DP13786 Information, Mobile Communication, and Referral Effects

Author(s): Panle Jia Barwick, Yanyan Liu, Eleonora Patacchini, Qi Wu
Publication Date: June 2019
Date Revised: July 2019
Keyword(s): Entrop, Information, Mobile Communication, Social Networks, Urban Labor Market
JEL(s): J60, L15, R23
Programme Areas: Labour Economics, Public Economics, Industrial Organization, Development Economics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=13786

Information is a crucial ingredient in economic decision making. Yet measuring the extent of information exchange among individuals and its effect on economic outcomes is a difficult task. We use the universe of de-identified cellphone usage records from more than one million users in a Chinese city over twelve months to quantify information exchange among individuals and examine the role of referrals -- human carriers of information -- in urban labor markets. We present the first evidence that information flow (measured by call volume) correlates strongly with worker flows, a pattern that persists at different levels of geographic aggregation. Condition on information flow, socioeconomic diversity in information sources (social contacts), especially that associated with the working population, is crucial and helps to predict worker flows. We supplement our phone records with auxiliary data sets on residential housing prices, job postings, and firm attributes from administrative data. Information passed on through referrals is valuable: referred jobs are associated with higher monetary gains, a higher likelihood to transition from part-time to full-time, reduced commuting time, and a higher probability of entering desirable jobs. Referral information is more valuable for young workers, people switching jobs from suburbs to the inner city, and those changing their industrial sector. Firms receiving referrals are more likely to have successful recruits and experience faster growth.