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This thesis comprises of four research papers on the economics of education and industrial relations, which contribute to the field of empirical economic research. All of the corresponding papers focus on analysing how much time individuals spend on specific activities. The allocation of available time resources is a decision that individuals make throughout their lifetime. In this thesis, we consider individuals at different stages of their lives - students at school, university students, and dependent employees at the workplace.
Part I includes two research studies on student's behaviour in secondary and tertiary education.
Chapter 2 explores whether students who are relatively younger or older within the school year exhibit differential time allocation. Building on previous findings showing that relatively younger students perform worse in school, the study shows that relatively younger students are aware of their poor performance in school and feel more strain as a result. Nevertheless, there are no clear differences to be found in terms of time spent on homework, while relatively younger students spend more time watching television and less time on sports activities. Thus, the results suggest that the lower learning outcomes are not associated with different time allocations between school-related activities and non-school-related activities.
Chapter 3 analyses how individual ability and labour market prospects affect study behaviour. The theoretical modelling predicts that both determinants increase study effort. The empirical investigation is based on cross-sectional data from the National Educational Panel Study (NEPS) and includes thousands of students in Germany. The analyses show that more gifted students exhibit lower subjective effort levels and invest less time in self-study. In contrast, very good labour market prospects lead to more effort exerted by the student, both qualitatively and quantitatively. The potential endogeneity problem is taken into account by using regional unemployment data as an instrumental variable.
Part II includes two labour economic studies on determinants of overtime. Both studies belong to the field of industrial relations, as they focus on union membership on the one hand and the interplay of works councils and collective bargaining coverage on the other.
Chapter 4 shows that union members work less overtime than non-members do. The econometric approach takes the problem of unobserved heterogeneity into account; but provides no evidence that this issue affects the results. Different channels that could lead to this relationship are analysed by examining relevant subgroups separately. For example, this effect of union membership can also be observed in establishments with works councils and for workers who are very likely to be covered by collective bargaining agreements. The study concludes that the observed effect is due to the fact that union membership can protect workers from corresponding increased working time demands by employers.
Chapter 5 builds on previous studies showing a negative effect of works councils on overtime. In addition to co-determination by works councils at the firm level, collective bargaining coverage is an important factor in the German industrial relations system. Corresponding data was not available in the SOEP for quite some time. Therefore, the study uses recent SOEP data, which also contains information on collective bargaining coverage. A cross-sectional analysis is conducted to examine the effects of works councils in establishments with and without collective bargaining coverage. Similar to studies analysing other outcome variables, the results show that the effect of works councils exists only for employees covered by a collective bargaining agreement.
A phenomenon of recent decades is that digital marketplaces on the Internet are establishing themselves for a wide variety of products and services. Recently, it has become possible for private individuals to invest in young and innovative companies (so-called "start-ups"). Via Internet portals, potential investors can examine various start-ups and then directly invest in their chosen start-up. In return, investors receive a share in the firm- profit, while companies can use the raised capital to finance their projects. This new way of financing is called "Equity Crowdfunding" (ECF) or "Crowdinvesting". The aim of this dissertation is to provide empirical findings about the characteristics of ECF. In particular, the question of whether ECF is able to overcome geographic barriers, the interdependence of ECF and capital structure, and the risk of failure for funded start-ups and their chances of receiving follow-up funding by venture capitalists or business angels will be analyzed. The results of the first part of this dissertation show that investors in ECF prefer local companies. In particular, investors who invest larger amounts have a stronger tendency to invest in local start-ups. The second part of the dissertation provides first indications of the interdependencies between capital structure and ECF. The analysis makes clear that the capital structure is not a determinant for undertaking an ECF campaign. The third part of the dissertation analyzes the success of companies financed by ECF in a country comparison. The results show that after a successful ECF campaign German companies have a higher chance of receiving follow-up funding by venture capitalists compared to British companies. The probability of survival, however, is slightly lower for German companies. The results provide relevant implications for theory and practice. The existing literature in the area of entrepreneurial finance will be extended by insights into investor behavior, additions to the capital structure theory and a country comparison in ECF. In addition, implications are provided for various actors in practice.
