Unit 3 Theory of Supply

MEANING
Supply in economics is the quantity of a particular product or service that suppliers
offer to consumers at a specified price at a certain period of time.

Determinants of supply
The factors on which the supply of a commodity depends are
known as the determinants of demand.

1. Price of the Commodity

It is the main and the most important determinant of demand.
When the price of the commodity is high, the producers or
suppliers are willing to sell more commodities.

Thus, the supply of the commodity increases. Similarly, when the

price is low the supply of the commodity decreases owing to the
direct relationship between the price of a commodity and its
supply.

2. Firm Goals
The supply of goods also depends on the goals of an organization.
An organization may have various goals such as profit
maximization, sales maximization, employment maximization, etc

Where the firm’s objective is the maximization of profit, it will sell

more goods when profits are high and less quantity of goods
when the profits are low.

3. Price of Inputs or Factors

The price of inputs or the factors of production such as land, labor,
capital, and entrepreneurship also determine the supply of the
goods. When the price of inputs is low the cost of production is
also low.

Thus, at this point, the firms tend to supply more goods in the
market and vice-versa.

4. Technology
When a firm uses new technology it saves the inputs and also
reduces the cost of production. Thus, firms produce more and
supply more goods.

5. Government Policy
The taxation policies and the subsidies given by the government
also impact the supply of goods.

When the taxes are high the producers are unwilling to produce
more goods and thus, the supply will decrease.

On the other hand, when the government grants various subsidies

and gives financial aids to the producers, they increase the
production of goods. Thus, the supply also increases.

6. Expectations
When the producers or suppliers expect that the price shall
increase in future they hoard the goods so that they can sell them
at higher prices later. This will result in a decrease in the supply of
goods.
Similarly, in case they expect a fall in price, they will increase the
supply of goods.

7. Prices of other Commodities

When the price of complementary goods increases their supply
also increases. Thus, this results in the increase in the supply
of commodity also and vice-versa.

Also, when the price of the substitutes increases their supply also
increases. This results in a decrease in the supply of goods.

8. Number of Firms
When the number of firms in the market increase the supply of
goods also increases and vice-versa.

9. Natural Factors
The factors like weather conditions, flood, drought, pests, etc. also
affect the supply of goods. When these factors are favorable the
supply will increase.

What Is the Law of Supply?

The law of supply is a microeconomic law. It states that, all other factors being
equal, as the price of a good or service increases, the quantity of that good or
service that suppliers offer will increase, and vice versa.
In plain terms, this law means that as the price of an item goes up, suppliers will
attempt to maximize their profits by increasing the number of that item that they
sell.
The price elasticity of supply is a measure of the degree of responsiveness of the
quantity supplied to the change in the price of a given commodity. It is an
important parameter in determining how the supply of a particular product is
affected by fluctuations in its market price. It also gives an idea about the profit
that could be made by selling that product at its price difference. In this article, we
will discuss the elasticity of the supply formula, different types of elasticity of
supply, the supply curve characteristics, and many more
Price Elasticity of Supply Formula
After having understood the elasticity of supply definition in economics, we now
move to the elasticity of supply formula which is based on its definition.

ES=%∆P/%∆Q
Here,
ES denotes the elasticity of supply which is equal to the percentage change in
quantity supplied divided by the percentage change in the price of the commodity.
5 Types of Elasticity of Supply
Price elasticity of supply is of 5 types; perfectly elastic, more than unit elastic, unit
elastic supply, less than unit elastic, and perfectly inelastic. Read below to know
them in more detail.
1. Perfectly Elastic Supply: A commodity becomes perfectly elastic when its
elasticity of supply is infinite. This means that even for a slight increase in
price, the supply becomes infinite. For a perfectly elastic supply, the
percentage change in the price is zero for any change in the quantity
supplied.
2. More than Unit Elastic Supply: When the percentage change in the supply is
greater than the percentage change in price, then the commodity has the
price elasticity of supply greater than 1.
3. Unit Elastic Supply: A product is said to have a unit elastic supply when the
change in its quantity supplied is proportionate or equal to the change in its
price. The elasticity of supply, in this case, is equal to 1.
4. Less than Unit Elastic Supply: When the change in the supply of a
commodity is lesser as compared to the change in its price, we can say that
it has a relatively less elastic supply. In such a case, the price elasticity of
supply is less than 1.
5. Perfectly Inelastic Supply: Product supply is said to be perfectly inelastic
when the percentage change in the quantity supplied is zero irrespective of
the change in its price. This type of price elasticity of supply applies to
exclusive items. For example, a designer gown styled by a famous
personality.

