We study the role of beauty in politics using candidate photos that figured prominently in electoral campaigns. Our investigation is based on visual assessments of 1,929 Finnish political candidates from 10,011 respondents (of which 3,708 were Finnish). An increase in beauty by one standard...

We study the role of beauty in politics using candidate photos that figured prominently in electoral campaigns. Our investigation is based on visual assessments of 1,929 Finnish political candidates from 10,011 respondents (of which 3,708 were Finnish). An increase in beauty by one standard...

This paper provides a new comparative analysis of pooled least squares and fixed effects estimators of the slope coefficients in the case of panel data models when the time dimension (T) is fixed while the cross section dimension (N) is allowed to increase without bounds. The individual effects...

This paper considers a class of GMM estimators for general dynamic panel models, allowing for cross sectional dependence due to spatial lags and due to unspecified common shocks. We significantly expand the scope of the existing literature by allowing for endogenous spatial weight matrices,...

This paper explores the properties of pre-test strategies in estimating a linear Cliff-Ord-type spatial model when the researcher is unsure about the nature of the spatial dependence. More specifically, the paper explores the finite sample properties of the pre-test estimators introduced in...

We propose a novel method of Mean-Capital Requirement portfolio optimization. The optimization is performed using a parallel framework for optimization based on the Nondominated Sorting Genetic Algorithm II. Capital requirements for market risk include an additional stress component introduced...

Multicollinearity, especially in combination with errors-in-variables, can increase the likelihood of a Type-I error by inflating the value of the estimated coefficients by more than it magnifies their standard errors, thereby increasing the likelihood of obtaining statistically significant...

Education policy-makers and practitioners want to know which policies and practices can best achieve their goals. But research that can inform evidence-based policy often requires complex methods to distinguish causation from accidental association. Avoiding econometric jargon and technical...

We use a marginal treatment effect (MTE) representation of a fuzzy regression discontinuity setting to propose a novel estimator. The estimator can be thought of as extrapolating the traditional fuzzy regression discontinuity estimate or as an observational study that adjusts for endogenous...

This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A Generalized Method of...