Two-Stage Least Squares
Two-stage least squares (2SLS) is a regression technique that is used when explanatory variables are believed to be correlated with the regression model’s error term used to obtain consistent estimators15. One or more instrumental variables (IVs) that are correlated with the endogenous explanatory variable, but uncorrelated with the dependent variable are used to isolate the effects of the endogenous explanatory variable. This process increases consistency (relative to OLS), at the expense of increasing sample variance.
InterVISTAS experimented with the use of two-stage least squares techniques to improve the consistency of elasticity estimates. The natural logarithm of distance and the natural logarithm of fuel prices were used separately and combined as potential IVs. In some data sets, distance was found to be a worthwhile IV, exhibiting high correlations with travel prices and low correlations with traffic. However, there is some concern that distance should be used as an explanatory variable instead of an instrument (if route distance is believed to have an impact on traffic). Fuel prices were found to be poor IVs. Fuel prices exhibited low correlations with traffic and travel prices.