The Delhi government has banned surge pricing by app-based taxi aggregator services such as Uber and Ola. Permanently lower prices benefit commuters, but they also lead to a lower number of taxis on the roads, resulting in complaints of non-availability and longer waiting times. Though a comprehensive cost-benefit analysis is only possible after analysing hard data, a simple thought experiment and some basic economic logic may provide preliminary answers.
Consider a situation of high demand, such as people attempting to go home after a movie show. Since the demand for taxis shoots up, surge pricing comes into force, in an attempt to equilibrate demand and supply. This has two benefits.
First, on the supply side, the higher prices signal that this is a valuable time for drivers to be on the road. In principle, drivers who at lower, 1x prices, did not find it worthwhile to work, will have greater incentive to do so after surge pricing kicks in. Similar logic creates incentives for drivers from nearby areas (which may have lower demand and hence lower prices) to move to areas of higher demand. Such reallocation of resources across time and space is impossible with a static, non-surge pricing model. (See: How Uber surge pricing really works http://wapo.st/1PUtLsm)
Second, surge pricing helps manage demand efficiently. A recent University of Chicago study (The Effects of Uber’s Surge Pricing: A Case Study http://bit.ly/1P83f0g) finds that with surge pricing, the number of app-openings is much larger than the number of actual Uber requests, suggesting that some people chose to take alternative modes of transport, or wait for the surge to abate. Others, through their willingness to pay higher surge prices, signalled that they valued the service more, and were able to get rides at the given point of time. Such “sorting” of people into those that value a service more or less is highly beneficial from an economic point of view and impossible with a static, non-surge pricing model.
Whether it is a busy neighbourhood in times of peak traffic or a lazy afternoon in central Delhi, surge pricing helps keep waiting times for taxis consistently low, providing a reliable transport service to commuters.
Such a rationing mechanism may be criticized because it favours the rich, who are less hurt by surge pricing. However, this argument implicitly assumes that without surge prices, all commuters will enjoy cheaper taxis. A closer look at how the market for taxis operates without surge pricing reveals that there may be significant short- and long-term supply-side adjustments that are not immediately obvious.
In the short run, a ban on surge pricing acts as a disincentive for drivers to come on the roads, especially when it is relatively costlier for them, such as at night or early in the morning. Similar logic may discourage drivers to weather heavy traffic and a high time cost that is required to reach a busy locality. For example, why would a taxi driver plough through the mess of Delhi’s Hauz Khas Village, if he can earn the same by ferrying passengers from Khan Market?
After the ban on surge pricing, the unavailability of Uber and Ola taxis has been widely reported in the media. Moreover, such instances are common at times when taxis are valued the most—late at night and during peak office hours. This is particularly inconvenient for women, who often prefer to travel by taxis due to safety concerns. For many commuters, it is the availability, and not the price of a taxi, that is a first order concern. In a city with inadequate public transport, especially at night, taxi aggregators provide reliable, relatively safe and a comfortable alternative for thousands of commuters. The claim that a ban on surge pricing is unambiguously welfare-enhancing is suspect.
The ban may also have undesirable, long-term effects. Consider the large difference between 1x prices of Ola and Uber taxis and fares of standard static-pricing radio taxis in Delhi (see chart). Taxi aggregators can sustain such low base rates, partly because they can charge higher in times of high demand. If the ban on surge pricing is permanent, revenue considerations may force the base, 1x rates to rise. Though surge pricing implies costlier taxis in times of peak demand, the counterfactual, in the long run, may result in more expensive taxis for everyone and at all times.
The intra-city market for taxis in Delhi is very competitive. This is reflected in price wars, lucrative incentives to drivers and discounted fares to riders. Last year, Ola slashed its rates twice between 27 May and 29 June: Ola Mini prices to ₹ 8/km from ₹ 10, followed by Sedan prices dropping from ₹ 16/km to ₹ 11. In the same year, rates for TaxiForSure (now merged with Ola) halved, from ₹ 14/km to ₹ 7 to match uberGO’s fare.
None of the above analysis of the working of the taxi market is weakened by the fact that the odd-even scheme is in operation. In fact, with a constraint on using one’s personal vehicle, the reliable availability of taxis is even more important. With no signs of market failure in the sector, and with several perverse implications of the ban on surge pricing, the Delhi government should reconsider its heedless intervention.
Ananya Kotia is a consultant at the National Institute of Public Finance and Policy, New Delhi. These are his personal views.
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