Handbook of Experimental Methodology.

Format:

Book

Author/Creator:

Yariv, Leeat.

Series:

Handbook of Experimental Methodology Series

Handbook of Experimental Methodology Series ; v.Volume 1

Language:

English

Subjects (All):

Experimental economics.

Methodology.

Physical Description:

1 online resource (498 pages)

Edition:

1st ed.

Place of Publication:

Chantilly : Elsevier Science & Technology, 2025.

Summary:

This handbook provides an in-depth review of cutting-edge methodologies in experimental economics.It explores various methods for eliciting preferences and beliefs in both static and dynamic settings, encompassing individual and group behavior across different techniques and diverse sample pools.

Contents:

Front Cover

Handbook of Experimental Methodology

Copyright

Introduction to the series

Contents

List of contributors

Preface

1 Evaluating experimental designs

1 Introduction

2 Evaluating measures

2.1 Construct validity

2.2 (Directional) responsiveness

2.3 Predictive validity

2.4 Monetary, time, and complexity costs

2.5 Reliability

2.6 Stability

2.7 Summary

3 Illustrative applications

3.1 Measures in the lab and in the field

3.2 Focal value response

3.3 Do monetary incentives matter?

4 Choosing design parameters

4.1 Documenting behavioral (ir)regularities

4.2 Discriminating between models

4.3 Institutional design

4.4 Policy experiments

4.5 Bringing reliability back

5 Discussion

References

2 Preference elicitation: common methods and potential pitfalls

2 Conceptual issues

2.1 Preferences in economics

2.2 Where do preferences come from?

2.3 Why elicit preferences?

2.4 Preference elicitations

2.5 Inconsistent choice and measurement error

3 The preference elicitation toolkit

3.1 Classic elicitation methods

3.1.1 Matching tasks

3.1.2 Binary choices

3.1.3 Experimental games

3.2 Recent elicitation methods

3.2.1 Multiple price lists

3.2.2 Convex budget sets

3.2.3 Alternative approaches to eliciting risk preferences

3.3 Frontier elicitation methods

3.3.1 Adaptive elicitation methods

3.3.2 Experimentally-validated question modules

3.4 Econometric techniques

4 A step-by-step guide to eliciting preferences

5 Future directions

3 Belief elicitation: a user's guide

1 How to use this chapter

2 The theory of incentive compatible belief elicitation

2.1 What is a belief?

2.1.1 Defining beliefs

2.1.2 Existence and uniqueness.

2.1.3 Well-behaved beliefs and reduction of compound lotteries

2.2 Eliciting "beliefs" under ambiguity aversion

2.3 The MPL and BDM mechanisms: definitions and incentive compatibility

2.4 (Binarized) scoring rules: definitions and incentive compatibility

2.4.1 Accounting for risk preferences

2.4.2 Incentive-compatibility of binarized rules

2.4.3 Comparison of scoring rules

3 Should I use (and emphasize) pecuniary incentives?

4 Choosing what to elicit

4.1 Beliefs about events versus beliefs about a number

4.2 An important distinction: frequencies versus probabilities

4.3 Coarse elicitation

5 The mechanisms

5.1 Eliciting the probability of an event

5.1.1 Multiple price lists

Incentives &amp

incentive compatibility

Coarse elicitation

Implementation details

5.1.2 Ternary price lists

5.1.3 Single response BDM mechanisms

5.1.4 Scoring rules

5.2 Eliciting the probability of multiple events

5.3 Eliciting the modal event

5.4 Eliciting a ranking of events ("qualitative probabilities")

5.5 Eliciting the modal set, mode, or modal interval

5.5.1 Modal set from an arbitrary collection

5.5.2 Mode or modal interval

5.6 Eliciting the median and other quantiles

5.6.1 Multiple price lists

5.6.2 Single response BDM mechanisms

Incentives &amp.

