Until now, we have discussed various aspects of inflation and some SAS procedures to evaluate the time series component. However, to deal with the business problem at hand, the modeling team needed to come up with a solution. The two approaches that the modeling team wanted to consider are as follows:
- Using a regression model to understand the interaction of various factors on CPI.
- Forecasting CPI for some periods based on the current CPI time series data. This did not involve understanding the interaction with various variables that can influence CPI.
There were pros and cons to both approaches. Whereas the multivariate regression model would help understand what aspect of consumer spending is statistically significant in predicting CPI, it at times isn't the best method to be used for forecasting. Multivariate regression could in this instance lead...