The point to be noted is that the elasticity of supply is always a positive number.
This is because the law of supply states that the quantity supplied is always
directly proportional to the change in the price of a particular commodity. This
means that the supply of a product either increases or remains the same with the
increase in its market price.
DEMAND FORECAST
Demand forecasting refers to the process of planning and predicting
goods and materials demand to help businesses stay as profitable as
possible
What Are the Methods of Demand Forecasting?
Demand forecasting methods greatly impact the accuracy of the prediction made for
future trends. They help you make well-informed business decisions that drive
profitability and productivity. There are many different methods of forecasting used by
businesses that are being explained further.
1. Statistical Method of Demand ForecastingStatistical methods are a commonly
used approach for demand forecasting as they can provide accurate predictions
based on historical data. Some of them used for predicting include Time series
analysis, Regression analysis, ARIMA (Autoregressive Integrated Moving
Average), and Exponential smoothing. The choice of method depends on the
nature of the data and the business problem. A combination of these may also
provide a more robust forecast.
2. Survey Method of Demand ForecastingThe survey method of demand
forecasting involves gathering data directly from consumers, customers, or
market participants to make predictions about future demand for a product or
service. This can be done through various means, such as telephone, online,
focus groups, or in-person interviews. The data collected through surveys can
provide valuable insights into consumers' opinions, attitudes, and buying
behavior, which can be used to make informed predictions about future demand.
The forecast's accuracy will depend on the size and representativeness of the
sample, the quality of the survey questions, and the ability to generalize the
findings to the larger population.
3. Delphi Method of Demand ForecastingThe Delphi method is a group consensus-
based approach for demand forecasting. It involves collecting predictions and
opinions from a panel of experts and then using an iterative process to reach a
consensus forecast. It involves identifying a panel of experts, collecting initial
projections from each expert, compiling, and aggregating the initial estimates,
providing expert feedback on the overall results, collecting updated forecasts
from the experts, and creating a consensus demand forecast. The Delphi method
is helpful for complex forecasting problems where a single expert's forecast may
need to be more reliable. It can help reduce the influence of personal biases and
improve the accuracy of the final predictions.
4. Barometric Method of Demand ForecastingThe barometric method of demand
forecasting is a technique that predicts the future trend for a product or service
based on an analysis of external factors such as economic indicators, market
trends, and industry-specific variables. It assumes that consumers’ expectation
for a product or service is closely related to changes in these external factors. It
involves:

o Collecting data on relevant indicators.

