This note concerns an asymptotic distribution result from the literature on nonlinear estimation with integrated variables. It points out a way of strengthening local asymptotic distribution results towards results that hold for the global minimizer of the criterion function.

We decompose the effect of distance on intercity retail price dispersion in US into transport and non-transport cost components. We find that distance contains more information than transport costs. Care should be taken in interpreting distance effect as transport costs only.

It is widely perceived that relative prices are more dispersed in periods of price decreases than in periods of price increases. We show that the asymmetry results from misspecifying the true, U-shaped, underlying model with a piecewise linear regression model.