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While a growing body of literature finds positive impacts of Start-Up Subsidies (SUS) on labor market outcomes of participants, little is known about how the design of these programs shapes their effectiveness and hence how to improve policy. As experimental variation in program design is unavailable, we exploit the 2011 reform of the current German SUS program for the unemployed which strengthened case-workers’ discretionary power, increased entry requirements and reduced monetary support. We estimate the impact of the reform on the program’s effectiveness using samples of participants and non-participants from before and after the reform. To control for time-constant unobserved heterogeneity as well as differential selection patterns based on observable characteristics over time, we combine Difference-in-Differences with inverse probability weighting using covariate balancing propensity scores. Holding participants’ observed characteristics as well as macroeconomic conditions constant, the results suggest that the reform was successful in raising employment effects on average. As these findings may be contaminated by changes in selection patterns based on unobserved characteristics, we assess our results using simulation-based sensitivity analyses and find that our estimates are highly robust to changes in unobserved characteristics. Hence, the reform most likely had a positive impact on the effectiveness of the program, suggesting that increasing entry requirements and reducing support in-creased the program’s impacts while reducing the cost per participant.
The large literature that aims to find evidence of climate migration delivers mixed findings. This meta-regression analysis i) summarizes direct links between adverse climatic events and migration, ii) maps patterns of climate migration, and iii) explains the variation in outcomes. Using a set of limited dependent variable models, we meta-analyze thus-far the most comprehensive sample of 3,625 estimates from 116 original studies and produce novel insights on climate migration. We find that extremely high temperatures and drying conditions increase migration. We do not find a significant effect of sudden-onset events. Climate migration is most likely to emerge due to contemporaneous events, to originate in rural areas and to take place in middle-income countries, internally, to cities. The likelihood to become trapped in affected areas is higher for women and in low-income countries, particularly in Africa. We uniquely quantify how pitfalls typical for the broader empirical climate impact literature affect climate migration findings. We also find evidence of different publication biases.
We develop a model of optimal carbon taxation and redistribution taking into account horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon taxes, transfers and energy subsidies, we then investigate analytically how horizontal equity is considered in the social welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal. Our results show that energy-intensive households should receive more redistributive resources than energy-efficient households if and only if social inequality aversion is sufficiently high. We further find that redistribution of carbon tax revenue via household-specific transfers is the first-best policy. Equal per-capita transfers do not suffer from informational problems, but increase mitigation costs by around 15 percent compared to the first- best for unity inequality aversion. Adding renewable energy subsidies or non-linear energy subsidies, reduces mitigation costs further without relying on observability of households’ energy efficiency.
Little is known about the conscious experience of internal bodily sensations in preschool-aged children. Given that preschoolers are in the most rapid phase of brain development, and display profound emotional development, it was the aim of the present study to establish an adapted interoceptive accuracy paradigm and to investigate associations between sociodemographic (age, sex) and emotional variables with interoceptive accuracy. Forty-nine children (aged 4–6 years) completed the jumping jack paradigm (JJP), a heartbeat tracking paradigm, which includes a noninvasive physical perturbation via performing jumping jacks for 10 s. An interoceptive accuracy score was based on the comparison between self-reported and objectively recorded heart rate prior to and after completion of jumping jacks. Children also completed validated measures for emotion recognition and emotion regulation. Children's objectively recorded heart rate significantly increased after the JJP by 20 bpm on average. There was a positive relationship between reactivity on self-reported heart rate and objectively recorded heart rate increase. The derived scores for interoceptive accuracy increased with age, suggesting older children to report more self-reported heart rate change than objectively recorded, but were unrelated to children's sex or BMI. While emotion recognition and regulation significantly increased with age, the interoceptive accuracy score was unrelated to emotion recognition, but marginally associated to emotion regulation. Children with higher interoceptive accuracy score (i.e., self-reporting more heart rate change than objectively recorded) received lower emotion regulation score. The present study is the first to depict a novel behavioral paradigm to assess interoceptive accuracy in preschool-aged children.
We investigate how the economic consequences of the pandemic, and of the government-mandated measures to contain its spread, affect the self-employed – particularly women – in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. Conversely, we do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, i.e. the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
In this paper, we study the effect of exogenous global crop price changes on migration from agricultural and non-agricultural households in Sub-Saharan Africa. We show that, similar to the effect of positive local weather shocks, the effect of a locally-relevant global crop price increase on household out-migration depends on the initial household wealth. Higher international producer prices relax the budget constraint of poor agricultural households and facilitate migration. The order of magnitude of a standardized price effect is approx. one third of the standardized effect of a local weather shock. Unlike positive weather shocks, which mostly facilitate internal rural-urban migration, positive income shocks through rising producer prices only increase migration to neighboring African countries, likely due to the simultaneous decrease in real income in nearby urban areas. Finally, we show that while higher producer prices induce conflict, conflict does not play a role for the household decision to send a member as a labor migrant.
We take an error management perspective on audit quality. Drawing on 18 months of participant observations and 38 interviews conducted in a Big 4 accounting firm, we develop a multi-level model of error management. With this model, we propose how organizational structures, team procedures and practices, and individual cognitions and emotions interact to manage errors. The multi-level model of error management allows us to conceptually integrate previous behavioral and social research on audit quality, contributes to the rising accounting firm error management literature, and explains how and why two general approaches from the broader error management literature to errors that are usually considered as opposing each other, i.e., error prevention and error resilience, may interact and actually entail each other in accounting firms.
This paper presents an experiment on the effect of retroactive price-reduction schemes on buyers’ repeated purchase decisions. Such schemes promise buyers a reduced price for all units that are bought in a certain time frame if the total quantity that is purchased passes a given threshold. This study finds a loyalty-enhancing effect of retroactive price-reduction schemes only if the buyers ex-ante expected that entering into the scheme would maximize their monetary gain, but later learn that they should leave the scheme. Furthermore, the effect crucially hinges on the framing of the price reduction.
The human personality predicts a wide range of activities and occupational choices-from musical sophistication to entrepreneurial careers. However, which method should be applied if information on personality traits is used for prediction and advice? In psychological research, group profiles are widely employed. In this contribution, we examine the performance of profiles using the example of career prediction and advice, involving a comparison of average trait scores of successful entrepreneurs with the traits of potential entrepreneurs. Based on a simple theoretical model estimated with GSOEP data and analyzed with Monte Carlo methods, we show, for the first time, that the choice of the comparison method matters substantially. We reveal that under certain conditions the performance of average profiles is inferior to the tossing of a coin. Alternative methods, such as directly estimating success probabilities, deliver better performance and are more robust.