This paper suggests an identification and estimation approach based on quantile regression to recover the underlying distribution of bidders' private values in ascending auctions under the IPV paradigm. The quantile regression approach provides a flexible and convenient parametrization of the...

In this paper, the effect of the social network on macroeconomic stability is examined using an agent-based, network-based DSGE (dynamic stochastic general equilibrium) model. While the authors' primitive (first-stage) examination has the network generation mechanism as its main focus, their...

In this paper we are concerned with shape restricted estimation in inverse regression problems with convolution-type operator. We use increasing rearrangements to compute increasingand convex estimates from an (in principle arbitrary) unconstrained estimate of the unknown regression function. An...

In this paper we are concerned with shape restricted estimation in inverse regression problems with convolution-type operator. We use increasing rearrangements to compute increasingand convex estimates from an (in principle arbitrary) unconstrained estimate of the unknown regression function. An...

Abstract Many statistical estimation techniques for high-dimensional or functional data are based on a preliminary dimension reduction step, which consists in projecting the sample X 1 ,..., X n onto the first D eigenvectors of the Principal Component Analysis (PCA) associated with the empirical...

Consider the regression problem with a response variable Y and with a d-dimensional feature vector X. For the regression function m(x)=E{Y|X=x}, this paper investigates methods for estimating the density of the residual Y−m(X) from independent and identically distributed data. For...

Statistical data sets often contain observations that differ markedly from the bulk of the data. These outlying observations, ‘outliers’, have given rise to notable risks for statistical analysis and inference. Unfortunately, many of the classical statistical methods, such as ordinary least...

We present the asymptotic properties of double-stage quantile regressionestimators with random regressors, where the first stage is based on quantile regressionswith the same quantile as in the second stage, which ensures robustness of the estimationprocedure. We derive invariance properties...