The McGraw-Hill Series Economics essentials of economics brue, McConnell, and Flynn Essentials of Economics

ratio scale, interval scale, ordinal scale,
and 
nominal
scale.
The types of variables that we have encountered in the preceding chapters were
essentially 
ratio scale.
But this should not give the impression that regression models can
deal only with ratio scale variables. Regression models can also handle other types of
variables mentioned previously. In this chapter, we consider models that may involve
not only ratio scale variables but also 
nominal scale
variables. Such variables are also
known as 
indicator variables, categorical variables, qualitative variables,
or 
dummy
variables.
1
9.1
The Nature of Dummy Variables
In regression analysis the dependent variable, or regressand, is frequently influenced not
only by ratio scale variables (e.g., income, output, prices, costs, height, temperature) but
also by variables that are essentially qualitative, or nominal scale, in nature, such as sex,
race, color, religion, nationality, geographical region, political upheavals, and party affilia-
tion. For example, holding all other factors constant, female workers are found to earn less
than their male counterparts or nonwhite workers are found to earn less than whites.
2
This
pattern may result from sex or racial discrimination, but whatever the reason, qualitative
variables such as sex and race seem to influence the regressand and clearly should be
included among the explanatory variables, or the regressors.
Since such variables usually indicate the presence or absence of a “quality” or an
attribute, such as male or female, black or white, Catholic or non-Catholic, Democrat or
Republican, they are essentially 
nominal scale
variables. One way we could “quantify”
such attributes is by constructing artificial variables that take on values of 1 or 0, 1 indicat-
ing the presence (or possession) of that attribute and 0 indicating the absence of that
attribute. For example, 1 may indicate that a person is a female and 0 may designate a male;
or 1 may indicate that a person is a college graduate, and 0 that the person is not, and so on.
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