ISSN (Print) 0473-453X

Discussion Paper No. 1169

ISSN (Online) 2435-0982

AN EXPERIMENTAL STUDYON STRATEGIC PREFERENCE FORMATION
IN TWO-SIDED MATCHING MARKETS
Natsumi Shimada

March 2022

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, JapanAn experimental study on strategic preference
formation in two-sided matching markets ∗Natsumi Shimada†March 16, 2022
Abstract

We study an experiment of the students-proposing deferred acceptance mechanism (DA)in matching markets where firms are matched with students. We investigated the twodifferent situations: (i) Students know firms’ preferences and firms submit their true
preference, (ii) Students know firms’ preferences and firms submit a higher ranking tostudents who give them higher ranking. This experiment confirms that the matching
results under DA influence students’ preference formation, which decreases the degreeof stability. If firms do not submit their true preferences, students also do not submit
their true preferences. As a result, the situation induces instability. Moreover, we findthe new pattern of submitted preferences – compromise strategy. If there is an extreme
option, students will tend to prefer the in-between option.

1

Introduction

Gale and Shapley’s (1962) deferred acceptance mechanism has been used for clearinghouses to match agents on two sides. The most well-known example is the National
Resident Matching Program which matches physicians with hospitals in the US. Although it is incentive compatible for one side, the experiment literature reveals thatagents often manipulate DA with their preferences over those on the other side (Hakimov and Kübler (2019)). In particular, the degree of manipulation is lower with less∗I thank Morimitsu Kurino for his guidance. I thank Takehito Masuda for the very helpful discussion. I also thank Eizo Akiyama, Ryoji Sawa, Hiroyasu Ando, Hidekazu Anno, Nobuyuki Hanaki and
Tsuruga Takayuki. I am deeply grateful to Natsuki Yamazaki and Kohei Akutsu.
†
Institute of Social and Economic Research, Osaka University, 6-1 Mihogaoka, Ibaraki, Osaka 5670047, Japan. E-mail: nshimada@iser.osaka-u.ac.jp. This paper is part of my doctoral dissertation at
University of Tsukuba in 2021.

1

information on the preferences on the other side ( Pais and Pintér (2008) ). We further
investigate what kind of preferences are submitted to the clearinghouse.
The Japanese entry-level labor market is another example of two-sided matchingmarkets for college students and recruiting firms. Although the market is decentralizedwith the unraveling phenomena ( Roth and Xing (1994)), there are platform companies
that post recruiting information about registering firms on the web and then provide
the information to registering students. One of such companies, Riku-nabi, analyzed
students’ behavior on the web and then sold their analyzed preferences of students. This was considered an invasion of students’ privacy and caused a social problem.
The reason why such information is valuable to firms is that firms desire students
who evaluate them high. This kind of firms’ preferences corresponds to the skippingdown strategy in the centralized matching mechanism (See Echenique et al. (2016) and
Kawagoe et al. (2018) for experimental evidence). The skipping-down strategy of anagent is the preference ordering of moving up agents on the other side if they evaluate
themselves highly.
We experimentally investigate agents’ strategy of submitting preferences, dependingon the behavior of those on the other side. In particular, in our two-sided matchingmarket, one side is “students,” while the other side is “firms.” We assume that there is aclearinghouse that uses a student-proposing deferred acceptance mechanism (hereafter,DA) for matching students and firms after collecting preferences from students andfirms. 1 Our information setting is complete information where all agents know theother agents’ true preferences. 2 Our baseline treatment is that firms sincerely reporttheir preferences, and this reporting behavior is known to students. We call it thesincere strategy (SS) treatment. Another treatment is that firms use the skippingdown strategy for reporting preferences, which is known to students. We call it theskipping-down strategy (SDS) treatment.
The SS treatment was investigated in Echenique et al. (2016) and other studies.
Their result is that students are not sincere but use the skipping-down strategy. However, we observe that the skipping-down strategy is rarely chosen in our two treatments.
Surprisingly, we find that a new type of strategy, what we call the compromise strategy, is pervasive in our experiment.
The compromise strategy is the preference ordering of putting the middle into the1
DA is the well-known two-sided matching mechanism. Each student applies to their most favorite
firm that has not been rejected. Each firm considers the students it has held together with all appliedstudents and decides to accept and reject. The mechanism terminates when no student remains
unassigned. We explain its procedure and properties in Section 2.
2
Echenique et al. (2016) mentioned that complete information setting is that it first step in understanding participants’ response. Moreover, most theoretical studies assumes agents has complete
information setting. Of course, like to Pais and Pintér (2008) and Pais et al. (2011), we can checkthe behavior various information settings. However, the skipping-down strategy in our experiment,
student’s skipping down strategy based on other sides preference. It is hard to make theoreticalpredictions.