The search for relevant determinants of knowledge acquisition has a long tradition in educational research, with systematic analyses having started over a century ago. To date, a variety of relevant environmental and learner-related characteristics have been identified, providing a wide body of empirical evidence. However, there are still some gaps in the literature, which are highlighted in the current dissertation. The dissertation includes two meta-analyses summarizing the evidence on the effectiveness of electrical brain stimulation and the effects of prior knowledge on later learning outcomes and one empirical study employing latent profile transition analysis to investigate the changes in conceptual knowledge over time. The results from the three studies demonstrate how learning outcomes can be advanced by input from the environment and that they are highly related to the students" level of prior knowledge. It is concluded that the effects of environmental and learner-related variables impact both the biological and cognitive processes underlying knowledge acquisition. Based on the findings from the three studies, methodological and practical implications are provided, followed by an outline of four recommendations for future research on knowledge acquisition.
While women's evolving contribution to entrepreneurship is irrefutable, in almost all nations, gender disparity is an existing reality of entrepreneurship. Social and economic outcomes make women entrepreneurship an important area for scholars and governments. In attempts to find reasons for this gender disparity, academic scholars evaluated various factors and recognised perceptual variables as having outstanding explanatory value in understanding women's entrepreneurship. To advance our knowledge of gender disparity in entrepreneurship, the present study explores the influence of entrepreneurial perceptual variables on women's entrepreneurship and considers the critical role of country-level institutional contexts on the women's entrepreneurial propensity. Therefore, this study examines the impact of perceptual variables in different nations. It also offers connections between entrepreneurial perceptions, women entrepreneurship, and institutional contexts as a critical topic for future studies.
Drawing on the importance of perceptual factors, this dissertation investigates whether and how their perception of entrepreneurial networks influences the individuals' decision to initiate a new venture. Prior scholars considered exposure to entrepreneurial role models as one of the most influential factors on the women's inclination towards entrepreneurship; thus, a systemized analysis makes it possible to identify existing research gaps related to this perception. Hence, to draw a clear picture of the relationship between entrepreneurial role models and entrepreneurship, this dissertation provides a systemized overview of prior studies. Subsequently, Chapter 2 structures the existing literature on entrepreneurial role models and reveals that past literature has focused on the different types of role models, the stage of life at which the exposure to role models occurs, and the context of the exposure. Current discourse argues that the women's lower access to entrepreneurial role models negatively influences their inclination towards entrepreneurship.
Additionally, although the research on women entrepreneurship has proliferated in recent years, little is known about how entrepreneurial perceptual variables form women's propensity towards entrepreneurship in various institutional contexts. The work of Koellinger et al. (2013), hereafter KMS, is one of the most influential papers that investigated the influence of perceptual variables, and it showed that a lower rate of women entrepreneurship is associated with a lower level of their entrepreneurial network, perceived entrepreneurial capability, and opportunity evaluation and with a higher fear of entrepreneurial failure. Thus, this dissertation replicates the work of KMS. Chapter 3 explicitly investigates the influence of the above perceptions on women's entrepreneurial propensity. This research has drawn data from the Global Entrepreneurship Monitor, a cross-national individual-level data set (2001-2006) covering 236,556 individuals across 17 countries. The results of this chapter suggest that gender disparities in entrepreneurial propensity are conditioned by differences in entrepreneurial perceptual variables. Women's lower levels of perceived entrepreneurial capability, entrepreneurial role models and opportunity evaluation and their higher fear of failure lead to lower entrepreneurial propensity.
To extend and generalise the relationship between perceptions and women's entrepreneurial propensity, in Chapter 4, two studies are conducted based on replicated research. Extension 1 generalises the results of KMS by using the same analysis on more recent data. Accordingly, this research implemented the same analysis on 372,069 individuals across the same countries (2011-2016). The recent data show that although gender disparity became significantly weaker, the gender gap is still in men's favour. However, similarly to the replicated study, this research revealed that perceptual factors explain a larger part of the gender disparity. To strengthen prior empirical evidence, in extension 2, utilising a sample of 1,029,863 individuals from 71 countries (2011-2016), the study conducted the same measures and analysis in a more global setting. By including developing countries, gender disparity in entrepreneurial propensity decreased significantly. The study revealed that the relative significance of the influences of perceptions' differs significantly across nations; however, perceptions have a worldwide effect. Moreover, this research found that the ratio of nascent women entrepreneurs in less developed countries to those in more developed nations is 2. More precisely, a higher level of economic development negatively influences the impact of perceptions on women's entrepreneurial propensity.