incentive compatibility

5.6.3 (Binarized) scoring rules

5.7 Eliciting a confidence interval

5.8 Eliciting the mean

5.8.1 Multiple price lists

5.8.2 Single response BDM mechanisms

5.8.3 (Binarized) scoring rules

5.9 Eliciting an entire distribution

5.9.1 Eliciting the PDF/PMF

5.9.2 Eliciting the CDF

5.10 Approximating other statistics of a distribution

6 Implementation details

6.1 Multiple price lists

6.1.1 Multiple switch points

6.1.2 Order effects

6.1.3 Iterative MPL

6.1.4 Embedded scroll box

6.2 Single-response BDM

6.3 Scoring rules

6.4 Input methods and uncertainty visualization

6.5 Hedging: ability to control the outcome

Appendix A Additional results

A.1 The BQSR for the mean is suitable for coarse elicitation

A.1.1 Proof of Lemma 1

A.1.2 Proof of Lemma 2

4 Communication in games

1 Prelude

2 Simultaneous-move games with multiple equilibria

2.1 Games with Pareto-ranked equilibria

2.2 Games with no natural ranking of equilibria

3 Games with unique equilibrium

3.1 Social dilemmas

3.2 Trust games

3.3 Oligopoly market games

4 Bargaining games

5 Collective decisions and voting games

6 Other games

7 Incorporating communication in an experiment

References.

5 Repeated games

2 Termination methods and payments

2.1 Termination methods

2.1.1 Visualizing the repeated game

2.2 Payment methods

2.3 Choosing between termination and payment methods

3 Experience

3.1 Experience as rounds within a supergame

3.2 Experience as repetitions of the supergame

3.3 Practical comments on conveying feedback

3.4 Lessons for other environments

3.5 Data analysis: a focus on experienced behavior

4 Strategies

4.1 Elicitation of strategies

4.2 Procuring data beyond the path of play

4.2.1 One-period ahead strategy method

4.2.2 Teams

4.2.3 Pre-play chat

4.3 Lessons for other environments

5 Conclusion

6 Lab experiments in developing country contexts

2 Experiments in developing countries

2.1 A brief history

2.2 Experiment taxonomy

2.3 Benefits of lab-in-the-field experiments

3 Alternative realities and worldviews

3.1 Researcher assumptions and experimental design

3.2 Research assumptions and the questions we ask

4 Logistical considerations

4.1 Site selection

4.2 Choosing participants

4.3 Infrastructural limits and other logistical challenges

4.4 Ensuring comprehension

4.5 Ethics and IRB approval

5 Experimenter demand effects

5.1 What is the experiment really about?

5.2 Assessment

5.3 Addressing experimenter demand effects

6 Conclusion

7 Designing survey experiments

2 Treatments, stimuli, and mechanisms

2.1 Assuring that treatments work as intended

2.2 Differential attrition or breakoff

3 Selecting valid outcome measures

3.1 Specificity

3.2 Stakes

3.3 Persistence

4 Statistical power

4.1 Covariate adjustment

4.2 Multi-item scales as outcome measures

4.3 Attention and quality checks.

4.4 Calculating statistical power

5 Representativeness

Appendix A Power in Clifford et al. (2021)

8 The methods and value of measuring choice processes in economics experiments

2 Simple measures of choice processes

2.1 Response times (RT)

2.2 Mouse tracking

2.3 Mouselab (eye-tracking on a budget)

2.4 Eye tracking

2.5 Language and voice

3 Complex measures of choice processes: psychophysiology and brain activity (fMRI, EEG)

3.1 Psychophysiology and emotion

3.2 Measuring brain activity

4 Causal manipulation of choice processes

4.1 Gaze and other process manipulations

4.2 Transcranial electric/magnetic stimulation

4.3 Stress induction

4.4 Pharmacological treatment

5 Conclusions and looking forward

5.1 Results of a de facto focus group

5.2 Specific research topics

9 Experimenting with networks

1 Networks, interference, and identification

1.1 A framework

1.2 Interference

1.3 Power

1.4 Are there spillovers?

1.5 Data considerations

1.5.1 Links and demographics

1.5.2 Panel data

1.5.3 Outcome choice

1.6 Factorialization

1.7 Networks themselves as treatment or outcome

2 Field experiments

2.1 Many networks versus single large network

2.2 Link elicitation

2.3 Partial link data

2.4 Many independent networks

2.5 A single, large network

2.5.1 Known G, single wave

2.5.2 Known G, two-wave

2.5.3 Partial G, single wave

2.5.4 Unknown G, single or multi-wave, with few clusters

2.6 Dealing with measurement error

2.7 Panels

3 Lab experiments

3.1 Designing networks in lab experiments

3.2 What do subjects know?

3.2.1 Network structure

3.2.2 Non-anonymity

3.3 Scope of behavior

3.4 Experiments on network formation

4 Natural experiments.

5 Concluding thoughts and synergies across types of experiments.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

0-443-31759-3

9780443317590

OCLC:

1559233419