Solving Old Puzzles With New Tricks: Addressing Endogeneity And Nonlinearity In Time-On-Market Research

The most commonly used econometric models for time-on-market in housing studies force researchers into a tradeoff between problems of nonlinearity, which may be addressed with a hazard model, and endogeneity, which may be addressed with a two-stage least squares model. This study introduces two modeling approaches-two-stage predictor substitution and two-stage residual inclusion-into the real estate literature. Each approach is able to address both nonlinearity and endogeneity in a single specification. Fit statistics consistently prefer the new methodologies to either two-stage least squares or hazard models of time-on-market. In the current sample, several commonly observed results are changed using the newer, more appropriate models. Some commonly accepted results are reversed, while others are reinforced. In addition to being produced by a more econometrically sound technique, the new results have the added benefit of being almost universally more intuitively appealing than previous results.