Putting on a Tight Leash and Levelling Playing Field: An Experiment

No 192
Putting on a Tight Leash
and Levelling Playing Field:
An Experiment in Strategic
Obfuscation and Consumer
Protection
Yiquan Gu,
Tobias Wenzel
July 2015
IMPRINT DICE DISCUSSION PAPER Published by düsseldorf university press (dup) on behalf of Heinrich‐Heine‐Universität Düsseldorf, Faculty of Economics, Düsseldorf Institute for Competition Economics (DICE), Universitätsstraße 1, 40225 Düsseldorf, Germany www.dice.hhu.de Editor: Prof. Dr. Hans‐Theo Normann Düsseldorf Institute for Competition Economics (DICE) Phone: +49(0) 211‐81‐15125, e‐mail: [email protected] DICE DISCUSSION PAPER All rights reserved. Düsseldorf, Germany, 2015 ISSN 2190‐9938 (online) – ISBN 978‐3‐86304‐191‐5 The working papers published in the Series constitute work in progress circulated to stimulate discussion and critical comments. Views expressed represent exclusively the authors’ own opinions and do not necessarily reflect those of the editor. Putting on a Tight Leash and Levelling Playing
Field: An Experiment in Strategic Obfuscation
and Consumer Protection∗
Yiquan Gu1,†
1
University of Liverpool
2
3
Tobias Wenzel2,3,‡
University of Bath
Düsseldorf Institute for Competition Economics (DICE)
July 2015
Abstract
The paper reports the results of an experiment where asymmetric sellers of a product can obfuscate the market. We show that policy measures may have unintended effects of increasing obfuscation
incentives. We find that policies that limit the effectiveness of obfuscation and policies that promote parity between firms can lead less
prominent firms to increase their obfuscation efforts. Despite this unintended effect, however, the former type of policies is effective in
boosting consumer welfare.
JEL Classification: C91; D18; D43; L13
Keywords: Experiment; Obfuscation; Consumer Protection; Behavioural
Industrial Organisation
∗
We thank Volker Benndorf, Sen Geng, Claudia Möllers, Hans-Theo Normann, Martin Peitz, Rune Stenbacka, Fangfang Tan, Jonathan Tan, Chris Wilson for helpful suggestions and discussions. We are grateful to the editors and two anonymous referees for their
valuable comments and suggestions which have substantially improved the paper. We also
thank seminar audiences at the Universities of Durham, East Anglia, Liverpool and Nottingham, participants at Asia-Pacific Regional Meeting of the Economic Science Association in
Xiamen, MaCCI Conference in Mannheim, IIOC in Arlington and the Royal Economic Society Annual Conference in Cambridge for helpful comments. Julia Frison provided valuable
research assistance.
†
Email: [email protected]; Address: University of Liverpool, Management School,
Chatham Street, Liverpool, L69 7ZH, United Kingdom.
‡
Email: [email protected]; Address: University of Bath, Department of Economics,
Claverton Down, Bath, BA2 7AY, United Kingdom.
1
1
Introduction
It is well documented in a variety of markets that consumers often make
sub-optimal choices.1 On the other hand, the supply side of the market has
been associated with strategies that are designed to exploit imperfection in
consumer decision making. In particular, firms may deliberately increase
the complexity in which relevant information is presented in order to confuse consumers. For example, in the retail financial industry, firms often
use complex language or invent new terms in the description of their products. Such obfuscation strategies make it more difficult for consumers to
compare available offers, and hence ease competitive pressure in pricing
and can have substantial welfare consequences for consumers (Calvet et al.,
2007; Campbell, 2006).
An important question in such a situation is whether traditional public policies can effectively discourage supply side obfuscation and protect consumers
from such practice. To answer this question, we first analyse a simple game
of strategic obfuscation and then test model predictions in a laboratory setting. To reflect observations in real markets, we allow the firms to differ
in prominence, i.e., their ability in attracting naive consumers. In such a
framework, we study the effects of two common policy measures: policies
that directly protect consumers by hampering the effectiveness of obfuscation (Putting on a Tight Leash)2 and policies that promote parity between
firms (Levelling Playing Field).3
In our simple model with a binary choice of obfuscation, it is found that
the more prominent firm always chooses to obfuscate. However, the incen1
Imperfect consumer decisions are well documented in telecommunication markets (Miravete, 2013), electricity markets (Wilson and Waddams, 2010), and in particular, retail financial markets where a number of reasons have been identified including cognitive limitations
(Calvet et al., 2009), behavioural biases (Stango and Zinman, 2009) and insufficient knowledge (Lusardi and Mitchell, 2007; van Rooij et al., 2011), among others.
2
Such policies might include, for instance, policies that prohibit certain obfuscation tactics or educational programmes to directly improve consumer decision making.
3
For example, in some economies, state owned firms play an important role and often
enjoy a higher level of prominence or trust than privately owned firms. Privatisation, which
may be proposed to address various objectives, can reduce asymmetry in firms’ prominence
levels.
As another example, consider the case where continued persuasive advertising is required to maintain brand loyalty and the resultant superior prominence. Policies that impose spending limits on advertising thus can level the market in terms of prominence over
time. We study the effects of such policies in relation to obfuscation.
2
tives of the less prominent firm to obfuscate are ambiguous. The incentives
to obfuscate depend on the extent of asymmetry, but also on the level of
consumer protection policy. In the model, a stronger consumer protection
policy reduces the effectiveness of firms’ obfuscation strategies. This theoretical model yields two surprising hypotheses. First, an increase in the
level of consumer protection policy may actually induce the less prominent
firm to obfuscate. Second, policies that promote parity between the firms
may also increase the propensity of obfuscation by the less prominent firm.
To test these hypotheses, we design an experiment where in the base treatment two rather asymmetric firms compete in obfuscation and prices. We
then implement two treatments where in the first, the level of consumer
protection policy is strengthened, and in the second, firms are more symmetric than they are in the base treatment. It is found that our experimental
evidence broadly supports the above two theoretical hypotheses.
Although both policy measures increase the propensity of the less prominent firm to obfuscate, our experimental results show that the effects on
consumer welfare are very different. Policies that promote parity increase
obfuscation. Hence, the share of naive consumers and product prices rise.
This unequivocally harms consumers. However, we note that consumer
protection policies are found to be effective in reducing the share of naive
consumers and consequently the prices consumers pay, despite the increased
propensity of obfuscation by the less prominent firm.
The literature on competition in the presence of behaviourally biased consumers is growing rapidly.4 Piccione and Spiegler (2012) offer a framework
of obfuscation where firms can choose different price frames. In an earlier
version, Piccione and Spiegler (2009), the authors also consider prominence
such that when unable to compare offers their consumers buy from the incumbent. In equilibrium, the prominent firm (the incumbent) minimises
comparability while the non-prominent firm (the entrant) does the opposite. In contrast, in our theoretical model firms directly choose obfuscation
as in Carlin (2009), and the degree of prominence can vary continuously.
Additionally, we study the impact of various policy measures in an asymmetric setting. Chioveanu and Zhou (2013) provide another analysis that
allows for the distinction of frame complexity and frame differentiation.
