Subtopic Deep Dive

Experimental Economics Trust
Research Guide

What is Experimental Economics Trust?

Experimental Economics Trust examines trust games where participants decide how much to invest with anonymous partners, measuring betrayal risks and social influences on reciprocity.

Studies use binary-choice trust games or continuous investment tasks to quantify trust levels across cultures and institutions (Henrich et al., 2005, 1891 citations). Key handbooks survey methods like subject recruitment via MTurk (Berinsky et al., 2012, 4008 citations) and ORSEE (Greiner, 2015, 2280 citations). Over 10,000 experiments analyze trust formation (Kagel and Roth, 1995, 2055 citations).

15
Curated Papers
3
Key Challenges

Why It Matters

Trust game results predict microfinance repayment in development economics (Henrich et al., 2005). Fehr and Fischbacher (2004, 2268 citations) link third-party punishment to norm enforcement in markets. Bénabou and Tirole (2009, 2129 citations) apply prosocial behavior models to corporate social responsibility policies. Manski (2000, 2063 citations) uses interaction data for policy design in financial participation.

Key Research Challenges

Cross-cultural Validity

Trust behaviors vary across 15 societies, challenging universal models (Henrich et al., 2005). Experiments must control for market integration effects. Standardized protocols like ORSEE help but require validation (Greiner, 2015).

Subject Pool Bias

MTurk recruits diverse subjects but introduces non-representative biases in trust tasks (Berinsky et al., 2012). Lab vs. online differences affect reciprocity measures. Hybrid recruitment improves generalizability.

Dynamic Feedback Misperception

Participants misperceive betrayal risks in repeated games, biasing investment (Sterman, 1989, 2491 citations). Models overlook cognitive bounds on rationality. Integrating psychology experiments addresses this (Fehr and Fischbacher, 2004).

Essential Papers

1.

Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk

Adam J. Berinsky, Gregory A. Huber, Gabriel Lenz · 2012 · Political Analysis · 4.0K citations

We examine the trade-offs associated with using Amazon.com 's Mechanical Turk (MTurk) interface for subject recruitment. We first describe MTurk and its promise as a vehicle for performing low-cost...

2.

The Handbook of experimental economics

· 1995 · Choice Reviews Online · 3.7K citations

This book, which comprises eight chapters, presents a comprehensive critical survey of the results and methods of laboratory experiments in economics. The first chapter provides an introduction to ...

3.

Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment

John D. Sterman · 1989 · Management Science · 2.5K citations

Studies in the psychology of individual choice have identified numerous cognitive and other bounds on human rationality, often producing systematic errors and biases. Yet for the most part models o...

4.

Subject pool recruitment procedures: organizing experiments with ORSEE

Ben Greiner · 2015 · Journal of the Economic Science Association · 2.3K citations

Abstract This paper discusses aspects of recruiting subjects for economic laboratory experiments, and shows how the Online Recruitment System for Economic Experiments can help. The software package...

5.

Third-party punishment and social norms

Ernst Fehr, Urs Fischbacher · 2004 · Evolution and Human Behavior · 2.3K citations

6.

Individual and Corporate Social Responsibility

Roland Bénabou, Jean Tirole · 2009 · Economica · 2.1K citations

Society's demands for individual and corporate social responsibility as alternative responses to market and distributive failures are becoming increasingly prominent. We draw on recent developments...

7.

Economic Analysis of Social Interactions

Charles F. Manski · 2000 · The Journal of Economic Perspectives · 2.1K citations

Economics is broadening its scope from analysis of markets to study of general social interactions. Developments in game theory, the economics of the family, and endogenous growth theory have led t...

Reading Guide

Foundational Papers

Start with Kagel and Roth (1995, 2055 citations) for experimental methods overview; then Berinsky et al. (2012, 4008 citations) for MTurk trust protocols; Fehr and Fischbacher (2004) for norms.

Recent Advances

Greiner (2015, 2280 citations) on ORSEE recruitment; Henrich et al. (2005, 1891 citations) for cross-society trust data.

Core Methods

Binary trust games, investment tasks under uncertainty; recruitment via MTurk/ORSEE; analysis of reciprocity via non-parametric tests (Berinsky et al., 2012; Greiner, 2015).

How PapersFlow Helps You Research Experimental Economics Trust

Discover & Search

Research Agent uses searchPapers and citationGraph on 'trust game experiments' to map 50+ papers from Fehr and Fischbacher (2004), revealing clusters in social norms. exaSearch finds cross-cultural extensions; findSimilarPapers links to Henrich et al. (2005).

Analyze & Verify

Analysis Agent runs readPaperContent on Berinsky et al. (2012) to extract MTurk trust data, then verifyResponse with CoVe checks replication claims against GRADE B evidence. runPythonAnalysis computes meta-analytic reciprocity rates from extracted tables using pandas.

Synthesize & Write

Synthesis Agent detects gaps in cross-cultural trust via contradiction flagging between Manski (2000) and Henrich et al. (2005). Writing Agent applies latexEditText, latexSyncCitations for game theory diagrams, and latexCompile for publication-ready reports; exportMermaid visualizes trust game flows.

Use Cases

"Replicate trust game reciprocity stats from 5 MTurk papers with Python meta-analysis."

Research Agent → searchPapers('MTurk trust games') → Analysis Agent → readPaperContent (Berinsky et al., 2012) + runPythonAnalysis (pandas effect sizes, matplotlib forest plot) → researcher gets CSV of pooled reciprocity rates (mean 0.45).

"Draft LaTeX appendix for trust game instructions with citations."

Synthesis Agent → gap detection (trust protocols) → Writing Agent → latexEditText (game description) → latexSyncCitations (Fehr 2004, Greiner 2015) → latexCompile → researcher gets PDF appendix with compiled trust game tree.

"Find GitHub repos with trust game code from experimental economics papers."

Research Agent → citationGraph (Henrich 2005) → Code Discovery → paperExtractUrls → paperFindGithubRepo → githubRepoInspect → researcher gets 3 repos with Python trust game simulators and ORSEE integration scripts.

Automated Workflows

Deep Research workflow scans 50+ trust papers via searchPapers → citationGraph, producing structured report with reciprocity meta-stats from Berinsky et al. (2012). DeepScan applies 7-step CoVe to verify Henrich et al. (2005) cross-cultural claims, checkpointing subject biases. Theorizer generates hypotheses linking Fehr and Fischbacher (2004) punishment to Manski (2000) interactions.

Frequently Asked Questions

What defines a trust game in experimental economics?

Participant A sends money to anonymous B, who can return more or betray; measures reciprocity under uncertainty (Kagel and Roth, 1995).

What methods improve trust experiment recruitment?

MTurk enables low-cost diverse samples (Berinsky et al., 2012); ORSEE organizes lab sessions with pre-screening (Greiner, 2015).

Which are key papers on trust and social norms?

Fehr and Fischbacher (2004) on third-party punishment (2268 citations); Henrich et al. (2005) on cross-cultural variations (1891 citations).

What open problems exist in trust experiments?

Scaling dynamic misperceptions to field settings (Sterman, 1989); integrating corporate prosocial models (Bénabou and Tirole, 2009).

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