Modeling Demand

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Modeling Demand
Module 7
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Conceptual Structure of SIMQ Market Model
Firm Demand Total Industry Demand Share of
Market
Firm Demand Average Firm Demand n Share of
Market
Firm Demand Average Firm Demand Normalized
Share of Market
Macro-economic Influences Seasonal
Patterns Stage of Life Cycle
Exogenous Demand
AFD
Industry Activity Pricing, Promotion,
Quality
Endogenous Demand
FD
NSOM
Competitive Profile Relative Pricing,
Promotion, Quality, and Loyalty
Relative Demand
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Normalised Share of Market
NSOM Firm Demand / Avg Firm Demand
Relative Price (current)
Pricing
Relative Advertising (current, t-1, t-2 )
NSOM
Promotion
Loyalty
NSOM (t-1)
Quality
Relative RD (t-1, t-2)
NSOM is firm specific and a measure of relative
demand, the predictor variables should also be
relative to industry averages. For example,
relative price of the firm is PREL Firms
Price / Industry Avg. Price
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Calculating NSOM
11) Use a multiple regression to estimate NSOM.
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Average Firm Demand
How many units will any firm sell on the
average. AFD Exogenous demand
Endogenous demand Exogenous demand Base
demand X Seasonal effects Endogenous demand
Influence of aggregate industry behavior
Error
Endog
Exog
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Average Firm Demand
AFD
Exogenous Demand
Endogenous Demand
Macro-Economic Influences - Seasonality -
Stage of Life Cycle Estimate Trend and
Seasonality using Time Series Analysis
Industry Behavior - Pricing (Avg Price) -
Promotion (Avg. Advertising) - Product Quality
(Avg. RD) Estimate weights of these factors
using Regression Analysis
AFD (TS) (B0B1Avg P..)
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AFD Exogenous Demand
Base demand Population, Income, Tastes, Product
life cycle, Substitutes and complements
(Macro-economic influences) Seasonal
demand Weather, Customs, Holidays Not all
products are affected Estimation is done using
Time
Series Decomposition
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Calculating Exogenous AFD
1) Use Statpro to generate Seasonal Indices
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Calculating Exogenous AFD
2) Use Seasonal Indices to De-seasonalize
observations.
1438 / .895 1607
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Calculating AFD
3) Fit a simple regression line to the
de-seasonalized observations.
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Calculating AFD
4) Use the regression line to create a
de-seasonalized forecast.
11 65.213 1237.9 1955.2
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Calculating AFD
5) Re-seasonalize the predicted forecast. This
is the exogenous portion of demand.
1.093 2150.9 2350.3
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Calculating AFD
6) Calculate the residual error from the
forecast. This is the endogenous portion of
demand.
2839 2350.3 488.7
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Calculating AFD
7) Fit a multiple regression with the residuals
as the dependent variable and the firm data as
the independent variables.
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Calculating AFD
8) Use the new regression equation to forecast
residuals. These are estimated of endogenous
demand.
15688.25 (-43.885) 371.9 (.0032) 97960
(.0127) 25610 4.2
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Calculating AFD
9) Add the exogenous forecast to the endogenous
forecast to create a composite forecast.
2350.3 204.2 2554.6
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Calculating AFD
10) Subtract the composite forecast from the
observations to find a total error.
2839 2554.6 284.4
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Calculating AFD
11) Calculate the standard deviation of the
residuals. Because there may be more explanation
that can be squeezed out of the trend and
attributed to the dependent variables, repeat the
process. For subsequent iterations, Raw AFD
Estimated Endogenous as starting data for time
series. Continue till error stops decreasing.
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Conceptual Structure of SIMQ Market Model
With Average Firm Demand and Normalized Share of
Market modeled, we can now create a decision
support system for any individual firm.
Exogenous Demand
AFD
Endogenous Demand
FD
NSOM
Relative Demand
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Example DSS