aidsCalc: Shares and Quantities of the Almost Ideal Demand System

In micEconAids: Demand Analysis with the Almost Ideal Demand System (AIDS)

Shares and Quantities of the Almost Ideal Demand System

Description

Given prices, total expenditure and coefficients this function calculates the demanded quantities and expenditure shares based on the Almost Ideal Demand System.

Usage

aidsCalc( priceNames, totExpName, coef, data, priceIndex = "TL",
   basePrices = NULL, baseShares = NULL, shifterNames = NULL )

## S3 method for class 'aidsEst'
predict( object, newdata = NULL,
   observedShares = FALSE, ... )

Arguments

priceNames	a vector of strings containing the names of the prices.
totExpName	a string containing the variable name of total expenditure.
coef	a list containing the coefficients alpha, beta, gamma, and (only for the translog price index) alpha0.
data	a data frame containing the data.
priceIndex	a character string specifying the price index (see aidsPx) or a numeric vector providing the log values of the price index.
basePrices	a vector specifying the base prices for the Paasche, Laspeyres, and Tornqvist price index.
baseShares	a vector specifying the base expenditure shares for the Laspeyres, simplified Laspeyres, and Tornqvist index.
shifterNames	a vector of strings containing the names of the demand shifters.
object	an object of class aidsEst.
newdata	an optional data frame which should contain the variables for the prediction. If omitted, the data frame used for the estimation is used also for the prediction.
observedShares	logical. Using observed shares? (see details).
...	currently not used.

Details

The predict method for objects of class aidsEst extracts all relevant elements from an object returned by aidsEst and passes them as arguments to aidsCalc. The optional argument observedShares determines whether fitted (default) or observed expenditure shares are used in the price index of the LA-AIDS.

Value

aidsCalc and the predict method for objects of class aidsEst return a list with following elements:

shares	a data frame containing the calculated expenditure shares.
quantities	a data frame containing the calculated quantites.

Author(s)

Arne Henningsen

References

Deaton, A.S. and J. Muellbauer (1980) An Almost Ideal Demand System. American Economic Review, 70, p. 312-326.

See Also

aidsEst, aidsPx

Examples

   data( Blanciforti86 )
   # Data on food consumption are available only for the first 32 years
   Blanciforti86 <- Blanciforti86[ 1:32, ]

   priceNames <- c( "pFood1", "pFood2", "pFood3", "pFood4" )
   shareNames <- c( "wFood1", "wFood2", "wFood3", "wFood4" )

   ## LA-AIDS
   estResult <- aidsEst( priceNames, shareNames, "xFood",
      data = Blanciforti86, priceIndex = "S" )

   # using observed shares in the Stone index
   lnp <- aidsPx( "S", priceNames, Blanciforti86, shareNames )
   fitted <- aidsCalc( priceNames, "xFood", coef = coef( estResult ),
      data = Blanciforti86, priceIndex = lnp )
   fitted$shares  # equal to estResult$wFitted
   fitted$quant   # equal to estResult$qFitted
   # now the same with the predict method
   fitted2 <- predict( estResult, observedShares = TRUE )
   all.equal( fitted, fitted2 ) 

   # using fitted shares in the Stone index
   fitted <- aidsCalc( priceNames, "xFood", coef = estResult$coef,
      data = Blanciforti86, priceIndex = "S" )
   # now the same with the predict method
   fitted2 <- predict( estResult )
   all.equal( fitted, fitted2 ) 

   ## AIDS
   estResult <- aidsEst( priceNames, shareNames, "xFood",
      data = Blanciforti86, method = "IL" )

   fitted <- aidsCalc( priceNames, "xFood", coef = coef( estResult ),
      data = Blanciforti86 )

   fitted$shares  # equal to estResult$wFitted
   fitted$quant   # equal to estResult$qFitted

   fitted2 <- predict( estResult )
   all.equal( fitted, fitted2 ) 

micEconAids documentation built on May 20, 2022, 5:05 p.m.