Learning by doing: Evidence from taxi driver wages in Singapore

The significance of “Learning by doing” (LBD) in the economy has been disputed by economists. We use a unique dataset from a Singaporean taxi fleet consisting of 3,250 drivers with over 520 million data points that tracks minute by minute cabdrivers’ work routine for two years to test if taxi drivers exhibit LBD phenomenon. After controlling for individual level differences i.e. socio-economics, we find strong evidence of LBD. Next, we document the mechanism and show taxi drivers learn through temporal (when) and locational (where) and technology (booking) optimization. The study has general implications on the contribution of LBD behaviour in the economy and its direct impact on individual wages. We also discuss the implication of our findings for taxi markets experiencing a rise in use of technology (i.e. booking systems based on applications) which is particularly of recent interest to policymakers.

Keywords: Learning-by-doing, Wages, Labor Supply, Taxi Drivers

JEL Classification Codes: J22, B49

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