Master project

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
1
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

2
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

3
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

4
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.

5
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

6
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.

7
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.

8
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

9
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

10
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_regul
ation_over_taxis_and_car_ride_services.html

11
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.

12
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.

13
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

14
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.

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.

16
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 ≥ ϵ 𝜋 ⟶ 𝜋𝑖𝑡 − 𝜋𝑖𝑡−1 ≥ ϵ 𝜋
Rearranging:
𝑝𝑖𝑡 − 𝑝𝑖𝑡−1 ≥
𝐶𝑖𝑡(𝑞𝑖𝑡)
𝑞𝑖𝑡
−
𝐶𝑖𝑡−1(𝑞𝑖𝑡 − 1)
𝑞𝑖−1
+ ϵ 𝜋
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

17
Therefore, the comparison considers whether the difference in prices is greater than the difference of
average total costs plus a ϵ 𝜋 term. The authors introduce the term ϵ 𝜋 as burden of proof which will vary
case-by-case. As higher (lower) ϵ 𝜋 the less likely to have Type I (Type II) error. Moreover, the term ϵ 𝜋
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

18
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

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 ϵ 𝜋 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

20
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.

21
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