This paper studies the effects of minimum wages on informal and formal sector employment in Indonesia between 1997 2007. Applying fixed-effects methods, estimates suggest that have a significant positive effect wages, while there are no spillover workers. Regarding employment, we find statistically negative probability being formally employed. These findings employers use adjustment channels other than or such as demand stimulus local level outweigh possible effects. Jel codes: J08, J46

Horse riding is a popular sport, which bears the risk of serious injuries. This study aims to assess whether individual factors influence sustain major injuries.Retrospective data were collected from all equine-related accidents at German Level I Trauma Centre between 2004 and 2014. Logistic regression was used identify for injures.770 patients included (87.9% females). Falling off horse (67.7%) being kicked by (16.5%) two main injury mechanisms. Men individuals higher age showed odds tested...

This paper analyzes several modifications to improve a simple measure of vulnerability as expected poverty. Firstly, in order model income, we apply distributional regression relating potentially each parameter the conditional income distribution covariates. Secondly, determine cutoff endogenously instead defining household vulnerable if its probability being poor next period is larger than 0.5. For this purpose, employ receiver operating characteristic curve that able consider prerequisites...

This paper introduces distributional regression also known as generalized additive models for location, scale and shape (GAMLSS) a modeling framework analyzing treatment effects beyond the mean. In contrast to mean models, GAMLSS relate each parameter covariates. Therefore, they can be used model effect not only on but whole conditional distribution. Since encompass wide range of different distributions, provide flexible non-normal outcomes in which additionally nonlinear spatial easily...

Summary We tackle two limitations of standard instrumental variable regression in experimental and observational studies: restricted estimation to the conditional mean outcome assumption a linear relationship between regressors outcome. More flexible approaches that solve these have already been developed but not yet adopted causality analysis. The paper develops an procedure building on framework generalized additive models for location, scale shape. This enables modelling all...

ABSTRACT In this work, a method to regularize Cox frailty models is proposed that accommodates time‐varying covariates and coefficients based on the full likelihood instead of partial likelihood. A particular advantage framework baseline hazard can be explicitly modeled in smooth, semiparametric way, for example, via P‐splines. Regularization variable selection performed lasso penalty group categorical variables while second regularizes wiggliness smooth estimates hazard. Additionally,...

Abstract Poverty is a multidimensional concept often comprising monetary outcome and other welfare dimensions such as education, subjective well-being or health that are measured on an ordinal scale. In applied research, poverty ubiquitously assessed by studying each dimension independently in univariate regression models combining several into scalar index. This approach inhibits thorough analysis of the potentially varying interdependence between dimensions. We propose multivariate copula...

Abstract Background Due to contradictory results in current research, whether age at menopause is increasing or decreasing Western countries remains an open question, yet worth studying as later ages are likely be related increased risk of breast cancer. Using data from cancer screening programs study the temporal trend difficult since especially younger women same generational cohort have often not reached menopause. Deleting these a analyses may bias results. The aim this therefore recover...

This paper introduces distributional regression, also known as generalized additive models for location, scale and shape (GAMLSS), a modeling framework analyzing treatment effects beyond the mean. By relating each parameter of response distribution to explanatory variables, GAMLSS model effect on whole conditional distribution. Additionally, any nonnormal outcome nonlinear variables can be incorporated. We elaborate combination with program evaluation methods in economics provide practical...

In this work a method to regularize Cox frailty models is proposed that accommodates time-varying covariates and coefficients based on the full instead of partial likelihood. A particular advantage in framework baseline hazard can be explicitly modeled smooth, semi-parametric way, e.g. via P-splines. Regularization for variable selection performed lasso penalty group categorical variables while second regularizes wiggliness smooth estimates hazard. Additionally, adaptive weights are included...

Poverty is a multidimensional concept often comprising monetary outcome and other welfare dimensions such as education, subjective well-being or health, that are measured on an ordinal scale. In applied research, poverty ubiquitously assessed by studying each dimension independently in univariate regression models combining several into scalar index. This inhibits thorough analysis of the potentially varying interdependence between dimensions. We propose multivariate copula generalized...