In this paper R2-type measures of the explanatory power of multivariate linear and categorical probit models proposed in the literature are reviewed and their deficiencies are discussed. It is argued that a measure of the explanatory power should take into account the components which are...

In this paper R2-type measures of the explanatory power of multivariate linear and categorical probit models proposed in the literature are reviewed and their deficiencies are discussed. It is argued that a measure of the explanatory power should take into account the components which are...

In 1986 German federal parental leave and benefit policy was expanded in several ways, extending the potential duration of leave from six to ten months and paying child-rearing benefits to all new mothers regardless of their employment status before childbirth. The potential duration has...

What determines the risk structure of financial portfolios of German households? In this paper we estimate the determinants of the share of financial wealth invested in three broad risk classes. We employ a new econometric approach - the so called fractional multinomial logit model - which...

While prior research has studied the motivations of individuals to consume content on social media platforms, limited work exists on how contributors are motivated to create content. We examine the role of peer influence in content production on YouTube, where content creators are competing for...

We conduct an extensive Monte Carlo experiment to examine the finite samples properties of maximum likelihood based inference in the bivariate probit model with endogenous dummy. We analyse the relative performance of alternative exogeneity tests, the impact of distributional misspecification...

This study examines whether developers learn from their experience and from interactions with peers in OSS projects. A Hidden Markov Model (HMM) is proposed that allows us to investigate (1) the extent to which OSS developers actually learn from their own experience and from interactions with...

Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature: many studies focus solely on measuring accuracy. Methods...

This paper proposes a simpleprocedure based on Meta-analysisto test Granger causality relationship betweenvariables in heterogeneous mixed panels.We evaluate the finite sample properties of the causality test based on Meta-analysisthrough Monte Carlo experiments for panels characterized by both...

A simulation study designed to evaluate the pseudo-R2 proposed by Spiess and Keller (1999) suggests that this measure represents the goodness-of-fit not only of the systematic part, but also of the assumed correlation structure in binary panel probit models.