Fixed Effects Regression Methods for Longitudinal Data Using SAS

6.5. Reciprocal Effects with Lagged Predictors

We have seen that many of the fixed and random effects models estimated in chapter 2 can also be estimated with PROC CALIS, and that there are both advantages and disadvantages to this approach. We are now going to consider some important fixed effects models that go considerably beyond those in chapter 2. These models involve reciprocal effects among two or more endogenous variables as well as lagged values of both endogenous and exogenous variables. The models are important because they offer the possibility of greatly advancing our ability to determine the direction of causality among variables that are associated with one another.

Let's suppose that we observe two variables, x and y, that are ...