A CASE OF EXCESSIVE PRICE UNDER

DYNAMIC PRICING COMPETITION

SCHEME

A study case of surge pricing in transportation

network economies

The expansion of the internet, mobile applications and

new technologies has changed the way that many

industries set prices – allowing them to increase or

decrease prices in a short time without incurring in any

significant cost when changes of demand occur. In the

ridesharing service the increase in price is call surge

pricing whereas many consumers have complained

about the jack-up in prices due possible arbitrage

opportunity some argue its efficiency. How

competition authority should act on this cases of

excessive price under a dynamic pricing competition?

Mauricio Escalera Franco Master in Competition and Market Regulation 2015-2016

Advisor: Anna Merino

MASTER PROJECT

A case of excessive price under dynamic pricing competition scheme

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INDEX

1 Introduction .......................................................................................................................................... 2

2 Background and Application of Dynamic Prices ................................................................................... 3

3 Dynamic Prices in the Transportation Industry .................................................................................... 5

4 Surge Pricing as an Excessive Price case ............................................................................................. 10

5 The effective test criteria for the Surge Pricing. ................................................................................. 15

6 Concluding remarks ............................................................................................................................ 20

7 References .......................................................................................................................................... 21

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1 INTRODUCTION

The expansion of the internet, mobile applications and new technologies have changed the way that many

industries set prices – allowing them to increase or decrease prices in a short time without incurring in

any significant cost when changes in demand occur. This way of setting prices is called dynamic pricing

(DP) and it is a major component of the so called sharing economies as well as other type of industries

with digital sales environment. However, some firms with certain market power could use DP to incur in

first-degree price discrimination in a short period.

Thereby, in the last years, the transportation industry is one of the industries that has joined to the trend

of using DP, in particular the taxi industry, usually called ridesharing service uses DP to allocate more

efficiently riders and drivers. One particular feature of DP in the ridesharing sector is the surge pricing,

which allows by a simple multiplier increase the price in order to match demand with supply. Though, the

surge pricing has created discomfort among users who believe that prices are excessive in some

circumstances whereby authorities have stepped into the matter and have issued different remedies to

regulate the DP in the ridesharing industry.

Having said that, the next project aims to analyze the economics of DP in overall and surge pricing in

specific. In doing so, the theory of harm of surge pricing is going to be a case of excessive price and, hence,

the remedies of regulate the price. In particular, I analyze the effects of capping surge pricing in Mexico

City and the competitive effects of those measures.

Finally, a friendly warning, this paper does not intend to analyze the regulation framework of the

ridesharing services thus only intends to analyze the possible anticompetitive effects of the surge pricing.

The paper is organized as follows. In section 2, I present the economies of Dynamic Pricing, the industries

where is more common this setting and I argue that more markets will be setting prices on a dynamic way

thus more cases of first price discrimination might appear. In section 3, I aboard how dynamic price has

changed the static taxi industry, opening room to ridesharing firms, however, in some cases consumers

would feel ripped off due to excessive surge pricing and in those cases competition authority should act

to avoid arbitrage opportunity. In section 4, I analyze surge pricing as a case of excessive price whereby I

conclude that only when certain rigorous accumulative conditions are meet, we should act against a surge

price or any dynamic price as an excessive price. In section 5, I link chapter 3 and 4 in order to evaluate

the decision of the Mexico City local government to cap the price under the test suggested in section 4

A case of excessive price under dynamic pricing competition scheme

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and the effects of the remedies issued by the authority. Finally, as conclusion I remark the importance of

authorities to have effective criteria test for excessive prices under a dynamic setting.

2 BACKGROUND AND APPLICATION OF DYNAMIC PRICES

One of the most important objectives of companies is to maximize profitability under the constraint of a

limit capacity, thus offering optimal selling prices to attract potential customers or maintain current

customers. Under this context Dynamic Pricing (DP) is a way to adjust prices in a short time without

incurring in large costs whenever there is a change in demand and to allocate more efficiently the product

among price sensitive consumers or consumers with the highest valuation for the product. Moreover,

according with Den Boer (2013), digital sales environments or digital markets generally provide firms with

an abundance of sales data to understand the preferences of consumers. This amount of data may contain

important insights on consumer behavior, in particular on how consumers respond to different selling

prices, making easier for those firms to use DP.

Additionally, firms would decide between DP or static prices depending in the cost incurred when

changing the price. Normally in the economic literature this cost is called menu costs (Mankiw, 1985) and

it referrers to all the costs implicit while changing the prices. Alternatively, firms would also consider

consumers’ strategies, uncertainty and perception to decide between both alternatives. However, in

based digital markets the costs associated with changes to the prices are greatly diminished (Smith, M.J.,

2000), intensifying competition which benefits consumers.

The literature on DP is vast and extensive, with contributions from different fields. Den Boer (2013) does

a compilation of more than 120 economic research papers in the field but only centers his work in DP with

incomplete demand information under a monopoly or competitive market structure. Den Boer divides

the DP literature in:

1) references prices based on price past history and expected changes;

2) dynamic of the optimal price caused by inventory level.

2.1) Inventory restriction – Bayesian or Non-Bayesian framework-

2.2) No Inventory restriction – Bayesian or Non-Bayesian framework-

Consequently, the applications of DP are common in several industries and extensive literature by industry

can be found. Unfortunately, there is no a work such Den Boers´ that compiles most of the research done

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in DP by industry, so the next examples intend to get a bit of insight in industries where DP is more widely

used; it is also intended to be a starting point for those who are more interested in DP in a specific industry.