4
See Spiegler (2011) for a textbook treatment and Huck and Zhou (2011) for an overview.
3
Spiegler (2014) offers a general duopoly framework that captures a variety of obfuscation strategies. Gu and Wenzel (2014) develop a theoretical
model of strategic obfuscation and analyse the effects of consumer protection policies. The experimental setting of the present paper is built on this
model.
Although most of the contributions so far are theoretical, there have also
been a few experimental studies. Kalayci and Potters (2011) examine whether
buyer confusion increases market prices and find results that support the
effectiveness of buyer confusion. Kalayci (2015) presents experimental evidence that a seller’s complexity and price choices are positively correlated.
This is in contrast to the findings in Sitzia and Zizzo (2011) where the authors are unable to detect a significant effect of product complexity on prices.
Kalayci (2012) investigates the effect of competition – captured by the number of sellers – on complexity choice. Contrary to theoretical predictions
in Carlin (2009), Kalayci (2012) finds that an increase in the number of sellers does not affect a seller’s complexity choice. Normann and Wenzel (2014)
present an experiment where sellers can coordinate shrouding of an add-on
product and find that the shrouding does only occur in concentrated markets. Relatedly, Crosetto and Gaudeul (2014) report an experiment where
sellers can choose a price format. They find that, if rival’s behaviour is observable, firms are able to coordinate on shrouded formats. Finally, our paper is also related to Morgan et al. (2006) which studies price distributions
in the presence of uninformed consumers.
The remainder of the paper is organised as follows. In Section 2 we describe
the model that is used for our experimental setup. Section 3 specifies the
design of the experiment and derives the hypotheses. In Section 4 we report
the results of the experimental study. Finally, Section 5 concludes.
2
2.1
Theoretical background
Model
To provide guidance for the experimental design, in this section we outline
a simplified model of strategic obfuscation following Gu and Wenzel (2014).
4
We consider a market where two firms compete to supply a homogeneous
product to a mass one of consumers each demanding one unit of the product
when the reservation price of r > 0 is not exceeded. Consumers are either
sophisticated or naive. Sophisticated consumers can compare prices and
buy from the firm that offers the lowest price. Naive consumers, on the other
hand, are unable to compare prices and buy at random with a distribution
to be specified below.
Shares of respective consumers are influenced by firms’ obfuscation choices
and the consumer protection policy. Naturally, more obfuscation and low
consumer protection lead to more naive consumers and accordingly, fewer
sophisticated consumers. Departing from Gu and Wenzel (2014), here we
treat obfuscation as a binary choice.5 Specifically, let Ii ∈ {0, 1} be an indicator variable that takes the value 1 if Firm i decides to obfuscate and 0
otherwise, and let x ∈ (0, 1) be the level of the consumer protection policy.
The share of naive buyers then is
µ(x, I1 , I2 ) = (1 − x)
I1 + I2
.
2
(1)
The proportion of sophisticated consumers is thus 1 − µ(x, I1 , I2 ).
We allow the firms to differ in their abilities in attracting naive consumers.6
Without loss of generality, Firm 1 is designated as the more prominent firm
which captures a larger share, φ ∈ 21 , 1 , of naive consumers. Firm 2 receives the rest of those naive consumers 1 − φ. We normalise both firms’
production costs to zero and we assume obfuscation is costless.
The timing of the game is as follows. In stage 1, the two firms simultaneously and independently decide on its own choice of obfuscation. After
knowing each other’s obfuscation choice, and hence the share of naive consumers, they compete in prices in the second stage.
5
An obfuscation strategy might, for instance, correspond to the use of different terms
and language - as can be observed in financial markets - which makes it harder for some
consumers to fully understand pricing and, hence, impedes comparisons between different
offers.
6
This reflects the observation that when unable to compare prices, consumers often resort
to factors like past experiences, firm reputation, name recognition, etc.
5
2.2
Theoretical results
Since a more elaborated version of the model has been fully analysed in Gu
and Wenzel (2014), we only highlight main results here.
In the second stage, there exists a unique Nash equilibrium in mixed strategies (Varian, 1980; Narasimhan, 1988). As the more prominent Firm 1 receives more naive consumers than Firm 2, its opportunity costs of competing aggressively for sophisticated consumers are higher. As a result, Firm 1
sets higher prices in equilibrium than Firm 2 in the usual stochastic order.
As our first theoretical prediction, we note:
Proposition 1. Firm 1 sets higher prices in equilibrium than Firm 2 in the
usual stochastic order.
Equilibrium profits are
E(Π1 ) = φµr and E(Π2 ) =
(1 − φµ)φµr
.
φµ + (1 − µ)
(2)
Note that Firm 1’s expected profit is equal to the level it could make by
focusing only on its own share of naive consumers while Firm 2’s is higher
than it would make by selling only to its naive consumers. In this sense,
Firm 2 benefits from the presence of sophisticated consumers.
In the first stage, Firm 1 chooses to obfuscate since its expected profit increases strictly in the share of naive consumers. For Firm 2, however, whether
obfuscation increases or decreases profits depends on the asymmetry φ and
the effectiveness of obfuscation in increasing the share of naive consumers.
Proposition 2. For a given combination of consumer protection policy x
and asymmetry in prominence φ, equilibrium obfuscation is as follows.
1. The more prominent Firm 1 chooses to obfuscate, I1∗ = 1.
√
(x+2)2 +8−(x+2)
2. Define φ̃ :=
.
2(1−x)
(a) If φ < φ̃, the less prominent Firm 2 chooses to obfuscate, I2∗ = 1;
6
(b) If φ = φ̃, the less prominent Firm 2 is indifferent between obfuscation and no obfuscation;
(c) If φ > φ̃, the less prominent Firm 2 chooses not to obfuscate,
I2∗ = 0.
Proof: As E(Π1 ) = φµr, Firm 1’s profits strictly increase in µ and hence
I1∗ = 1. Given this, Firm 2 chooses between µ(x, 1, 1) = µ = 1 − x which is
obtained by obfuscation, and µ(x, 1, 0) = µ =
1−x
2
by no obfuscation. The
proposition then follows because
φ Q φ̃ ⇐ E(Π2 ; µ) =
(1 − φµ)φµr
(1 − φµ)φµr
R
= E(Π2 ; µ).
φµ + (1 − µ)
φµ + (1 − µ)
Q.E.D.
In general, Firm 1 has larger incentives to obfuscate than Firm 2. Intuitively,
when deciding on whether or not to obfuscate, Firm 2 weighs an increased
demand from naive consumers and a softened price competition against the
associated decrease in the demand from sophisticated consumers. When
the two firms are rather asymmetric (φ > φ̃), Firm 2 is better off with no
obfuscation and competing for sophisticated consumers since the number
of naive consumers it would receive by obfuscation is rather small. On the
other hand, when the two firms are rather symmetric (φ < φ̃), Firm 2 benefits from obfuscation as the combined positive effect of reduced price competition and more naive consumers dominates the negative effect resulting
from fewer sophisticated consumers.7
With equilibrium obfuscation, we can derive the equilibrium share of naive
consumers for a given combination of x and φ.