2

first choice, excluding the best and the worst choice, in the preference ordering. This
type of strategy explains about 40% and 50% of the data in SS and SDS treatments, respectively. The compromise strategy applies the Simonson and Tversky (1992) extreme
aversion in individual decision-making to preference strategies in two-sided matchingmarkets.
As Roth (2002) documented, the stability has been the most important property
for the functioning of mechanisms in two-sided matching markets. Stability requiresthat there is no pair of agents who are not matched prefer to match each other. In
the realized matching of our experiment, as a result of frequent use of compromise
strategy above mentioned especially in , we observed blocking pairs amounts 2 out of
48 students in SS treatment, 17 out of 48 students in SDS treatment had blocking pairs,
respectively.
This paper contributes to the literature in two ways. First, we are first in finding
compromise strategy can be a major subjects behavior in matching experiment. Moreover, compromising has a commonly reported behavior in individual decision making,which is originally systematically investigated by Simonson and Tversky (1992). Second, to the best of our knowledge, our study is new in conducting treatments in whichfirms change its behavior based on the preferences submitted by the students automatically(such that by programmed).

1.1

Related literature

DA has desirable properties of strategy-proofness and stability in full information setting. First, Stable in the sense that its resulting matching is stable at the reported
preference profile (Gale and Shapley (1962)). Second, it is strategy-proof in the sensethat it is a weakly dominant strategy for all students to submit their true preferences(Dubins and Freedman (1981), Roth (1982)). Subsequent to these seminal studies, thefollowing three strands of literature have emerged.
Type of untruthful preference submission in matching experiments
Many experimental studies show that the truth-telling rate is not 100% in DA (See therecent survey by Hakimov and Kübler (2019)).
Other previous experiments found many biases in decision making, for example,• Skipping-down strategy(Echenique et al. (2016), Kawagoe et al. (2018)) in whicha student moves up the firm if it evaluates the student highly. That is similar topriority school bias.
• Priority school bias(Pais and Pintér (2008), Pais et al. (2011)): Students submit
to the school where they have a priority higher than their true preference.

3• District school bias(Chen and Sönmez (2006)): A student puts their district school
into a higher ranking than true preference. Each student is highly prioritized by
the school in the district they live in, and hence they are likely to be matched withthere. with the school. The bias can be regarded as the same as the skipping-down
strategy.
• Minneapolis strategy: (Chen and Sönmez (2006)): Students rank a school with alarge capacity (or own school-zone higher.
• Small size bias (Chen and Sönmez (2006), Pais and Pintér (2008), Pais et al.
(2011)): Students rank schools with fewer seats lower. Our experiment’s capacity
is the same(capacity = 1), so the bias is not applicable.
• Similarity preference bias((Chen and Sönmez (2006))): Students avoid conflict by
predicting that they will have similar behavior to their own. Students only know
their own preferences. Therefore, our experiment’s deviation behavior does not
apply to any of these.
Recently, other studies have shown deviations from the dominant strategy(Dreyfuss
et al. (2019)).
Robustness check of matching theory in various settings
Antler (2015) apply the preferences formation. If agent i ’s message expresses thathe/she desires agent j , then this makes him/her more attractive to j. This is similar
to skipping-strategy; however, they considered changing true preference, not bias.
We use the standard matching model and formulate the skipping-down and compromise strategies in general as follows. Section 2 describes the theoretical background, andour experimental design includes the skipping-down strategy formulation. Section 3 explains our experimental settings. Section 4 presents our experimental results, including
the compromise strategy formulation. Section 5 provides the concluding remarks.

