Dummy Variable (statistics)

Dummy Variable (statistics)

In statistics and econometrics, particularly in regression analysis, a dummy variable (also known as an indicator variable) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome. For example, in econometric time series analysis, dummy variables may be used to indicate the occurrence of wars, or major strikes. It could thus be thought of as a truth value represented as a numerical value 0 or 1 (as is sometimes done in computer programming).

Dummy variables are "proxy" variables or numeric stand-ins for qualitative facts in a regression model. In regression analysis, the dependent variables are influenced not only by quantitative variables (income, output, prices, etc.), but also by qualitative variables (gender, religion, geographic region, etc.) Dummy independent variables take the value of 0 or 1. Hence, they are also called binary variables. A dummy explanatory variable with a value of 0 will cause that variable's coefficient to disappear and a dummy with a value 1 will cause the coefficient to act as a supplemental intercept in a regression model. For example, suppose Gender is one of the qualitative variables relevant to a regression. Then, female and male would be the categories included under the Gender variable. If female is assigned the value of 1, then male would get the value 0 (or vice-versa).

Thus, a dummy variable can be defined as a qualitative representative variable incorporated into a regression, such that it assumes the value 1 whenever the category it represents occurs, and 0 otherwise. Dummy variables are used as devices to sort data into mutually exclusive categories (such as male/female, smoker/non-smoker, etc.).

Dummy variables are generally used frequently in time series analysis with regime switching, seasonal analysis and qualitative data applications. Dummy variables are involved in studies for economic forecasting, bio-medical studies, credit scoring, response modelling, etc.. Dummy variables may be incorporated in traditional regression methods or newly developed modeling paradigms.

Synonyms for the term dummy variables include design variables, Boolean indicators, proxies, indicator variables, categorical variables and qualitative variables.