Proposition 3. The share of naive consumers in equilibrium is



1−x


∗
µ = 1 − x or



 1−x
2
7
if φ < φ̃
1−x
2
if φ = φ̃
if φ > φ̃.
Note that for x > 31 , φ̃ > 1 and it follows that Firm 2 always obfuscates.
7
(3)
A direct implication of Proposition 2 and 3 concerning a change in asymmetry is the following result.
Proposition 4. For a given consumer protection
policy x, if the measure of
√
asymmetry φ decreases from above φ̃ =
(x+2)2 +8−(x+2)
2(1−x)
to below φ̃, Firm
2 switches from no obfuscation to obfuscation and the share of naive consumers doubles from
1−x
2
to (1 − x).
On the other hand, if we hold asymmetry fixed, an increase in the consumer
protection policy x may induce Firm 2 to obfuscate. To see this, note first
that φ̃ as defined in Proposition 2 increases in x. It follows that if previously
φ > φ̃(x1 ) and φ < φ̃(x2 ) after the strengthening of the consumer protection policy (x2 > x1 ), Firm 2 switches from no obfuscation to obfuscation.
Accordingly, the share of naive consumers changes from
1−x1
2
to 1 − x2 . To
summarise:
Proposition 5. For a given level of asymmetry φ, if the increase in consumer protection policy from x1 to x2 is such that φ̃(x1 ) < φ < φ̃(x2 ), Firm
2 switches from no obfuscation to obfuscation. Accordingly, the share of
naive consumers changes from
2.3
1−x1
2
to 1 − x2 .
Concerns for relative profits
In our model the effects of obfuscation on firms’ profits are quite asymmetric. Even in cases where Firm 2 benefits from choosing to obfuscate Firm
1’s profits would increase even more, that is, with Firm 2 obfuscating the
profit gap between the two firms widens. Here, we discuss how the model’s
predictions would change if firm managers not only care about their profit
level, but also about relative profits.
Concerns for relative profits may indeed influence firm behaviour (Armstrong and Huck, 2010). For instance, firms or rather firm managers might
be concerned with relative profits because relative performance might be an
important factor for future career opportunities. Managers who have performed relatively well compared to their peers may have better job prospects
8
in the future. Managers may also face incentive contracts that deviate from
pure profit maximisation and which might include relative performance
measures (Gibbons and Murphy, 1990). It might also be the case that firm
managers or CEOs are intrinsically competitive and have innate preferences
regarding relative standings (Armstrong and Huck, 2010). Moreover, evolutionary models of oligopolistic competition also argue that relative profits
may matter for firm / manager survival (e.g., Schaffer, 1989; Hehenkamp
and Wambach, 2010).
Let us discuss how our model’s results are affected if relative profits concerns are taken into account.8 As with profit maximisation pricing in the
second stage of the game is in mixed strategies, and Firm 1 charges on average a higher price than Firm 2. However, when managers are concerned
of relative profits, pricing will become more competitive. The new prices
are stochastically dominated by that of the standard profit maximisation,
and the lower bound of the price distributions also decreases. The reason
is that a firm that finds it is undercut by the competitor suffers not only the
loss of the share of sophisticated consumers to the competitor, but also finds
it profits much reduced in comparison to the competitor. This increases a
firm’s incentive to charge lower prices, and in equilibrium, the price distribution and average prices are lower than with profit maximisation. In the
first stage, the obfuscation incentives remain comparable to the standard
case. However, while the more prominent firm still prefers to obfuscate as
much as possible, Firm 2’s obfuscation incentives are reduced as obfuscation may increase the more prominent firm’s profits even more. Thus, when
relative profits matter we should expect Firm 2 to obfuscate to a smaller extent than with pure profit maximisation. The strength of this effect depends,
of course, on the degree of relative profit concerns.
3
Experimental design and hypotheses
3.1
Experimental Design
Our main goal is to analyse the impact of consumer protection and asymmetry on obfuscation choices. We therefore ran sessions with different levels
8
In Appendix A we provide a formal derivation of the following verbal discussion.
9
Treatment
BASE
POL
SYM
Asymmetry φ
0.9
0.9
0.6
Policy x
0.2
0.6
0.2
100(1−x)
2
40
20
40
Participants
56
56
56
# Groups
7
7
7
Table 1: Treatments
of consumer protection and asymmetry.
We consider markets with 100 buyers where each buyer purchases exactly
one unit. Buyers are programmed so that sophisticated buyers choose to
buy from the seller charging the lowest price, while each seller receives his
share of the naive buyers independent of the price charged. In case of a tie
sophisticated buyers are also divided according to the same rule as with the
naive buyers.
With obfuscation choices Ii and consumer protection parameter x, the num2
ber of naive buyers is 100(1 − x) I1 +I
2 . Instead of providing the value of x
directly to participants, we report the value
100(1−x)
2
which can be more eas-
ily interpreted as the increase in the number of naive consumers for every
obfuscating firm.
At the start of each period, sellers are randomly matched into groups of
two competing sellers: one subject is randomly assigned the role of Firm
1 and the other subject is assigned the role of Firm 2. In the first stage,
each seller decides whether or not to obfuscate which increases the number
of naive buyers by 40 (20). The decisions are revealed to both sellers, and
in the second stage of each round, each seller determines its price which
has to be an integer in [0, 100]. At the end of each round, participants are
informed about the competitor’s price, the quantities sold to sophisticated
and naive buyers as well as the profit earned in this period. This stage game
is repeated for 25 periods with a random-matching procedure mimicking
the one-shot nature of our theoretical model. Note also that subjects may
switch roles between periods. Whether a participant takes the role of Firm
1 or of Firm 2 is randomly determined in each period.
We have run three treatments - see Table 1. In our base treatment BASE, the
asymmetry level is high with φ = 0.9 and each obfuscating firm increases
10
Obf. by Firm 1
Obf. by Firm 2
Naive consumers
Avg. price
Min. price
Consumer surplus
BASE
1
0
40
60.0
37.5
40
POL
1
1
40
60.0
37.5
40
SYM
1
1
80
84.7
70.6
15.3
Table 2: Theoretical predictions
the number of naive consumers by 40. In treatment POL, mimicking the
effect of consumer protection, we reduce the effectiveness of obfuscation to
20. Finally, in treatment SYM we reduce the asymmetry level to φ = 0.6. For
each treatment, we have seven independent observations (corresponding to
the number of matching groups each consisting of 8 participants). Table 2
summarises, assuming profit-maximising firms, the point predictions of the
three treatments .
All sessions were conducted at the experimental economics laboratory at
the University of Düsseldorf. The experiment was implemented using the
software z-Tree (Fischbacher, 2007). Appendix B contains an English translation of the instructions. Subjects received a show-up fee of 4 EUR and
could earn additional amounts during the experiment. On average, participants received an amount of 13 EUR for a 60-minute session. In total, 168
subjects participated in our experiment. No subject participated in more
than one session and none of the subjects had ever participated in any similar experiment before.
