Demand functions estimated for actual products are obviously much more complex
than the simple examples presented in Equations 4.2 and 4.6. Managers could not use
the results of such simple equations for decision making. However, these examples
provide a starting point for understanding the more complex analyses discussed
below. The estimation process and the choice of functional form in real-world
demand equations are based on the issues presented in these simple examples.
The variables included in a multiple regression analysis may be influenced by
data availability, as well as by the underlying economic theory. Data for demand
estimation are often drawn from large-scale surveys undertaken by the federal
government, universities, nonprofit groups, industry or trade associations, and
company consumer research departments. In many cases, analysts would like to
include certain variables, but a consistent set of observations for all individuals in
the analysis may not be available. Some data sources may have better information
on economic variables, while others may have more data on personal characteris-
tics of the individuals included in the analysis. Analysts may also have to use other
variables as proxies for the variables of greatest interest
Demand functions estimated for actual products are obviously much more complex than the simple examples presented in Equations 4.2 and 4.6. Managers could not use the results of such simple equations for decision making. However, these examples provide a starting point for understanding the more complex analyses discussed below. The estimation process and the choice of functional form in real-world demand equations are based on the issues presented in these simple examples.The variables included in a multiple regression analysis may be influenced by data availability, as well as by the underlying economic theory. Data for demand estimation are often drawn from large-scale surveys undertaken by the federal government, universities, nonprofit groups, industry or trade associations, and company consumer research departments. In many cases, analysts would like to include certain variables, but a consistent set of observations for all individuals in the analysis may not be available. Some data sources may have better information on economic variables, while others may have more data on personal characteris-tics of the individuals included in the analysis. Analysts may also have to use other variables as proxies for the variables of greatest interest
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