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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 its role in urban labor markets. We present the first empirical evidence that information flow (measured by call volume) correlates strongly with worker flows, a pattern that persists at different levels of geographic aggregation. Conditional on information flow, socioeconomic diversity in the source of information (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 social contacts 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 sectors. Firms receiving referrals are more likely to have successful recruits and experience faster growth.
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We use the universe of de-identified and geocoded cellphone records for 1.8 million individuals from a major Chinese telecommunication provider to examine the role of information exchange in urban labor markets. Information flow, as measured by call volume, correlates strongly with worker flows at different levels of geographic aggregation. Having a referral in a location increases by close to four times the likelihood that a job switcher moves there. Different from the communication pattern between nonreferral pairs, communication between referral pairs exhibits a distinct inverted-U shape that peaks prior to the job switch. Compared with our referral measure, the commonly-used social network proxies deliver a lower bound estimate of the referral effect. We supplement the phone records with administrative data on firm attributes and auxiliary data on job postings and residential housing prices. 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 sectors. Firms receiving referred workers are associated with more successful recruits, higher matching rates and faster growth.
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