  This paper considers identification and estimation of ceteris paribus effects
of continuous regressors in nonseparable panel models with time homogeneity.
The effects of interest are derivatives of the average and quantile structural
functions of the model. We find that these derivatives are identified with two
time periods for "stayers", i.e. for individuals with the same regressor values
in two time periods. We show that the identification results carry over to
models that allow location and scale time effects. We propose nonparametric
series methods and a weighted bootstrap scheme to estimate and make inference
on the identified effects. The bootstrap proposed allows uniform inference for
function-valued parameters such as quantile effects uniformly over a region of
quantile indices and/or regressor values. An empirical application to Engel
curve estimation with panel data illustrates the results.