o Creating a model to establish the relationship between the indicators and
demand.
o Using the model to forecast future demand.
The accuracy of the forecast will depend on the quality of the data and the
interdependence between external factors and demand.
5. Econometric Method of Demand ForecastingThe econometric method of
demand forecasting is a statistical approach to predicting future sales for a
product or service based on past sales data and relevant economic and market
factors. It uses regression analysis and other statistical tools to establish
relationships between demand and independent variables such as economic
indicators, market trends, and other relevant variables. The model is then used to
predict future trends based on expected changes in the independent variables.
The econometric method is considered highly reliable and accurate, especially for
products or services with a long sales history. However, it requires a large amount
of data and a good understanding of statistical techniques to implement
effectively.
6. Expert Opinion Method of Demand ForecastingThe expert opinion method of
demand forecasting involves gathering opinions and insights from individuals
with expertise in a particular product or market to make predictions about future
demand. It typically relies on experts in a given field's experience, knowledge, and
judgment, who can provide insights into market trends, consumer behavior, and
other relevant factors. Expert opinion can be collected through interviews, surveys, or
by consulting industry publications and reports. This method can be useful when
data is limited or consumer behavior changes rapidly. Still, it can also be subject
to bias and error if the experts consulted do not have a broad or accurate
understanding of the market. The forecast's accuracy will depend on the
expertise of the individuals consulted and the validity of their assumptions.
7. Trend Projection Method of Demand ForecastingThe trend projection method of
demand forecasting is a statistical technique used to forecast sales based on
past trends. It assumes that the demand will continue in the same direction as
the past trend, with the same or a similar rate of growth or decline. This involves
fitting a trend line to historical data and extrapolating the line into the future to
estimate the trends. Trend projection techniques use different mathematical
models to fit the trend line to the data to minimize the difference between
predicted and realized values. The trend projection method is best suited for
forecasting demand in stable, predictable environments where past trends are
expected to continue. However, it is important to consider external factors such
as changes in the market, competitors, or government regulations that may
impact demand and adjust the trend projections accordingly.
8. Sales Force Opinion Method of Demand ForecastingThe Sales Force Opinion
method of demand forecasting involves gathering forecasts from the company's
sales force, such as sales representatives and managers. These individuals are in
close contact with customers and have direct insight into current and future
customer demand for a product or service. The sales force's opinions are
combined and analyzed to create a forecast. It can provide valuable information
and help to identify regional, customer-specific, and product-specific trends.
However, it may also be subject to biases and personal opinions, so it is often
used in conjunction with other methods to increase accuracy.
9. Market Test Method of Demand ForecastingThe Market Test method of demand
forecasting involves conducting a limited-scale launch of a new product or
service in a specific geographic area or customer segment to gather info. The
data collected from the market test is then used to forecast regarding the product
or service in a larger-scale launch. This is advantageous when launching a new
product or entering a new market. It provides real-world information on customer
demand, which can be difficult to estimate using other forecasting techniques.
However, it can be expensive and time-consuming, and results may not represent
trends for other regions. This is often used with other forecasting methods to
increase accuracy.
10. Demand Forecasting Machine Learning MethodThe demand forecasting
machine learning method involves statistical algorithms and models to analyze
historical data and predict demand for a product or service. These models
leverage large amounts of data for modern businesses to create accurate
forecasts. Some popular ML methods for demand forecasting include Time
series, Artificial Neural Networks, Decision trees, and Random Forest. They can
provide highly accurate forecasts, especially when combined with domain-
specific knowledge and human insights. However, it is essential to carefully
 validate and test the accuracy of these models before implementing them in
decision-making processes.

Types of Forecasting
There are two types of forecasting:

● Based on Economy
● Based on the time period
1. Based on Economy

There are three types of forecasting based on the economy:

i. Macro-level forecasting: It deals with the general

economic environment relating to the economy as measured
by the Index of Industrial Production(IIP), national income
and general level of employment, etc.
ii. Industry level forecasting: Industry level forecasting deals
with the demand for the industry’s products as a whole. For
example demand for cement in India, demand for clothes in
India, etc.
iii.Firm-level forecasting: It means forecasting the demand for
a particular firm’s product. For example, demand for Birla
cement, demand for Raymond clothes, etc.
2. Based on the Time Period

Forecasting based on time may be short-term forecasting and

long-term forecasting

i. Short-term forecasting: It covers a short period of time,

depending upon the nature of the industry. It is done
generally for six months or less than one year. Short-term
 forecasting is generally useful in tactical decisions.
ii. Long-term forecasting casting: Long-term forecasts are for a
longer period of time say, two to five years or more. It gives
information for major strategic decisions of the firm. For
example, expansion of plant capacity, opening a new unit of
business, etc.
IMPORTANCE OF DEMAND FORECAST
Demand forecasting is a critical process for businesses to plan and predict
demand for goods and materials. It's important because it helps businesses:
●Improve customer satisfaction
By ensuring that desired products are delivered on time, businesses can increase
customer satisfaction and loyalty.
●Reduce inventory costs
Accurate predictions can help businesses avoid stockouts and unnecessary inventory
holding costs.
●Improve production planning
Businesses can plan production processes more efficiently by using demand
forecasting.
●Optimize the supply chain
Demand forecasting can help businesses reduce logistics costs and improve the
efficiency of their supply chain.
●Gain a competitive advantage
By understanding market trends, businesses can gain an edge over their competitors.
●Make better decisions
Businesses can make better decisions about marketing spend, production, staffing, and
more with a better understanding of demand.
●Run smoothly during peak periods
Demand forecasting can help businesses ensure that they run smoothly during peak
periods like promotions, sales, or seasonal spikes.
●Plan for staffing and resource needs
Businesses can plan for staffing and resource needs to ensure they are prepared for
peak times.
Demand forecasting uses historical data, market trends, and other factors to
predict future demand. While no one can predict the future with absolute certainty,
there are several techniques that can help businesses make educated guesses