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# Ch. 4-demand-estimation(2)

## on Feb 25, 2011

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Microeconomics-Salvatore

Microeconomics-Salvatore

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## Ch. 4-demand-estimation(2)Presentation Transcript

• Marketing Research Approaches to Demand Estimation
Consumer Surveys
data from survey questions
Observational Research
data from observed behavior
Consumer Clinics
data from laboratory experiments
Market Experiments
data from real market tests
• Scatter Diagram
Regression Analysis
• Regression Analysis
Regression Line: Line of Best Fit
Regression Line: Minimizes the sum of the squared vertical deviations (et) of each point from the regression line.
Ordinary Least Squares (OLS) Method
• Ordinary Least Squares (OLS)
Model:
• Ordinary Least Squares (OLS)
Objective: Determine the slope and intercept that minimize the sum of the squared errors.
• Ordinary Least Squares (OLS)
Estimation Procedure
• Ordinary Least Squares (OLS)
Estimation Example
• Ordinary Least Squares (OLS)
Estimation Example
• Tests of Significance
Standard Error of the Slope Estimate
• Tests of Significance
Example Calculation
• Tests of Significance
Example Calculation
• Tests of Significance
Calculation of the t Statistic
Degrees of Freedom = (n-k) = (10-2) = 8
Critical Value at 5% level =2.306
• Tests of Significance
Decomposition of Sum of Squares
Total Variation = Explained Variation + Unexplained Variation
• Tests of Significance
Coefficient of Determination
• Tests of Significance
Coefficient of Correlation
• Multiple Regression Analysis
Model:
• Multiple Regression Analysis
• Multiple Regression Analysis
Analysis of Variance and F Statistic
• Problems in Regression Analysis
Multicollinearity: Two or more explanatory variables are highly correlated.
Heteroskedasticity: Variance of error term is not independent of the Y variable.
Autocorrelation: Consecutive error terms are correlated.
• Durbin-Watson Statistic
Test for Autocorrelation
If d = 2, autocorrelation is absent.
• Steps in Demand Estimation
Model Specification: Identify Variables
Collect Data
Specify Functional Form
Estimate Function
Test the Results
• Functional Form Specifications
Linear Function:
Power Function:
Estimation Format:
• Chapter 4 Appendix
• Getting Started
Install the Analysis ToolPak add-in from the Excel installation media if it has not already been installed
When the Add-Ins dialog appears, select Analysis ToolPak and then click OK.
• Entering Data
Data on each variable must be entered in a separate column
Label the top of each column with a symbol or brief description to identify the variable
Multiple regression analysis requires that all data on independent variables be in adjacent columns
• Example Data
• Running the Regression
Select the Regression tool from the Analysis ToolPak dialog
From the menu, select Tools and then Data Analysis...
On the Data Analysis dialog, scroll down the list of Analysis Tools, select Regression, and then click OK
The Regression tool dialog will then be displayed
• Select the Data Ranges
Type in the data range for the Y variable or select the range on the worksheet
Type in the data range for the X variable(s) or select the range on the worksheet
If your ranges include the data labels (recommended) then check the labels option
• Select an Output Option
Output to a selected range
Selection is the upper left corner of the output range
Output to a new worksheet
Optionally enter a name for the worksheet
Output to a new workbook
And then click OK
• Regression Output
• Multiple Regression Data
• Regression Output