  This paper studies semiparametric identification of substitution and
complementarity patterns between two goods using a panel multinomial choice
model with bundles. The model allows the two goods to be either substitutes or
complements and admits heterogeneous complementarity through observed
characteristics. I first provide testable implications for the complementarity
relationship between goods. I then characterize the sharp identified set for
the model parameters and provide sufficient conditions for point
identification. The identification analysis accommodates endogenous covariates
through flexible dependence structures between observed characteristics and
fixed effects while placing no distributional assumptions on unobserved
preference shocks. My method is shown to perform more robustly than the
parametric method through Monte Carlo simulations. As an extension, I allow for
unobserved heterogeneity in the complementarity, investigate scenarios
involving more than two goods, and study a class of nonseparable utility
functions.