3.2
Hypotheses
Here, we summarise our main hypotheses for two different assumptions
regarding firm behaviour. As a benchmark we consider firms to maximise
profits. As an alternative we provide hypotheses for the case that firms also
care about relative profit levels.
Our first set of hypotheses is about the obfuscation frequency by the two
firm types. For profit-maximising firms Proposition 2 suggests that Firm 1
has in general larger incentives to obfuscate than Firm 2:
11
Hypothesis 1. Firm 1 always chooses obfuscation; Firm 2 chooses obfuscation only in treatments POL and SYM.
With relative profit concerns the predictions are softened in the sense that,
depending on the extent of relative profit concerns, Firm 2 may not always
choose to obfuscate in treatments POL and SYM. We therefore state as an
alternative hypothesis:
Hypothesis 1’. Firm 1 chooses obfuscation more frequently than Firm 2.
Concerning the effects of consumer protection policy, since xBASE = 0.2
and xPOL = 0.6, φ̃(xBASE ) < φ = 0.9 < φ̃(xPOL ). With profit-maximising
firms it follows from Proposition 5 that Firm 2 switches from no obfuscation to obfuscation while the share of naive consumers remains unaffected
as
1−xBASE
2
= 1 − xPOL = 0.4. Given that the share of naive consumers and
asymmetry do not change in the second stage, the pricing equilibrium is
also unaffected.
Hypothesis 2. Compared to BASE, in treatment POL: a) Firm 2 always obfuscates; b) The number of naive consumers does not change; c) Prices and
consumer surplus do not change.
When relative profits play a role, the effects of regulation may be less strong
than under profit maximisation, and we would expect more obfuscation
than under BASE, but to a lesser extent than predicted with pure profit maximisation. As a result, the policy might be effective in reducing the number
of naive consumers and also in reducing prices:
Hypothesis 2’. Compared to BASE, in treatment POL: a) Firm 2 obfuscates
more frequently; b) The number of naive consumers decreases; c) In treatment POL prices are lower and consumer surplus higher.
We now discuss the hypotheses regarding the treatment SYM. With the consumer protection policy being fixed at 0.2, φBASE = 0.9 > φ̃ while φSYM =
12
0.6 < φ̃. From Proposition 4, Firm 2 switches from no obfuscation to obfuscation and the number of naive consumers increases from 40 to 80. Regarding the intensity of price competition there are two effects. First, for a
given share of naive consumers, price competition is intensified in a more
symmetric market. Second, with more naive consumers price competition
is weakened. With profit-maximising firms, the second effect dominates
and hence, equilibrium prices increase (see Table 2).
Hypothesis 3. Compared to BASE, in treatment SYM: a) Firm 2 always obfuscates; b) The number of naive consumers is higher; c) In treatment SYM
prices are higher and consumer surplus lower.
With concerns for relative profits, we would again expect weaker effects on
the obfuscation choices. Firm 2 still has stronger incentives to obfuscate under SYM than under BASE, but due to relative profit concerns not all Firm 2
participants may choose to do so. There is no qualitative change regarding
the number of naive consumers. Regarding the intensity of price competition, there are again the two opposing effects. However, with concerns
for relative profits, the price-increasing effect of more naive consumers is
smaller, and the overall effect becomes ambiguous: If the obfuscation effect
is large (small) prices increase (decrease).
Hypothesis 3’. Compared to BASE, in treatment SYM: a) Firm 2 obfuscates
more frequently; b) The number of naive consumers is higher; c) In treatment SYM the effects on prices and consumer surplus are ambiguous.
4
Results
This section presents the experimental results, and Table 3 contains our
main findings. To account for learning effects, all comparisons and tests are
based on the last ten periods. We employ non-parametric tests, where the
number of independent observations corresponds to the number of matching groups. We report two-sided p-values throughout.
13
Obf. by Firm 1
Obf. by Firm 2
Naive consumers
Avg. price
Min. price
Cons. surplus
BASE
0.97
0.07
41.6
69.0
61.2
31.0
POL
0.94
0.43
27.4
50.5
45.4
49.5
SYM
0.95
0.58
61.1
74.5
69.5
25.5
Table 3: Main results
4.1
Obfuscation choices by firm types
Table 3 reports the average propensity to obfuscate by firm type in each
treatment. The table indicates that in all treatments Firm 1 chooses obfuscation more frequently than Firm 2 (Wilcoxon signed-rank test, p = 0.018
and 0.018 and 0.028, respectively), providing evidence in favour of Hypothesis 1’:
Result 1. Firm 1 obfuscates more frequently than Firm 2.
Observe that the obfuscation level chosen by Firm 1 is similar and close to
one in all treatments (which is in line with hypotheses 1 and 1’), while this is
not the case for Firm 2. Indeed, in all treatments (in particular, in POL and
SYM) Firm 2’s obfuscation rates are far below one, contradicting Hypothesis
1. In the following we focus on Firm 2’s behaviour in more detail.
4.2
The impact of consumer protection
We next study the effects of the consumer protection policy on obfuscation
decisions by Firm 2. As can be seen in Table 3, obfuscation is more prevalent
with the policy in place and obfuscation decisions by Firm 2 are significantly
higher with the consumer protection policy (Mann-Whitney rank-sum test,
p = 0.002). Due to the policy, the obfuscation rate increases from 0.07 to 0.43.
The left panel of Figure 1 also reveals a time trend: in the POL treatment
14
0.8
100
0.7
0.6
80
0.5
0.4
BASE
0.3
POL
60
BASE
POL
0.2
40
0.1
0
20
1
3
5
7
9 11 13 15 17 19 21 23 25
1
(a) Firm 2’s obfuscation rates
3
5
7
9 11 13 15 17 19 21 23 25
(b) Average prices paid by all consumers
Figure 1: Impact of consumer protection: evolution of obfuscation rates and prices
obfuscation rates are increasing over time and towards the last periods the
obfuscation rate exceeds 60%, but is far below 100%.9 This gives support
for our hypothesis 2’a):
Result 2. The introduction of a consumer protection policy increases the
propensity of Firm 2 to obfuscate.
Even though we have observed that Firm 2 obfuscates more in treatment
POL, this effect is much lower than predicted by the model under profit
maximisation. One possible explanation for this finding, as also discussed
in the theory section, may be that participants in the experiment care about
relative payoffs and thus exhibit inequality aversion. Our results lend support to hypothesis 2’a) rather than hypothesis 2a). If Firm 2 chooses to obfuscate this not only increases its own profits, but also increases Firm 1’s
profits. Indeed, profits of Firm 1 increase to a larger extent than Firm 2’s
profits, decreasing the relative payoff of a Firm 2-player.
Table 4 shows the impact of Firm 2’s obfuscation decision on both firms’
profits given that Firm 1 has chosen to obfuscate. The table reports the realised profits we observe in the experiment. The table shows that in the
9
This suggests that some learning effects are present. It might take some time for participants to understand the effects of obfuscation by Firm 2. Therefore, to takes such effects
into account all statistical tests are based upon the last ten rounds of the experiment.
