3.1 DEMAND ESTIMATION AND FORECASTING Flashcards
attempts to quantify the link between the level of demand for a product and the variable which determines it
Demand estimation
attempts to predict the level of sales at some particular future date
Demand forecasting
7 stages of demand estimation
- Statement of a theory or hypothesis
- Model specification
- Data collection
- Estimation parameters
- Checking goodness of fit
- Hypothesis testing
- Forecasting
this usually comes from a mixture of economic theory and previous empirical studies
Statement of a Theory or Hypothesis
This means determining what variable should be included in the demand model and what mathematical form or forms such a relationship should take
Model specification
Gathering necessary information
Data collection
2 types of data
Cross-selection data
Time-series data
provide information on a group of entities at a given time
Cross-selection data
provide information on the entity over time
Time-series data
Data that are expressed in nominal in either ordinal or cardinal
Quantitative data
Data that are expressed in all categories
Qualitative data
This means computing the value of the coefficient of the variables in the model
Estimation of parameters
Once a model or maybe several alternative models have been estimated, it is necessary to determine how well the model fits the data and to determine which model fits best.
Checking goodness of fit
This is the ultimate focus of economic analysis
Forecasting
Methods of forecasting
Qualitative methods:
- Consumer survey
- Market experiment
- Virtual shopping
Quantitative methods:
- Statistics method
- Model specification
- Mathematical models
Sources of data
- Record of firms
- Commercial and private agencies
- Official sources
Presentation of data
- Tabular form
- Graphs
The most basic and common method in presentation
Tabular form
In order to examine the relationship more closely the next step is to draw a _____
Graph
This means finding the line that minimizes the sum of the squares of the differences between the observed values of the dependent variable and the fitted values from the line.
OLS (Ordinary Least Squares) Method for Regression
Examines the type of relationsip between variables
Regression Analysis
Examines the strength if the relationship (goodness of fit)
Correlation Analysis
Refers to how closely the points fit in the line, taking into consideration the units of measurement.
Goodness of fit
Measures the degree of linear association between variables
Correlation coefficient
