Donors

Dynamics of Charitable Giving

a pseudo-panel of 32 individuals

number of observations : 1039

number of individual observations : 4-80

country : United States

JEL codes: C93, D64, D82, H41, L31, Z12

Chapter : 08

Usage

data(Donors)

Format

A dataframe containing:

id

the id of the sollicitor

solsex

the sex of the sollicitor

solmin

does the sollicitor belongs to a minority ?

beauty

beauty rating for the sollicitor

assertive

assertive rating for the sollicitor

social

social rating for the sollicitor

efficacy

efficacy rating for the sollicitor

performance

performance rating for the sollicitor

confidence

confidence rating for the sollicitor

age

age of the individual

sex

sex of the individual

min

does the individual belongs to a minority

treatment

the treatment, one of "vcm", "sgift" and "lgift"

refgift

has the individual refused the gift ?

donation

the amount of the donation

prior

has the individual been visited during the previous campaign ?

prtreat

the treatment during the previous campaign, one of "none", "vcm", and "lottery"

prcontr

has the individual made a donation during the previous campaign ?

prdonation

the amount of the donation during the previous campaign

prsolsex

the sex of the sollicitor during the previous campaign

prsolmin

did the sollicitor of the previous campaign belong to a minority ?

prbeauty

beauty rating for the sollicitor of the previous campaign

References

Landry, Craig E.; Lange, Andreas; List, John A.; Price, Michael K. and Nicholas G. Rupp (2010) “Is a Donor in Hand Better Than Two in the Bush ? Evidence From a Natural Field Experiment”, American Economic Review, 100(3), 958--983, 10.1257/aer.100.3.958 .

Aliases

• Donors

Examples

# NOT RUN {
#### Example 8-5

## ------------------------------------------------------------------------
# }
# NOT RUN {
data("Donors", package = "pder")
library("plm")
T3.1 <- plm(donation ~ treatment +  prcontr, Donors, index = "id")
T3.2 <- plm(donation ~ treatment * prcontr - prcontr, Donors, index = "id")
T5.A <- pldv(donation ~ treatment +  prcontr, Donors, index = "id", 
             model = "random", method = "bfgs")
T5.B <- pldv(donation ~ treatment * prcontr - prcontr, Donors, index = "id", 
             model = "random", method = "bfgs")
# }
# NOT RUN {
# }