2

Model

Our experiment considers a two-sided matching market with agents from two (disjoint)sides, students and firms. For simplicity, we focus on one-to-one matching interaction
with the number of students equal to that of firms.
Let there be a finite set of students, S, and a finite set of firms, F . Each students ∈ S has a strict preference relation s over the set of firms, and each firm f ∈ F
has a strict preference relation f over the set of students. Let S = (s )s∈S andF = (f )f ∈F . Strict preference means that there are no tied ranks; each participant4

arranges the members of the other group in ranking order. We denote by ps (f ) the
position of firm f with respect to the student s’s preference s . For example, if a
student s lists fA as the most preferred firm, fB as the second preferred firm, thenps (fA ) = 1 and ps (fB ) = 2.
Similarly, we denote pf (s) the position of student s with respect to the firm f ’s
preference f . For example, if a firm f ’s second choice is student s1 , ps1 (f ) = 2.
A matching µ is a function µ: S ∪ F → S ∪ F such that each student is assigned afirm and each firm is assigned a student, i.e., for each s ∈ S and each f ∈ F satisfies(i) µ(s) ∈ F , (ii) µ(f ) ∈ S, (iii) µ(s) = f ⇔ µ(f ) = s. Given matching µ, a pair(s, f ) ∈ S × F is called a blocking pair if s f µ(f ) and f s µ(s). A matching µ is
stable if there is no blocking pair.
We assume that a clearinghouse collects preferences from students and firms. It
determines the matching via a mechanism using collected preferences. In other words,
each agent submits their preference to the clearinghouse, which implements an mechanism to determine the matching result. We call a collection of preferences (i )i∈S∪F
as a preference profile. A mechanism ϕ is a function that maps preference profiles tomatchings. Let ϕi be the agent who is matched with agent i. A participant i ∈ S ∪ F
has their own true preference i , other preference 0i and other participants’ preference
represented by −i . We call truth-telling is a dominant strategy for participant i if
ϕi (i , −i ) i ϕi (0i ,−i ) for any 0i and any −i . Moreover, when it is the dominant
strategy for all participants s ∈ S to submit their true preference s , the mechanism
is called strategy-proof.
We use Gale and Shapley (1962)’s student-proposing deferred acceptance mechanism(DA) that selects a matching by using the following algorithm.
DA
Step 1: Each student applies to her first choice. Each firm tentatively assigns its
seats to its applicants following the firm’s preferences. Any unassigned student isrejected.
Step k ≥ 2: Each student who was rejected at the previous step applies to her
next favorite firm. Each firm considers the students it has been holding together
with its new applicants and tentatively assigns its seats following the firm’s preferences. Any unassigned student is rejected. The mechanism terminates when no
student remains unassigned.
DA is known to satisfy the following properties. First, DA is stable in the sense thatits resulting matching is stable at the reported preference profile (Gale and Shapley(1962)). Second, it is strategy-proof in the sense that it is a weakly dominant strategy
for all students to submit their true preferences (Dubins and Freedman (1981), Roth(1982)).
5In our experiment, we let the participants play the role of students, not firms, andthen submit their preferences to the clearinghouse, i,e., experimenter which uses DA. In
our design of experiments, participants as students are endowed with their true preferences. In submitting their preferences, participants as students do not have to submit
their true preferences but can choose any. If the submitted preferences are not true, we
say that they manipulate preferences. Since DA is strategy-proof, participants have no
incentives to manipulate preferences. Hence, if we observe manipulating preferences inexperiments, the reason would not be the mechanism in use.
The literature reports that deviation from truth-telling in DA is pervasive (Hakimov and Kübler (2019)). Although DA is strategy-proof, many previous experiments
studies show some tendency of deviating preferences. A typical example is the skippingdown strategy in which a student moves up the firm if it evaluates the student highly(Echenique et al. (2016), Kawagoe et al. (2018)). For example, if firm fA has s as its
top choice and firm fB has s as its the second choice, student s prefers fA to fB . We
assume strict preferences, so the skipping-down strategy is uniquely determined. We
define the skipping-down strategy as follows;
Skipping-Down Strategy
1 Given true preference s of student s and true preference profile F of firms F ,we say that strategy 0s is the skipping-down strategy of student s if for any two
0
firms f and f 0 , f s f 0 ⇔ [pf (s) < pf 0 (s)] or [pf (s) = pf 0 (s) and f s f 0 ].
2 Given true preference f of firm f and the preference profile S of students S,
we say that strategy 0f is the skipping-down strategy of firm f if for any two0students s and s0 , s f s0 ⇔ [pf (s) < pf (s0 )] .
As an example, suppose that firm fA has student s1 as its first choice and fB has
student s1 its third choice. Then, 1 = pfA (s1 ) < pfB (s1 ) = 3, so the student s1 ’s
skipping-down strategy 0s1 implies fA 0s1 fB . Similarly suppose that both firms fAand fB has student s1 its first choice, ps1 (fA ) = ps1 (fB ) = 1. Suppose also student s1
has fA s1 fB as his true preference s1 . Then the student s1 ’s skipping-down strategy
0s1 is fA 0s1 fB .

