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Let's get LADE : robust estimation of semiparametric multiplicative volatility models
Koo, Bonsoo; Linton, Oliver - 2013
We investigate a model in which we connect slowly time varying unconditional long-run volatility with short …-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …
Persistent link: https://www.econbiz.de/10009719116
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Locally robust semiparametric estimation
Chernozhukov, Victor; Escanciano, Juan Carlos; … - 2016
This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions have zero derivative with respect to the first step and the first step does not affect the asymptotic variance. They are constructed by adding to the moment functions the...
Persistent link: https://www.econbiz.de/10011517194
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Locally robust semiparametric estimation
Chernozhukov, Victor; Escanciano, Juan Carlos; … - 2018
We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the derivative with respect to first step nonparametric estimation is zero and equivalently first step estimation has no effect on the influence function. This construction consists of...
Persistent link: https://www.econbiz.de/10011824067
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Doubly robust uniform confidence band for the conditional average treatment effect function
Lee, Sokbae; Okui, Ryo; Wang, Yoon-Jae - 2016 - This version: January 2016
In this paper, we propose a doubly robust method to present the heterogeneity of the average treatment effect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the average treatment effect but the covariates of...
Persistent link: https://www.econbiz.de/10011412143
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Double debiased machine learning nonparametric inference with continuous treatments
Colangelo, Kyle; Lee, Ying-Ying - 2019
We propose a nonparametric inference method for causal effects of continuous treatment variables, under unconfoundedness and in the presence of high-dimensional or nonparametric nuisance parameters. Our simple kernel-based double debiased machine learning (DML) estimators for the average...
Persistent link: https://www.econbiz.de/10012111514
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Double debiased machine learning nonparametric inference with continuous treatments
Colangelo, Kyle; Lee, Ying-Ying - 2019
We propose a nonparametric inference method for causal effects of continuous treatment variables, under unconfoundedness and in the presence of high-dimensional or nonparametric nuisance parameters. Our simple kernel-based double debiased machine learning (DML) estimators for the average...
Persistent link: https://www.econbiz.de/10012137890
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Optimal bandwidth selection for robust generalized method of moments estimation
Wilhelm, Daniel - 2014
A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and autocorrelation in the data by using a nonparametric estimator of the optimal weighting matrix. This paper addresses the issue of choosing the corresponding smoothing parameter (or...
Persistent link: https://www.econbiz.de/10010336485
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Estimation of stochastic volatility models by nonparametric filtering
Kanaya, Shin; Kristensen, Dennis - 2015
A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed … diffusion processes are employed, but with the filtered/estimated volatility process replacing the latent process. Our …
Persistent link: https://www.econbiz.de/10010487528
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Estimation with mixed data frequencies : a bias-correction approach
Ghosh, Anisha; Linton, Oliver - 2019
We propose a solution to the measurement error problem that plagues the estimation of the relation between the expected return of the stock market and its conditional variance due to the latency of these conditional moments. We use intra-period returns to construct a nonparametric proxy for the...
Persistent link: https://www.econbiz.de/10012128650
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Random coefficients in static games of complete information
Dunker, Fabian; Hoderlein, Stefan; Kaido, Hiroaki - 2013
Individual players in a simultaneous equation binary choice model act differently in different environments in ways that are frequently not captured by observables and a simple additive random error. This paper proposes a random coefficient specification to capture this type of heterogeneity in...
Persistent link: https://www.econbiz.de/10009725714