USMeatConsump | R Documentation |
The USMeatConsump
data set contains quarterly retail prices
and consumption quantities for four meat product categories:
beef, pork, chicken, and turkey.
The data period ranges from the first quarter of 1975
to the third quarter of 1999.
Hence, there are 99 observations.
data(USMeatConsump)
This data frame contains the following columns:
Year.
Quarter of the year.
Time trend.
Population [million].
Consumer price index.
Total per capita expenditure.
Per capita expenditure on meat.
Per capita consumption of beef [pound].
Per capita consumption of pork[pound].
Per capita consumption of chicken [pound].
Per capita consumption of turkey [pound].
Retail price of beef [cents / pound].
Retail price of pork [cents / pound].
Retail price of chicken [cents / pound].
Retail price of turkey [cents / pound].
Expenditure share of beef (in meat).
Expenditure share of pork (in meat).
Expenditure share of chicken (in meat).
Expenditure share of turkey (in meat).
SAS, SAS/ETS Examples: Estimating an Almost Ideal Demand System Model, https://support.sas.com/rnd/app/ets/examples/aids/index.htm.
## replicating the LA-AIDS estimation of the SAS example # loading data set data( USMeatConsump ) # adding shifter variables for modeling seasonal effects USMeatConsump$co1 <- cos( 1 / 2 * 3.14159 * USMeatConsump$t ) USMeatConsump$si1 <- sin( 1 / 2 * 3.14159 * USMeatConsump$t ) # Scaling prices by their means USMeatConsump$beef_pm <- USMeatConsump$beef_p / mean( USMeatConsump$beef_p ) USMeatConsump$pork_pm <- USMeatConsump$pork_p / mean( USMeatConsump$pork_p ) USMeatConsump$chick_pm <- USMeatConsump$chick_p / mean( USMeatConsump$chick_p ) USMeatConsump$turkey_pm <- USMeatConsump$turkey_p / mean( USMeatConsump$turkey_p ) # Estimation of the model meatModel <- aidsEst( c( "beef_pm", "pork_pm", "chick_pm", "turkey_pm" ), c( "beef_w", "pork_w", "chick_w", "turkey_w" ), "meat_exp", shifterNames = c( "co1", "si1", "t" ), priceIndex ="S", data = USMeatConsump, maxiter=1000 ) summary( meatModel )
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