demand estimation final
TRANSCRIPT
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DEMAND ESTIMATIONAND
ITS METHODS
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DEMAND ESTIMATION
TECHNIQUES
QUALITATIVE
TECHNIQUES
Consumer survey
Market experiments
Consumer clinics Virtual shopping
QUANTATIVE
TECHNIQUES
Statistical techniques
Regression
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CONSUMER SURVEYS
Gathering of
information
Surveys are conducted
to assess consumers
perception of various
aspects
Drawback of this
method
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Qualitative techniques
MARKET EXPERIMENTATIONS
Seller of a product introduces variations and tries it
out in a representative market
High cost technique
Advantage
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CONSUMER
CLINICSConsumers are asked to act
in a simulated situation
These are laboratory
experiments
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A representative sample of
consumers shop in a virtual
store simulated on the
computer screen
Eliminates the high cost in
terms of time and money
Consumer reaction
recorded
VIRTUAL SHOPPING
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Demandforecasting
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TECHNIQUES OF DEMAND
FORECASTING
1) Experts Opinion Poll
2) Reasoned Opinion-Delphi Technique
3) Consumers Survey- Complete Enumeration
4) Consumer Survey-Sample Survey5) End-user Method of Consumers Survey
SIMPLE
SURVEYMETHODS
1) Time series analysis or trend method2) Barometric Techniques or Lead-Lag indicators
method
3) Correlation and Regression
COMPLEX
STATISTICAL
METHODS
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EXPERTS OPINION POLL
Experts are requested to give
their opinion or feel about the
product
Number of such experts is large
and their experience-based
reactions are different
Also called the hunch method
Simple Survey Method
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REASONED OPINION - DELPHI TECHNIQUE
Relies on a panel of independent experts
Experts answer questionnaires in two or morerounds
Process is stopped aftera pre-defined stop criterionand the mean ormedian scores of the final roundsdetermine the results
http://en.wikipedia.org/wiki/Meanhttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Meanhttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Mean -
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CONSUMERS SURVEY- COMPLETE
ENUMERATION METHOD
Forecaster undertakes a complete
survey of all consumers whose demand
he intends to forecast
Principle merit of this method
Not feasible where a large number ofconsumers are involved
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Select a few consuming units out
of the relevant population
Total demand of sample units isfinally blown up to generate the
total demand forecast.
Comparison to the formersurvey
Sampling error can decrease
with every increase in sample size
CONSUMER SURVEY-SAMPLE SURVEY
METHOD
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END-USER METHOD OF CONSUMERS
SURVEY
Sales of a product are projected
through a survey of its end-users
A product is used for final
consumption
Demands for final consumption
and exports net of imports
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Relies on historical data to predict the future
The simplest form of forecasting using trend analysis is theprojection into the future of the current value of aneconomic variable
Advantage
Limitation
Appropriate for long-run forecasts, but inappropriate forshort-run forecasts
TREND ANALYSIS
E.g. One might forecast that next year sales would be a function of salesin the existing year or alternately next year sales would be a function ofthis years sales and the change in sales between this year and last year.Or a forecaster might predict next year sales based on sketching a linethat appears to best fit the historical data
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BAROMETRIC TECHNIQUES OR LEAD-
LAG INDICATORS METHOD
Use of current values of certain economic
variable called indicators to predict the futurevalues of other economic variable
leading indicator
coincident variables
lagging indicators
Ideally, changes in leading indicators
consistently precede changes in values of other
variables
EXAMPLE
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REGRESSION AND CORRELATION
Use of econometric methods to determine the nature and
degree of association between/among a set of variables
Relationship between a dependent variable and one or more
independent variables
The relationship may be expressed in the form of a demand
function
The principle advantage of this method
Technique has got both explanatory and predictive value
Use not only time-series data but also cross section data
Only precaution
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A SIMPLE LINEAR REGRESSION MODEL
Case where demand is stated as that between the dependent
variable and only one independent variable is a simple linear
regression model
Regression analysis attempts to fit the best possible linear
relationship between the dependent and the independentvariable
Y = a + BX + u
Y is the dependent variable (Petrol consumption)X is the independent variable (distance traveled)
a is the intercept ; b is the slope; u is the error
term.
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PROBLEMS IN REGRESSION
MULTICOLLINEARITYIDENTIFICATION
PROBLEM
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SIMULTANEOUS EQUATIONS
METHOD
Also known as the complete system approach or
econometric model building
It involves simultaneous considerations of all variables
Normally used in macro-level forecasting for the economy
Indeed very complicated
Principle advantage
The values of exogenous variables are easier to predict than
those of the endogenous variables
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EXAMPLE
Case examines the wide
variation in the demand for call
centers.
Importance of demand
forecasting for call centers
Difficulties involved in
estimating the demand for call
centers
Various strategies that can
be adopted to overcome
uneven demand conditions
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NIYAZ QURESHI 63
RAHAT ADENWALLA 73
SAAD SYED 83
SHEHNAZ SHAIKH 93
SURAJ THAKUR 103
VISHAL MANDOWARA 113