Research Article

Walk the Talk? The Effect of Voting and Excludability in Public Goods Experiments

Table 6

Best results from the genetic algorithm runs for Experiment 2(mixed effects models, maximum likelihood estimation).

Model 10Model 11
Dependent variableIndividual contribution

CONSTANT
ROUND
INDIVIDUAL CONTRIBUTION (−1)a
SUCCESSb(−1) (YES= 1)
FEMALE (YES= 1)
FRESHMAN (YES= 1)
GREW UP IN URBAN AREA (YES= 1)
PLAYING XPG FIRST∗ SOCIAL SCIENCES (YES= 1)
INDIVIDUAL CONTRIBUTION (−1)∗ [SUCCESS (−1) (YES= 1)]
INDIVIDUAL CONTRIBUTION (−1)∗ [FEMALE (YES= 1)]
INDIVIDUAL CONTRIBUTION (−1)∗ EMPATHY
GROUP CONTRIBUTION (−1)∗ EMPATHY
UNFAIR CONTRIBUTION (−1)∗ [ROUNDS 1–10 (YES= 1)]
[FEMALE (YES= 1)]∗ EMPATHY
ECONOMICS∗ SENIOR (YES= 1)
SOCIAL SCIENCES∗ GREW UP IN URBAN AREA (YES= 1)
[FRESHMAN (YES= 1)]∗ INTERNAL LOCUS OF CONTROL
[GREW UP IN URBAN AREA (YES= 1)]∗ PARENT EDUCATION
INDIVIDUAL EARNINGS (−1) SQUARED
INDIVIDUAL EARNINGS FROM GROUP PROJECT (−1) SQUARED
Akaike Info Criterion10233.4610233.67
Bayes Info Criterion10347.9410348.15
Log Likelihood5096.735096.84
Number of obs.2400 (random effect for 24 groups)

The sign (−1) next to a variable means that the variable is lagged by one round.
SUCCESS is a dummy variable with the value of 1 if the group contribution reached the provision point and 0 otherwise.