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Last registered on October 28, 2015

Trial Information

Name

Affiliation

State University of New York (Binghamton) & Harvard University

PI Name

PI Affiliation

Renmin University of China

Status

On going

Start date

2010-07-01

End date

2018-07-01

Keywords

Additional Keywords

JEL code(s)

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)

Citation

Asher, Sam, Plamen Nikolov and Maoliang Ye. 2015. "One Step at a Time: Does Gradualism Build Coordination?." AEA RCT Registry. October 28. https://doi.org/10.1257/rct.929-3.0.

Former Citation

Asher, Sam et al. 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

Intervention(s)

The experiment consists of 18 sessions, which are computerized using the z-Tree software package (Fischbacher, 2007). Both the instructions and the game information shown on the computer screen are in Chinese. In each session, we randomly assign subjects to groups of four; our sample consist of 64 groups in total.

The experiment includes two stages: The first stage comprises twelve periods, whereas the second one comprises eight periods. Group members do not change within each stage but subjects are randomly reshuffled into groups of four after the first stage; this rule is made to be common information. The subjects are not told the exact number of periods in each stage. Instead, the subjects are 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 understand the experimental rule, and final payment. We note two features of this design. First, we want to reduce the possibility of backward induction. Second, our study design approximates 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 know 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 endow each subject with 20 points and ask 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 contribute, then each member not only receives the stake back, but also gains an extra return, which equals the stake. If not all group members contribute, then each member finishes 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 knows 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 equals the accumulated earnings over all periods plus a show-up fee. The exchange rate is 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 covers ordinary meals for one to two days on campus. With regard to the purchasing power, this payment is comparable to those experiments conducted in other countries.

Our experiment comprises 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 face the same stake in the second half (Periods 7–12) of the first stage, but stake paths differ for each treatment in the first half (Periods 1–6). The first half of the first stage feature 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 introduce the High Show-up Fee treatment, which is a variant of the Big Bang treatment. We randomly assign 12 subjects into the three main treatments for 8 of the 18 sessions. In the remaining 10 sessions, we randomly assign 16 subjects into the four treatments (three main treatments and one supplementary High Show-up Fee treatment). In total, we have 18, 18, 18, and 10 groups in Big Bang, Semi-Gradualism, Gradualism, and High Show-up Fee treatments, respectively.

The experiment includes two stages: The first stage comprises twelve periods, whereas the second one comprises eight periods. Group members do not change within each stage but subjects are randomly reshuffled into groups of four after the first stage; this rule is made to be common information. The subjects are not told the exact number of periods in each stage. Instead, the subjects are 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 understand the experimental rule, and final payment. We note two features of this design. First, we want to reduce the possibility of backward induction. Second, our study design approximates 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 know 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 endow each subject with 20 points and ask 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 contribute, then each member not only receives the stake back, but also gains an extra return, which equals the stake. If not all group members contribute, then each member finishes 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 knows 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 equals the accumulated earnings over all periods plus a show-up fee. The exchange rate is 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 covers ordinary meals for one to two days on campus. With regard to the purchasing power, this payment is comparable to those experiments conducted in other countries.

Our experiment comprises 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 face the same stake in the second half (Periods 7–12) of the first stage, but stake paths differ for each treatment in the first half (Periods 1–6). The first half of the first stage feature 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 introduce the High Show-up Fee treatment, which is a variant of the Big Bang treatment. We randomly assign 12 subjects into the three main treatments for 8 of the 18 sessions. In the remaining 10 sessions, we randomly assign 16 subjects into the four treatments (three main treatments and one supplementary High Show-up Fee treatment). In total, we have 18, 18, 18, and 10 groups in Big Bang, Semi-Gradualism, Gradualism, and High Show-up Fee treatments, respectively.

Intervention Start Date

2010-07-01

Intervention End Date

2018-07-01

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 (end points)

Secondary Outcomes (explanation)

Experimental Design

The experiment consists of 18 sessions, which are computerized using the z-Tree software package (Fischbacher, 2007). Both the instructions and the game information shown on the computer screen are in Chinese. In each session, we randomly assign subjects to groups of four; our sample consist of 64 groups in total.

The experiment includes two stages: The first stage comprises twelve periods, whereas the second one comprises eight periods. Group members do not change within each stage but subjects are randomly reshuffled into groups of four after the first stage; this rule is made to be common information. The subjects are not told the exact number of periods in each stage. Instead, the subjects are 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 understand the experimental rule, and final payment. We note two features of this design. First, we want to reduce the possibility of backward induction. Second, our study design approximates 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 know 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 endow each subject with 20 points and ask 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 contribute, then each member not only receives the stake back, but also gains an extra return, which equals the stake. If not all group members contribute, then each member finishes 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 knows 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 equals the accumulated earnings over all periods plus a show-up fee. The exchange rate is 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 covers ordinary meals for one to two days on campus. With regard to the purchasing power, this payment is comparable to those experiments conducted in other countries.

Our experiment comprises 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 face the same stake in the second half (Periods 7–12) of the first stage, but stake paths differ for each treatment in the first half (Periods 1–6). The first half of the first stage feature 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 introduce the High Show-up Fee treatment, which is a variant of the Big Bang treatment. We randomly assign 12 subjects into the three main treatments for 8 of the 18 sessions. In the remaining 10 sessions, we randomly assign 16 subjects into the four treatments (three main treatments and one supplementary High Show-up Fee treatment). In total, we have 18, 18, 18, and 10 groups in Big Bang, Semi-Gradualism, Gradualism, and High Show-up Fee treatments, respectively.

The experiment includes two stages: The first stage comprises twelve periods, whereas the second one comprises eight periods. Group members do not change within each stage but subjects are randomly reshuffled into groups of four after the first stage; this rule is made to be common information. The subjects are not told the exact number of periods in each stage. Instead, the subjects are 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 understand the experimental rule, and final payment. We note two features of this design. First, we want to reduce the possibility of backward induction. Second, our study design approximates 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 know 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 endow each subject with 20 points and ask 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 contribute, then each member not only receives the stake back, but also gains an extra return, which equals the stake. If not all group members contribute, then each member finishes 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 knows 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 equals the accumulated earnings over all periods plus a show-up fee. The exchange rate is 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 covers ordinary meals for one to two days on campus. With regard to the purchasing power, this payment is comparable to those experiments conducted in other countries.

Our experiment comprises 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 face the same stake in the second half (Periods 7–12) of the first stage, but stake paths differ for each treatment in the first half (Periods 1–6). The first half of the first stage feature 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 introduce the High Show-up Fee treatment, which is a variant of the Big Bang treatment. We randomly assign 12 subjects into the three main treatments for 8 of the 18 sessions. In the remaining 10 sessions, we randomly assign 16 subjects into the four treatments (three main treatments and one supplementary High Show-up Fee treatment). In total, we have 18, 18, 18, and 10 groups in Big Bang, Semi-Gradualism, Gradualism, and High Show-up Fee treatments, respectively.

Experimental Design Details

Randomization Method

Computer program

Randomization Unit

Experimental Session

Was the treatment clustered?

Yes

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 Information

Is the intervention completed?

No

Is data collection complete?

Data Publication

Is public data available?

No

Program Files