For example, in the airline industry where the first real application of DP can be found, Preston and Velde

(2007) find that dynamic price discrimination is only important in the last twenty or so sales, and the most

important effect of DP is that addresses an incomplete flight.

Abdel et al. (2011) modelled a DP policy to optimize maximum revenue in hotel room booking. In

electronic commerce or online retailing Demirci and Alptekin (2013) point out that three factors

contribute the use of DP in the industry, such as: 1) increased availability of demand data; 2) ease of

varying prices using new technologies; and 3) an availability of “decision support tools” to analyze demand

data and pricing dynamics. In perishable products such as ticket events, Sweetings´ (2012) DP model

supports the idea that for sport tickets it is optimal for sellers to cut prices substantially as a game

approaches. In the electricity market some countries have started to use a real time prices instead of the

traditional two-part tariffs, Brennan (2002) has positive externalities for reduce the probability of random

blackouts while Jessoe and Rapson (2013) conclude that dynamic retail pricing mitigate market power and

make residential consumers more efficient in their consumption.

Finally, in the private transportation industry or ridesharing economies, the DP started with the irruption

of Uber in the market so the next chapter is dedicated to the research done in the transportation industry

and the benefits of using DP in the industry.

Despite the many benefits of DP across different industries, economists have seen DP as a way of price

discrimination because the same product can be sold with different prices over time or consumers. Even

though there are several classifications of price discrimination, one of the first to take into account a

dynamic perspective is Armstrong’s (2006) who defines three types of price discrimination: 1) static price

discrimination to final customers; 2) dynamic price discrimination to final customers; and, 3) price

discrimination to downstream customers by an upstream supplier.

Following with the same author, he pointed out three important reasons why competition policy might

be concerned about price discrimination. First, the dominant firm may address exploitative strategies and

extract consumer surplus. Secondly, in Europe due to a single market policy issues firms are forbidden to

segment markets in order to prevent parallel imports. Third, a dominant firm could exclude actual or

potential rivals using price discrimination.

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Hence, some forms of DP would not be legitimate under article 102 EC. On the one hand, when firms offer

low prices that are not profitable can take the form of predatory pricing. On the other hand, when firms

charge “unfair” prices or high prices, it’s considered as a case of excessive pricing due the exploitative

abuse. In both practices there is a loss in welfare, in some cases the price induces competitors to exit the

market (predatory pricing) and in other the price extracts the consumer rents (excessive prices).

In sum, the decreasing cost of information technology indicates that more industries will start to use DP

in a normal basis thus competition authorities should be prepared for dealing with more cases of price

discrimination. Moreover, the available data-mass collection and automated algorithmic is making to

firms know the true value of a product for consumers in order to leave consumers without surplus, even

without the need of possess a dominant position in some cases.

As the project only limits to the analysis of excessive prices under dynamic framework with exploitative

effects on consumer surplus; the next chapters focus the attention to DP in the transportation industry as

a case of excessive price when firms increase the price or surge the price to apply dissimilar conditions to

an equivalent transaction. We study more carefully this practice due to large complaints of consumer

perceive surge pricing as an opportunistic behaviour of Uber for extracting more rents, and in some cases

authorities have forbidden surging practices, as in example in New Delhi, India1; or have capped the

surging price as in Mexico City, Mexico2, as well as ongoing price regulation in the sector by other

authorities.

3 DYNAMIC PRICES IN THE TRANSPORTATION INDUSTRY

In the past 8 years new companies such as Uber, Lyft, Side Car and other similar, normally called

ridesharing services, have changed the status quo of the conventional taxi business model. Nowadays the

most important firm in the industry is Uber which has operations in 468 cities around the globe including

50 cities in Europe, moreover, it has been estimated to be value $62.5 billion dollars3.

This exponential grow has been possible thanks to use of modern internet-based mobile applications

(apps) that connects passengers and drivers in a two-sided platform. Also, contrary to the traditional rigid

1 Financial Times (2016). New Delhi bans Uber “surging prices”. Retrieved from http://www.ft.com/cms/s/0/742d189a-0785-11e6-96e5-f85cb08b0730.html 2 Gonzalez, N., (2015). In the courts and in the streets: Uber in Mexico City. Council on Hemispheric Affairs. Retrieved from http://www.coha.org/in-the-courts-and-in-the-streets-uber-in-mexico-city/#_edn3 3 Newcomer, E. (2015). Uber raises funding at $62.5 billion valuation. Bloomberg Technology. Retrieved from http://www.bloomberg.com/news/articles/2015-12-03/uber-raises-funding-at-62-5-valuation

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taxi fares which has a starting price plus a charge per kilometer and/or charge per minute, the ridesharing

services uses a dynamic tariff by which it matches supply and demand. Additionally, the ridesharing

services is an activity that is part of broader economy called “sharing economies” that basically depend

on online platforms which matches providers of different underused assets or services with consumers´

need, Botsman (2015). In the ridesharing economies the underused assets are personal cars and the

platform is the app that connects riders with drivers in exchange of a fee commission that is around 15%-

25% of the service.

There are many competition and regulatory challenges in the sharing economies due to the involvement

of new forms of production, transaction and consumption that involve real-time data. According to some

commentators’ traditional business models, do not compete with the same regulatory field against

sharing economies so some anti-competition complaints can arise. In the case of ridesharing services,

normally drivers4 do not possess the medallion and license required for normal taxis, avoiding thus sunk

costs; another concern is that prices charged can also be below the fixed taxi rates set by authorities which

taxis cannot compete against; and, finally the surge in pricing, main topic of this paper.

