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Monotonicity-Preserving Bootstrapped Kriging Metamodels for Expensive Simulations

Kleijnen, Jack P. C.; Beers, Wim C. M. van - 2009

metamodel that preserves this known shape, this article uses bootstrapping (or resampling). Parametric bootstrapping assuming …-event simulation) using distribution-free bootstrapping. In stochastic simulation, the analysts should simulate each input combination … variation, so the Kriging metamodel does not need to interpolate the average outputs. Bootstrapping provides a simple method for …

Persistent link: https://www.econbiz.de/10014203752

Nonparametric tests for common values at first-price sealed bid auctions

Haile, Philip A.; Hong, Han; Shum, Matthew - 2003

Persistent link: https://www.econbiz.de/10001833591

Simulation and estimation of hedonic models

Heckman, James J.; Matzkin, Rosa L.; Nesheim, Lars - 2003

Making use of restrictions imposed by equilibrium, theoretical progress has been made on the nonparametric and semiparametric estimation and identification of scalar additive hedonic models (Ekeland, Heckman, and Nesheim, 2002) and scalar nonadditive hedonic models (Heckman, Matzkin, and...

Persistent link: https://www.econbiz.de/10001784247

A Consistent Nonparametric Test of Ergodicity for Time Series with Applications

Domowitz, Ian; El-Gamal, Mahmoud A. - 1999

We propose a set of algorithms for testing the ergodicity of empirical time series, without reliance on a specific parametric framework. It is shown that the resulting test asymptotically obtains the correct size for stationary and nonstationary processes, and maximal power against non-ergodic...

Persistent link: https://www.econbiz.de/10014184182

Nonparametric Estimation of Higher-Order Moments of Technical Efficiency

Henderson, Daniel J. - 2007

In this paper nonparametric techniques are used to estimate higher-order moments of technical efficiency. The procedures developed in this paper allow the moments to be estimated with relative ease, while at the same not requiring restrictive assumptions on the distribution of inefficiency. The...

Persistent link: https://www.econbiz.de/10014049970

Estimating Derivatives in Nonseparable Models with Limited Dependent Variables

Altonji, Joseph G.; Otsu, Taisuke; Ichimura, Hidehiko - 2008

We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables. We treat models in which Y is censored from above or below or potentially from both. The basic idea...

Persistent link: https://www.econbiz.de/10014216569

Information-Theoretic Deconvolution Approximation of Treatment Effect Distribution

Wu, Ximing; Perloff, Jeffrey M. - 2006

This study proposes an information-theoretic deconvolution method to approximate the entire distribution of individual treatment effect. This method uses higher-order information implied by the standard average treatment effect estimator to construct a maximum entropy approximation to the...

Persistent link: https://www.econbiz.de/10014058130

On Nonparametric Identification of Treatment Effects in Duration Models

Johansson, Per - 2016

We show that the main nonparametric identification finding of Abbring and Van den Berg (2003b, Econometrica) for the effect of a timing-chosen treatment on an event duration of interest does not hold. The main problem is that the identification is based on the competing-risks identification...

Persistent link: https://www.econbiz.de/10012981520

Inference in Additively Separable Models with a High-Dimensional Set of Conditioning Variables

Kozbur, Damian - 2018

This paper studies nonparametric series estimation and inference for the effect of a single variable of interest x on an outcome y in the presence of potentially high-dimensional conditioning variables z. The context is an additively separable model E[y|x, z] = g<sub>0</sub> (x) h<sub>0</sub> (z). The model is...

Persistent link: https://www.econbiz.de/10012920814

Nonparametric Assessment of Hedge Fund Performance

Almeida, Caio - 2019

We propose a new class of performance measures for Hedge Fund (HF) returns based on a family of empirically identifiable stochastic discount factors (SDFs). The SDF-based measures incorporate no-arbitrage pricing restrictions and naturally embed information about higher-order mixed moments...

Persistent link: https://www.econbiz.de/10012905264