arXiv subjects

Peter Pütz

Publications and source records attributed to Peter Pütz.

3 recordsLinked to original sources

arXiv2022

A Proposed Hybrid Effect Size Plus $p$-Value Criterion: A Comment on Goodman et al. (2019)

In a recent simulation study, Goodman et al. (2019) compare several methods with regard to their type I and type II error rates in case of a thick null hypothesis that includes all values that are practically equivalent to the point null hypothesis. They propose a hybrid decision criterion only declaring a result "significant" if both a small $p$-value and a sufficiently large effect size are obtained. We successfully verify the results using our own software code in R and discuss an additional decision method that is tailored to maintain a pre-defined false positive rate. We confirm that the hybrid decision criterion has comparably low error rates in settings one can check for but point out that the false discovery rate cannot be easily controlled by the researcher. Our analyses are readily accessible and customizable on https://github.com/drehero/goodman-replication.

stat.ME↗

arXiv2019

Treatment effects beyond the mean using GAMLSS

This paper introduces distributional regression, also known as generalized additive models for location, scale and shape (GAMLSS), as a modeling framework for analyzing treatment effects beyond the mean. By relating each parameter of the response distribution to explanatory variables, GAMLSS model the treatment effect on the whole conditional distribution. Additionally, any nonnormal outcome and nonlinear effects of explanatory variables can be incorporated. We elaborate on the combination of GAMLSS with program evaluation methods in economics and provide practical guidance on the usage of GAMLSS by reanalyzing data from the Mexican \textit{Progresa} program. Contrary to expectations, no significant effects of a cash transfer on the conditional inequality level between treatment and control group are found.

stat.AP↗

arXiv2016

Do Mature Economies Grow Exponentially?

Most models that try to explain economic growth indicate exponential growth paths. In recent years, however, a lively discussion has emerged considering the validity of this notion. In the empirical literature dealing with drivers of economic growth, the majority of articles is based upon an implicit assumption of exponential growth. Few scholarly articles have addressed this issue so far. In order to shed light on this issue, we estimate autoregressive integrated moving average time series models based on Gross Domestic Product Per Capita data for 18 mature economies from 1960 to 2013. We compare the adequacy of linear and exponential growth models and conduct several robustness checks. Our fndings cast doubts on the widespread belief of exponential growth and suggest a deeper discussion on alternative economic grow theories.

econ.GN↗