It is commonplace that the data needed for econometric inference are not contained in a single source. In this paper we analyze the problem of parametric inference from combined individual-level data when data combination is based on personal and demographic identifiers such as name, age, or...

Businesses routinely rely on econometric models to analyze and predict consumer behavior. Estimation of such models may require combining a firm's internal data with external datasets to take into account sample selection, missing observations, omitted variables and errors in measurement within...

We explore existence and properties of equilibrium when N ≥ 2 bidders compete for L ≥ 2 objects via simultaneous but separate auctions. Bidders have private combinatorial valuations over all sets of objects they could win, and objects are complements in the sense that these valuations are...

Most empirical and theoretical econometric studies of dynamic discrete choice models assume the discount factor to be known. We show the knowledge of the discount factor is not necessary to identify parts, or all, of the payoff function. We show the discount factor can be generically identified...

This paper proposes an approach to proving nonparametric identification for distributions of bidders' values in asymmetric second-price auctions. I consider the case when bidders have independent private values and the only available data pertain to the winner's identity and the transaction...

The econometric literature on program-evaluation and optimal treatment-choice takes functionals of outcome-distributions as `social-welfare' and ignores program-impacts on unobserved utilities, whereas the utility-based welfare-analysis tradition in public-finance ignores unobserved...

Empirical economic research crucially relies on highly sensitive individual datasets.At the same time, increasing availability of public individual-level data that comes from socialnetworks, public government records and directories makes it possible for adversaries to poten-tially de-identify...

We introduce a notion of median uncorrelation that is a natural extension of mean (linear) uncorrelation. A scalar random variable Y is median uncorrelated with a kdimensional random vector X if and only if the slope from an LAD regression of Y on X is zero. Using this simple definition, we...

This paper proposes an approach to proving nonparametric identification for distributions of bidders' values in asymmetric second-price auctions. I consider the case when bidders have independent private values and the only available data pertain to the winner's identity and the transaction...