Title: Developing causal theories
Course: UGQuants (SSPS) > Section: Causality

Developing causal theories

The idea of something causing something else is a theoretical hypothesis about what we believe would make logical and substantive sense in the context of our research. Causality cannot usually be deduced from our empirical data directly. Our ideas about causality come from our theories or models of the social world, not from our empirical data.  The only exception (at least partially) is data that is longitudinal, meaning that some variables were measured at different time points from each other. If a certain measurement (variable 1) occurs before another measurement (variable 2), we know that variable 2 cannot have caused variable 1 – any effect must have the reverse direction.

However we can use our statistical tests to lend potential weight to whatever model we envisage by exploring whether our evidence is consistent with a model that we develop, or our ideas about causes in the world. We know that for causation to exist, there must be association between the variables. If X is not correlated to Y, neither can cause the other directly.

However, Correlation is not the same as causation.

Rather, correlation is a necessary but insufficient condition of causation.

We also know that any event may have multiple causes and may also have multiple effects. Because of this, we need to be aware of alternative sources of variation in our variable of interest. We normally describe our variable of interest as a 'dependent' variable - because its values may depend upon that of other independent variable.

Heart disease might be caused by drinking, smoking, or genetic inheritance, or some combination of these, or some other unknown factor altogether. What we can do, is examine what potential patterns of cause and effect might link drinking, smoking, or genetic profile (as independent variables) with heart disease (as a dependent variable) and examine what models (there will probably be more than one) are consistent with the empirical evidence.