multiple regression analysis Demand evaluation 1

one independent variable affecting the demand, and the required quantity

In some cases, changes in demand are satisfactorily explained by changes of one independent variable, such as price

more than one independent variable that can be changed

as a result of price changes, while other variables are

The market price is set by the intersection of demand and supply curves

If the market price changes, then shifted either the demand curve or the supply curve, or both of these curves

If you move only the supply curve, the point of a "price-quantity" will lie only along the demand curve

Here to determine the demand curve, you can use simple regression

Ех: the market of microprocessors

Technological progress is rapidly reduced production costs of these devices, so the producers had a desire to expand production: the supply curve shifted to the right

a shift of the demand curve
«identification problem»
Three balance points got

The demand function of one variable?

Can be solved by using multiple regression

If the firm mistakenly take this line for the demand curve, it may reduce the price in anticipation of a strong increase of income due to a sharp increase of sales

The true demand curve is less elastic, i.e. an anticipated increase in sales will not occur

dependent and independent variables

of product demanded
Demand is a function of many variables.
Price
Tastes of

Consumer’s Income level

Prices of substitutes

Consumer’s expectations

Available Volume of product

Number of potential consumers

Advertising

Another factors

The demand model may have the following form:

In any empirical study it is necessary to identify the independent variables and their relationship with the dependent variable

to each other
It is not enough to determine the relationship

Construction of multivariable demand function

Step 1. Identification of variables

data
Consider the following aspects:
Organization of information (month, quarter, year);
The number

allows us to achieve greater statistical efficiency
Correction: taking into account

availability!

Construction of multivariable demand function

Step 2. Collection and refinement of data

well-chosen model requires the number of observations, that is at

Construction of multivariable demand function

Step 2. Collection and refinement of data

variable is approximately linear, and there are many independent variables,

The estimated demand

The value of independent variable

Constant value

Estimated value of the i-th regression parameter

˄

Construction of multivariable demand function

Step 3. Choosing the best form of equation

regression equation
14
Import of mushrooms data
City
Sales per week
(boxes)
Quantity of potential consumers
(thousands)
Income

regression equation
15
Quantity of potential consumers (thousands)
Sales per week
(boxes)
Sales per week
(boxes)
Income

X2
Construction of multivariable demand function
Step 4. The determination of the

Variable №

Dispersion analysis

Root-mean-square error of regression coef.

sum of squares

coefficient of determination

Root-mean-square error of regression

of the model can be determined by answering two fundamental

The answer is based on economic theory and on the judgment of the researcher

There should be some statistical tests conducted that evaluate the individual parameters and the model in general

Testing the suitability of the model

Computer makes any regression analysis, the data for which is presented in the correct form, regardless of economic sense

The task of the researcher is to determine the correctness of application of the results for demand forecasting