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Easy bootstrap-like estimation of asymptotic variances

Honoré, Bo E.; Hu, Luojia - 2018

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated … econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a … "Poor (Wo)man's Bootstrap" based on one-dimensional estimators. In this paper, we propose a modified, simpler method and …

Persistent link: https://www.econbiz.de/10011879253

Non-Modellable Risk Factor (NMRF) Measurement Using Gaussian Process Regression (GPR)

Slime, Badreddine - 2019

One innovation defined in the new market risk rules by the Fundamental Review of the Trading Book (FRTB) is the Non-Modellable Risk Factor (NMRF) framework. This new concept introduces a methodology to differentiate between modellable and non-modellable risk factors in the Internal Models...

Persistent link: https://www.econbiz.de/10012897595

Application of Local Influence Diagnostics to the Linear Logistic Regression Models

Hossain, Monzur; Islam, M. Ataharul - 2004

This paper focuses the development of the diagnostics for the perturbations of case-weights and explanatory variables (one or more) in a linear logistic regression model. The effect of specific perturbation scheme on the estimation of parameters is also assessed. In addition, the interpretation...

Persistent link: https://www.econbiz.de/10014069878

Testing for Reverse Causation and Omitted Variable Bias in Regressions

Marvell, Thomas B. - 2020

This paper shows through regression simulations that, when there are two highly collinear regressors, at least one of which has a simultaneous relationship with the dependent variable, t-ratios typically do not decline to non-significance as text book theory predicts. Coefficients and/or...

Persistent link: https://www.econbiz.de/10012848483

The Kumaraswamy Distribution : Median-Dispersion Re-Parameterizations for Regression Modeling and Simulation-Based Estimation

Mitnik, Pablo A. - 2011

The Kumaraswamy distribution is very similar to the Beta distribution, but has the important advantage of an invertible closed-form cumulative distribution function. The parameterization of the distribution in terms of shape parameters and the lack of simple expressions for its mean and variance...

Persistent link: https://www.econbiz.de/10012756542

Simulation-Based Finite Sample Normality Tests in Linear Regressions

Dufour, Jean-Marie; Farhat, Abdeljelil; Gardiol, Lucien; … - 1999

In the literature on tests of normality, much concern has been expressed over the problems associated with residual-based procedures. Indeed, the specialized tables of critical points which are needed to perform the tests have been derived for the location-scale model; hence, reliance on...

Persistent link: https://www.econbiz.de/10014197182

Testing for Reverse Causation and Omitted Variable Bias in Regressions

Marvell, Thomas B. - 2022

Textbook theory predicts that t-ratios decline towards zero in regressions when there is collinearity between two regressors. This paper shows that this often does not occur if the regression suffers from simultaneity or omitted variable bias. With more collinearity, t-ratios generally increase...

Persistent link: https://www.econbiz.de/10013308808

Local Linear Quantile Regression for Time Series Under Near Epoch Dependence

Ren, Xiaohang - 2020

This paper aims to establish asymptotic normality of the local linear kernel estimator for quantile regression under near epoch dependence, a useful concept in characterising time series dependence of extensive interests in Econometrics. In particular, near epoch dependence can cover a wide...

Persistent link: https://www.econbiz.de/10012839310

The COVID report card

Czasonis, Megan; Kritzman, Mark; Pamir, Baykan; … - 2020 - This version: October 16, 2020

The authors model COVID infections and COVID deaths, both reported and implied, for the 50 U.S. states as well as the District of Columbia, and separately for a sample of 33 countries, as a function of pre-existing circumstances that citizens have no ability to control over the short term. These...

Persistent link: https://www.econbiz.de/10012502027

Distribution regression difference-in-differences

Fernández-Val, Iván; Meier, Jonas; Vuuren, Aico van; … - 2024

We provide a simple distribution regression estimator for treatment effects in the difference-in-differences (DiD) design. Our procedure is particularly useful when the treatment effect differs across the distribution of the outcome variable. Our proposed estimator easily incorporates covariates...

Persistent link: https://www.econbiz.de/10015052864