This paper discusses three families of flexible parametric probability density functions: the skewed generalized t, the exponential generalized beta of the second kind, and the inverse hyperbolic sin distributions. These families allow quite flexible modeling the first four moments of a...

Assumptions about explanatory variables and errors are central in regression analysis. For example, the well-known method of ordinary least squares yields consistent and efficient estimators if the underlying error terms are independently, identically, and normally distributed. Additionally, the...

This paper explores the ability of some popular income distributions to model observed skewness and kurtosis. We present the generalized beta type 1 (GB1) and type 2 (GB2) distributions' skewness-kurtosis spaces and clarify and expand on previously known results on other distributions'...

This paper discusses three families of flexible parametric probability density functions: the skewed generalized t, the exponential generalized beta of the second kind, and the inverse hyperbolic sin distributions. These families allow quite flexible modeling the first four moments of a...

The five-parameter generalized beta distribution and ten of its special cases are considered as models fore the size distribution of income. The models are fit to income data for 23 countries and various years - a total of 82 datasets. Of the models considered, the Weibull, Daagum and...

Instrumental variables are often associated with low estimator precision. This paper explores efficiency gains which might be achievable using moment conditions which are nonlinear in the disturbances and are based on flexible parametric families for error distributions. We show that these...