It is important to point that back in the days not only all the medallions and licenses in the taxi industry

was pro-consumer in order to ensure quality and reliability in the service; but also a rate control by the

authority was necessary to generate certainty due to the lack of coordination of consumers (Geradin,

2015). Thus, after decades of relatively any change, new technologies have allowed to overcome some of

the problems that the taxi industry, as it is artificial cap on supply, regulatory capture by associations and

longtime waiting.

Researches about ridesharing services have only appeared recently, but some have showed the efficiency

of how using an internet-based mobile technology helps drivers to have a passenger in the car more time

than the traditional system, where taxis search for new passengers. Cramer and Krueger (2016) studied

the efficiencies in time and share in miles of the Uber app to match drivers with passengers in 5 major

cities5 in the United States. They concluded that for the passengers there is a reduction in taxi search time

of 9.3% and for drivers the capacity utilization in average is 38% higher for UberX6 drivers than for normal

4 Uber consider drivers as independent partners due it does not possess own cars. Additionally, drivers are either self-employed, or drive the car of somebody else, also drivers decide their own work-load. Therefore, Uber, or similar, only provides the technology base and establishes the policy rules charging between 10%-20% of the fare. 5 The cities studied are Boston, Los Angeles, New York, San Francisco and Seattle. 6 There are four types of Uber which depend of the size and luxury (UberX, UberXL, Uber Select and Uber Black). The most common type and least expensive is UberX which normally correspond to sedan cars.

A case of excessive price under dynamic pricing competition scheme

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taxi drivers. Lastly, they suggest four factors that will contribute to the higher capacity and efficiency: 1)

Uber’s more efficient driver-passenger matching technology; 2) the larger scale of Uber than taxi

companies; 3) inefficient taxi regulations; and 4) Uber’s flexible labor supply model and surge pricing more

closely matching supply with demand throughout the day.

It is important to remember that Uber drivers and Lyft drivers, the two most important ridesharing

companies nowadays, are free to choose as much time or as little time as they want to offer their services.

Thus, they are not subject to any fixed time by the companies so drivers optimize their time as they

consider more convenient. In this context, Krueger and Hall (2015) find that conventional taxi drivers are

5 times more likely to work 50 or more hours per week than Uber drivers (35% taxi drivers versus 7% Uber

drivers work 50 hours or more per week). Also they show that Uber´ drivers earn at least as much as taxi

drivers and in many cases more than taxi drivers. The explanation of higher earnings and lower working

hours suggest that Uber´ platform is more efficient than traditional taxi services due to labor flexibility.

Not only surge pricing give Uber´ drivers more revenue in overall than its counterparts but also consumers

also get benefited with time reduction in searching for cabs.

But how surge pricing really works, Hall et al. (2016) explains that the algorithm assigns a simple

“multiplier” that increases the standard fare, in order to derive the “surged” fare; the surge multiplier is

presented to a rider in the app which at the end accept or deny the higher price before a request is sent

to nearby drivers. In light of these findings, we can observe that the DP policy has two effects. First in the

demand side it ensures reliability and availability for those who agree to pay more or whose valuation is

higher when the demand increase; secondly in the supply side it incentivizes drivers to provide services in

the area where there is an excesses in demand.

Furthermore, Hall et al. (2016) used two real examples to illustrate the economics of Uber´s surge pricing

in action. In the first example, on March 21, 2015, pop superstar Ariana Grande played a sold out concert

at Madison Square Garden, New York City. The next figure shows how the demand and supply interact

before and after the concert from 8pm until 2 am in a geospatial bounding box containing Madison Square

Garden and the surge period when the surge multiplier increased beyond 1.0x.

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Figure 1. Surge pricing in Madison Square and surrounding for Ariana Grande´ concert.

Note: Figure reports the number of users opening the Uber app each minute (in red), as well as the sum of total requests for Uber rides in 15minute intervals over the same time period (blue circles), and the number of “active” uberX driverpartners within the same geospatial box each minute (green line). In this case, “active” means they were either open and ready to accept a trip. The volume has been normalized to a presurge baseline, defined as the average of values between 9:00 and 9:30 PM that evening, before surge turned on.

Source: Hall, Kendrick and Nosko (2016).

As we can see, firstly the surge pricing has the effect expected to equilibrate demand and supply,

increasing the drivers supply in the zone. Secondly, even that a lot of users opened the app not all of them

required the service and only the ones with higher valuation for the service or willing to pay the surge

price of 4.5X - 5X get the service. As a result, the surge pricing has an allocative effect in the market,

matching drivers with the customers that value more the service.

The second example used by the same authors is a counterexample of what could happened when the

surge pricing is not active. The authors study a technical glitch in the system on New Year´s Eve (January

1, 2015) in New York City, when for 26 minutes7, in one of the busiest days of the year for Uber, the surge

pricing stopped working and the basic tariffs were used instead. The day is meaningful due to the high

demand and low supply because drivers are simultaneously reluctant to work and prefer to enjoy their

own leisure time. The authors show that the completion rate, percentage of requests that are fulfilled

divided by the sum of completed trips and fulfilled trips, drop in more than 75%, proving thus the low

7 Uber’s surge pricing algorithm broke down due to a technical glitch, from 1:24am to 1:50am EST.

Ride request Users opening the app Driver supply

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incentives that drivers have for ride completion and the average waiting time for an Uber pass from two

minutes to roughly eight minutes.

