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One Step at a Time: Does Gradualism Build Coordination?

Last registered on October 28, 2015

Pre-Trial

Trial Information

General Information

Title
One Step at a Time: Does Gradualism Build Coordination?
RCT ID
AEARCTR-0000929
Initial registration date
October 28, 2015

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 28, 2015, 8:11 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation
State University of New York (Binghamton) & Harvard University

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2010-07-01
End date
2018-07-01
Secondary IDs
Abstract
This study investigates a potential mechanism to promote coordination. With theoretical guidance using a belief-based learning model with level-k thinking, we conduct a multiple-period, binary-choice, and weakest-link coordination experiment in the laboratory to study the effect of gradualism – increasing the required levels (“stakes”) of contributions slowly over time rather than requiring a high level of contribution immediately – on group coordination performances in high-stake projects. We randomly assign subjects to three treatments: starting and continuing at a high stake, starting at a low stake but jumping to a high stake after a few periods, as well as starting at a low stake and gradually increasing the stakes over time (the Gradualism treatment). We find that groups coordinate most successfully with high stakes in the Gradualism treatment relative to the other two treatments. We also find evidence that supports the belief-based learning model. These findings point to a simple mechanism for promoting successful voluntary coordination when other mechanisms, such as communication and information feedback, are absent or limited.
External Link(s)

Registration Citation

Citation
Nikolov, Plamen. 2015. "One Step at a Time: Does Gradualism Build Coordination?." AEA RCT Registry. October 28. https://doi.org/10.1257/rct.929
Former Citation
Nikolov, Plamen and Plamen Nikolov. 2015. "One Step at a Time: Does Gradualism Build Coordination?." AEA RCT Registry. October 28. https://www.socialscienceregistry.org/trials/929/history/5805
Experimental Details

Interventions

Intervention(s)
We conduct a laboratory experiment at the Renmin University of China in Beijing, China, with 256 subjects recruited through the bulletin board system and posters. The majority of the subjects are students from Renmin University and nearby universities.
The experiment consisted of 18 sessions, which were all computerized using the z-Tree software package (Fischbacher, 2007). Both the instructions (see Appendix A) and the game information shown on the computer screen were in Chinese. In each session, we randomly assigned subjects to groups of four; our sample consisted of 64 groups in total.
The experiment included two stages: The first stage comprised twelve periods, whereas the second one comprised eight periods. Group members did not change within each stage but subjects were randomly reshuffled into groups of four after the first stage; this rule was made to be common information. The subjects were not told the exact number of periods in each stage. Instead, the subjects were told that the experiment would last from 30 minutes to one hour, including the time for sign-up, reading of instructions, taking a quiz designed to ensure that subjects understood the experimental rule, and final payment. We note two features of this design. First, we wanted to reduce the possibility of backward induction. Second, our study design approximated features of real-world situations. In many real-world cases, people do not know the exact number of coordination opportunities.
At the beginning of each period, subjects knew the stake of the current period but not those of future periods. This condition replicates the circumstances of many real-world cases, in which people do not know what is at stake in future interactions.
In each period, we endowed each subject with 20 points and asked each to give a certain number of points to the common pool of his/her assigned group. The required number could vary across periods, and each subject could only choose either “to give the exact points required” (we use the natural term “give” rather than “contribute” in the instruction), which we refer to as stake, or “not to give” at all. If all members in a group contributed, then each member not only received the stake back, but also gained an extra return, which equaled the stake. If not all group members contributed, then each member finished the period with only his/her remaining points (i.e., the initial endowment in each period minus the contribution of the subject).
At the end of each period, each subject knew whether all four group members (including himself/herself) contributed the stake for that period but did not know the total number of group members who contributed (in case fewer than four members contributed). This design is consistent with the standard design in the literature of minimum-effort coordination games (e.g., Van Huyck et al., 1990), in which the only commonly available historical data to players is the minimum contribution of group members. , By adopting this design we can also increase the difficulty of coordination given other aspects of the experiment, and study whether gradualism can help overcome such a difficulty.
The final total payment to each player equaled the accumulated earnings over all periods plus a show-up fee. The exchange rate was 40 points per CNY 1. An average subject earned CNY 21–22 (around USD 3) including the show-up fee for the whole experiment, which covered ordinary meals for one to two days on campus. With regard to the purchasing power, this payment was comparable to those experiments conducted in other countries.
Our experiment comprised four treatments: (1) Big Bang, (2) Semi-Gradualism, (3) Gradualism, and (4) a variant of the Big Bang treatment, which we call the High Show-up Fee treatment. All groups in the three main treatments faced the same stake in the second half (Periods 7–12) of the first stage, but stake paths differed for each treatment in the first half (Periods 1–6). The first half of the first stage featured different stake paths for each treatment. The different stake paths might yield potential earning differences and could potentially lead to a wealth effect across treatments. To isolate the wealth effect on the contribution of participants from the effect of the three main treatments in the second half of the first stage, we introduced the High Show-up Fee treatment, which is a variant of the Big Bang treatment. We describe the High Show-up Fee treatment in detail later in this Section. We randomly assigned 12 subjects into the three main treatments for 8 of the 18 sessions. In the remaining 10 sessions, we randomly assigned 16 subjects into the four treatments (three main treatments and one supplementary High Show-up Fee treatment). In total, we had 18, 18, 18, and 10 groups in Big Bang, Semi-Gradualism, Gradualism, and High Show-up Fee treatments, respectively. Unreported randomization checks show that the randomization of treatment assignment worked well (available upon request).
Intervention Start Date
2010-07-01
Intervention End Date
2018-07-01

