Analysis of Financial Data

Chapter 7. Regression with dummy variables

Previous chapters used quantitative data to demonstrate important statistical concepts. However, some of the data financial analysts use is qualitative (see Chapter 2 for a discussion of the distinction between qualitative and quantive data). Dummy variables, briefly described in Chapter 2, are a way of turning qualitative variables into quantitative variables. Once the variables are quantitative, then the correlation and regression techniques described in previous chapters can be used. Formally, a dummy variable is a variable that can take on only two values, 0 or 1. We will demonstrate how regression works when some of the explanatory variables are dummies using the following examples.

Example: The determinants of market capitalization

We have discussed this example in previous chapters. However, an important issue involving this data sets was not discussed previously since it involved a dummy explanatory variable. By way of motivating this issue, note that most of the shares traded on the stock market are old shares in existing firms. However, many old firms will issue some new shares in addition to those already trading – what are referred to as "seasoned equity offerings" or SEOs. Furthermore, some firms that have not traded shares on the stock market in the past may decide to now issue such shares (e.g. a computer software firm owned by one individual may decide to "go public" and sell shares in order to raise money for future investment ...