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SOEP-LEE2
(2023)
This article presents the new linked employee-employer study of the Socio-Economic Panel (SOEP-LEE2), which offers new research opportunities for various academic fields. In particular, the study contains two waves of an employer survey for persons in dependent work that is also linkable to the SOEP, a large representative German annual household panel (SOEP-LEE2-Core). Moreover, SOEP-LEE2 includes two waves of self-employed surveys based on self-employed in the SOEP-Core (SOEP-LEE2-Self-employed) and three additional representative employer surveys, independent of the SOEP in terms of sampling employers (SOEP-LEE2-Compare). Survey topics include digitalisation and cybersecurity, human capital formation, COVID-19, and human resource management. Here, we describe the content, survey design, and comparability of the different datasets in the SOEP-LEE2 to potential users in different disciplines of research.
This study quantifies the distributional effects of the minimum wage introduced in Germany in 2015. Using detailed Socio-Economic Panel survey data, we assess changes in the hourly wages, working hours, and monthly wages of employees who were entitled to be paid the minimum wage. We employ a difference-in-differences analysis, exploiting regional variation in the “bite” of the minimum wage. At the bottom of the hourly wage distribution, we document wage growth of 9% in the short term and 21% in the medium term. At the same time, we find a reduction in working hours, such that the increase in hourly wages does not lead to a subortionate increase in monthly wages. We conclude that working hours adjustments play an important role in the distributional effects of minimum wages.
This paper evaluates the short-run impact of the introduction of a statutory minimum wage in Germany on the hourly wages and monthly earnings of workers targeted by the reform. We first provide detailed descriptive evidence of changes to the wage structure in particular at the bottom of the distribution and distinguish between trends for regularly employed and marginally employed workers. In the causal analysis, we then employ a differential trend adjusted difference-in-differences (DTADD) strategy to identify the extent to which these changes in wages and earnings can be attributed to the minimum wage introduction. We find that the minimum wage introduction can account for hourly wage growth in the order of roughly 6.5 % or (sic)0.45/hour and an increase in monthly earnings of 6.6 % or (sic)53/month. Despite finding wage growth at the bottom of the distribution, the paper documents widespread non-compliance with the mandated wage floor of (sic)8.50/hour.
In 2015, Germany introduced a statutory hourly minimum wage that was not only universally binding but also set at a relatively high level. We discuss the short-run effects of this new minimum wage on a wide set of socio-economic outcomes, such as employment and working hours, earnings and wage inequality, dependent and self-employment, as well as reservation wages and satisfaction. We also discuss difficulties in the implementation of the minimum wage and the measurement of its effects related to non-compliance and suitability of data sources. Two years after the minimum wage introduction, the following conclusions can be drawn: while hourly wages increased for low-wage earners, some small negative employment effects are also identifiable. The effects on aspired goals, such as poverty and inequality reduction, have not materialized in the short run. Instead, a tendency to reduce working hours is found, which alleviates the desired positive impact on monthly income. Additionally, the level of non-compliance was substantial in the short run, thus drawing attention to problems when implementing such a wide-reaching policy.
We assess the short-term employment effects of the introduction of a national statutory minimum wage in Germany in 2015. For this purpose, we exploit variation in the regional treatment intensity, assuming that the stronger a minimum wage ‘bites’ into the regional wage distribution, the stronger the regional labour market will be affected. In contrast to previous studies, we construct two regional bite indicators based upon detailed individual wage data from the Structure of Earnings Survey (SES) 2014 and combine it with administrative information on regional employment. Moreover, using the Socio-Economic Panel (SOEP), we are able to affirm the absence of anticipation effects and verify the assumption of a common trend in wages before the reform. In sum, we find only moderate negative effects on overall employment of about 140,000 (0.4%) jobs, which are mainly driven by a sharp decline of marginal employment (‘mini-jobs’), while we do not find pronounced significant effects for regular employment in most specifications. Our results are robust to a variety of sensitivity tests.
EXO modifies sucrose and trehalose responses and connects the extracellular carbon status to growth
(2013)
Plants have the capacity to adapt growth to changing environmental conditions. This implies the modulation of metabolism according to the availability of carbon (C). Particular interest in the response to the C availability is based on the increasing atmospheric levels of CO2. Several regulatory pathways that link the C status to growth have emerged. The extracellular EXO protein is essential for cell expansion and promotes shoot and root growth. Homologous proteins were identified in evolutionarily distant green plants. We show here that the EXO protein connects growth with C responses. The exo mutant displayed altered responses to exogenous sucrose supplemented to the growth medium. Impaired growth of the mutant in synthetic medium was associated with the accumulation of starch and anthocyanins, altered expression of sugar-responsive genes, and increased abscisic acid levels. Thus, EXO modulates several responses related to the C availability. Growth retardation on medium supplemented with 2-deoxy-glucose, mannose, and palatinose was similar to the wildtype. Trehalose feeding stimulated root growth and shoot biomass production of exoplants where as it inhibited growth of the wildtype. The phenotypic features of the exo mutant suggest that apoplastic processes coordinate growth and C responses.
Collinearity a review of methods to deal with it and a simulation study evaluating their performance
(2013)
Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the folk lore'-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.
Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.