15
Decision by Firm 2
no obfuscation
obfuscation
Profit change (abs)
Profit change (rel)
Firm type
Firm 1
Firm 2
Firm 1
Firm 2
Firm 1
Firm 2
Firm 1
Firm 2
observed average profit
2035
2028
4008
2640
1973
612
0.97
0.30
Table 4: Average profit levels
treatment POL it is profitable to obfuscate, but it also shows that the profit
gap widens. By obfuscating Firm 2 profits rise by ca. 600 while those of
Firm 1 rise by ca. 2000. In relative terms Firm 2 profits increase by 30%
while Firm 1 profits almost double.
From our experimental data we can elicit the critical degree of inequality
aversion from which on a subject does not choose to obfuscate even though
obfuscation would increase its material payoff. Analogously to Fehr and
Schmidt (1999) the utility of a subject i is given by
Ui (πi , πj ) = πi − αi (πj − πi ),
(4)
where αi is a measure for the extent of the (disadvantageous) inequality
aversion of subject i.10 The critical degree of inequality aversion α̂ equalises
a subject’s utility (taking the role of Firm 2) from obfuscating and not obfuscating. Taking the observed profit levels from Table 4, the critical envy parameter is implicitly given by 2028− α̂(2035−2028) = 2640− α̂(4008−2640),
which implies α̂ = 0.45. This means that subjects with an inequality aversion parameter smaller than α̂ decide to obfuscate while those with a larger
inequality aversion parameter decide not to obfuscate.
The extent of inequality aversion observed in our experiment is similar to
other studies. For instance, Blanco et al. (2011) elicit the distribution of the
10
In Fehr and Schmidt (1999) individuals may also suffer from advantageous inequality
aversion when an individual earns a higher material payoff than its comparison group. In
our experiment, we do not observe advantageous inequality aversion: Subjects taking the
role of Firm 1 almost always choose to obfuscate even though this increases the payoff gap.
16
inequality parameters by using an ultimatum experiment.11 According to
their results, 33% of their participants have an α lower than 0.4 (close to the
critical α in the treatment POL) and 51% an α lower than 0.61. Interpolating
their results would yield that around 37% of subjects have an α lower than
0.45. In our experiment, we observe an obfuscation rate of 0.43. Hence, our
results are in a similar range, though inequality aversion is slightly weaker
in our study.12
Though obfuscation choices by Firm 2 increase due to the policy, this effect is not sufficiently strong to weed out the positive effects of the reform,
see Table 3. In particular, there is a significant reduction in the number
of naive consumers from 41.6 to 27.4 (Mann-Whitney rank-sum test, p =
0.002). Moreover, the average price as well as the minimum price in the
market drops significantly (Mann-Whitney rank-sum test, p = 0.006 for
both prices). Accordingly, consumer surplus rises from 31.0 to 49.5 (MannWhitney rank-sum test, p = 0.006). These results are in line with our hypotheses 2’b) and 2’c).
Result 3. The introduction of a consumer protection policy decreases the
number of naive consumers. Prices decrease and consumer surplus increases.
4.3
The impact of asymmetry
We now consider the effects of asymmetry by comparing the treatments
BASE and SYM. In line with our predictions we find that in a more symmetric market obfuscation rates by Firm 2 are higher. The average obfuscation
rate increases from 7% to 58% (Mann-Whitney rank-sum test, p = 0.007).
This effect is also stable over time, see Figure 2. Note, however, that the
11
Fehr and Schmidt (1999) also elicit the distribution of the inequality parameter α. However, the intervals are broader than in Blanco et al. (2011) which is why we focus on the
comparison with their distribution. Note, however, that the distributions derived in both
studies are quite similar.
12
We note that our results suggest that some level of inequality aversion is present in our
framework despite some mitigating effects. For instance, in our design with role switching
subjects should be less concerned with relative payoff concerns than in a design without
such role switching. However, a random matching procedure may make such differences
somewhat smaller.
17
0.8
100
0.7
0.6
80
0.5
0.4
BASE
0.3
SYM
60
BASE
SYM
0.2
40
0.1
0
20
1
3
5
7
9 11 13 15 17 19 21 23 25
1
(a) Firm 2’s obfuscation rates
3
5
7
9 11 13 15 17 19 21 23 25
(b) Average prices paid by all consumers
Figure 2: The impact of symmetry: evolution of obfuscation rates and prices
strength of this effect again falls short compared to the theoretical prediction under pure profit maximisation, inequality aversion being a potential
explanation.13
Table 3 reports the effects on the number of naive consumer and prices.
As a consequence of a higher obfuscation level we find that the number of
naive consumers is larger in the more symmetric treatment. The number
of naive consumer rises from 41.6 to 61.1 which is statistically significant
(Mann-Whitney rank-sum test, p = 0.005). We also see that prices are higher
in the symmetric treatment: The average price (minimum price) paid by
consumers rises from 69.0 to 74.5 (61.2 to 69.5). However, this price effect
is small (Mann-Whitney rank-sum test, p = 0.142 and p = 0.048; see also
the right panel of Figure 2). Consumer surplus decreases from 31.0 to 25.5.
Summarising the effects of asymmetry and confirming hypotheses 3 and 3’:
Result 4. Obfuscation rates and the number of naive consumers are higher
in a more symmetric market. Prices are higher and consumer surplus is
lower.
13
In the treatment SYM, we observe that profits of Firm 1 increase by ca. 2300 while profits of Firm 2 increase only by ca. 750 if Firm 2 chooses obfuscation. This implies a critical
inequality aversion parameter of α = 0.61. With a Firm 2- obfuscation rate of 0.58 this is in
a similar range as the evidence in Blanco et al. (2011).
18
Treatment
BASE
POL
SYM
Firm 1
81.1
66.5
80.6
Firm 2
66.0
52.5
75.1
Table 5: Average prices by firm type
Treatment
Obfuscation by one firm
Obfuscation by both firms
POL
Price CV
46.6 0.54
66.5 0.36
SYM
Price CV
58.7 0.38
88.5 0.24
Table 6: The impact of obfuscation on average prices
4.4
Prices
In the following we briefly comment on the price choices in the second stage
of the experiment, thereby confirming some existing results and providing
some new findings.14
As suggested by the theory, Firm 1 attracting a larger share of naive consumers has less incentive to compete on low prices. This is confirmed in
the experimental data. As can be seen in Table 5, we find that in all treatments Firm 1 charges higher prices than Firm 2 (Wilcoxon signed-rank test,
p-values 0.018, 0.028 and 0.043, respectively).
Result 5. Firm 1 charges on average a higher price than Firm 2.
The theoretical model suggests that in more obfuscated markets competition is weakened and prices are higher. This mechanism is an important
reason for firms to obfuscate. We now provide evidence that this is indeed
the case. We focus on treatments POL and SYM as only in those two treatments we observe sufficient variation in the number of naive consumers.
Table 6 shows that in both treatments average prices rise with more obfus14
Our results suggest that relative profit concerns play less role on pricing decisions than
in the obfuscation decisions. Comparing the pricing decisions of subject who frequently
obfuscate with those who rarely obfuscate we find that those decisions are quite similar.
