In this paper, we introduce a new identification and estimation strategy for partially linear regression models with a general form of unknown heteroscedasticity, that is, Y = X'β₀ + m(Z) + U and U = ...

In the linear regression model when the design matrix X is a function of a set of unknowns ρ, a marginal likelihood is derived for making inferences about ρ. Several special cases are considered and a ...