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of 93
pro vyhledávání: '"Fan, Qingliang"'
Different from existing literature on testing the macro-spanning hypothesis of bond risk premia, which only considers mean regressions, this paper investigates whether the yield curve represented by CP factor (Cochrane and Piazzesi, 2005) contains al
Externí odkaz:
http://arxiv.org/abs/2410.03557
This paper proposes a robust, shocks-adaptive portfolio in a large-dimensional assets universe where the number of assets could be comparable to or even larger than the sample size. It is well documented that portfolios based on optimizations are sen
Externí odkaz:
http://arxiv.org/abs/2410.01826
This paper analyzes the statistical properties of constrained portfolio formation in a high dimensional portfolio with a large number of assets. Namely, we consider portfolios with tracking error constraints, portfolios with tracking error jointly wi
Externí odkaz:
http://arxiv.org/abs/2402.17523
We propose a robust hypothesis testing procedure for the predictability of multiple predictors that could be highly persistent. Our method improves the popular extended instrumental variable (IVX) testing (Phillips and Lee, 2013; Kostakis et al., 201
Externí odkaz:
http://arxiv.org/abs/2401.01064
Nonlinearity and endogeneity are prevalent challenges in causal analysis using observational data. This paper proposes an inference procedure for a nonlinear and endogenous marginal effect function, defined as the derivative of the nonparametric trea
Externí odkaz:
http://arxiv.org/abs/2310.08063
We discuss the fundamental issue of identification in linear instrumental variable (IV) models with unknown IV validity. With the assumption of the "sparsest rule", which is equivalent to the plurality rule but becomes operational in computation algo
Externí odkaz:
http://arxiv.org/abs/2207.03035
This paper proposes an overidentifying restriction test for high-dimensional linear instrumental variable models. The novelty of the proposed test is that it allows the number of covariates and instruments to be larger than the sample size. The test
Externí odkaz:
http://arxiv.org/abs/2205.00171
Publikováno v:
In Journal of Econometrics February 2024 239(2)
Autor:
Fan, Qingliang, Wu, Yaqian
Instrumental variables (IV) regression is a popular method for the estimation of the endogenous treatment effects. Conventional IV methods require all the instruments are relevant and valid. However, this is impractical especially in high-dimensional
Externí odkaz:
http://arxiv.org/abs/2006.14998
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