However, external validity of this conclusion can be claimed because drivers could infer that a glitch was

happening in that moment or that the app was not working correctly due to previous experience of the

demand in that day or high prices before the glitch, so they decided not to provide the service in that

moment until the surge pricing will be fixed.

Regardless of how DP via surge pricing works in the ridesharing economies to attract drivers into the zones

with higher demand, there is a common concern and complaints by angry consumers that in some cases

surge pricing lead to excessive tariffs. As in the example, in New York City new year´s eve of 2013 prices

were 8x higher than normal rate8 and same happen during new years´ of 2015 with a medium surge

pricing of 6.9x9. In Mexico City, last April 6th of 2016, prices reach 7x higher than the base tariff10. In Sidney,

during a hostage siege, Uber´ prices escalated four times the normal price11. Although, in Stockholm in

2013, the company "tested" demand at a 50X surge12. Hence, the same situation has been detected in

different cities were people has complained about the surge pricing.

The economics behind of such a high price it is because Uber has capacity constraint which after is reached

leaves a residual demand. This residual is almost inelastic due to every new unit that enter to the zone

where surge pricing is on there will be somebody willing to pay whatever price Uber impose. It is important

to mention that the duration of this surge pricing oscillates during the day depending the peak-on or peak-

off on demand, until the market is in equilibrium. However, we cannot deny that under exceptional

circumstances firms with a DP setting could charge as much as they want due to inelasticity of the demand.

Consequently, as I mentioned in the previous chapter, authorities have decided to eliminate the surge

pricing in some cases, as in New Delhi, India. Others have decided to put a cap in the surge pricing as it is

8 Soper, T., (2016). Customers complain a Uber prices surge near 10X on New Years Eve. GeewWire. Retrieved from http://www.geekwire.com/2016/customers-complain-uber-prices-surge-near-10x-new-years-eve/ 9 Crilly R., (2016). Customer complain about Uber´s surge pricing on New Year´s Eve. The Telegraph. Retrieved from http://www.telegraph.co.uk/news/worldnews/northamerica/usa/12078264/Customers-complain-about-Ubers-surge-pricing-on-New-Years-Eve.html 10 Olivas O., (2016). Usuarios furiosos con Uber por el disparo en la tarifa dinámica provocado por el Hoy No Circula. Merca2.0. Retrieved from http://www.merca20.com/usuarios-furiosos-con-uber-por-el-disparo-en-la-tarifa-dinamica-provocado-por-el-hoy-no-circula/ 11 Ries, B., & Ryall J., (2014). Uber intros surge pricing during Sydney hostage siege, then backtracks after user outcry. Mashable. Retrieved from http://mashable.com/2014/12/14/uber-sydney-surge-pricing/#4RWDGwtrbSqS 12 Shontell A., (2014). Is This The Highest Surge Price Ever Recorded In Uber History?. Business Insider. Retrieved from http://www.businessinsider.com/ubers-highest-surge-price-ever-may-be-50x-2014-11

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the case of the authorities of Mexico City, Mexico. And more authorities around the world are taking

different actions against the DP13 in the ridesharing platforms. But is it a real threat the surge pricing for

capture consumers´ surplus? Or authorities are just acting for please irritate consumer without thinking

in overall welfare?

Surprisingly is that in other markets, with a similar internet-based technology model, an increase in prices

according to the demand or the season is accepted by consumers. For example: airline tickets, sports

events, hotel accommodation, real-time retail electricity. As some commentators have said over time

people can be persuaded of the benefits of a dynamic tariff and become accepted as the new normal.

In the next chapter I will focus in understanding when an economical practice can be considered as an

excessive price under a dynamic perspective, so under the rule of reason to analyze which type of error

(type I & type II) is costlier for society and finally link what theory predicts with a real case of surge pricing.

4 SURGE PRICING AS AN EXCESSIVE PRICE CASE

Under Article 102 (a) of the EC Treaty, it’s considered an excessive price when a dominant firm “directly

or indirectly” imposes “unfair purchase or selling prices or other unfair conditions”. In this sense, Motta

and de Streel (2006) defines a price as excessive when the price is significantly above the effective

competitive level, or above the economic value of the product. Yet, the definition of “unfair” is subjective

to the way that the price-margin cost is measured, especially when some part of the cost of a product is

common across a product range and finding a proper benchmark for analyze the correct price could result

particularly harsh for the authority.

However, authorities agree that excessive prices can have two effects, the first one is an exclusionary

effects and the second is an exploitative effect. The first takes the form of refusal to a deal or margin

squeeze and the second directly extracts the consumers´ surplus. That be said, we analyze surge pricing

as a case of exploitative abuse due to high prices extracted surplus from consumers.

Consequently, for the surge pricing, as well as for any type of DP setting, it is difficult to distinguish when

the price is high but still competitive and when becomes “unfair” by itself. At the end most of the DP

depends of a logarithm that takes into account different factors to discriminate customers with higher

13 Posner, E., (2015). Why Uber will -and should- be regulated. Slate. Retrieved from http://www.slate.com/articles/news_and_politics/view_from_chicago/2015/01/uber_surge_pricing_federal_regulation_over_taxis_and_car_ride_services.html

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valuation than those who valued the object less while matching demand with supply in a real time manner.

As Mehra (2015) mentions, there is a suspicion about Ubers´ algorithm, whether it has been designed to

exploit consumers or it follows a neutrality basis competition framework. Although, as economic theory

shows, a firm or group of firms, with a monopoly or market power would seek to charge prices above the

competitive level to maximize its revenue, causing a deadweight loss to the society14.

