The influence of licensing on real estate agents’ income: An analysis using propensity score matching

Chung-Chang Lee (), Pei-Syuan Lin (), Ya-Zhu Hong () and Jun-Chao Chen ()

Humanities and Social Sciences Letters, 2025, vol. 13, issue 1, 344-364

Abstract: This study explored the influence of real estate licenses on their income. The potential interference of personal attributes was controlled using propensity score matching to reduce selection bias. On average, the matching results showed that the treatment effect was 0.42 indicating that licensed agents had a 42% higher monthly income than unlicensed agents after matching. The regression found that the coefficient of licensing was 0.397 at a 5% significance level. Indeed, licensed agents had a 48.7% higher monthly income than unlicensed agents. This indicates that the monthly income gap between licensed and unlicensed agents was smaller after accounting for the estimation efficiency and including the control variables. The main reason for the large differences between our findings and those of previous studies is the use of regression analysis in the latter. The results suggest that real estate agents should be more aware of the importance of professional licensing for gaining a higher income.

Keywords: Average treatment effect on the treated; Income; License; Propensity score matching; Real estate agent. (search for similar items in EconPapers)
Date: 2025
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