Whereas prior scholars increasingly underlined the importance of perceptions in explaining a large part of gender disparities in entrepreneurship, most of the prior investigations focused on nascent (early-stage) entrepreneurship, and evidence on the relationship between perceptions and other types of self-employment, such as innovative entrepreneurship, is scant. Innovation is a confirmed key driver of a firm's sustainability, higher competitive capability, and growth. Therefore, Chapter 5 investigates the influence of perceptions on women's innovative entrepreneurship. The chapter points out that entrepreneurial perceptions are the main determinants of the women's decision to offer a new product or service. This chapter also finds that women's innovative entrepreneurship is associated with the country's specific economic setting.
Overall, by underlining the critical role of institutional contexts, this dissertation provides considerable insights into the interaction between perceptions and women entrepreneurship, and its results have implications for policymakers and practitioners, who may find it helpful to consider women entrepreneurship in systemized challenges. Formal and informal barriers affect women's entrepreneurial perceptions and can differ from one country to the other. In this sense, it is crucial to design operational plans to mitigate formal and stereotypical challenges, and thus, more women will be able to start a business, particularly in developing countries in which women significantly comprise a smaller portion of the labour markets. This type of policy could write the "rules of the game" such that these rules enhance the women's propensity towards entrepreneurship.
This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.
Globalization and the emergence of global value chains have not only changed the way we live, but also the way economists study international economics. These changes are visible in various areas and dimension. This dissertation deals " mostly empirically " with some of these issues related to global value chains. It starts by critically examining the political economy forces determining the occurrence and the extent of trade liberalization conditions in World Bank lending agreements. The focal point is whether these are affected by the World Bank- most influential member countries. Afterwards, the thesis moves on to describe trade of the European Union member countries at each stage of the value chain. The description is based on a new classification of goods into parts, components and final products as well as a newly developed measure describing the average level of development of a countries trading partners. This descriptive exercise is followed by critically examining discrepancies between gross trade and trade in value added with respect to comparative advantage. A gravity model is employed to contrast results when studying the institutional determinants of comparative advantage. Finally, the thesis deals with determinants of regional location choices for foreign direct investment. The analysis is based on a theoretical new economic geography model and employs a newly developed index that accounts for the presence of potentially all suppliers and buyers at all stages of the value chain.
Shape optimization is of interest in many fields of application. In particular, shape optimization problems arise frequently in technological processes which are modelled by partial differential equations (PDEs). In a lot of practical circumstances, the shape under investigation is parametrized by a finite number of parameters, which, on the one hand, allows the application of standard optimization approaches, but, on the other hand, unnecessarily limits the space of reachable shapes. Shape calculus presents a way to circumvent this dilemma. However, so far shape optimization based on shape calculus is mainly performed using gradient descent methods. One reason for this is the lack of symmetry of second order shape derivatives or shape Hessians. A major difference between shape optimization and the standard PDE constrained optimization framework is the lack of a linear space structure on shape spaces. If one cannot use a linear space structure, then the next best structure is a Riemannian manifold structure, in which one works with Riemannian shape Hessians. They possess the often sought property of symmetry, characterize well-posedness of optimization problems and define sufficient optimality conditions. In general, shape Hessians are used to accelerate gradient-based shape optimization methods. This thesis deals with shape optimization problems constrained by PDEs and embeds these problems in the framework of optimization on Riemannian manifolds to provide efficient techniques for PDE constrained shape optimization problems on shape spaces. A Lagrange-Newton and a quasi-Newton technique in shape spaces for PDE constrained shape optimization problems are formulated. These techniques are based on the Hadamard-form of shape derivatives, i.e., on the form of integrals over the surface of the shape under investigation. It is often a very tedious, not to say painful, process to derive such surface expressions. Along the way, volume formulations in the form of integrals over the entire domain appear as an intermediate step. This thesis couples volume integral formulations of shape derivatives with optimization strategies on shape spaces in order to establish efficient shape algorithms reducing analytical effort and programming work. In this context, a novel shape space is proposed.
