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Found 4 papers, 0 papers with code
Robust Inference on Income Inequality: $t$-Statistic Based Approaches
Following the approaches, in particular, a robust large sample test on equality of two parameters of interest (e. g., a test of equality of inequality measures in two regions or countries considered) is conducted as follows: The data in the two samples dealt with is partitioned into fixed numbers $q_1, q_2\ge 2$ (e. g., $q_1=q_2=2, 4, 8$) of groups, the parameters (inequality measures dealt with) are estimated for each group, and inference is based on a standard two-sample $t-$test with the resulting $q_1, q_2$ group estimators.
COVID-19: Tail Risk and Predictive Regressions
The paper focuses on econometrically justified robust analysis of the effects of the COVID-19 pandemic on financial markets in different countries across the World.
New Approaches to Robust Inference on Market (Non-)Efficiency, Volatility Clustering and Nonlinear Dependence
The approaches are based on robust $t-$statistics tests and new results on their applicability are presented.
New robust inference for predictive regressions
To relax the exogenous volatility assumption, we propose another method which relies on the nonparametric correction of volatility.
