Fanfare. Fanfare International, Inc. designs, distributes, and markets ceiling fans and li...

Fanfare. Fanfare International, Inc. designs, distributes, and markets ceiling fans and lighting fixtures. The company’s product line includes 120 basic models of ceiling fans and 138 compatible fan light kits and table lamps. These products are marketed to over 1000 lighting showrooms and electrical wholesalers that supply the remodeling and new construction markets. The product line is distributed by a sales organization of 58 independent sales representatives.

In the summer of 1994, Fanfare decided it needed to develop forecasts of future sales to help determine future sales force needs, capital expenditures, and so on. The data file named FAN4 on the CD contains data on the following variables:

The data are monthly and cover the period from July 1990 through May 1994. (Note: These data have been modified as requested by the company to provide confidentiality.)

As a consultant to Fanfare, your job is to find a causal regression model to forecast future sales. Use the techniques discussed in Chapters 3 and 4 to help you decide which variables you should include in the equation and which should be omitted. Justify your choices. How well do you believe the equation you developed will do at forecasting future sales? What additional analyses might you use to examine forecasting ability?

Now use the techniques discussed in Chapters 3 and 4 to build an extrapolative model to forecast sales. Generate forecasts from both the causal model and the extrapolative model. What are the benefits and drawbacks of each of the models? How could you compare the forecasting ability of the two models?