As it is also argued by Motta and Streel (2006), there are some pros and cons of actions against excessive

pricing. The authors enlist 3 main factors as negative when high prices are forbidden: (i) it will undermine

the investment incentives; (ii) high price is a reward for novel products and risky investment in industries

where innovation play a key role; (iii) authorities are subject to lobbying when the price of a product

(service) is fixed or capped due to pressure of consumers that would always prefer low prices.

For the first factor, (i) high prices attract more competitors that see profitable to enter the market, so is

the case of ridesharing market, new companies are entering into the market and contributing to a more

fiercely competition15. Also, in some countries traditional taxis are acquiring ridesharing technology to

help users find a taxi faster. The second factor (ii) also applies to sharing economies where innovation

plays a key role and the price-cost margin will be typically large to fund initial capital and future invest in

better algorithms. Finally, factor three (iii), economists argue that market forces in normal circumstances

will correct excessive prices better than administrative action or litigation16.

In the positive side of banning an excessive price, the authors argue that firms with significant market

power will exploit consumers, in special, in industries where the market design does not let new

competitors enter due to high barriers; thus consumers will be harmed in a persistent form. Secondly, if

consumers cannot coordinate or cannot exert buyer’s power to offset the excessive prices, authorities

might intervene and try to regulate the prices; this was relevant in the days when taxi associations had

the monopoly of the market and consumers required the certainty of a price.

14 A monopolist will maximize its profits when marginal cost is equal to marginal revenue. Therefore, the demand curve of the monopolist would be given by the price-quantity combination at the point where marginal revenue equals marginal cost. 15 Stone, B., (2015). Exclusive: Google is Developing its own Uber Competitor. Bloomberg Technology. Retrieved from http://www.bloomberg.com/news/articles/2015-02-02/exclusive-google-and-uber-are-going-to-war-over-taxis 16 O’Donoghue and Padilla (2013) consider that cases of excessive pricing should be only limit when the market has high entry barriers, therefore, consumers could be exploited. But if the market is contestable, high prices will attract new competitors that will reduce the margins of the incumbents and restore the competitive levels.

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Regardless of the pros and cons of the actions against excessive prices, competition authorities should be

cautious and avoid the violation that is found when there is not (type I error or false negative); or truly

violation does not go without punishment (type II error or false positive). So, on the one hand a false

condemning of surge pricing will bring a reduction in the supply side in the moments when there is a peak

in the demand and reduction in the investment in the surge pricing´ algorithm. On the other hand,

allowing surge pricing when exceptional circumstances exist 17 would lead to arbitrage opportunities to

extract all consumers rent and harming. In general, for excessive prices cases the majority of experts

coincide that under the rule of reason type I errors “the false condemnation of legitimate prices” is more

likely and costly (O’Donoghue and Padilla, 2013).

Additionally, tests have been design to prove when a practice can be qualified as an excessive price.

Nonetheless, in the EU the only legal test in excessive price cases is the United Brand Test18 which consists

of a two-stage test: (i) the price-cost margin is excessive; and, (ii) the price is excessive in itself or by

comparison. As some commentators argue, the United Brand test is too simplistic, thus every price-cost

margin would lead to positive revenues and finding a comparable benchmark could be a bias method, the

result, at the end, depends of who applies the test. In addition, other commentators have proposed

additional conditions for competition authorities to take into action against excessive prices.

Motta and De Streel (2006) make an excellent summary of all the tests proposed for excessive prices and

also suggests their own test. Furthermore, Akman and Garrod (2010) claim that any effective test in cases

of excessive pricing should satisfy four criteria: (i) be well-defined; (ii) provide ex ante legal certainty; (iii)

be simple to implement; and (iv) improve welfare.

Then, the next table summarizes all conditions that have been proposed so far by different commentators

to infer whether it is a case of excessive pricing or not.

17 Exceptional circumstances in the case of surge prices should be understand as the moments when an exogenous event affect the demand in transportation moving upward the demand beyond the normal limits. Examples of this is natural disaster or environmental problems that reduce the supply of cars in the area. 18 Case 27/6, United Brands Company(UBC) vs Commission. UBC was the largest group on the world banana market, almost exporting 35% of the global production and 45% of the relevant market. The commission considered that UBC abuse its dominant position and accused UBC of 4 offenses. One of the offenses was impose unfair prices above 30%-40% above prices in other Member States to customers in Belgium, Luxembourg, Denmark and Germany.

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Table 1. Different tests proposed for Excessive pricing cases

Evans &

Padilla

(2005)

O´Donoghue

& Padilla

(2012)

Roller

(2007)

Fletcher

& Jardine

(2007)

Paulis

(2007)

Motta

and De

Streel

(2006)

Akman

&

Garrod

(2010)

Market power by exclusionary abuse* and not result of past investment **

X** X** X* X*-** X*

Price exceed widely average total cost* or by comparison** or reference transaction***

X * X* X** X***

Effect in adjacent markets

X X

Market cannot be self-regulated* or no regulator in the market**

X* X**

Significant barriers to entry or no possibility of successful new entry

X* X* X** X* X*

Investment and innovation is marginal in the market

X

Firm has gained at its customers´ expense

X

Past prices charged

X

Source: Own elaboration. Based on Motta and De Streel (2006) and Akman and Garrod (2010)

As we can see, except for Paulis (2007) which only requires significant entry barriers for intervention, the

majority of commentators agree in set many conditions in cases of excessive price. Furthermore, all agree

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that in all the tests proposed the conditions should be cumulative thus authorities should drop the case if

one of the condition is not fulfilled, or if the different tests in practice lead to different results19.

