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EXPANDING OPPORTUNITIES<br />

113<br />

The internet makes labor markets more efficient<br />

by connecting a larger pool of individuals and firms at<br />

lower cost. 56 Indeed.com, Monster.com, and elempleo<br />

.com are international platforms that aggregate job<br />

vacancies from different sources and allow firms to<br />

post job openings, and workers to apply for jobs and<br />

post résumés. Similar services exist for local markets,<br />

such as aldaba.com in the Dominican Republic and<br />

kariyer.net in Turkey. Social and professional networking<br />

sites also provide information on potential<br />

workers, often on behavioral aspects and social ties<br />

not reflected in traditional resumes. LinkedIn, the<br />

largest online professional network, has more than<br />

310 million registered members, 67 percent outside<br />

the United States. In Brazil, LinkedIn’s penetration<br />

rate is already at 8 percent. 57 In most countries, online<br />

job search remains concentrated among youth and<br />

the best educated and grows with income: online job<br />

search among the employed and unemployed is above<br />

20 percent in urban Armenia and Georgia, but below<br />

5 percent in urban Bolivia, Ghana, the Lao People’s<br />

Democratic Republic, Sri Lanka, and Vietnam. 58<br />

Online job boards, social media, and matching<br />

platforms can improve labor market efficiency, especially<br />

in developing countries and in the informal<br />

sector, where information failures are large. Online<br />

job matching is cheaper and faster than traditional<br />

methods. 59 In Peru, integrating mobile phones into<br />

traditional public intermediation services increased<br />

employment among job seekers by 8 percentage<br />

points in the short term. 60 In Germany, online job<br />

seekers are better matched to jobs, are happier with<br />

work, and have higher chances of promotion and job<br />

security. 61 But other studies find no effect of online<br />

tools on the speed of matching or on the length of<br />

unemployment. 62 The large number of applications<br />

per vacancy and stale resumes and job posts makes it<br />

costly for employers to select workers and for workers<br />

to find available jobs. As online tools become more<br />

advanced, however, matching is becoming more<br />

effective. In the United States, the average unemployment<br />

duration for internet searchers was 25 percent<br />

shorter than for noninternet searchers, reversing<br />

earlier results. 63<br />

Online tools can address many labor market frictions,<br />

but much of this potential remains unrealized.<br />

A first challenge is reaching lower-skilled workers.<br />

Some services, such as Souktel, are solving this via<br />

mobile phone (box 2.5). Babajob in India and Duma<br />

in Kenya have also implemented innovations to<br />

reach the bottom of the pyramid. They use text messaging<br />

and “missed calls” to connect low-skilled and<br />

informal workers to vacancies. A second challenge is<br />

Figure 2.9 Returns to education remain high despite<br />

significant expansion in the supply of educated<br />

workers, especially for tertiary education<br />

Average return to one additional year of education in tertiary education<br />

Percent<br />

25<br />

20<br />

15<br />

10<br />

5<br />

0<br />

2004 2005 2006 2007 2008 2009 2010 2011 2012<br />

Women, low- and middle-income countries<br />

Men, low- and middle-income countries<br />

Women, high-income countries<br />

Men, high-income countries<br />

Source: WDR 2016 team, based on Montenegro and Patrinos 2014. Data at http://bit.do<br />

/WDR2016-Fig2_9.<br />

Note: Includes 97 countries and only wage employees. The regressions control for potential experience<br />

and potential experience squared using individuals’ age.<br />

Figure 2.10 Returns to education<br />

are particularly high in ICT-intensive<br />

occupations<br />

Wage premium, beyond returns to education, for working in<br />

an ICT-intensive occupation<br />

Percent<br />

6<br />

5<br />

4<br />

3<br />

2<br />

1<br />

0<br />

Low- and middle-income<br />

countries<br />

Women<br />

High-income countries<br />

Men<br />

Source: WDR 2016 team, based on Monroy-Taborda, Moreno, and Santos,<br />

forthcoming, for the WDR 2016. Data at http://bit.do/WDR2016-Fig2_10.<br />

Note: An ICT-intensive occupation scores 4 or higher in an index between 0<br />

(no use of technology at work) and 6 (most use of technology at work).<br />

ICT = information and communication technology.

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