Demand Analysis

PRESENTED BY :-BABASAB PATIL

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The sources of Data Collection for Demand

Forecasting

Through a market research a variety of information .

Qualitative and quantitative is called as “DATA”.

This have to be collected to estimation of Demand

function and demand forecasting.

These information may be pertaining to varies aspects of

market and demand.

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Cont….

Demand in Past and Present.

Nature of product.

Types of consumer-

Domestic consumers and Industrial consumers.

Age.

Sex.

income of the consumers.

Attitude.

Preferences.

Tastes.

Habits.

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Price Quotations in the retail and wholesale markets.

Urban.

Rural.

Local.

National.

International or Global.

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Sales Promotion.

Advertising .

Free samples.

Discounts.

Window display.

As well as the expenditures so incurred or involved.

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Primary and Secondary Data

Primary Data:

Primary data or information are original in character

which are collected for the first time for the purpose of

analysis. Primary data are raw data and require statistical

processing.

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Secondary Data

Secondary data or information are those which are

obtained from someone else’s records. These Data are already

in existence in the recorded or published forms. Secondary

Data are like finished products since they have been processed

statistically in some form or the other.

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Secondary Sources of Data

Official publications of the Central, state and local

Governments.

1) Plan documents.

2) census of India.

3) Statistical Abstracts of the Indian Union.

4) Annual Survey of Industries.

5) Annual bulletin of Statistical of Exports and Imports.

6) monthly studies of production of selected Industries.

7) Economic Survey, National Sample Survey Reports.

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Trade and Technical or Economic journals and

publication

1) Economic and political weekly.

2) Indian Economic journal.

3) Stock exchange directory.

4) Basic statistics and other information's supplied by the centre

for monitoring Indian Economy.

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Official publications of International Bodies

1) IMF.

2) UNO.

3) World Bank etc.

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Market reports and trade bulletins published by

stock exchange

1) Trader associations.

2) Large business houses.

3) Chambers of Commerce, etc.

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Publications brought out by research institutions

1) Universities.

2) Associations. etc.

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Unpublished Data

1) Firm’s account books

1) Sales.

2) Profits.etc.

secondary data should not be taken at their face

value and are never to be used blindly.

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Statistical Methods of Forecasting Demand

• There are various methods adopted to estimate potential demand.

• Statistical methods are obviously more scientific, against crude value

judgment used to estimate future demand.

• One must take a mid-way by combining statistical results with the value

judgment.

• Again different statistical forecasting methods are not mutually exclusive.

• They are to be used in combination for accuracy and cross checking

purposes.

• For forecasting purposes, it is essential to estimate the structural form and

parameters of the demand function empirically.

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Two types of data for demand estimation:

• Time series data

• Cross-sectional data

Time series data

• Time series data refer to data collected over a period of time according

historical changes in price, income, and other relevant variables influencing

demand for a commodity.

• Time series analysis relate to the determination of change in a variables in

relation to time. Usually trend projections are important in this regard.

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Cross-sectional Data

• Cross -sectional analysis is undertaken to determine the effects

of changes in determining variables like price, income etc. On

the demand for a commodity, at a point of time.

• In time series analysis for instance, for measuring income

elasticity of demand, a sales income relationship may be

established from the historical data and their fast variations in

cross-sectional analysis, however different levels of sales

among different income groups may be compared at a specific

point of time.

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The Important Demand Forecasting Methods

are:

• Consumption Level Method

• Trend Projection Method

• Regression Analysis and Econometric Method

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Consumption Level Method

• Consumption Level demand may be estimated on the basis of the co-

efficients of income elasticity and price elasticity of demand.

• Viewing projected income level and income elasticity of demand

relationship, demand forecasting may be made as under:

D*=D(1+M*.em)

Where, D*=Projected per capita demand

D=Per capita demand

M*=Projected relative/percentage change in per capita

income.

em=Income elasticity of demand.

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Trend Projection Method

• A time series analysis of sales data over a period of time is

considered to serve as a good guide for sales or demand forecasting.

• For long-term demand forecasting trend is computed from the time

based demand function data.

• Trends refers to the long-term persistent movement of data in one

direction – upward or downward.

There are two important methods used for trend projections:

• The method as moving averages.

• The least square method

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The Method of Moving Averages.

• A moving average forecast is based on the average of a certain

number of most recent periods.

• One can select the number of months or years or other period

units in the moving average according to how for back the data

is relevant to future observations.

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The least square method

• The method of least squares is more scientific as compared to

the method of moving averages.

• It uses the straight line equation y= a+bx, to fit the trend to the

data.

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Regression analysis and econometric model

building

• Most commonly for demand forecasting proposes, the

parameters of the demand function are estimated with

regression analysis.

• In demand regression equations relevant variables have to be

included with practical considerations and relevant data have

to be obtained.

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Examples:

• Personal disposal income towards demand for

consumer product.

• Agricultural or farm incomes towards demand for

the agricultural equipments, fertilizers, etc.

• Construction contracts for demand towards

building material such as cement, bricks, steel,

tiles etc.

• Automobile registry over a period towards

demand for car spare parts, petrol etc.

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Thank you

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