The seeming unreliability of rank-ordered data as a consequence of model misspecification

The rank-ordered logit model's coefficients often vary significantly with the depth of rankings used in the estimation process. The common interpretation of the unstable coefficients across ranks is that survey respondents state their more and less preferred alternatives in an incoherent manner. We point out another source of the same empirical regularity: stochastic misspecification of the random utility function. An example is provided to show how the well-known symptoms of incoherent ranking behavior can result from stochastic misspecification, followed by Monte Carlo evidence. Our finding implies that the empirical regularity can be addressed by the development of robust estimation methods.