Demand estimation involves estimating the demand for a product or service within a specific timeframe using various methods such as market experiments, surveys, and regression analysis. Forecasting can be classified into passive and active, aiding in short-term and long-term planning for production, pricing, and financial requirements based on past trends and current market conditions. Key determinants for demand forecasts include consumer characteristics, economic factors, and product types.

1. Demand
Estimation and Forecast

2. Demand Estimation
It is the process that involves coming up with an
estimate of the amount of demand for a product
or a service. It is confined to a particular period
of time.

3. Methods
Market
Experimentation
Actual Market
Market
Stimulation
Survey of
Consumers’
Intentions
Census
Sample
Regression
Analysis
Identifying
Demand Function
Collecting
Historical Data
Select an
Appropriate
Function
Estimation of
Selected Function
Analyzing the
Estimated
Demand Function

4. Actual Stimulation
 Shops are opened in different
localities and then consumer
behavior is observed.
 Reaction to the price changes
can be observed from
consumer’s income, cast,
religion, gender, taste etc.
 Disadvantages- expensive,
small scale, non controllable
variables.
 It provides token money to a
set of consumers.
 Reaction to price changes can
be observed from prices of
various goods, packaging,
quality etc.
 Disadvantages- consciousness
of the consumer.
Demand Estimation Market Experiment

5. Census Method Survey Method
 All the consumers are
contacted.
 Disadvantages – costly,
hesitant to disclose the plan
because of
personal/commercial privacy.
 A few consumers out of the
whole population are
contacted.
 Disadvantages – costly to carry
the test marketing, selection of
test area, rival action.
Demand Estimation Survey of Consumers’ Intention

6. Regression Analysis is a statistical process
for estimating the relationships among variables.
 Simple Regression Analysis – is used when the
quantity demanded is taken as a function of a
single independent variable.
 Multiple Regression Analysis – is used to
estimate demand as a function of two or more
independent variables that vary simultaneously.

7. Specification
of Variable
Data
Collection
Demand
Estimation
Choice of a
Functional
Form
Interpretation
Steps for
Regression
Analysis

8. Demand Forecast
It is predicting future demand for the product.
The prediction of probable demand for a product or
a service on the basis of the past events and
prevailing trends in the present.

9. Forecast are broadly classified into two categories-
 Passive forecast - prediction about future is
based on the assumption that the firm does not
change the course of its action.
 Active forecast - prediction is done under the
condition of likely future changes in the actions,
by the firms.

10. Purposes of Forecasting
 Purposes of short-term forecasting
Seasonal Patterns are of prime importance.
a. Appropriate production scheduling.
b. Determining appropriate price policy
c. Evolving a suitable advertising and promotional
campaign.
d. Forecasting short term financial requirements.
 Purposes of long-term forecasting
Helpful in Capital Planning
a. Planning of a new unit or expansion of an existing unit.
b. Planning long term financial requirements.
c. Planning man-power requirements.

11. Identify the
objective.
Determine
the nature of
goods.
Select a
proper
method.
Interpret the
result.
Steps in
Forecasting

12. Scope of Forecasting
 Period of forecast.
 Levels of forecast.
 General Purpose or specific purpose forecast.
 Forecast of established or new products.
 Type of commodity for which forecast is to be
undertaken.
 Miscellaneous factors to be included or not.

13. Short term
forecasts refers
to a period up to
3 months.
• Seasonal
factors are the
ingredients of
short run
forecasts.
Medium term
forecasts refers
to a period of 3
months to one
year.
• It is forecasted
by trends.
Long term
forecasts refers
to a period
above one year.
• Statistical
techniques
are used to
judge the long
run forecasts.
Period of Forecasts

14. i. Macro Economic Forecasts – concerned with
the business conditions all over the world.
ii. Industry Demand Forecasts – gives indication
to a firm regarding direction in which the whole
industry will be moving.
iii. Firm Demand Forecasting – a big firm will do
forecasting of its own products independent of
the rest of the firms.
iv. Product Line Forecasting – to decide which
product should have the priority.
Levels of Forecasts

15. General/Specific Purpose – general forecast is
broken into specific forecasts.
Forecasts of Established/New Product – for
established, past sale trends and competitive
conditions are used.
Type of Commodity – capital goods, consumer
durable and non-durable goods.
Miscellaneous Factors – inclusion of sociological
and psychological factors.

16. Determinants for Demand
Forecasts
 Replacement VS New
Demand
 Change in size and
characteristic of
population.
 Saturation limit of
market.
 Existing stock of good.
 Income level of
consumers.
 Consumer credit
outstanding.
 Taste and preference
of consumers.
Consumer Durable Goods

17.  Disposable Income.
 Price
 Size and
characteristic of
population.
Non-Durable Consumer Goods

18.  Growth possibilities.
 Extent of excess
capacity.
 The forecasts of
demand for the good
which producers’ good
help producing.
 Existing stock.
 Age distribution of
existing stock.
 Rate of obsolescence.
 Availability of funds.
 Nature of tax
provision.
 Prices of substitute
and complementary
goods.
 Market structure.
Capital Goods