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Expert Services and Fraud in Taxi Markets: Evidence from Athens, Greece

This study examines the presence of fraud in the taxi market, where taxi drivers provide an expert service. The research investigates how overtreatment and overcharging vary based on passenger origin, familiarization with the city, and income level.

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Expert Services and Fraud in Taxi Markets: Evidence from Athens, Greece

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  1. 1 Expert Services – Credence Goods • Definition • an expert seller knows more about the quality a consumer needs than the consumer herself • Examples • repair services (cars, computers) • medical treatments • Problem: • the expert can cheat • overtreatment - providing a unnecessarily high quality • undertreatment - providing a too low quality • overcharging - charging unjustifiably much

  2. 2 Expert Services – Literature • Theory • Darby and Karni (1973) • Dulleck and Kerschbamer (2006) • Experiments in the lab • Dulleck, Kerschbamer, and Sutter (2010) • Field data • Hughes and Yule (1992), Gruber and Owings (1996), Gruber et al. (1999), Izuka (2007):medicine • Schneider (2009):car repairs • Problems with data collection, control • Our solution: Natural field experiment in the taxi market

  3. 3 Taxi services • Literature on labor supply of taxi drivers (Camerer et al., 1997; Farber, 2005; Farber, 2008, Crawford and Meng, 2011), and on stopping behavior of taxi drivers (Gambetta and Hamill, 2005) • however, little is known about the actual product taxi drivers sell – an expert service! • Possible types of fraud • overtreatment = taking longer route • overcharging = charging more than justified by chosen route (e.g. night tariff, fictional fares etc.) • undertreatment ruled out

  4. 4 Research Question – Hypotheses • H1: Information about city • passengers who are not familiar with the city are more likely to face overtreatment • H2: Information about fares • passengers who are not familiar with the fares are more likely to face overcharging • H3: Income • high-income passengers receive worse service than low-income passengers

  5. 5 local native non-local native foreigner low income 29 29 29 high income 29 29 29 Treatments • Treatment design: 3x2 • 174 taxi rides in Athens, Greece

  6. 6 Method • The experiment • three experimenters (all male in their mid-late twenties) • manipulation of origin • simultaneous observations: same starting point, same destination, different roles • create reference point with local native • randomization over routes, days, and time

  7. 7 Method – Signaling Income • High income • wearing suit • top-end hotel • Low income • shabby clothes • low-end accommodation

  8. 8 Method – GPS Logger • keeping track of fraud • GPS-logger • records exact position every single second • allows reconstructing exact route, duration etc.

  9. 9 Method • Facts • 15 routes • 63 h net driving time • 2,236 km net travelled distance (≈ Innsbruck to Damascus) • 13 km mean trip distance • 22 min mean trip lenght • 3% female drivers • 42% Skoda, 30% Toyota

  10. 10 Method – Routes

  11. 11 Example for Overtreatment

  12. 12 Example for Overtreatment OT-index: 1.43 additional distance: 4.2km

  13. 13 Example for Overcharging non-local foreigner local price-index: 1.61 additional fare: €9.5

  14. 14 locals non-locals foreigners price-index 1.04 1.09 1.19 +4.4% +9.3% / +14.2% Results – Origin of Customer

  15. 15 locals non-locals foreigners OT-index 1.03 1.08 1.08 +5.4% +-0 / +5.4% Results – Origin of Customer

  16. 16 locals non-locals foreigners OC frequency 0.02 0.03 0.17 +50% +567% / +850% Results – Origin of Customer

  17. 17 price-index locals non-locals foreigners total low income 1.01 1.07 1.19 1.09 high income 1.07 1.11 1.18 1.12 Results – Income of Customer

  18. 18 OT-index locals non-locals foreigners total low income 1.01 1.06 1.06 1.05 high income 1.05 1.10 1.11 1.09 Results – Income of Customer

  19. 19 OC frequency locals non-locals foreigners total low income 0.00 0.00 0.21 0.07 high income 0.03 0.07 0.14 0.08 Results – Income of Customer

  20. 20 (1) Price Index (2) Overtreatment Index (3) Overcharging Dummy nonlocal 0.101** (0.051) 0.093*** (0.035) 0.018 (0.027) foreign 0.147*** (0.054) 0.005 (0.024) 0.094 *** (0.045) rich 0.046 (0.045) 0.060** (0.026) 0.018 (0.045) timezone -0.000 (0.003) -0.004** (0.002) 0.006 ** (0.003) Additional controls Yes Yes Yes Results – Econometric Analysis

  21. 21 Conclusion • Overtreatment: more extensive for passengers who are not from the city (H1) • Overcharging: more common for foreigners (H2) • Income: Partial effects only (overtreatment) • (Some) taxi drivers know whom to cheat and how to cheat!

  22. 22 Thank you!

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