Tax pass-through with information asymmetry in an online labor market

  • Sep. 22-23, 2022
  • 12:00 am - 12:00 am


We use a regression discontinuity approach to study a change from a 10% flat tax to a marginal tax structure for workers in a large online labor market. Under the new regime, the first $500 earned with a given employer is taxed at 20%, earnings on the next $9,500 at 10%, and earnings above $10,000 at 5%. Our first finding is that average wages increased more than average fees. We give evidence that workers are uncertain about the length of the job when initially bidding a wage, and we do not find evidence of re-negotiation upon reaching the thresholds. Our second finding is that the fraction of jobs which made a hire decreased. These results suggest that this marginal tax structure without a credible signal of which bracket a job will end up in created inflated wages and a lower fill rate. We also propose an experiment to complement these findings by randomizing whether workers or employers pay the platform fees. Because employers have private information about how long a job will last, we hypothesize that job posts where fees are borne by the employer will get lower bids but have a higher chance of filling.

This event is open to faculty, doctoral students, academic researchers, and graduate students.

    The DI is now part of the Digital, Data, and Design (D^3) Institute at Harvard. Read more about this change..