Adding lagged price effects
Next, you will check if the effects of temporary price changes on sales extend into the next period.
Like before, you shift the PRICE predictor back by using the function lag(). The result is assigned to a new variable Price.lag. The Price.lag variable is added to the log(SALES) ~ PRICE relationship. This simple lag-model can also be estimated by using the function lm().
This exercise is part of the course
Building Response Models in R
Exercise instructions
- Create a lagged variable for
PRICEnamedPrice.lag. - Estimate a lagged response model explaining
log(SALES)byPRICEandPrice.lag. Use the functionlm()and assign the result again to an object calledlag.model. - Obtain the coefficients of the
lag.modelby using the functioncoef().
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Take the lag of PRICE
Price.lag <- lag(___)
# Explain log(SALES) by PRICE and Price.lag
lag.model <- ___(___ ~ ___ + ___, data = sales.data)
# Obtain the coefficients