3

Experimental design

The participants played the role of students. At the same time, firms’ behavior isprogrammed. We have three treatments, varying information given to the participants
on firms’ strategies. Once all the preference profiles were collected, the matching results
were calculated by DA. Specifically, three treatments are:6• Treatment 1 (SS) – Students know firms’ true preferences, and firms are programmed to submit their own true preferences.
• Treatment 2 (SDS) – Students know firms’ true preferences, and firms submit
are programmed to follow the skipping-down strategy.
Table 1: Example of SS(a) Firm f ’s true
preference

First
SecondThird
Fourth
Fifth
Sixth

s1
s2
s3
s4
s5
s6

(b) submitted rankingof firm f by studentsFirst
s3 , s4
Second s5
Third
s1 ,s2 , s6
FourthFifth
Sixth(c)Firm f ’ submit
preference

First
SecondThird
Fourth
Fifth
Sixth

s3
s4
s5
s1
s2
s6

For example in SDS as shown in Table 1, a firm f ’s true preference f = s1 f s2 f
s3 f s4 f s5 f s6 in panel(a). Suppose that s3 and s4 submitted firm f as their first
choice, s5 submitted as the second choice, s1 , s2 and s6 submitted as the third choice inpanel(b). Then, firm f submits its preference 0f = s3 f s4 f s5 f s1 f s2 f s6
in panel(c).
The SS is a typical treatment. Table 2 panels (a) and (b) summarize true preferencesused across three treatments. We chose true preferences as in panels (a) and (b) for
two reasons. First, in SS if all participants submit their truth-telling, then everyone
will match with their second-ranked firms (indicated by TT in panel (a) first column).
Second, panel (c) indicates students’ skipping-down strategy. In SS, firms submit theirtrue preference as panel (b). In SDS, firms submit their skipping-down strategy as
panel (d) based on students skipping down strategy as panel (b). This design would
verify whether participants take the skipping-down strategy even at the cost of being
worse off (indicated by SD in panel (a) first column).
Table 3 summarized the first choice of truth-telling and skipping down strategy.
Under our specification of true preferences shown in Table 2 panels (a) and (b), any
student following the skipping-down strategy manipulates their own first choice. We
distinguish which truth-telling or skipping-down strategy is taken.
Our experiment was computerized using the experimental software oTree (Chenet al. (2016)). One group consists of six participants. Each participant was seatedrandomly. No communication among participants was allowed. The total number ofparticipants was 96 (each treatment has 48 participants × 2). We recruited participantsat the University of Tsukuba.
7

SS and SDS each had three experimental sessions. At the beginning of each session,
we distributed the instructions and read it to them by reading software. We prepared
the review question along with the instructions, and we gave participants points as anincentive to solve the review question (15 minutes). All participants answered all questions correctly and got all points. We distributed the answer to the review question,and participants checked the collect answer (5 minutes). After gathering the review
questions and answers, we started the participants to play only one round. There wasno time limit for the decision-making. Matching results were displayed after every participant in the group submitted preferences. The points gained depended on the resultof the match, as follows; If a participant match with the first choice, the participant
gets 14 points, second choice 11 points, third choice, 9 points, fourth choice 8 points,
fifth 7.5 points, sixth 7 points. Note that points are converted based on the rankingof true preference. After the matching result was displayed, participants answered aquestionnaire. Each subject was privately paid the sum of his/her earnings for thereview question and experiment(show-up fee is 500 JPY, 1 point equals 50 JPY).
Table 2: Experimental settings(b) True preference of firms(a) True preference of students

s1
fA
TT fE
fC
SD fB
fF
fD

s2
fB
fC
fD
fF
fA
fE

s3
fF
fA
fB
fC
fE
fD

s4
fA
fB
fF
fD
fC
fE

s5
fB
fF
fA
fE
fD
fC

s6
fF
fD
fE
fA
fC
fB

 fA
s6
s5
s3
s2
s1
s4

fB
s1
s3
s4
s6
s2
s5

fC
s6
s1
s2
s3
s5
s4

fD
s1
s2
s6
s4
s3
s5

fE
s2
s6
s1
s5
s4
s3

fF
s2
s4
s5
s1
s6
s3

(c) Skipping-down strategy of students based on Table (b) true preference of firms(d) Skipping-down strategy of firms
based on Table (c) skipping-down
strategy of students

