EDFCHT

NameEDFCHT
DescriptionThe project looks into the use of heteroskedasticity consistent variance-covariance estimators for conducting hypothesis testing. It uses Monte Carlo and bootstrap techniques to find the distribution of t-statistics using heteroskedasticity consistent variance-covariance estimator under normality and nonnormality. Comparison between using different heteroskedasticity consistent estimators are included and possible corrections are proposed and will be examined.
OrganizationUC Riverside
DepartmentEconomics
Sponsor Campus GridOSG Connect
Principal Investigator
Jianghao Chu
Field Of ScienceEconomics
DisableFalse