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MICRO ECONOMICS ANALYSIS
4: BASIC DEMAND ESTIMATION ANDFORECASTING

Table of Content
1
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Introduction
3
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The functional Form of Empirical Demand Function
A Linear Empirical Demand Function
A Non-Linear Empirical Demand Function
Selection of a Demand Specification
5
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Forecasting
Linear Trend Forecasting
Presence of Cyclical/Seasonal Variation
Use of Dummy Variables to Correct Seasonal Variation
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1: MICRO ECONOMICS ANALYSIS
MODULE No
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Learning Outcomes
After studying this module, you shall be able to understand clearly
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The direct methods of estimating demand function
Specification of the empirical demand function
Linear and non-linear empirical demand function
Method to estimate the parameters
Forecasting methods
Linear trend forecasting technique
Forecasting in the presence of seasonal variations
Use of dummy variables to correct seasonal variation

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Information about demand is also essential for making production and pricing decisions
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Big corporations use empirical
demand functions and econometric price forecasts while taking pricing decisions as it is really
important to set an optimal price
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The statistical
forecasting does not fully eliminate the uncertainty prevailing with the pricing decisions but
nevertheless it definitely provides better insights thus helping in better pricing decisions
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The fundamental integrant of this statistical analysis is the empirical demand estimation
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In this chapter,
we will discuss methods of demand estimation, firstly the direct method and secondly by using
regression analysis
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This method can be used for a wide variety of forecasting needs of a business
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METHODS OF DEMAND ESTIMATION
There are direct techniques of demand estimation that do not involve regression analysis
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They include a) Market Experiments; and b) Consumer Interviews
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Market Experiments
This is quite an expensive and somewhat difficult technique of estimating demand functions
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There are laboratory experiments as well as field experiments, where in the former,
volunteers are used to simulate actual buying conditions; and in the latter, firms display their
products in different showrooms at different locations with different characteristics and
population over a period of time and observe consumer’s behavior and choices
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In these lab experiments, firms look for suitable volunteers and pay them to simulate
actual buying conditions but without going through the real markets
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With numerous shopping trips by various consumers, an approximation of demand is obtained
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In the second method i
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field experiments/field study, when firms display their products in the
actual markets, they make certain that there are enough units available at the showroom at each
price in order to satisfy demand
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The researchers
want to change the price of goods and actually observe the behavior of the consumers
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With this, it is possible to remove influence of other things and a realistic
approximation of the actual demand is made possible
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This straightforward method simply involves asking the potential buyers how much
of the good they would buy at different prices
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The interviewer has to be careful while selecting the right
representative sample
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A random selection of members from the population has to be made
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In real life, it is difficult to get a perfect sample and true representation of the population
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The sample would consist of
relatively well-off people and it would be upwardly biased and will not represent the true
population where most population is middle class
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Yet another problem is that the interviewee is unable to answer accurately
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However, though the method has some problems, it is still a very valuable method to know the
actual needs of the people and quantifying the demand on the basis of their responses
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It can have both, a linear or a
non-linear form, and both will be discussed below
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For example, we need to define the
physical boundaries of the market in which the product is to be sold
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Similarly, we need to look at the available substitutes and should include their prices
because they affect sales of the product
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Hence overall, careful consideration is required
while collecting information for estimating the demand function

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