To analyze the study of surge pricing as a case of excessive prices, the effective criteria test proposed by

Akman and Garrod (2015) (hereinafter A&G test) can be the most appropriate, because it considers past

prices charged by the dominant firm as a comparable benchmark, so we can compare apples with apples.

This is in the line of sharing economies that poses a big sample of data of past prices; being relatively easy

to request such information. Additionally, we consider that this test is the most proper in a dynamic

environment so it could be used for any firm that sets dynamic prices; so the next chapter will analyze

properly the surge pricing based in the A&G test.

The last issue to solve is the remedies, even if the authority asses correctly a case of excessive price, an

inappropriate remedy could distort even more the competitive process. At first sight the easiest remedy

could be a price cap or price regulation, but as some argue price regulation could distort investment

incentives. Moreover, price regulation is difficult to assess, to implement and to monitor. Not only

competition authority is not aimed to act as a price regulator but also a competition authority, under this

scenario, it would act as a social planner. Therefore, as Lyons (2007) claims, price regulation should be

chosen by the competition authority if there is no sectoral regulator in the market or in large industries

subject to economies of scale.

Therefore, on the one hand Motta and De Streel (2006) suggest that depending of the structure of the

market and the behaviour of the market, the next remedies could be used: (i) encourage consumers

switching towards less expensive offers of new entrants; (ii) remove and prohibit such entry barriers

(either legal or economical); and, (iii) remove artificial switching cost. On the other hand, O´Donoghue

and Padilla (2013) suggest the next remedies: (i) forced divestitures; and (ii) structural changes aimed at

lowering barriers to entry in the market under scrutiny.

We can conclude that only if the tests and conditions always lead to the same direction, excessive prices

should be punished, and even so, one should be very careful when dealing with these cases. Thus is more

19 In Motta and De Streel (2006) is mentioned that there are four methodologies for in practice identify excessive prices: (i) comparison between costs of production and prices; (ii) comparison between prices charged by the dominant firm in different markets; (iii) comparison between the prices charged by the dominant firm and those charged by other firms either in same market, or in other market; (iv) comparing the profits of the dominant firm and comparing such profit either with a normal competitive profit, or the profits of other firms. Each of the methodologies present different difficulties thus if one methodology shows different result the case should be dismiss.

A case of excessive price under dynamic pricing competition scheme

15

likely to commit false condemnation (type I error) of a legitimate price and it is more probably that market

forces will correct the problem without the intervention of the authority. Finally, also we analyze that

remedies should correct the structural problems of the market instead of implement a regulated price,

which in most of the times would not be correctly assess.

5 THE EFFECTIVE TEST CRITERIA FOR SURGE PRICING CASE.

In this section, I analyze the surge pricing case under the test or procedure proposed by Akman and Garrod,

due to other tests it´s only consider excessive price cases when they are persistent and do not consider a

dynamic setting where supracompetitive prices can be charged in a short period of time. The A&G test is

based on the Dual Entitlement principle developed by Kahneman et al (1986)20 that explains when people

perceive a price, rent or wage level as unfair to relative comparable transactions.

The Dual Entitlement suggests that people use reference points when forming an opinion of price fairness.

Such transaction reference points can be past prices of the firm, a competitor´s price or comparable

markets. Therefore, if an exogenous shock appears in the market and the reference point is past prices,

customers will consider that the price is unfair by itself if only the firm gains at the customers´ expense

but it will not be unfair if the firm and customers gain from the transaction.

The key point to understand the dual entitlement is to know when the firm gains at the expense of the

consumer. In doing so, the dual entitlement does not consider as an unfair price if (i) the price increases

due to higher production cost or (ii) production cost is lower but the price remains the same. Hence, the

firm would be able to charge prices that recoup investment in cost efficiencies.

Therefore, the A&G test21 only starts if the firm do possess a dominant position in the relevant market

and it consists in 3 stages. The next figure shows the structure of the A&G test.

20 Kahneman et al (1986) use household surveys of public opinions to infer rules of price fairness. The research has two main objectives: (i) to identify common standards of fairness that apply to price; and (ii) to consider the possible implications of the rules of fairness. The authors argue that people perceive as an exploitative behaviour of market power many firms´ actions that are profitable in the short run which in many occasions can contrast with economic theory. 21 As it was mentioned in chapter IV, the A&G test fulfill the four criteria for an effective test: (i) be well-defined; (ii) provide ex ante legal certainty; (iii) be simple to implement; and (iv) improve welfare.

A case of excessive price under dynamic pricing competition scheme

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Figure 1. The Akman and Garrod test for excessive pricing case

Source: Based on Akman and Garrod (2010).

The first step refers whether the terms of trade are significantly different to a given reference

transaction22. There are two possibilities in this step: (i) for single-product firm the transaction should be

higher than the reference transaction is; and, (ii) for multiproduct firm the comparison should be a higher

average price of a representative bundle to the reference.

In the second step it is required some discretion by the authority due to its necessity to analyze whether

the overall gains of the firm, compared to the reference transaction, are at its customers´ expense. Having

said that, the authors develop the next formula, in order to understand the profitability of the action.