0s1
fB
fD
fC
fE
fF
fA

0fA
s6
s5
s3
s2
s4
s1

0s2
fF
fE
fD
fC
fA
fB

0s3
fB
fA
fC
fD
fF
fE

0s4
fF
fB
fD
fE
fA
fC

0s5
fA
fF
fE
fC
fB
fD

0s6
fA
fC
fE
fD
fB
fF

8

0fB
s1
s3
s4
s6
s5
s2

0fC
s6
s1
s3
s2
s5
s4

0fD
s1
s2
s4
s6
s3
s5

0fE
s2
s6
s5
s1
s4
s3

0fF
s2
s4
s5
s1
s3
s6

Table 3: Experimental settings, first choicess1
Truth telling fA
Skipping-down fB

4

s2
fB
fF

s3
fF
fB

s4
fA
fF

s5
fB
fA

s6
fF
fA

Results

Our interest is how the difference in firms’ decision-making affects students’ decisionmaking process. The stability is compared by the number of blocking pairs.

4.1

Stability

We evaluate what percentages of realized matching under each treatment are unstable,using the number of participants who have blocking pairs. The number of students who
have blocking pairs are as follows; 1 in SS, and 14 in SDS. 3
Result 1. Having information about firms taking skipping-down strategy results in moreunstable matchings.
Support. Significantly more participants had blocking pairs in SDS compared to SS(p < 0.001, one-sided proportion test), .
Table 4: summary of decision making
truth telling
manipulation
first choice manipulation
skipping-down

SS
43.75 %
56.25 %
47.9 %
8.3 %SDS
29.16 %
70.84 %
60.41 %
12.5 %

Notes: Each proportion is divided by the number of participants (such as 48).

4.2

Truth-telling

Table 4 presents the proportion of participants who played truthfully (regarding induced
preference). We check whether participants manipulated their first choice firm or not(We call such behavior first choice manipulation). Note that first choice manipulation
includes skipping-down strategy as shown in Table 3.
3

The number of blocking pairs is as follows; 2 in SS, 17 in SDS, respectively.

9Result 2. Having information about firms taking the skipping-down strategy reduces
truth-telling. Approximately ten percent of the participants take the skipping-down strategy in both treatments.
Support. Table 4 shows the truth-telling rate. Significantly more participants submitted their true preference in SS compared to SDS (p < 0.0068, one-sided proportiontest) . We check whether first-ranking firms were skipping-down strategies for each student’s submitted rank; the first-ranked firm is consistent with the one predicted under
the skipping-down strategy. In our experiment, the rates of taking the skipping-down
strategy are 8.3 % in SS and 12.5 % in SDS.
Although our specification of true preferences is motivated by skipping-down strategies observed in Echenique et al. (2016), Kawagoe et al. (2018), such strategy is not
typical in our data.4

4.3

Compromise strategy

Given that skipping-down is not frequently observed in our experiment, we introduce
another type of strategy called compromise strategy to better explain our data. Thisbias is similar to a compromise effect (Simonson (1989), Simonson and Tversky (1992)).
Simonson (1989) distinguished compromise effect from the other effect, Simonson andTversky (1992) surveyed in which they asked people to choose one of three options thatdiffered in price and quality. They show that the chosen rate of the middle option isrelative to the other extreme. To the best of the author’s knowledge, this is the firststudy to find a compromise strategy in matching.
We model the students who submit their preferences, taking care of the balance
between i) to which firms they rank highly and ii) from which firms they are highly
ranked. Note that the skipping-down strategy emphasizes only ii), but the novel pointof compromise strategy is to consider i) and ii) simultaneously.
To illustrate our idea of compromise strategy, let us look at Table 5 , which illustrates
how student 1 makes his compromise strategy.
Table 5 consist of panel (a), (b) and (c). Panel (a) extracted student 1’s truepreference. Panel (b) extracted how student 1 is ranked by each firm. Panel (c) is
generated by panels (a) and (b), where x-axis is pf (s1 )and y-axis is ps1 (f ). For simplicity, we denote point (x, y) = (pfA (s1 ), ps1 (fA )) by A. That is, point A = (5, 1)
summarizes the balance between how firm A ranks s1 (fifth) and how s1 ranks firm
A (first). Similarly, we can plot B = (1, 4), C = (2, 3), D = (1, 6), E = (3, 2) andF = (4, 5).
4

Other biases reported in existing experimental matching literature are not applicable since any
firm has capacity of one in our design and we focus on first-choice manipulations.

