Many structural economics models are semiparametric ones in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly nonnested or overlapping conditioning sets, and the finite dimensional parameters of interest are over-identified via...

The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the...

In this note, we characterize the semiparametric efficiency bound for a class of semi- parametric models in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional...

In the various fields of creative, cultural, and artistic production, there exists a competitive struggle amongst creators of innovative works or ideas to persuade agents in the field to accept and value the new work. This is a significant challenge since cultural innovators do not produce in...

We introduce two simple new variants of the Jackknife Instrumental Variables (JIVE) estimator for overidentified linear models and show that they are superior to the existing JIVE estimator, significantly improving on its small sample bias properties. We also compare our new estimators to...

Buy price auctions merge a posted price option with a standard bidding mechanisms, and have been used by various online auction sites including eBay and General Motors Assistance Corporation. A buyer in a buy price auction can accept the buy price to win with certainty and end the auction early....

Treatment effects are often estimated by the least squares estimator controlling for some covariates. This paper investigates its properties. When the propensity score is constant, it is a consistent estimator of the average treatment effects if it is viewed as a semiparametric partially linear...

Fixed effects estimators of panel models can be severely biased because of the well-known incidental parameters problem. We show that this bias can be reduced by using a panel jackknife or an analytical bias correction motivated by large T. We give bias corrections for averages over the fixed...

Many social experiments are run in multiple waves, or are replications of earlier social experiments. In principle, the sampling design can be modified in later stages or replications to allow for more efficient estimation of causal effects. We consider the design of a two-stage experiment for...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...