Endowment Effect for Sports Cards

Description

Trading sports cards: Does ownership increase the value of goods to consumers?

Usage

data("SportsCards")

Format

A data frame containing 148 observations on 9 variables.

good

factor. Was the individual given good A or B (see below)?

dealer

factor. Was the individual a dealer?

permonth

number of trades per month reported by the individual.

years

number of years that the individual has been trading.

income

factor indicating income group (in 1000 USD).

gender

factor indicating gender.

education

factor indicating highest level of education (8th grade or less, high school, 2-year college, other post-high school, 4-year college or graduate school).

age

age in years.

trade

factor. Did the individual trade the good he was given for the other good?

Details

SportsCards contains data from 148 randomly selected traders who attended a trading card show in Orlando, Florida, in 1998. Traders were randomly given one of two sports collectables, say good A or good B, that had approximately equal market value. Those receiving good A were then given the option of trading good A for good B with the experimenter; those receiving good B were given the option of trading good B for good A with the experimenter. Good A was a ticket stub from the game that Cal Ripken Jr. set the record for consecutive games played, and Good B was a souvenir from the game that Nolan Ryan won his 300th game.

Source

Online complements to Stock and Watson (2007).

http://wps.aw.com/aw_stock_ie_2/

References

List, J.A. (2003). Does Market Experience Eliminate Market Anomalies? Quarterly Journal of Economcis, 118, 41–71.

Stock, J.H. and Watson, M.W. (2007). Introduction to Econometrics, 2nd ed. Boston: Addison Wesley.

See Also

StockWatson2007

Examples

data("SportsCards")
summary(SportsCards)

plot(trade ~ permonth, data = SportsCards,
  ylevels = 2:1, breaks = c(0, 5, 10, 20, 30, 70))
plot(trade ~ years, data = SportsCards,
  ylevels = 2:1, breaks = c(0, 5, 10, 20, 60))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(AER)
Loading required package: car
Loading required package: lmtest
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: sandwich
Loading required package: survival
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AER/SportsCards.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SportsCards
> ### Title: Endowment Effect for Sports Cards
> ### Aliases: SportsCards
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data("SportsCards")
> summary(SportsCards)
 good   dealer      permonth         years              income      gender   
 A:70   no :74   Min.   : 0.00   Min.   : 0.000   [40, 50) :39   male  :133  
 B:78   yes:74   1st Qu.: 3.00   1st Qu.: 3.000   [0, 10)  :27   female: 15  
                 Median : 8.00   Median : 7.000   [50, 75) :24               
                 Mean   :10.24   Mean   : 8.655   [30, 40) :20               
                 3rd Qu.:15.00   3rd Qu.:11.250   [75, 100):15               
                 Max.   :70.00   Max.   :60.000   [10, 20) :11               
                                                  (Other)  :12               
            education       age        trade   
 8th grade       : 8   Min.   :10.00   no :98  
 high school     :37   1st Qu.:25.00   yes:50  
 2y college      :20   Median :34.00           
 post-high school:37   Mean   :34.69           
 4y college      :29   3rd Qu.:43.00           
 graduate school :17   Max.   :76.00           
                                               
> 
> plot(trade ~ permonth, data = SportsCards,
+   ylevels = 2:1, breaks = c(0, 5, 10, 20, 30, 70))
> plot(trade ~ years, data = SportsCards,
+   ylevels = 2:1, breaks = c(0, 5, 10, 20, 60))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>