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Eco 550 Demand Estimation

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Submitted By abetterstacy
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Demand Estimation
Stacy D. Lucero
Strayer University
April 28, 2015
Abstract
By using data from the month of April from 26 supermarkets around the country that sells our low-calorie, frozen microwavable dinners we are going to discover which independent variables have the greatest effect on the demand of our products. We are also going to graph a demand and supply curve in order to more accurately forecast our demand.

Demand Estimation
As an analyst for the leading brand of low-calorie, frozen microwavable dinners my boss has asked me to produce a demand estimation using existing data. We are trying to forecast how to price our products to increase our sales by taking independent variables and estimating how elastic they are in relation to our products. We are also going to determine our demand and supply curve to further our knowledge for more accurate forecasting.
Elasticity for Independent Variables
We wanted to see how elastic the demand for our product is by using data from 26 supermarkets around the country for the month of April. When referring to the elasticity of demand we are trying to determine if prices changes to our product will help us to sell more of our dinners. To do this we used a regression equation. We then computed the elasticity’s of several independent variables that would have an impact on our sales. The independent variables that we used were the price of the competitor’s product, the per capita income of the area nearest the supermarkets, monthly advertising expenditures and the number of microwave ovens sold in the chosen supermarkets. The following equations show just how elastic each independent variable is in relation to our microwaveable dinners.
Value of Independent Variables
P = Price of the product = 500 cents per 3 pack unit
PX = Price of leading competitor’s product = 600 cents per 3 pack unit
I = Per

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