Measuring Experimenter Demand

Last registered on May 18, 2017

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Pre-Trial

Trial Information

General Information

Title

Measuring Experimenter Demand

RCT ID

AEARCTR-0001248

Initial registration date

May 18, 2016

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

May 18, 2016, 8:31 AM EDT

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

Last updated

May 18, 2017, 6:12 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

United States of America

Region

Primary Investigator

Name

Christopher Roth

Affiliation

University of Warwick

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Jonathan Quidt

PI Affiliation

IIES Stockholm

Contact Investigator

PI Name

Johannes Haushofer

PI Affiliation

Department of Psychology and Public Affairs Princeton

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2016-05-18

End date

2016-05-20

Keywords

Labor

Additional Keywords

JEL code(s)

Secondary IDs

Abstract

Experimenter demand effects pose an important challenge to understand and interpret results from laboratory and field studies. In this paper, we manipulate participants’ beliefs about the intentions and desires of the experimenters. In particular, we are interested in how far people’s behavior in economic games is elastic to experimenter demand. In our experiment, people are randomly assigned to play either a dictator game, an investment game or to complete a convex time budget. We randomly assign whether people will be exposed to positive, negative or no experimenter demand and whether the choices involve real money or are hypothetical.

External Link(s)

Registration Citation

Citation

Haushofer, Johannes, Jonathan Quidt and Christopher Roth. 2017. "Measuring Experimenter Demand." AEA RCT Registry. May 18. https://doi.org/10.1257/rct.1248-7.0

Former Citation

Haushofer, Johannes, Jonathan Quidt and Christopher Roth. 2017. "Measuring Experimenter Demand." AEA RCT Registry. May 18. https://www.socialscienceregistry.org/trials/1248/history/17765

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2016-05-18

Intervention End Date

2016-05-20

Primary Outcomes

Primary Outcomes (end points)

Giving in a dictator game;
Points invested in an investment game;
Choices in convex time budgets.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

In all three different behavioral measures we either induce positive negative or no demand by telling them that they will do us a favor if, for example, they invest more in a project than they normally would. We will now outline the instructions for each of the different games:

Dictator game:
Positive Demand: You will do us a favor if you give more to the other participant than you normally would.
Negative Demand: You will do us a favor if you give less to the other participant than you normally would.
No Demand: We do not induce any demand.

Investment game:
- Positive Demand: You will do us a favor if you invest more in the project than you normally would.
- Negative Demand: You will do us a favor if you invest less in the project than you normally would.
- No Demand: We do not induce any demand.

Convex time budgets:
- Positive Demand: You will do us a favor if you choose to receive more money in seven days than you normally would.
- Negative Demand: You will do us a favor if you choose to receive less money in seven days than you normally would.
- No Demand: We do not induce any demand.

Experimental Design Details

Randomization Method

Randomization done by a computer.

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

4500

Sample size: planned number of observations

4500

Sample size (or number of clusters) by treatment arms

1500 positive demand (750 positive demand with monetary incentives; 750 positive demand no monetary incentives)
1500 negative demand (750 negative demand with monetary incentives; 750 negative demand no monetary incentives)
1500 control (750 control with monetary incentives; 750 control no monetary incentives)

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

For our main test of interest, i.e. comparing the behavior of people in the positive and negative demand condition we have a power of .8 to detect standardized effect sizes of .105 at alpha= 0.05. To test for heterogeneous treatment effects by incentives and gender we have a power of .8 to detect effect sizes of .145 at alpha= 0.05 respectively. Finally, to test for heterogeneous responses to demand for the three different games, we can detect effect sizes of .18 with power .8 at alpha= 0.05.

Supporting Documents and Materials

IRB