Managerial Economics

5.

Demand Estimation and Forecasting

5.1.

Methods of Demand Estimation

5.1.1.

Consumer Surveys

5.1.1.1.

Survey Design Principles

5.1.1.2.

Sampling Methods

5.1.1.3.

Response Bias Issues

5.1.2.

Market Experiments

5.1.2.1.

Experimental Design

5.1.2.2.

Field vs. Laboratory Experiments

5.1.2.3.

Controlled Testing

5.1.3.

Statistical Methods

5.1.3.1.

Data Collection Techniques

5.1.3.2.

Data Analysis Approaches

5.2.

Regression Analysis in Demand Estimation

5.2.1.

Simple Linear Regression

5.2.1.1.

Model Specification

5.2.1.2.

Interpretation of Coefficients

5.2.1.3.

Assumptions and Limitations

5.2.2.

Multiple Regression

5.2.2.1.

Inclusion of Multiple Variables

5.2.2.2.

Multicollinearity Issues

5.2.2.3.

Variable Selection

5.2.3.

Interpreting Regression Results

5.2.3.1.

Statistical Significance

5.2.3.2.

Goodness of Fit

5.2.3.3.

Confidence Intervals

5.2.3.4.

Limitations of Regression Analysis

5.3.

Demand Forecasting Techniques

5.3.1.

Qualitative Forecasting

5.3.1.1.

5.3.1.2.

5.3.1.3.

Market Research

5.3.1.4.

Consumer Intention Surveys

5.3.2.

Quantitative Forecasting

5.3.2.1.

Time-Series Analysis

5.3.2.1.1.

5.3.2.1.2.

Seasonal Variations

5.3.2.1.3.

Cyclical Patterns

5.3.2.2.

Smoothing Techniques

5.3.2.2.1.

Simple Moving Average

5.3.2.2.2.

Weighted Moving Average

5.3.2.2.3.

Exponential Smoothing

5.3.2.3.

Trend Projection

5.3.2.3.1.

5.3.2.3.2.

Nonlinear Trend

5.3.2.3.3.

5.3.3.

Forecast Accuracy and Evaluation

5.3.3.1.

Error Measurement

5.3.3.2.

Forecast Validation

5.3.3.3.

Model Selection Criteria

Previous

4. Demand Elasticity

Go to top

Next

6. Production Theory and Analysis