Empirical models of demand for–and, often, supply of–differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This work...

Empirical models of demand for -- and, often, supply of -- differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This...

We develop a methodology to construct nonparametric counterfactual predictions, free of functional-form restrictions on preferences and technology, in neoclassical models of international trade. First, we establish the equivalence between such models and reduced exchange models in which...

We propose a new technique for identification and estimation of aggregation functions in multidimensional evaluations and multiple indicator settings. These functions may represent "latent" objects. They occur in many different contexts, for instance in propensity scores, multivariate measures...

We derive mean-unbiased estimators for the structural parameter in instrumental variables models where the sign of one or more first stage coefficients is known. In the case with a single instrument, the unbiased estimator is unique. For cases with multiple instruments we propose a class of...

We consider two new approaches to nonparametric estimation of the leverage effect. The first approach uses stock prices alone. The second approach uses the data on stock prices as well as a certain volatility instrument, such as the CBOE volatility index (VIX) or the Black-Scholes implied...

We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coefficients is known. In the case with a single instrument, the unbiased estimator is unique. For cases with multiple...

We construct a Malmquist productivity index based on stochastic non-parametric envelopment of data (StoNED) method, and we study how the distributional assumptions in the second StoNED stage affect productivity change and its decompositions. Our discussion show that the distributional...

In a recent paper Johnson and Kuosmanen (2011) propose a new, semi-parametric, general cost-frontier model, the stochastic nonparametric envelopment of data (StoNED). The model is semi-parametric in the sense that the cost function is estimated nonparametrically, while the functional form of the...

We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coefficients is known. In the case with a single instrument, the unbiased estimator is unique. For cases with multiple...