ajaz_eco_204_2012_2013_chapter_16_Market_Power

Lets illustrate demand models derived from regression

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Unformatted text preview: s you’ll see in ECO 220, one can estimate the parameters , , , by collecting data on , a regression of on , , , by minimizing the sum of squared errors: , ,, ∑ ∑( , ,, and running ) In ECO 204, you are not responsible for the algebra of estimating the parameters , , , but you are responsible for estimating these parameters by using Excel. Let’s illustrate demand models derived from regression analysis by two examples. Suppose we want to estimate a simple economic demand model of the form: () The regression (econometric) model is: () We haven’t specified the functional form of ( ): is it linear, quadratic, etc.? Typically, business analysts proceed by collecting data on and such as the data in following table containing a “snapshot” of a supermarket scanner data set for two brands of “diet” sodas X and Y, sold in seven stores (“62” through “68”) of a supermarket over 52 weeks (“101” through “152”): 4 We have seen regression analysis before in the “short run CMP” chapter. 8 ECO 20...
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This document was uploaded on 01/19/2014.

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