scholarly journals Controlling for presentation effects in choice

2021 ◽  
Vol 12 (1) ◽  
pp. 251-281 ◽  
Author(s):  
Yves Breitmoser
Keyword(s):  
Simple Model ◽  
User Interfaces ◽  
Dictator Game ◽  
Model Testing ◽  
Comparative Statics ◽  
Economic Experiments ◽  
Dictator Games ◽  
Stochastic Errors ◽  
Out Of Sample

Experimenters make theoretically irrelevant decisions concerning user interfaces and ordering or labeling of options. Reanalyzing dictator games, I first show that such decisions may drastically affect comparative statics and cause results to appear contradictory across experiments. This obstructs model testing, preference analyses, and policy predictions. I then propose a simple model of choice incorporating both presentation effects and stochastic errors, and test the model by reanalyzing the dictator game experiments. Controlling for presentation effects, preference estimates become consistent across experiments and predictive out‐of‐sample. This highlights both the necessity and the possibility to control for presentation in economic experiments.

scholarly journals Learning to be selfish? A large-scale longitudinal analysis of Dictator games played on Amazon Mechanical Turk

2019 ◽  
Author(s):  
Antonio Alonso Arechar ◽  
David Gertler Rand
Keyword(s):  
Longitudinal Analysis ◽  
Large Scale ◽  
Dictator Game ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Social Setting ◽  
Negative Effects ◽  
Dictator Games

We investigate whether experience playing the Dictator Game (DG) affects prosociality by aggregating data from 37 experiments run on Amazon Mechanical Turk over a six-year period. While prior evidence has shown a correlation between experience on Amazon Mechanical Turk and selfishness, it is unclear to what extent this is the result of selection versus learning. Examining a total of 27,266 decisions made by 17,791 unique individuals, our data shows evidence of significant negative effects of both selection and learning. First, people who participated in a greater total number of our experiments were more selfish, even in their first game – indicating that people who are more likely to select into our experiments are more selfish. Second, a given individual tends to transfer less money over successive experiments – indicating that experience with the DG leads to greater selfishness. These results provide clear evidence of learning even in this non-strategic social setting.

scholarly journals The Effect of Sense of Community Responsibility on Residents’ Altruistic Behavior: Evidence from the Dictator Game

2020 ◽  
Vol 17 (2) ◽  
pp. 460
Author(s):  
Chao Yang ◽  
Yanli Wang ◽  
Yuhui Wang ◽  
Xuemeng Zhang ◽  
Yong Liu ◽  
...  
Keyword(s):  
Sense Of Community ◽  
Dictator Game ◽  
Demographic Variables ◽  
Altruistic Behavior ◽  
Future Research ◽  
Dictator Games ◽  
Significant Difference ◽  
Community Responsibility ◽  
The Rich ◽  
High Level

Understanding the new mechanism of altruistic behavior is pivotal to people’s health and social development. Despite the rich literature on altruism, this is the first study exploring the association between the sense of community responsibility (SOC-R) and altruistic behavior by repeated dictator games. Data were gathered from 95 residents (30% male; M age = 33.20 years). Demographic variables, money motivation, and SOC-R were measured. The results revealed that there was a significant positive correlation between SOC-R and altruistic behavior, and SOC-R had a positive predictive effect on residents’ altruistic behavior. With the increasing of the number of tasks assigned, the level of residents’ altruistic behavior gradually decreased. There was a significant difference in money allocation between the groups with high and low levels of SOC-R. The level of altruistic behavior in the group with a high level of SOC-R was significantly higher than that in the the group with a low level of SOC-R. Findings from the present study highlighted the potential value of strengthening residents’ SOC-R in the improvement of altruism. Implications and directions for future research were also discussed.

scholarly journals Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

2016 ◽  
Vol 106 (5) ◽  
pp. 114-118 ◽  
Author(s):  
Edward L. Glaeser ◽  
Andrew Hillis ◽  
Scott Duke Kominers ◽  
Michael Luca
Keyword(s):  
Big Data ◽  
Simple Model ◽  
City Government ◽  
Opportunity Costs ◽  
City Governments ◽  
Prediction Algorithms ◽  
Out Of Sample

