Research Interests : Macro Labor - Search and Matching, Social Networks, Inequality, and Economic Theory

Papers

"The Cyclical Behavior of a Firm's Optimal Market and Referral Hiring (PDF)

Abstract: Empirical evidence from the United States (U.S.) and the European Union (EU) shows that referral hiring is procyclical, while market hiring is countercyclical, with labor productivity. I built and calibrated a stochastic search-and-matching model in which firms choose between allocating resources to market and referral hiring. Expected match quality is endogenous, and referred workers expect to earn 16% higher wages. Optimal allocation choice is characterized by a quantity-quality-cost tradeoff. Precisely, for the employer, the referral channel is less likely to connect with a job applicant, is more likely to bring a ``good-fit" applicant, and has a lower per-hire cost. I also allow the effectiveness of referrals to differ from the network-implied contact rate through a preference-bias wedge that shifts the conversion of referral contacts into callbacks/offers and hires. I study three aggregate environments: productivity shocks only; a linked separation-risk specification in which separations are countercyclical with productivity; and a joint-shock specification in which separation risk fluctuates independently. I show that turnover risk strengthens cyclical reallocation across channels. It does so by shifting the expected match duration and vacancy posting. Quantitatively, the joint specification generates the largest hiring fluctuations among the remaining two specifications. It accounts for about 83% of cyclical variation in market hiring and 63% in referral hiring in the targeted U.S. economy. By contrast, the other regimes deliver about 24-61% of cyclical hiring variation in the U.S..

"Market vs Referral Hiring: Implications on Aggregate Welfare, Match Quality and Wage Inequality with Yun Pei (PDF)

Abstract: Empirical evidence from the Survey of Consumer Expectations (SCE) suggests that, in the U.S., between 2013 and 2021, on average, about 50% of workers were hired by a firm through employee referrals and the market channel during a given survey year. This paper builds and calibrates a deterministic Diamond-Mortensen-Pissarides (DMP) search and matching model to study what governs a firm’s optimal market and referral hiring decisions. At the calibrated steady state, we find that, relative to the market channel, the referral channel is more likely to produce a good match, is associated with a lower hiring cost, but also has a lower probability of a match. These trade-offs eventually imply that each channel is equally profitable to hire for a firm. Furthermore, the model is simulated to show that the market hiring rate decreases and the referral hiring rate increases with labor productivity, implying higher aggregate match quality and expected wage gap, favoring referred applicants. Regarding the policy implications of the model, higher unemployment benefits decrease vacancy postings, which in turn increase the unemployment rate, reduce market tightness, encourage market hiring, and discourage referral hiring.

Work in Progress

"A Dynamic Model of a Firm's Market and Referral Hiring"

"Optimal Unemployment Insurance and Firm's Market & Referral Hiring "