Primary Outcomes

Primary Outcomes (end points)
We focus our analysis on the following three outcome variables per period: (1) whether a group coordinates successfully (defined as whether all four group members contribute) or not, (2) whether an individual contributes or not, and (3) payoff of each individual.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct a laboratory experiment at the Renmin University of China in Beijing, China, with 256 subjects recruited through the bulletin board system and posters. The majority of the subjects are students from Renmin University and nearby universities.
The experiment consisted of 18 sessions, which were all computerized using the z-Tree software package (Fischbacher, 2007). Both the instructions (see Appendix A) and the game information shown on the computer screen were in Chinese. In each session, we randomly assigned subjects to groups of four; our sample consisted of 64 groups in total.
The experiment included two stages: The first stage comprised twelve periods, whereas the second one comprised eight periods. Group members did not change within each stage but subjects were randomly reshuffled into groups of four after the first stage; this rule was made to be common information. The subjects were not told the exact number of periods in each stage. Instead, the subjects were told that the experiment would last from 30 minutes to one hour, including the time for sign-up, reading of instructions, taking a quiz designed to ensure that subjects understood the experimental rule, and final payment. We note two features of this design. First, we wanted to reduce the possibility of backward induction. Second, our study design approximated features of real-world situations. In many real-world cases, people do not know the exact number of coordination opportunities.
At the beginning of each period, subjects knew the stake of the current period but not those of future periods. This condition replicates the circumstances of many real-world cases, in which people do not know what is at stake in future interactions.
In each period, we endowed each subject with 20 points and asked each to give a certain number of points to the common pool of his/her assigned group. The required number could vary across periods, and each subject could only choose either “to give the exact points required” (we use the natural term “give” rather than “contribute” in the instruction), which we refer to as stake, or “not to give” at all. If all members in a group contributed, then each member not only received the stake back, but also gained an extra return, which equaled the stake. If not all group members contributed, then each member finished the period with only his/her remaining points (i.e., the initial endowment in each period minus the contribution of the subject).
At the end of each period, each subject knew whether all four group members (including himself/herself) contributed the stake for that period but did not know the total number of group members who contributed (in case fewer than four members contributed). This design is consistent with the standard design in the literature of minimum-effort coordination games (e.g., Van Huyck et al., 1990), in which the only commonly available historical data to players is the minimum contribution of group members. , By adopting this design we can also increase the difficulty of coordination given other aspects of the experiment, and study whether gradualism can help overcome such a difficulty.
The final total payment to each player equaled the accumulated earnings over all periods plus a show-up fee. The exchange rate was 40 points per CNY 1. An average subject earned CNY 21–22 (around USD 3) including the show-up fee for the whole experiment, which covered ordinary meals for one to two days on campus. With regard to the purchasing power, this payment was comparable to those experiments conducted in other countries.
Our experiment comprised four treatments: (1) Big Bang, (2) Semi-Gradualism, (3) Gradualism, and (4) a variant of the Big Bang treatment, which we call the High Show-up Fee treatment. All groups in the three main treatments faced the same stake in the second half (Periods 7–12) of the first stage, but stake paths differed for each treatment in the first half (Periods 1–6). The first half of the first stage featured different stake paths for each treatment. The different stake paths might yield potential earning differences and could potentially lead to a wealth effect across treatments. To isolate the wealth effect on the contribution of participants from the effect of the three main treatments in the second half of the first stage, we introduced the High Show-up Fee treatment, which is a variant of the Big Bang treatment. We describe the High Show-up Fee treatment in detail later in this Section. We randomly assigned 12 subjects into the three main treatments for 8 of the 18 sessions. In the remaining 10 sessions, we randomly assigned 16 subjects into the four treatments (three main treatments and one supplementary High Show-up Fee treatment). In total, we had 18, 18, 18, and 10 groups in Big Bang, Semi-Gradualism, Gradualism, and High Show-up Fee treatments, respectively. Unreported randomization checks show that the randomization of treatment assignment worked well (available upon request).
Experimental Design Details
Randomization Method
Computer program
Randomization Unit
Experimental Session
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
256 individuals
Sample size: planned number of observations
500
Sample size (or number of clusters) by treatment arms
256 subjects across 12 periods
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Harvard University
IRB Approval Date
2010-07-23
IRB Approval Number
F19258-101

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials