Each student will be responsible for generating a sales forecast for a selected industry or multi-national firm using econometric methods, using a sales data set collected from the available Compustat or Bloomberg systems. In addition, students must gather information on relevant measures of prices, income, advertising data, and other relevant (socio-economic) data to support the construction of a multi-variate regression model. The student must build the econometric model utilizing Excel or Eviews. Results of the analysis must include (a) an executive summary of the outcomes; (b) information supporting the choice of the variables, including the socio-economic variables (model specification), (c) detail concerning the model development and data acquired; (d) a sensitivity analysis for alternative scenarios, and interpretation of the elasticities and the implication to pricing strategy; and (e) interpretation of the results with implications to business policy. The discussion part of the project, excluding any tables or graphs, can be done within three pages. Five scores will be provided. The basis for these scores are the student ability to (a) provide a justification for the model specification based on relevant theory and gather the appropriate data; (b) use Excel or EViews to generate forecasted demand outcomes; (c) assess the impact of the socio-economic variable on the demand for the product under alternative scenarios; (d) discuss the relevant economic implications of the estimated elasticities; and (e) suggest meaningful implications that inform business policy of a multi-national firm.
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