demand forecosting and elasticity of demad
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Demand forecasting
Presented By :
Hidayat ullah Sardar ahmad khan Jamshaid Amir rahman Mukhtiar ahmad Mustaqeem khan
managerial economics
MBA (022), section (A)
Demand
Demand means desire to buy something and ability to pay for it.
Demand = desire + purchasing power
Demand schedule
Demand schedule is the table that shows the relationship between price of goods and quantity demand .
Price of sugar Rs/ kg
Quantity demand
40 200
35 300
30 400
25 500
20 600
15 700
Demand curve
Demand curve is a
graph showing the
relationship between
the price of goods
and quantity
demanded.
Elasticity
The responsiveness of one variable to an other variable is called elasticity.
Elasticity of demand
The percentage change in quantity divided by the percentage change in price.
Elastic demand
Elastic demand
A small change in price
cause a big change in
quantity demanded
Price Demand
10 100
9 150
Inelastic demand
A large change in
price has a small
effect on quantity
demanded.
Price Demand
10 100
5 110
Sardar ahmad khan MBA(022)A
MEASUREMENT OF ELASTICITY
MEASUREMENT OF ELASTICITY
Total expenditure method
Point elasticity method OR
(geometric method)
Arc elasticity method
Total expenditure method
The price elasticity can be
measured by noting the
changes in total expenditure
brought by changes in price
and quantity demanded.
there are three condition in
total expenditure method.
Increase in total exp
When % change in quantity demand is more then % change in price it cause increase in T E. the demand will be elastic (E>1)
prices Quantity expenditure
RS 20 10 pens RS 200
RS 10 30 pens RS 300
No change in exp
When % change in price occur and T E do not change. The demand will be unitary (E=1)
prices Quantity expenditure
RS 10 30 pens RS 300
RS 5 60 pens RS 300
Decrease in exp
The % change in quantity demand is less then % change in price it cause decrease in T E (E<1)
prices Quantity expenditure
RS 5 60 pens RS 300
RS 2 100 pens RS 200
Point elasticity of demand
The measurement of elasticity at a point of the demand curve is called point elasticity.
Point elasticity of demand is used when the change in quantity demand is occur from a very small change in price.
measurement on linear demand curve
measurement on non linear demand curve
On linear demand curve
the formula (ΔQ ÷ ΔP) x (P ÷
Q)
the point C shows
maximum revenue
On non linear demand curve
Elasticity at a point can be measured by drawing a tangent at the particular point.
Arc elasticity
Arc elasticity means measuring elasticity between any tow points on the demand curve E= (ΔQ ÷ ΔP) ÷(p1+p2) ÷ (Q1+Q2)
Jamshaid khan MBA(022)A
MEASUREMENT OF ELASTICITY
Income elasticity
Def: “income elasticity of demand is the rate of responsiveness of demand to
changes in the income of the consumer.”
It is calculated as the ratio of the percent change in demand to the percent change in income.
= %change in Qd
%change in consumer income
ie. If, in response to a 10%increase in income, the demand of a good increased by 20%, the income elasticity of demand would be 20%/10%=2%
Inferior good's demand falls as consumer income increases.
Negative income elasticity Positive income elasticity Zero income elasticity
Cross elasticity
def: the rate of responsiveness of Qd of commodity A to changes in price of commodity B.
CEAB= QA PB
PB QA
SUBTITUTE GOODS
PA QdB +
COMPLEMENT GOODS
PA QdB _
Amir rahman MBA(022)A
Demand forecasting
Demand Forecasting
Def: The process of predicting the values of a certain quantity, over a certain time horizon, based on past trends and/or a number of relevant factors.
Forecasting methods
Qualitative techniques
Quantitative techniques
Qualitative techniques
Qualitative forecasting techniques are generally more subjective than their quantitative counterparts. Qualitative techniques are more useful in the earlier stages of the product life cycle, when less past data exists for use in quantitative methods.
Qualitative methods include
Surveys techniques,
Opinion polls
Survey techniques
The survey is a non-experimental, descriptive research method. Surveys can be useful when a researcher wants to collect data on phenomena that cannot be directly observed (such as, consumer’s decisions to purchase houses, automobiles, TV sets etc.)
Surveys are used to forecast consumer demand in general and the level of consumer confidence in the economy.
Opinion polls
The opinion polls are used by firms to forecast its own sales by polling experts within and outside the firm.
Several polling techniques
Executive polling
Sales force polling
Consumers intention polling
Executive polling
The firm poll its top mgt of functional areas( sales, production, finance etc.) on their views on the sales outlook for the firm during the next year.
The Delphi method can also be used, where experts are polled separately, and the feedback is provided without identifying the experts. the procedure is repeated until they reach at some consensus forecast.
Sales force polling
This is a forecast of the firm's sales in each region and for each product line. it is based on the firm’s sale force. these are the people closest to the market. And their opinion can provide valuable information to the top mgt
Consumer intention polling
The customers are asked about their purchasing plans and their projected buying behavior. A large number of respondents is needed here to be able to generalize certain results.
Mukhtiar ahmad MBA(022)A
Time series analysis
Time series analysis
A time series is an arrangement of time series in accordance with its time of occurrence by time series data, we mean numerical data which are collected observed or recorded at successive period of time,
Examples of time series
The annual production of wheat in Pakistan over a number of years.
The hourly temperature recorded in a days
The monthly rain fall recorded at a particular place
Components of time series analysis
There are four components of time series Secular trend Secular trend is regular smooth and long term
movements of data series. some series may show an upward or downward trend, for example tea which shows an upward trend now a days. the population of Pakistan shows an upward trend, infant death in the world shows a downward trend
Seasonal variations
These variations are caused due to changes in seasons, seasonal fluctuation are regular up and down movements ,for example the sale of warm clothes increases in winter and decreases in summer,
Cyclical fluctuation
The long term trend one complete period is called cyclical there are the swing to prosperity ,recession, depression and recovery back again to prosperity in business and economic activities,
Irregular or random variation
These variations are irregular or random such as wars, floods, strikes, earthquakes, etc these movements are also called residual variations,
Mustaqeem khan MBA(022)A
Smoothing techniques
Smoothing techniques
These predict values of a time series on the bases of some average of its past values.
Smoothing techniques are useful when the time series has irregular or random variation :There are tow types of ST
Moving averages Exponential smoothing
Moving averages
The simplest smoothing techniques is moving averages. Here the forecasted value of a time series in a given period (month, year. Etc) is equal to the average value of the time series in a number of previous periods.
Three quarter & five quarter MV
Market share (A)
3 quarter MV (F)
A-F (A-F)2 5 quarter MV (F)
A-F (A-F)2
1 20 - - - - - -
2 22 - - - - - -
3 23 - - - - - -
4 24 21.67 2.33 5.43 - - -
5 18 23 -5 25 - - -
6 23 21.67 1,33 1.77 21.4 1.6 2.56
7 19 21.67 -2.67 7.13 22 -3 9
8 17 20 -3 9 21.4 -4.4 19.36
9 22 19.67 2.33 5.43 20.2 1.8 3.24
10 23 19.33 3.67 13.47 19.8 3.2 10.24
11 18 20.67 -2.67 7.13 20.8 -2.8 7.84
12 23 21 2 4 19.8 3.2 10.24
Total 78.35 Toital 62.48
13 - 21.33 20.6
Which quarter is best
Following formula will give answer RMSE (root mean square error)
RMSE = √ ∑(A-F)2 ÷n
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