The paper reconsiders existing estimators for the panel data fixed effects ordered logit model, including one that has not been used in econometric studies before, and studies
the small sample properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the literature are inconsistent. Second, the new estimator seems to be more immune to small sample bias than other consistent estimators and is easy to implement. The empirical relevance is illustrated in an application to the effect of unemployment on happiness. Choosing the right estimator avoids a bias of up to 30 percent in key parameters.