributed Lag analysis documents that these series (female employment, e-commerce and control variables) are cointegrated, thus, a unit increase in per credit card e-commerce transactions leads the female employment rate to grow by 0.13 units in long-run at 1% significance level, whereas a percentage increase in internet penetration rate in Turkey augments the rates by 0.33%. Third, error-correction model analysis refers that the system quickly corrects its previous period disequilibrium converging at a speed of 75.43%, and also documents that the lags of per credit card e-commerce jointly have short-run impact on female employment rates. Thus, the study concludes that developing e-commerce incentivizing policies might help to empower women in Turkey significantly.

KEYWORDS:

• Female employment
• job creation
• e-commerce
• digitalization
• cointegration
• ARDL bound test

JEL CLASSIFICATIONS:

• L81
• J21
• J16
• F16

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1 http://www.internetlivestats.com/:

Worldwide Internet activities in 1 second: 1,948 Skype calls; 10,860 tweets; 51,750 google searches; 112,345 youtube video plays; 3,081 Instagram photo uploads; 800 Apple store and 964 Android store app downloads; 312,500 whatsapp messages; 2,446,928 emails (it was just 113,000 emails in 2000); 3 new websites (there was only 1 website in 1991, but today it is about 1 trillion websites); 5 computer and 40 smart phone sales; USD 2,361 Amazon sales; and 31,368 GB of internet traffic.

2 See Lisbon European Council 23–24 March 2000 Report at http://www.europarl.europa.eu/summits/lis1_en.htm.

3 See OECD ‘Statistics of Female Employment’ at http://www.oecd-ilibrary.org/employment/employment-rate-of-women_20752342-table5.

4 See TurkStat ‘Labor Statistics’ at https://biruni.tuik.gov.tr/isgucuapp/isgucu.zul.

5 Long-run multipliers for EC, IP, GDP, and INF are calculated by formula –ϕ_i= ϕ₁ where i represents related explanatory variable. In this respect, long-run multiplier for EC is −0.1689/−1.2785 = 0.1321; for IP is −0.4243/−1.2785 = 0.3319; GDP is −0.0681/−1.2785 = 0.0532; and for INF is −0.0307/−1.2785 = 0.0240.

Additional information

Notes on contributors

Yhlas Sovbetov

Yhlas Sovbetov holds PhD degree in Economics from Istanbul University, and is currently a research fellow in the Department of Economics at London School of Commerce. His areas of research interest include international economics, growth economics, labour economics, early crisis warning sytem (EWS), financial economics, and asset pricing.