The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to crowdsource competence by making data public and offering a reward for the best algorithm. A simple model suggests that open tournaments dominate consulting contracts when cities can tolerate risk and when there is enough labor with low opportunity costs. We also report on an inexpensive Boston-based restaurant tournament, which yielded algorithms that proved reasonably accurate when tested “out-of-sample” on hygiene inspections.

scholarly journals Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments

2012 ◽  
Vol 4 (4) ◽  
pp. 35-64 ◽  
Author(s):  
Mikhail Anufriev ◽  
Cars Hommes
Keyword(s):  
Asset Pricing ◽  
Simple Model ◽  
Predictive Power ◽  
Experimental Setting ◽  
Price Behavior ◽  
Switching Model ◽  
Evolutionary Selection ◽  
Out Of Sample ◽  
Monotonic Convergence ◽  
Selection Of

In recent “learning to forecast” experiments (Hommes et al. 2005), three different patterns in aggregate price behavior have been observed: slow monotonic convergence, permanent oscillations, and dampened fluctuations. We show that a simple model of individual learning can explain these different aggregate outcomes within the same experimental setting. The key idea is evolutionary selection among heterogeneous expectation rules, driven by their relative performance. The out-of-sample predictive power of our switching model is higher compared to the rational or other homogeneous expectations benchmarks. Our results show that heterogeneity in expectations is crucial to describe individual forecasting and aggregate price behavior. (JEL C53, C91, D83, D84, G12)

scholarly journals Altruistic Preferences in the Dictator Game: Replication of Andreoni and Miller (2002) in Japan

2020 ◽  
Vol 11 (1) ◽  
pp. 17-21
Author(s):  
Jiayi Xue ◽  
Yohsuke Ohtsubo
Keyword(s):  
Utility Maximization ◽  
Revealed Preference ◽  
Dictator Game ◽  
Fixed Number ◽  
Replication Studies ◽  
Dictator Games

We conducted two replication studies of Andreoni and Miller’s (2002) modified dictator game study, which revealed that participants’ altruistic decisions were consistent with the notion of utility maximization. The two studies (Study 1 with small stake sizes and Study 2 with large stake sizes) included 11 modified dictator games, in which participants allocated a fixed number of tokens between themselves and their recipient. In eight of the 11 games, each token’s value was different for each player. In Study 1 (N = 78), 85% of participants did not violate the generalized axiom of revealed preference (GARP) throughout the 11 games. In Study 2 (N = 58), 81% of participants did not violate GARP. These results suggest that participants’ decisions were largely consistent with utility maximization. Following Andreoni and Miller’s analysis, we classified all participants (except one anomalous case) into the Selfish, Leontief (egalitarian), and Perfect Substitutes (utilitarian) groups. The majority of participants were classified into either the Leontief or Prefect Substitutes groups (i.e., non-selfish groups).

scholarly journals Emotional Intelligence and Bargaining Behavior

2021 ◽  
Author(s):  
Daniel Sazhin
Keyword(s):  
Emotional Intelligence ◽  
Emotional Regulation ◽  
Ultimatum Game ◽  
Dictator Game ◽  
Trait Emotional Intelligence ◽  
Dictator Games ◽  
Bargaining Behavior

In this experiment, we examined how trait Emotional Intelligence (EI) related tobehavior in social bargaining tasks. EI is theoretically related to both higher trait levels of empathy and better emotional regulation. More empathetic people may act more generously toward a bargaining partner. Subjects with better emotional regulation may be better at controlling their emotions in bargaining situations, which may help them make more self-interested choices. We used the Ultimatum and Dictator games to measure whether higher EI individuals behaved more generously or selfishly. These games are played between two people, where one person receives an endowment from the experimenter and decides how much to share with a recipient. The Ultimatum Game allows the recipient to reject offers, which forces the proposer to give his money back to the experimenter. In the Dictator Game, the recipient is unable to reject the proposer's offer. To maximize earnings, the most strategic thing to do in the Ultimatum Game is to make offers closer to even splits to avoid getting rejected by one's partner and to keep the whole endowment in the Dictator Game where there is no threat of retribution. Conversely, if a subject is motivated by fairness, they would make fair offers in both games. We found that subjects with higher EI acted strategically by being fair in the Ultimatum Game and selfish in the Dictator Game. These findings suggest that EI predicts more self interested behavior in bargaining situations.

