Didn’t Plan One but got One: Unintended and sooner-than-intended Parents in the East and the West of Europe

European Journal of Population - The realisation rates of short-term childbearing intentions are known to be consistently lower in post-socialist countries than in the rest of Europe. However, the...     

Reflective Photobooth – a way to visualise,and challenge perceptions and representations of distanced social groups

Taken-for-granted knowledge about people from other social groups is a key challenge for overcoming stereotypes. This article describes a novel arts-based research method to visualise participants’ frames of distanced social groups and aims to trigger reflections among them. The Reflective Photobooth invites participants to dress up as members of distanced social groups, stage a scene, produce pictures, answer prompting questions, and discuss their visualisations. We argue that the artistic re-enactment that underlies the visualisation process can attract diverse groups of participants to engage with research topics, create places for the articulation of critical statements against existing societal clichés and stereotypical media representations, and trigger reflections among participants about taken-for-granted knowledge. The method was tested within the Frame-a-Farmer project, in which the social distance between consumers and food producers in modern agrifood systems was addressed. Results indicate that despite the method bearing some risks and facing some challenges, three promising areas of future application could be identified: (i) raising awareness among large groups of people, (ii) collecting stories or topical vignettes, and (iii) deconstructing taken-for-granted knowledge and societal clichés.     

The effect of accounting standards on Big Bath behavior

This paper investigates the influence of accounting standards on systematic earnings understatement. To isolate the effect of reporting regulations from those of other institutional drivers of earnings management, Holthausen (2003) proposes analyzing reporting practices in a country undergoing a transition in accounting standards. We respond to this call by analyzing earnings management practices of large German-listed companies before and after their transitions from German GAAP to IFRS. Specifically, we focus on Big Bath behavior following Chief Financial Officer turnovers between 1999 and 2006. Our findings provide evidence of the effect of accounting standards on the existence of this particular earnings understatement pattern. However, while we detect Big Bath behavior for our sample of German GAAP firms, we find no such indication for those firms reporting under IFRS. Controlling for alternative explanations such as self-selection bias does not change our findings. We conclude that accounting standards seem to have a considerable influence on earnings management behavior, independent of managers’ and auditors’ incentives.     

Quantifying Economic Dependency

In this paper we compare several types of economic dependency ratios for a selection of European countries. These dependency ratios take into account not only the demographic structure of the population, but also the differences in age-specific economic behaviour such as labour market activity, income and consumption as well as age-specific public transfers. In selected simulations where we combine patterns of age-specific economic behaviour and transfers with population projections, we show that in all countries population ageing would lead to a pronounced increase in dependency ratios if present age-specific patterns were not to change. Our analysis of cross-country differences in economic dependency demonstrates that these differences are driven by both differences in age-specific economic behaviour and in the age composition of the populations. The choice of which dependency ratio to use in a specific policy context is determined by the nature of the question to be answered. The comparison of our various dependency ratios across countries gives insights into which strategies might be effective in mitigating the expected increase in economic dependency due to demographic change.     

Analysis of Deviance for Hypothesis Testing in Generalized Partially Linear Models

In this study, we develop nonparametric analysis of deviance tools for generalized partially linear models based on local polynomial fitting. Assuming a canonical link, we propose expressions for both local and global analysis of deviance, which admit an additivity property that reduces to analysis of variance decompositions in the Gaussian case. Chi-square tests based on integrated likelihood functions are proposed to formally test whether the nonparametric term is significant. Simulation results are shown to illustrate the proposed chi-square tests and to compare them with an existing procedure based on penalized splines. The methodology is applied to German Bundesbank Federal Reserve data.     

Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form

In this article, we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests by a Monte Carlo experiment and compare these to the most widely used linear test. Our tests appear to be well-sized and have reasonably good power properties.     

Using Panel Data to Understand the Dynamics of Human Behavior in Response to Flooding

Insights into the dynamics of human behavior in response to flooding are urgently needed for the development of effective integrated flood risk management strategies, and for integrating human behavior in flood risk modeling. However, our understanding of the dynamics of risk perceptions, attitudes, individual recovery processes, as well as adaptive (i.e., risk reducing) intention and behavior are currently limited because of the predominant use of cross-sectional surveys in the flood risk domain. Here, we present the results from one of the first panel surveys in the flood risk domain covering a relatively long period of time (i.e., four years after a damaging event), three survey waves, and a wide range of topics relevant to the role of citizens in integrated flood risk management. The panel data, consisting of 227 individuals affected by the 2013 flood in Germany, were analyzed using repeated-measures ANOVA and latent class growth analysis (LCGA) to utilize the unique temporal dimension of the data set. Results show that attitudes, such as the respondents’ perceived responsibility within flood risk management, remain fairly stable over time. Changes are observed partly for risk perceptions and mainly for individual recovery and intentions to undertake risk-reducing measures. LCGA reveal heterogeneous recovery and adaptation trajectories that need to be taken into account in policies supporting individual recovery and stimulating societal preparedness. More panel studies in the flood risk domain are needed to gain better insights into the dynamics of individual recovery, risk-reducing behavior, and associated risk and protective factors.     

Multiple hypothesis tests based On conditional differences in means

Many hypothesis tests are univariate tests and cannot cope with multiple hypothesis without an auxiliary procedure as e. g. the Bonferroni-Holm-procedure. At the same time, there is an urgent need for testing multiple hypothesis due to the very simple existing methods as the Bonferroni-correction or the Bonferroni-Holm-procedure, which suffers from a very small local significance level to detect statistical inferences or the drawback that logical and statistical dependencies among the test statistics are not used, whereby its detection is NP-hard. In honour of this occasion, we present a multiple hypothesis test for i.i.d. random variables based on conditional differences in means, which is capable to cope with multiple hypothesis and does not suffer on such drawbacks as the Bonferroni-correction or the Bonferroni-Holm-procedure. Thereby, the computation time can be neglected.     

Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective

Statistics and Computing - We formulate probabilistic numerical approximations to solutions of ordinary differential equations (ODEs) as problems in Gaussian process (GP) regression with nonlinear...