This paper develops a new method for estimating a demand function and the welfare consequences of price changes. The method is applied to gasoline demand in the United States and is applicable to other goods. The method uses shape restrictions derived from economic theory to improve the...

Often semiparametric estimators are asymptotically equivalent to a sample average. The object being averaged is referred to as the influence function. The influence function is useful in formulating primitive regularity conditions for asymptotic normality, in efficiency comparions, for bias...

We develop a method for distributional regression of joint multidimensional choice on nonlinear prices departing from a household model of labor supply that focuses on tax policy effects. Our distribution functions are derived under minimal theoretical assumptions and have a simple structure. We...

We introduce econometric methods to perform estimation and inference on the permanent and transitory components of the stochastic discount factor (SDF) in dynamic Markov environments. The approach is nonparametric in that it does not impose parametric restrictions on the law of motion of the...

The market for commercial properties is characterised by extreme heterogeneity in demand. In this paper, we aim to gain more insight in the heterogeneity in demand for employment agglomeration and size of the rental property using a two-stage hedonic approach following Bajari and Benkard (2005)....

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g say, is discontinuous and must be regularised (that is, modified) to make consistent estimation possible. The amount of modification is contolled by a regularisation parameter. The optimal...

In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...