∆π ≥ ϵ𝜋 ⟶ 𝜋𝑖𝑡 − 𝜋𝑖𝑡−1 ≥ ϵ𝜋

Rearranging:

𝑝𝑖𝑡 − 𝑝𝑖𝑡−1 ≥ 𝐶𝑖𝑡(𝑞𝑖𝑡)

𝑞𝑖𝑡−

𝐶𝑖𝑡−1(𝑞𝑖𝑡 − 1)

𝑞𝑖−1+ ϵ𝜋

22 Akman and Garrod (2010) define four possible reference transaction. (i) price charged in the past by the firm; (ii) current price by the firm on a comparable yet separate market; (iii) rivals´ prices in the investigated market; and, (iv) rivals´ prices in a comparable separate market.

Step 2. Compared to the

reference transaction, is

the firm´s profit

sufficiently larger?

The price can be deemed

unfair under Article

102TFEU

The Price shouldn´t be

deemed unfair or

excessive Yes

No

Lack of competition

The price is unfair

according to dual

entitlement

It isn´t in the remit

of the competition

law to intervene

Demand Supply

No

Step 3. What caused the

larger profit?

Step 1. Are the terms of

trade sufficiently close to

those of the reference

transaction?

Yes

A case of excessive price under dynamic pricing competition scheme

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Therefore, the comparison considers whether the difference in prices is greater than the difference of

average total costs plus a ϵ𝜋 term. The authors introduce the term ϵ𝜋 as burden of proof which will vary

case-by-case. As higher (lower) ϵ𝜋 the less likely to have Type I (Type II) error. Moreover, the term ϵ𝜋

would be helpful to take into account risk investment and innovation proposed by other authors.

Finally, in the step 3 the authors analyze exogenous fluctuations in supply and demand that alter firms´

price decisions. The authors argue that excessive price cases should only be found when there is a lack of

competition in the market.

Therefore, once the criteria test has been defined for excessive price cases, I do apply the test in the

Mexican case against Ubers´ surge pricing. The main reason to study the Mexican case is because it is the

most recent complain and more information is available in the web, nevertheless, the test can be applied

for any case related with Ubers´ surge pricing. Finally, I analyze the effects of cap the surge pricing, as it

happened in Mexico City, or ban the surging price, as it happened in New Delhi.

5.1 Mexico City case.

In 2013, Uber started operations in the Mexican Capital which is one of the most traffic-congested cities

in the world23. Nowadays, the company has approximately 10,000 driver partners24, and according with

the local transportation authority there are around 140,000 taxi units25 and an unspecified number of

“pirate” taxis. Furthermore, Mexico City suffers of high concentrations of air pollution during the dry

seasons, which has forced the local government to introduce the program “Hoy no Circula” which bans

drivers from using their vehicles one weekday per week on the basis of the last digit of the vehicle’s license

plate26, and depending of the traffic either can be one number or two numbers which are banned on that

specific day.

Last 6 of April, due to high levels of air pollution the Mexico City Government applied “Doble no circula”

which orders all motor oil cars off the road which license plate ends with the numbers 1&7 . The action

not only reduced the supply of Uber but also increased the demand, increasing thus the surge price to

23 The TomTom traffic index measures traffic congestion around the world. In its last publication, Mexico City was the first place with most congestion level around the world. Retrieved from https://www.tomtom.com/en_gb/trafficindex/ 24 Chavez, G.(2015). Costos de Autos, ¿El pero en la regulación a Uber en el DF? CNN Expansión. http://expansion.mx/tecnologia/2015/07/16/error-limitar-costo-de-autos-para-uber-y-cabify-analistas 25 De Haldevang W(2016). Exclusive: Mexico City to regulate Uber with license fees, ride levy – draft. Reuters. Retrieved from http://www.reuters.com/article/us-mexico-uber-idUSKCN0PI17420150708 26 Davis (2008) studies the effectiveness of the “Hoy no Circula” program. He argues that the program, instead of improve the air quality in the city, has increased the total number of vehicles in circulation

A case of excessive price under dynamic pricing competition scheme

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even 6.9X from base tariff which brought thousands of furious costumers to complain with the local

authority of supracompetitive prices and arbitrage opportunity by Uber. Consequently, one month after

local authority accused Uber of charging excessive prices27 and capped the price to 4.9X on normal days

and to 2.9X on days with high indexes of air pollution.

In order to exercise the A&G test in this case, first we should check if Uber has a dominant position in the

relevant market. At first sight, there are two types of transport which are perfect substitutes to

consumers: ridesharing services and conventional taxis. However, a formal analysis of this hypothesis

might check diversion ratios of how consumers switch away among competitors when prices increase28.

Hence, Uber would have low market share in the relevant market under this perspective. Moreover, the

switching cost from ride-sharing services to taxis is negligible close to zero or just the time that

consumer has to wait for find a better option but not the other way around because consumers always

need a smartphone for use the service. So in equilibrium if one firm decides to raise the price, consumers

in theory could change to the competitor. In sum, the case of excessive price would be discharged since

in the begging if we consider that Uber do not have dominant position in the relevant market.

However, another hypothesis based on Shapiro and Farrell (1988) points out that even under dynamic

competition consumers can be “locked-in” due to specific investment, efficiency advantages or network

externalities. So if we consider that consumers are locked-in within the ride-sharing services because of

efficiency advantages on ordering a ride by an app; then we could consider that in the relevant market of

ride-sharing services, Uber holds a dominant position29 because it was the first to enter in the market and

at least in Mexico it has the largest number of driver-partners.

Following with the first step, I consider as a reference transaction the past prices charged by Uber.