19
1
0
.2
.4
.6
.8
1
.8
.6
.4
.2
0
0
20
40
60
80
100
0
20
40
p
20 uninf. buyers
60
80
100
p
40 uninf.buyers
20 uninf. buyers
(a) Firm 1
40 uninf. buyers
(b) Firm 2
Figure 3: The impact of firms’ pricing behaviour if obfuscation increases in treatment POL
cation (Wilcoxon signed-rank test, p-value 0.018 in both treatments).
Another way to compare the effects of obfuscation on pricing is by looking at
the entire price distributions. Figure 3 plots the observed cumulative price
distributions for the treatment POL. The figure shows that the cumulative
price distribution for both firms shifts out to the right if the market is more
obfuscated and there are more naive buyers. Indeed, obfuscation seems to
have a particularly strong impact on pricing by Firm 2. If only one firm
obfuscates, the probability of Firm 2 charging a price higher than 50 is low
(around 20%); the empirical distribution is rather flat for prices over 50. In
contrast, if both firms obfuscate, this probability is four times higher and
increases to 80%.15
These findings are in line with the ones obtained by Morgan et al. (2006)
who show that, in a setting where naive consumers are equally divided
among firms, prices rise with more naive consumers.16 We extend this result to the case with asymmetric firms. We summarise our findings:
Result 6. Prices are higher in more obfuscated markets.
15
Similar results are obtained if we consider the effects for the treatment SYM.
Relatedly, Kalayci and Potters (2011) report evidence from a laboratory experiment
where participants take both the roles of sellers and buyers. Sellers can make price comparisons harder by deciding on the number of attributes of a product. They find that prices
increase with the average number of product attributes.
16
20
1
0
.2
.4
.6
.8
1
.8
.6
.4
.2
0
0
20
40
60
80
100
0
20
40
p
theoretical distribution
60
80
100
p
empirical distribution
theoretical distribution
(a) Firm 1
empirical distribution
(b) Firm 2
Figure 4: Comparison of the theoretical and empirical price distribution: treatment
BASE with 40 naive consumers
Table 6 also reports the coefficient of variation (CV), a common measure of
price dispersion. We replicate the finding from Morgan et al. (2006) that
price dispersion is higher in markets with more informed consumers (that
is, in less obfuscated markets). We find this results in both treatments POL
and SYM.
Finally, we briefly comment on the comparison of the theoretical price distribution as predicted by the theory and the observed price distribution.
In line with the two-player treatments in Morgan et al. (2006) we find that
observed prices are somewhat higher than predicted by the theory. As an
example, Figure 4 shows the cumulative price distribution in the treatment
BASE with 40 naive consumers. As can be seen the empirical distribution
almost dominates the theoretical distribution, leading to higher observed
average prices.17
5
Conclusion
This paper has studied firms’ incentives to obfuscate in a laboratory experiment and the effects of public policies intended to improve market outcomes. Our main result is that protection policies intended to help consumers make good decisions and policies intended to level the playing field
between firms may have unintended consequences.
17
There are qualitatively similar effects in the other treatments.
21
Regarding consumer protection policies our experimental findings suggest
that less prominent firms increase their obfuscation efforts in response to
such a policy. However, such policies are still effective in increasing competition, though to a smaller extent than initially expected. We find that policy
measures that lead to more equal levels between firms lead to worse market
outcomes. Both the obfuscation level and the price level rise following such
an intervention.
A
Pricing when managers are concerned of relative profits
Here we briefly discuss pricing and obfuscation incentives when managers are concerned of relative profits. We focus on the case where the level of profit concerns
of managers is identical and publicly known.
The managers of the firms are concerned of relative profits. The utility of manager
i = 1, 2 is
Ui = Πi + α(Πi − Πj ),
(5)
where Πi are the monetary profits and α > 0 measures the degree of concern for
relative profits. In the pricing stage, the managers simultaneously and independently select prices to maximise their utility.
As in the standard case pricing is in mixed strategies. Firm 1 prices according to
the cumulative distribution function
F1 (p) = 1 +
(1 − φ)µ
φµ(1 − φµ)
−
1−µ
(1 − µ)[φµ + (1 − µ)]
1+α
1+2α
r
,
p
(6)
and Firm 2 prices according to the cumulative distribution function
φµ
φµ
F2 (p) = 1 +
−
1−µ 1−µ
on [p0 , r] and [p0 , r) resp., where p0 = r
φµ
φµ+(1−µ)
1+α
1+2α
r
p
1+2α
1+α
(7)
.
The main properties are preserved from the case with no relative profit concerns
(Gu and Wenzel, 2014). Both firms randomise over prices, and on average Firm 1
charges higher prices than Firm 2. More precisely, as ∂F1 (p)/∂α > 0 and ∂F2 (p)/∂α >
0 prices with relative profit concerns are stochastically dominated by prices in the
case with pure profit maximisation (α = 0).
22
Finally, we briefly discuss that the incentives to obfuscate are similar as in the standard case, but the incentives for Firm 2 to obfuscate decrease with the extent of
relative profit concerns. At stage 1 the utility of Firm 1 manager is
U1 = (1 + α)φµr − α[(1 − φ)µ + (1 − µ)]E(p2 ),
(8)
which can be shown to be increasing in µ so that also in the case of relative profit
concerns Firm 1 would like to obfuscate as much as possible. Firm 2 manager earns
utility of
U2 = (1 + α)[(1 − φ)µ + (1 − µ)]p0 − αφµE(p1 ).
(9)
As in the standard case whether or not Firm 2 manager would like to increase obfuscation depends on the asymmetry φ. It also depends on the relative profit concerns. Particularly, one can show that Firm 2 prefers less obfuscation for higher
values of α.
B
Instructions
Welcome to this experiment in decision making. Please read the instructions carefully.
During the experiment you can earn points depending on your own decisions and
those of the other participants. At the end of the experiment points are converted
at a rate of 10.000 points = 1 EUR and paid to you.
You are starting with an amount of 40.000 points. This amount is increased by the
earnings in each period.
The setup
In this experiment you are assigned the role of a seller. In each period of the experiment you are competing with another seller which is randomly determined
among the other participants of the experiment. Your competitor is determined
each round anew so that in each round you are competing with another participant.
There are two types of sellers, type A and type B, who interact with each other.
Which role is assigned to you is determined at the start of each period and is communicated to you. If you are a seller of type A you are interacting with a seller of
type B.
23
You and the other seller are selling a good to 100 buyers. Each buyer purchases
exactly one unit of the good. The buyers are simulated by the computer. There
are two types of buyers: “searching” and “non-searching” buyers. A “searching” buyer purchases the good from the seller that has chosen the lower price.
“Non-searching” are programmed such that a share of 90% (60%) automatically
purchases from the seller of type A and a share of 10% (40%) automatically purchases from the seller of type B.
In each period of the experiment you have to make two decisions which are described in the following.
