We propose two new methods for estimating models with nonseparable errors and endogenous regressors. The first method estimates a local average response. One estimates the response of the conditional mean of the dependent variable to a change in the explanatory variable while conditioning on an external variable and then undoes the conditioning. The second method estimates the nonseparable function and the joint distribution of the observable and unobservable explanatory variables. An external variable is used to impose an equality restriction, at two points of support, on the conditional distribution of the unobservable random term given the regressor and the external variable. Our methods apply to cross sections, but our lead examples involve panel data cases in which the choice of the external variable is guided by the assumption that the distribution of the unobservable variables is exchangeable in the values of the endogenous variable for members of a group. Copyright The Econometric Society 2005.

We present a new method for solving asset pricing models, which yields an analytic price-dividend function of one state variable. To illustrate our method we give a detailed analysis of Abel's asset pricing model. A function is analytic in an open interval if it can be represented as a convergent power series near every point of that interval. In addition to allowing us to solve for the exact equilibrium price-dividend function, the analyticity property also lets us assess the accuracy of any numerical solution procedure used in the asset pricing literature. Copyright The Econometric Society 2005.