Preferably, the price should be the average price at the time where the surge price reached the peak on

27 In the article 53.I, of the Mexican Federal Competition Law, is forbidden fix, elevate, coordinate or manipulate the selling or buying price different of what is offer or demand by the market. 28 Recent studies have showed that in some cities the price of taxi licenses decrease since Uber enter into the market, indicating that Uber is a strong substitute of taxis. The Economist (2015). Taxis vs Uber. A tale of two cities. Retrieved from http://www.economist.com/news/united-states/21661016-does-uber-substitute-cabs-or-attract-new-riders-it-depends-where-you-live-tale 29 Until now there is any study that shows the market shares in the ride-sharing services in Mexico City but some reports show that Uber is the major firm in the market with some competitors in the city as Cabify, Fácil Taxi and Yaxi. Moreover, Buggy Rides is a new competitor who entered this year in the market and more apps are being developed for local taxis. Retrieved from: http://www.forbes.com.mx/asi-se-reparten-el-mundo-uber-y-sus-competidores/ http://www.xataka.com.mx/emprendedores/llego-la-competencia-mexicana-de-uber-y-cabify-buggy-rides

A case of excessive price under dynamic pricing competition scheme

19

the affected geospatial spaces. We can assume that prices which reached 7 times the basic tariff are not

close to the reference transaction, so the first step of the test would be satisfied.

The second step would require to check if the firms´ profit is at its customers´ expense. In so doing, we

should calculate the average total cost carry by Uber. I consider that Uber´ short average variable cost

basically consists in the personnel and maintaining expenses requires to administrate the app. Moreover,

I assume that neither the personal nor the expenses could increase during the time of the surge pricing is

on due to Ubers´ algorithm activates automatically. Finally, in this case our ϵ𝜋 should compensate the

investment capital and the associated risk; however, these variables were also contemplated in the past

prices. So we can conclude that under dual entitlement the price seems unfair by consumers.

Finally, in the third step we should check that even though that excessive surge pricing is unfair in the eyes

of consumers in terms of competition the market is self-contained. Having said that, we should check the

supply and demand sides of the market. During the days that the “Doble no cirula” program is activated

there is a double effect that rises the price, on the one hand there is a reduction in the capacity of available

Ubers´ cars by 40%30; on the other hand, the demand for units is larger than normal.

Moreover, as it was mentioned in chapter 3 the surge pricing attracts drivers closer to the area and

allocates efficiently the consumers with higher willingness to pay. Additionally, the app is really

transparent when surge pricing is activated, showing to the costumers that they are going to be charged

a larger fare and asking for their confirmation before ordering the service, besides, the Authority informs

one day beforehand that the program is going to be implemented. Therefore, the third step shows us that

costumers are fully informed about the real price, so there is no asymmetric information, thus neither

exploitative effects can be claimed nor an intervention in the price.

5.2 Effects

As it has been mentioned in previous chapters, a price regulation is unlikely to be successful in excessive

price cases due to the difficulty to determine the efficient price, monitor and compliance. In doing so,

authorities face the problem to do more harm in the market than ex-ante situation. Yet, there are other

structural remedies that could be more effective in these cases.

30 Gallegos, Z. (2016). Todos los coches de la Ciudad de México dejarán de circular al menos un día. El País. Retrieved from http://internacional.elpais.com/internacional/2016/03/30/mexico/1459367615_324883.html

A case of excessive price under dynamic pricing competition scheme

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Nonetheless, the effects of cap or ban the surge pricing are going to be different in the market. In the

former case, a price cap would still give some room for possible entry in the market thus there might be

a mark-up to the entrants. In the latter case, a surge price ban would lead to the expected rate of return

be insufficient to cover the company´ initial cost of capital and it might force ridesharing companies to

exit the market or deter new entry.

Perhaps, more to the point, without any intervention by the authority onwards we might observe less of

these cases due to past consumer experience and Ubers´ profit will stimulate entry by other firms, as it

has been happening in the last years, or it will stimulate the scale of Ubers´ capacity. Moreover, not only

the price regulation will not resolve the underline problem that affect the taxi industry with the irruption

of the ridesharing services but also consumers will be harm with the reduction of available rides and the

increase on waiting times.

6 CONCLUDING REMARKS

Along this paper we analyze the importance of dynamic price for match demand and supply in a real time,

especially in the ridesharing economies. Moreover, as there is an increase trend in selling products

through digital technology different industries will tend to move towards a dynamic price setting which

might increase the likelihood of third price discrimination cases. Therefore, regulators will have to face

several challenges, including cases of excessive prices under a dynamic environment.

In example, we find that a distinct feature of dynamic price in the rideshare services is surge pricing which

allows to allocate efficiently consumers with higher value among the available units. However, under

exceptional circumstances demand can rise so much that the incumbent will face an inelastic demand,

allowing to charge supracompetitive prices.

As a result, some authorities already has enforced actions against the surge pricing without doing a proper

competition analysis. Almost all the authors claim that excessive price should be only deemed when some

accumulative criteria are fulfilled, tough. Therefore, I suggest that the effective test criteria for this cases,

under a dynamic setting, should be the Akman and Garrod test due to the clarity and legal certainty.

It must be noted that in the coming years more cases of abuse of dominance will be done by firms which

set dynamic prices and try to be under the radar when arbitrage opportunities are presented. Therefore,

in a world where dynamic trumps static, competition authorities should be prepared with proper tools,

as well as ongoing with regulation that ensure competition in new markets that technology is opening.

A case of excessive price under dynamic pricing competition scheme

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