The first stage
In the first stage of each period, both sellers simultaneously decide whether to increase the number of “non-searching” buyers. In the initial situation, there are 0
“non-searching” buyers and 100 “searching” buyers. For each seller deciding to
increase the number of “non-searching” buyers , the number of “non-searching”
buyers is increased by 40 (20). The number of “searching” buyers is decreased accordingly. The following table shows the number of “non-searching” and “searching” buyers depending on the decisions of both sellers:
Number of sellers deciding to increase
the number of “non-searching” buyers
“Non-searching” buyers
“Searching” buyers
0
1
2
0
100
40 (20)
60 (80)
80 (40)
20 (60)
The second stage
In the second stage of each period, you receive information on the decisions taken
in the first stage, and thus you receive information on the number of “searching”
and “non-searching” buyers. Subsequently, both sellers simultaneously decide on
the price they charge. The chosen price must be an integer between 0 and 100.
End of each period
At the end of each period, the computer calculates how many units you and the
other seller have sold. Note that each buyer buys exactly one unit of the good. The
number of sold units is calculated as follows:
• your share of the non-searching buyers will buy from you
24
• searching buyers will only buy from you if you have chosen a lower price
than the other seller. In case both sellers choose the same price a share of
90% (60%) of those consumers will buy from the type A seller and a share of
10% (40%) will buy from the type B seller.
Finally, you receive information about the points that you earned in this period.
The number of points earned is the number of sold units multiplied by the price
you have chosen.
End of the experiment
The experiment is repeated for 25 rounds. Whether you take the role of seller A
or B is randomly determined in each period. At the end of the experiment your
earnings will be paid out to you. Your earnings comprises the show-up fee and the
points you have earned during the experiment.
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Published in: Economics Letters, 124 (2014), pp. 122-126.
145
Blanco, Mariana, Engelmann, Dirk, Koch, Alexander K. and Normann, Hans-Theo,
Preferences and Beliefs in a Sequential Social Dilemma: A Within-Subjects Analysis,
May 2014.
Published in: Games and Economic Behavior, 87 (2014), pp. 122-135.
144
Jeitschko, Thomas D., Jung, Yeonjei and Kim, Jaesoo, Bundling and Joint Marketing
by Rival Firms, May 2014.
143
Benndorf, Volker and Normann, Hans-Theo, The Willingness to Sell Personal Data,
April 2014.
142
Dauth, Wolfgang and Suedekum, Jens, Globalization and Local Profiles of Economic
Growth and Industrial Change, April 2014.
141
Nowak, Verena, Schwarz, Christian and Suedekum, Jens, Asymmetric Spiders:
Supplier Heterogeneity and the Organization of Firms, April 2014.
140
Hasnas, Irina, A Note on Consumer Flexibility, Data Quality and Collusion, April 2014.
139
Baye, Irina and Hasnas, Irina, Consumer Flexibility, Data Quality and Location
Choice, April 2014.
138
Aghadadashli, Hamid and Wey, Christian, Multi-Union Bargaining: Tariff Plurality and
Tariff Competition, April 2014.
A revised version of the paper is forthcoming in: Journal of Institutional and Theoretical
Economics.
137
Duso, Tomaso, Herr, Annika and Suppliet, Moritz, The Welfare Impact of Parallel
Imports: A Structural Approach Applied to the German Market for Oral Anti-diabetics,
April 2014.
Published in: Health Economics, 23 (2014), pp. 1036-1057.
136
Haucap, Justus and Müller, Andrea, Why are Economists so Different? Nature,
Nurture and Gender Effects in a Simple Trust Game, March 2014.
135
Normann, Hans-Theo and Rau, Holger A., Simultaneous and Sequential
Contributions to Step-Level Public Goods: One vs. Two Provision Levels,
March 2014.
Forthcoming in: Journal of Conflict Resolution.
134
Bucher, Monika, Hauck, Achim and Neyer, Ulrike, Frictions in the Interbank Market
and Uncertain Liquidity Needs: Implications for Monetary Policy Implementation,
July 2014 (First Version March 2014).
133
Czarnitzki, Dirk, Hall, Bronwyn, H. and Hottenrott, Hanna, Patents as Quality Signals?
The Implications for Financing Constraints on R&D?, February 2014.
132
Dewenter, Ralf and Heimeshoff, Ulrich, Media Bias and Advertising: Evidence from a
German Car Magazine, February 2014.
Published in: Review of Economics, 65 (2014), pp. 77-94.
131
Baye, Irina and Sapi, Geza, Targeted Pricing, Consumer Myopia and Investment in
Customer-Tracking Technology, February 2014.
130
Clemens, Georg and Rau, Holger A., Do Leniency Policies Facilitate Collusion?
Experimental Evidence, January 2014.
129
Hottenrott, Hanna and Lawson, Cornelia, Fishing for Complementarities: Competitive
Research Funding and Research Productivity, December 2013.
128
Hottenrott, Hanna and Rexhäuser, Sascha, Policy-Induced Environmental
Technology and Inventive Efforts: Is There a Crowding Out?, December 2013.
Forthcoming in: Industry and Innovation.
127
Dauth, Wolfgang, Findeisen, Sebastian and Suedekum, Jens, The Rise of the East
and the Far East: German Labor Markets and Trade Integration, December 2013.
Published in: Journal of the European Economic Association, 12 (2014), pp. 1643-1675.
126
Wenzel, Tobias, Consumer Myopia, Competition and the Incentives to Unshroud
Add-on Information, December 2013.
Published in: Journal of Economic Behavior and Organization, 98 (2014), pp. 89-96.
125
Schwarz, Christian and Suedekum, Jens, Global Sourcing of Complex Production
Processes, December 2013.
Published in: Journal of International Economics, 93 (2014), pp. 123-139.
124
Defever, Fabrice and Suedekum, Jens, Financial Liberalization and the RelationshipSpecificity of Exports, December 2013.
Published in: Economics Letters, 122 (2014), pp. 375-379.
123
Bauernschuster, Stefan, Falck, Oliver, Heblich, Stephan and Suedekum, Jens,
Why Are Educated and Risk-Loving Persons More Mobile Across Regions?,
December 2013.
Published in: Journal of Economic Behavior and Organization, 98 (2014), pp. 56-69.
122
Hottenrott, Hanna and Lopes-Bento, Cindy, Quantity or Quality? Knowledge Alliances
and their Effects on Patenting, December 2013.
Forthcoming in: Industrial and Corporate Change.
121
Hottenrott, Hanna and Lopes-Bento, Cindy, (International) R&D Collaboration and
SMEs: The Effectiveness of Targeted Public R&D Support Schemes,
December 2013.
Published in: Research Policy, 43 (2014), pp.1055-1066.
120
Giesen, Kristian and Suedekum, Jens, City Age and City Size, November 2013.
Published in: European Economic Review, 71 (2014), pp. 193-208.
119
Trax, Michaela, Brunow, Stephan and Suedekum, Jens, Cultural Diversity and PlantLevel Productivity, November 2013.
118
Manasakis, Constantine and Vlassis, Minas, Downstream Mode of Competition with
Upstream Market Power, November 2013.
Published in: Research in Economics, 68 (2014), pp. 84-93.
117
Sapi, Geza and Suleymanova, Irina, Consumer Flexibility, Data Quality and Targeted
Pricing, November 2013.
116
Hinloopen, Jeroen, Müller, Wieland and Normann, Hans-Theo, Output Commitment
Through Product Bundling: Experimental Evidence, November 2013.
