Chapter 4 Basis regression

Chapter 4 Basis regression - :DEMAND ESTIMATION product(s)...

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Basic Estimation Technique: DEMAND  ESTIMATION In planning and in making policy decisions,  managers must have some idea about the  characteristics of the demand for their   product(s)  in order to attain the objectives  of the firm or even to enable the firm to  survive. 1
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Demand information about customer  sensitivity to modifications in price advertising packaging product innovations economic conditions etc. are needed for product-development strategy For competitive strategy details about customer  reactions to changes in competitor prices and the  quality of competing products play a significant role 2
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What Do Customers Want? How would you try to find out customer  behavior? How can actual demand curves be  estimated? 3
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From Theory to Practice D:  Q x  = f(p x , Y, p s , p c Τ , N)   ( p x =price of good x, Y=income, p s =price of  substitute, p c =price of complement,  Τ =preferences, N=number of consumers) What is the true quantitative relationship between  demand and the factors that affect it? How can demand functions be estimated? How can managers interpret and use these  estimations? 4
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Regression Analysis and Demand  Estimation A frequently used statistical technique in demand estimation Estimates the quantitative relationship between the  dependent  variable  and  independent variable(s) quantity demanded being the  dependent  variable if only one  independent  variable (predictor) used: simple  regression if several independent variables used: multiple regression  5
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A Linear Regression Model In practice the dependence of one variable on another  might take any number of forms, but an assumption of  linear dependency will often provide an adequate  approximation to the true relationship  Intercept parameter ( a ) gives values of Y where  regression line crosses Y-axis, which is the value of Y  when X  is zero. Slope parameter ( b ) gives the change in Y associated  with a one-unit change in X (b= 6 Y a bX = + b Y / X = ∆
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general form: Q i  =  α  -  β 1 p β 2  Y +  β 3 p s  -  β 4 p β 5 Z +  ε where Q i  = quantity demanded of good i Y  = income p i  = price of good i p s  = price of substitute(s) p c  = price of complement(s) Z  = other relevant determinant(s) of demand ε  = error term  Values of  α  and  β ? 7
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This note was uploaded on 10/02/2011 for the course MGE 429041 taught by Professor Isseyteh during the Spring '10 term at SUNY Buffalo.

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Chapter 4 Basis regression - :DEMAND ESTIMATION product(s)...

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