No Magic for Market Entry in the Field: Evidence from Taxi Markets

Abstract

We study taxi markets in Singapore to understand market entry in the field. Although market-entry games in the laboratory consistently produce equilibrium outcomes, we show that a lack of market knowledge hinders the markets from consistently reaching equilibrium in the field. In Singapore, a small, 720-square-kilometre island city that can be divided into 29 taxi markets, full equilibrium is elusive: 68% of the market-entry decisions made by the 2,728 taxi drivers in our data could be improved. Using three months of earnings and detailed movement data from these taxi drivers, we find an average 20% gap in marginal wage rates across markets. We use dynamic programming to derive the optimal solution for more than 3 million search decisions and find that only 32% of the searches ended in an optimal market. Finally, we find that market knowledge developed in a given month explains an additional 3% variation of the earning losses in the 2.6 million decisions for the subsequent two months, an improvement in model fit of 74%, whereas strategic thinking and minimization risk have no impact on earning loss. This paper was accepted by Yan Chen, behavioral economics and decision analysis.