Published in: European Economic Review, 65 (2014), pp. 164-180.
115
Baumann, Florian, Denter, Philipp and Friehe Tim, Hide or Show? Endogenous
Observability of Private Precautions Against Crime When Property Value is Private
Information, November 2013.
114
Fan, Ying, Kühn, Kai-Uwe and Lafontaine, Francine, Financial Constraints and Moral
Hazard: The Case of Franchising, November 2013.
113
Aguzzoni, Luca, Argentesi, Elena, Buccirossi, Paolo, Ciari, Lorenzo, Duso, Tomaso,
Tognoni, Massimo and Vitale, Cristiana, They Played the Merger Game:
A Retrospective Analysis in the UK Videogames Market, October 2013.
Published in: Journal of Competition Law and Economics under the title: “A Retrospective
Merger Analysis in the UK Videogame Market”, (10) (2014), pp. 933-958.
112
Myrseth, Kristian Ove R., Riener, Gerhard and Wollbrant, Conny, Tangible
Temptation in the Social Dilemma: Cash, Cooperation, and Self-Control,
October 2013.
111
Hasnas, Irina, Lambertini, Luca and Palestini, Arsen, Open Innovation in a Dynamic
Cournot Duopoly, October 2013.
Published in: Economic Modelling, 36 (2014), pp. 79-87.
110
Baumann, Florian and Friehe, Tim, Competitive Pressure and Corporate Crime,
September 2013.
109
Böckers, Veit, Haucap, Justus and Heimeshoff, Ulrich, Benefits of an Integrated
European Electricity Market, September 2013.
108
Normann, Hans-Theo and Tan, Elaine S., Effects of Different Cartel Policies:
Evidence from the German Power-Cable Industry, September 2013.
Published in: Industrial and Corporate Change, 23 (2014), pp. 1037-1057.
107
Haucap, Justus, Heimeshoff, Ulrich, Klein, Gordon J., Rickert, Dennis and Wey,
Christian, Bargaining Power in Manufacturer-Retailer Relationships, September 2013.
106
Baumann, Florian and Friehe, Tim, Design Standards and Technology Adoption:
Welfare Effects of Increasing Environmental Fines when the Number of Firms is
Endogenous, September 2013.
105
Jeitschko, Thomas D., NYSE Changing Hands: Antitrust and Attempted Acquisitions
of an Erstwhile Monopoly, August 2013.
Published in: Journal of Stock and Forex Trading, 2 (2) (2013), pp. 1-6.
104
Böckers, Veit, Giessing, Leonie and Rösch, Jürgen, The Green Game Changer: An
Empirical Assessment of the Effects of Wind and Solar Power on the Merit Order,
August 2013.
103
Haucap, Justus and Muck, Johannes, What Drives the Relevance and Reputation of
Economics Journals? An Update from a Survey among Economists, August 2013.
Published in: Scientometrics, 103 (2015), pp. 849-877.
102
Jovanovic, Dragan and Wey, Christian, Passive Partial Ownership, Sneaky
Takeovers, and Merger Control, August 2013.
Published in: Economics Letters, 125 (2014), pp. 32-35.
101
Haucap, Justus, Heimeshoff, Ulrich, Klein, Gordon J., Rickert, Dennis and Wey,
Christian, Inter-Format Competition Among Retailers – The Role of Private Label
Products in Market Delineation, August 2013.
100
Normann, Hans-Theo, Requate, Till and Waichman, Israel, Do Short-Term Laboratory
Experiments Provide Valid Descriptions of Long-Term Economic Interactions? A
Study of Cournot Markets, July 2013.
Published in: Experimental Economics, 17 (2014), pp. 371-390.
99
Dertwinkel-Kalt, Markus, Haucap, Justus and Wey, Christian, Input Price
Discrimination (Bans), Entry and Welfare, June 2013.
98
Aguzzoni, Luca, Argentesi, Elena, Ciari, Lorenzo, Duso, Tomaso and Tognoni,
Massimo, Ex-post Merger Evaluation in the UK Retail Market for Books, June 2013. Forthcoming in: Journal of Industrial Economics.
97
Caprice, Stéphane and von Schlippenbach, Vanessa, One-Stop Shopping as a
Cause of Slotting Fees: A Rent-Shifting Mechanism, May 2012.
Published in: Journal of Economics and Management Strategy, 22 (2013), pp. 468-487.
96
Wenzel, Tobias, Independent Service Operators in ATM Markets, June 2013.
Published in: Scottish Journal of Political Economy, 61 (2014), pp. 26-47.
95
Coublucq, Daniel, Econometric Analysis of Productivity with Measurement Error:
Empirical Application to the US Railroad Industry, June 2013.
94
Coublucq, Daniel, Demand Estimation with Selection Bias: A Dynamic Game
Approach with an Application to the US Railroad Industry, June 2013.
93
Baumann, Florian and Friehe, Tim, Status Concerns as a Motive for Crime?,
April 2013.
A revised version of the paper is forthcoming in: International Review of Law and Economics.
92
Jeitschko, Thomas D. and Zhang, Nanyun, Adverse Effects of Patent Pooling on
Product Development and Commercialization, April 2013.
Published in: The B. E. Journal of Theoretical Economics, 14 (1) (2014), Art. No. 2013-0038.
91
Baumann, Florian and Friehe, Tim, Private Protection Against Crime when Property
Value is Private Information, April 2013.
Published in: International Review of Law and Economics, 35 (2013), pp. 73-79.
90
Baumann, Florian and Friehe, Tim, Cheap Talk About the Detection Probability,
April 2013.
Published in: International Game Theory Review, 15 (2013), Art. No. 1350003.
89
Pagel, Beatrice and Wey, Christian, How to Counter Union Power? Equilibrium
Mergers in International Oligopoly, April 2013.
88
Jovanovic, Dragan, Mergers, Managerial Incentives, and Efficiencies, April 2014
(First Version April 2013).
87
Heimeshoff, Ulrich and Klein Gordon J., Bargaining Power and Local Heroes,
March 2013.
86
Bertschek, Irene, Cerquera, Daniel and Klein, Gordon J., More Bits – More Bucks?
Measuring the Impact of Broadband Internet on Firm Performance, February 2013.
Published in: Information Economics and Policy, 25 (2013), pp. 190-203.
85
Rasch, Alexander and Wenzel, Tobias, Piracy in a Two-Sided Software Market,
February 2013.
Published in: Journal of Economic Behavior & Organization, 88 (2013), pp. 78-89.
84
Bataille, Marc and Steinmetz, Alexander, Intermodal Competition on Some Routes in
Transportation Networks: The Case of Inter Urban Buses and Railways,
January 2013.
83
Haucap, Justus and Heimeshoff, Ulrich, Google, Facebook, Amazon, eBay: Is the
Internet Driving Competition or Market Monopolization?, January 2013.
Published in: International Economics and Economic Policy, 11 (2014), pp. 49-61.
Older discussion papers can be found online at:
http://ideas.repec.org/s/zbw/dicedp.html
ISSN 2190-9938 (online)
ISBN 978-3-86304-191-5

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