Chp4 Demand Estimation

8/2/2019 Chp4 Demand Estimation

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Demand Estimation

Approaches to demand estimation Consumer surveys: record the response of a sample of

consumers for changes in its and related goods prices,

income, credit incentives, advertising throughquestionnaires.

Observational research: Watch consumers buying inresponse to the change factors above through scanners

and people meters. Consumer clinics: participants are given money in a

laboratory experiment set up to shop in simulated storewhich are affected by changes in the factors.


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Demand Estimation(contd)

Market Experiments: By selecting several markets withsimilar socio-economic environments, collect data on theresponse of buyers for changes in the influence factorsincluding demographics in which every market faces adifferent influence factor.

Virtual Shopping: representative sample of customersshop in a virtual store simulated on the computer screen.During course of time various influence factors arechanged to observe the behaviour of virtual shoppers.


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Virtual Reality


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Virtual Shopping


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Introduction to Regression Analysis

Example: Sales revenue (Y) depends onAdvertising exp. (X) (unit: mills of Rs)

Yr 1 2 3 4 5 6 7 8 9 10

X 10 9 11 12 11 12 13 13 14 15

Y 44 40 42 46 48 52 54 58 56 60


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Regression (contd)


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Regression (contd)

Objective: draw the line of best fit through thescatter points of Y and X.

Line is:

Points above and below the line are written:

t

Xba

t

Y

ttteXbaY


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Regression (contd) Principle: draw the line in such a way that the

distance between the line and the points isminimized (best is to minimize the square). Minimize

Minimization occurs when

n

1

2

tt

n

1t

2

t)Xba(Ye

XbYa

2)X

t(X

)Yt

)(YXt

(X

b


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Regression Equation

Estimated equation is:

Standard error (deviations) of b:

t3.53X7.6

tY

2)Xt(Xk)(n

2)t

Yt

(Y

b

S


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Regression

Hypothesis testing:

Involves examining whether an estimated coefficient (such as )is statistically different from zero. If different from zero, then thevariable associated affects the dependent variable.

Estimated coefficient is considered to be different from zero (i.e.

significant) with better evidence only if its t-value falls on theextreme 5% of its tail (or check the p-value in the last column ofestimation: if p-value is smaller than 0.05, then the coefficient can betaken different from zero in statistical sense.

Normally statisticians take p-value


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Some problems with regression

Wrong form of the regression equation

Autocorrelation problem

Heteroscedasticity problem

Chp4 Demand Estimation

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