Dr Benedikt Koehler
Dissertation submitted in partial fulfilment of the
MSc in Economic Regulation and Competition
Department of Economics
City University, London (England)
The paper is concerned with supply of taxis in markets with quantity and price restrictions. The paper models an Index of Potential Supply (IPS) for use in taxi market regulation.
Economic regulation of taxi markets encompasses quantity, quality and prices. Taxi market regulation originally applied to quantity and quality but did not extend to fares. In the nineteenth century price regulation began as a means of consumer protection. From the 1930s price regulation took on the purpose of income protection.
The paper reviews arguments for and against entry and price regulation, and research on licence values. Licence values existed since the introduction of quantity restrictions. Since the introduction of price regulation licence values have increased dramatically. Licence values manifest monopoly rent.
The paper reviews entry and price deregulation in taxi markets. Outcomes did not confirm expectations. Even though increased supply typically results in lower prices, prices often increased rather than declined. This outcome shows the need for further research.
The paper features a spreadsheet showing how price levels and elasticity of demand predicate the number of taxis. An Index of Potential Supply (IPS) equips regulators with a supply side tool for assessing the effects of changes to quantity and fare levels.
Changes in taxi numbers have repercussions on licence values. The paper asks whether reductions in licence values are tantamount to regulatory taking. The paper cites cases from separate jurisdictions showing this view does not stand up in court.
An Appendix narrates the evolution of taxi services in the context of the evolution of transport infrastructure.
Right click to download the spreadsheet, a 25Kb Excel xls file.
The first section features data on taxi markets. The second section derives ratios from these data. The third section features two cells where users can introduce assumptions.
Cell A 29 allows the user to raise or reduce price per mile.
Cell B 29 allows the user to assume different elasticity of demand.
Changes to A 29 and B 29 affect revenue per cab. Depending on elasticity of demand, cab revenue may go up even if nominal prices decline.
The fourth section of the spreadsheet models how the number of taxis would go up or down. This is how it works: changes to revenue/cab are grossed up to arrive at an industry total. The difference to industry total is divided by the figure for revenue/cab to show net market entry or exit.
Taxi regulators can use this spreadsheet by changing the data to reflect their own market. Then, they can model different price setting scenarios and see their effect on taxi numbers. This puts them into a position to compare current market conditions with 'what-if' scenarios.
When licence values go up year after year, then the implication is that markets are clearing at prices in excess of competitive equilibrium. The spreadsheet shows how much room for additional taxis exist, depending on your price regime.
Go to the complete paper, a 625Kb PDF document.
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