Social Preferences and Fairness Norms as Informal Institutions: Experimental Evidence

2011 ◽  
Vol 101 (3) ◽  
pp. 509-513 ◽  
Author(s):  
Pamela Jakiela
Keyword(s):  
Experimental Evidence ◽  
Social Preferences ◽  
Important Determinant ◽  
Dictator Game ◽  
Informal Institutions ◽  
Relative Importance ◽  
Dictator Games ◽  
The Status ◽  
Rural Kenya ◽  
Fairness Norms

We conduct a series of dictator games in which the status of the dictator relative to other players varies across treatments. Experiments are conducted in a conventional university lab and in villages in rural Kenya. We find that status is an important determinant of dictator game giving, but the relative importance of earned and unearned status differs across cultures.

scholarly journals A Review Essay about Foundations of Neuroeconomic Analysis by Paul Glimcher

2013 ◽  
Vol 51 (4) ◽  
pp. 1155-1182 ◽  
Author(s):  
Colin F Camerer
Keyword(s):  
Simple Model ◽  
Behavioral Economics ◽  
Review Essay ◽  
Prediction Error ◽  
Social Preferences ◽  
Risky Choice ◽  
Comparative Statics ◽  
Random Utility ◽  
Time Discounting ◽  
Visual Neuroscience

Neuroeconomics aims to discover mechanisms of economic decision, and express them mathematically, to predict observed choice. While the contents of neuroeconomic models and evidence are obviously different than in traditional economics, (some of the) goals are identical: to explain and predict choice, the effects of comparative statics, and perhaps make interesting new welfare judgments that are defensible. To this end, Paul Glimcher's important book carefully describes how economics, psychological, and neural levels of explanation can be linked (a structure which has been successful in visual neuroscience). As Glimcher shows, the neural evidence is quite strong for a process of learning valuations through prediction error, and a simple model of neural valuation and comparison that corresponds to random utility (though subject to normalization, which produces menu effects). There is also rapidly growing evidence for more complicated constructs in behavioral economics, including prospect theory's account of risky choice, hyperbolic time discounting, level-k models of games, and social preferences corresponding to internal reward based on what happens to other agents. (JEL D01, D03, Y30)

scholarly journals Limitations of Bayesian Leave-One-Out Cross-Validation for Model Selection

2018 ◽  
Author(s):  
Quentin Frederik Gronau ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Simple Model ◽  
Model Selection ◽  
Cross Validation ◽  
Predictive Performance ◽  
Data Set ◽  
General Law ◽  
Out Of Sample ◽  
Measure Model ◽  
Leave One Out ◽  
And Behavior

Cross-validation (CV) is increasingly popular as a generic method to adjudicate between mathematical models of cognition and behavior. In order to measure model generalizability, CV quantifies out-of-sample predictive performance, and the CV preference goes to the model that predicted the out-of-sample data best. The advantages of CV include theoretic simplicity and practical feasibility. Despite its prominence, however, the limitations of CV are often underappreciated. Here we demonstrate the limitations of a particular form of CV --Bayesian leave-one-out cross-validation or LOO-- with three concrete examples. In each example, a data set of infinite size is perfectly in line with the predictions of a simple model (i.e., a general law or invariance). Nevertheless, LOO shows bounded and relatively modest support for the simple model. We conclude that CV is not a panacea for model selection.

scholarly journals A Kuhn–Tucker model for behaviour in dictator games

2021 ◽  
Author(s):  
Peter G. Moffatt ◽  
Graciela Zevallos
Keyword(s):  
Utility Function ◽  
Econometric Model ◽  
Dictator Game ◽  
Maximum Simulated Likelihood ◽  
Constrained Optimisation ◽  
Simulated Likelihood ◽  
Dictator Games ◽  
Corner Solutions

AbstractWe consider a dictator game experiment in which dictators perform a sequence of giving tasks and taking tasks. The data are used to estimate the parameters of a Stone–Geary utility function over own-payoff and other’s payoff. The econometric model incorporates zero observations (e.g. zero-giving or zero-taking) by applying the Kuhn–Tucker theorem and treating zeros as corner solutions in the dictator’s constrained optimisation problem. The method of maximum simulated likelihood (MSL) is used for estimation. We find that selfishness is significantly lower in taking tasks than in giving tasks, and we attribute this difference to the “cold prickle of taking”.

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