We analyze a dynamic model of agenda formation in which players compete in each period to put their ideal policies on the agenda. In each period, with some probability, a decision maker is called upon to take an action from the agenda. We show that in any Markov equilibrium of this game, players...

We propose a model of religious organizations which relies on the ability of such organizations to affect individual beliefs about the causality between actions in the social context and personal utility shocks. We show how religious organizations arise endogenously and characterize their...

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...

This paper investigates how quantity competition operates in economies in which a network describes the set of feasible trades. A general equilibrium model is presented in which prices and .ows of goods are endogenously determined. In such economies equilibrium dictates whether an individual...

We propose a semiparametric IGARCH model that allows for persistence in variance but also allows for more flexible functional form. We assume that the difference of the squared process is weakly stationary. We propose an estimation strategy based on the nonparametric instrumental variable...

We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a nonparametric long run component and a unit multivariate GARCH short run dynamic component. We suggest various kernel-based estimation procedures for the parametric and...

In semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothing may result as we show from inefficient estimation methods or technical...

In this paper we investigate a class of semiparametric models for panel datasets where the cross-section and time dimensions are large. Our model contains a latent time series that is to be estimated and perhaps forecasted along with a nonparametric covariate effect. Our model is motivated by...

This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and Anderson, Ge, and Leo (2006) based on kernel estimation techniques. We give the asymptotic distribution theory of our estimator, which in some cases is nonstandard due to a boundary...

We use local polynomial fitting to estimate the nonparametric M-regression function for strongly mixing stationary processes {(Y_i,▁X_i ) } . We establish a strong uniform consistency rate for the Bahadur representation of estimators of the regression function and its derivatives. These...