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How much should we trust differences-in-differences estimates?

Bertrand, Marianne (contributor); Duflo, Esther (contributor) - 2001 - [Elektronische Ressource]

allowing for an arbitrary covariance structure between time periods. We also suggest a third technique, based on randomization …

Persistent link: https://www.econbiz.de/10001620672

Correlation analysis of financial contagion : what one should know before running a test

Corsetti, Giancarlo; Pericoli, Marcello; Sbracia, Massimo - 2000

Persistent link: https://www.econbiz.de/10001580233

A New Paradigm : A Joint Test of Structural and Correlation Parameters in Instrumental Variables Regression When Perfect Exogeneity is Violated

Caner, Mehmet; Morrill, Melinda Sandler - 2009

Currently, the commonly employed instrumental variables strategy relies on the knife-edge assumption of perfect exogeneity for valid inference. To make reliable inferences on the structural parameters under violations of exogeneity one must know the true correlation between the structural error...

Persistent link: https://www.econbiz.de/10014205574

A Practical, Powerful, Robust and Interpretable Family of Correlation Coefficients

Papadopoulos, Savas - 2022

If we conducted a competition for which statistical quantity would be the most valuable in exploratory data analysis, the winner would most likely be the correlation coefficient with a significant difference from its first competitor. In addition, most data applications contain non-normal data...

Persistent link: https://www.econbiz.de/10014084103

On a New Correlation Coefficient, its Orthogonal Decomoposition, and Associated Tests of Independence

Bergsma, Wicher - 2006

A possible drawback of the ordinary correlation coefficient p for two real random variables X and Y is that zero correlation does not imply independence. In this paper we introduce a new correlation coefficient p* which assumes values between zero and one, equalling zero iff the two variables...

Persistent link: https://www.econbiz.de/10014057932

Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity

Boudt, Kris - 2017

uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to …

Persistent link: https://www.econbiz.de/10012973570

Robust Bootstrap Densities for Dynamic Conditional Correlations : Implications for Portfolio Selection and Value-at-Risk

Trucíos, Carlos - 2017

are based on forecasts covariance matrix little is known about effects of outliers on the uncertainty associated with …

Persistent link: https://www.econbiz.de/10012956168

A New Semiparametric Estimation Approach of Large Dynamic Covariance Matrices with Multiple Conditioning Variables

Chen, Jia - 2018

This paper studies the estimation of dynamic covariance matrices with multiple conditioning variables, where the matrix …-to-implement semiparametric method to estimate each entry of the covariance matrix via model averaging marginal regression, and then apply a … shrinkage technique to obtain the large dynamic covariance matrix estimation. Under some regularity conditions, we derive the …

Persistent link: https://www.econbiz.de/10012915138

Testing Covariates in High Dimensional Regression

Lan, Wei - 2013

In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically, we employ the partial covariances between the response variable and the tested covariates to obtain a test statistic. The resulting...

Persistent link: https://www.econbiz.de/10013082410

On Covariation Estimation for Multivariate Continuous Itô Semimartingales with Noise in Non-Synchronous Observation Schemes

Christensen, Kim - 2014

observed with noise. The coordinates of the multivariate process are assumed to be observed at highly frequent nonsynchronous …

Persistent link: https://www.econbiz.de/10013066163