10In our data, student 1 is likely to submit firm E or C as her first choice. That isthese points are middle-ranked in the set. Note that this behavior can be explained byneither truth-telling nor skipping-down strategy: if student 1 follows truth-telling, heshould submit firm A as his first choice; if student 1 follows skipping-down strategy, heshould submit firm B or D as his first choice.
Table 5: Example: Student 1’s compromise strategy
s1
A
E
C
B
F
D
(a) s1

 fA

fB
s1

fC

fD
s1

fE

fF

s1
s1
s1
s1

(b) student ’s rank from firms(c) plot of s1

Notes: In (c), red-diamonds is true preference, blue-square is skipping-down strategy, green-circle
is compromise strategy, gray-cross is other.

We formalize compromise strategies as follows.
Compromise strategy
We formalize the compromise strategy of student s. Plot a point (pf (s), ps (f )) for eachfirm f . Here pf (s) is the position of student s in firm f ’s preference, while ps (f ) is the
position of firm f in student s’s preference. We denote fA for the firm corresponding
to point A. We say that a point A dominates a point B in the graph if pfA (s) ≤pfB (s) and ps (fA ) ≤ ps (fB ) for at least one strict inequality. Consider the set of
undominated points, Z. When there are more than one undominated points, we havethe two extreme points: the points for the lowest and the highest in the verticalaxis.5 We define a compromise strategy to be any strategy whose first choice is in
the undominated set excluding the two extreme points.6 .
Now, we show that, following the above elimination steps of choices, student 1
participants to submit firms C or E. For example, in Table 5 panel (c), student 1
has six points: {(5, 1), (1, 4), (2, 3), (1, 6), (3, 2), (4, 5)}. Since (1, 6) ≥ (1, 4), point D
is eliminated. Similarly, (4, 5) ≥ (1, 4), point F is eliminated. Then, student 1’s Z =5

Due to the domination relation in the undominated set, the lowest (highest) point in the verticalaxis corresponds to the highest (lowest) one in the horizontal axis.
6
The compromise strategy occurs when there are at least three points in Z11

{(5, 1), (1, 4), (2, 3), (3, 2)}. Since (5, 1) has minimal y-coordinate, point A is eliminated.
Similarly, (1, 4) has maximal y-coordinate, point B is eliminated. Thus, the points
which survives the elimination procedure are {(2, 3), (3, 2)}. Since the points (2, 3) and(3, 2) respectively corresponds firms C and E. Therefore, a compromise strategy is tosubmit firms C or E.
Figure 1 summarizes all students’ preferences and strategies of our interest; reddiamond is the true preference, blue-square is skipping-down strategy, green-circle iscompromise strategy, gray-cross is other, respectively. Table 6 summarized participants’compromise strategy of their first choice like as Table 3. If the subject has several
compromise strategies, we indicate ”self” that the participant submits a firm as her
first choice as the highest-ranking, and we denote ”firm” that the participant submits afirm as her first choice is highly regarded. Table 7 shows the rate of chosen compromise
strategy as first choice like as Table 4.

Figure 1: Plot of each student’s preference
Result 3. Under SS and SDS, the number of compromise strategies is significantly
higher than the number of skipping down strategies.
12

Table 6: Compromise strategy as first submits1
s2 s3
Compromise C,E C,D A- selfEC- firm
C
D
-

s4
B
-

s5
F
-

s6
D,E
D
E

Notes:‘self’ means that the participant submit a firm as her first choice as the highest ranking ofher. ‘firm’ mean that the participant submit a firm as her first choice which highly regarded.

Table 7: Summary of compromise strategySScompromise 39.58 %- self20.83 %
18.75 %- firm

SDS
47.91 %
29.16 %
18.75 %

Notes: Each proportion is divided by the number of participants (such as 48).

Support. The skipping-down strategy was taken 8.3% in SS, and 12.5% in SDS in Table
4. The compromise strategy was taken 39.58% in SS, and 47.91% in SDS in Table 7.
Significantly, participants who chose the skipping-down strategy compared to participants who chose compromise strategy in SS (p <0.001, one-sided proportion test), also
we compare these in SDS (p <0.001, one-sided proportion test).

5

Conclusion

In this study, we have focused on the effect of preferences disclosure on matching. As
other previous studies have shown, people use the skipping-down strategy of ranking
the firm, which evaluates him higher. Our experiment supposes that the preference
information is disclosed, and firms take the skipping-down strategy. In this case, we
observed that students hardly submit their true preferences. As a result, the situationinduces instability is observed. Moreover, we find the new pattern of submitted preferences – compromise strategy. If there is an extreme option, students will tend to prefer
the in-between option.

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