Large scale non-parametric applied shape optimization for computational fluid dynamics is considered. Treating a shape optimization problem as a standard optimal control problem by means of a parameterization, the Lagrangian usually requires knowledge of the partial derivative of the shape parameterization and deformation chain with respect to input parameters. For a variety of reasons, this mesh sensitivity Jacobian is usually quite problematic. For a sufficiently smooth boundary, the Hadamard theorem provides a gradient expression that exists on the surface alone, completely bypassing the mesh sensitivity Jacobian. Building upon this, the gradient computation becomes independent of the number of design parameters and all surface mesh nodes are used as design unknown in this work, effectively allowing a free morphing of shapes during optimization. Contrary to a parameterized shape optimization problem, where a smooth surface is usually created independently of the input parameters by construction, regularity is not preserved automatically in the non-parametric case. As part of this work, the shape Hessian is used in an approximative Newton method, also known as Sobolev method or gradient smoothing, to ensure a certain regularity of the updates, and thus a smooth shape is preserved while at the same time the one-shot optimization method is also accelerated considerably. For PDE constrained shape optimization, the Hessian usually is a pseudo-differential operator. Fourier analysis is used to identify the operator symbol both analytically and discretely. Preconditioning the one-shot optimization by an appropriate Hessian symbol is shown to greatly accelerate the optimization. As the correct discretization of the Hadamard form usually requires evaluating certain surface quantities such as tangential divergence and curvature, special attention is also given to discrete differential geometry on triangulated surfaces for evaluating shape gradients and Hessians. The Hadamard formula and Hessian approximations are applied to a variety of flow situations. In addition to shape optimization of internal and external flows, major focus lies on aerodynamic design such as optimizing two dimensional airfoils and three dimensional wings. Shock waves form when the local speed of sound is reached, and the gradient must be evaluated correctly at discontinuous states. To ensure proper shock resolution, an adaptive multi-level optimization of the Onera M6 wing is conducted using more than 36, 000 shape unknowns on a standard office workstation, demonstrating the applicability of the shape-one-shot method to industry size problems.
In this thesis, global surrogate models for responses of expensive simulations are investigated. Computational fluid dynamics (CFD) have become an indispensable tool in the aircraft industry. But simulations of realistic aircraft configurations remain challenging and computationally expensive despite the sustained advances in computing power. With the demand for numerous simulations to describe the behavior of an output quantity over a design space, the need for surrogate models arises. They are easy to evaluate and approximate quantities of interest of a computer code. Only a few number of evaluations of the simulation are stored for determining the behavior of the response over a whole range of the input parameter domain. The Kriging method is capable of interpolating highly nonlinear, deterministic functions based on scattered datasets. Using correlation functions, distinct sensitivities of the response with respect to the input parameters can be considered automatically. Kriging can be extended to incorporate not only evaluations of the simulation, but also gradient information, which is called gradient-enhanced Kriging. Adaptive sampling strategies can generate more efficient surrogate models. Contrary to traditional one-stage approaches, the surrogate model is built step-by-step. In every stage of an adaptive process, the current surrogate is assessed in order to determine new sample locations, where the response is evaluated and the new samples are added to the existing set of samples. In this way, the sampling strategy learns about the behavior of the response and a problem-specific design is generated. Critical regions of the input parameter space are identified automatically and sampled more densely for reproducing the response's behavior correctly. The number of required expensive simulations is decreased considerably. All these approaches treat the response itself more or less as an unknown output of a black-box. A new approach is motivated by the assumption that for a predefined problem class, the behavior of the response is not arbitrary, but rather related to other instances of the mutual problem class. In CFD, for example, responses of aerodynamic coefficients share structural similarities for different airfoil geometries. The goal is to identify the similarities in a database of responses via principal component analysis and to use them for a generic surrogate model. Characteristic structures of the problem class can be used for increasing the approximation quality in new test cases. Traditional approaches still require a large number of response evaluations, in order to achieve a globally high approximation quality. Validating the generic surrogate model for industrial relevant test cases shows that they generate efficient surrogates, which are more accurate than common interpolations. Thus practical, i.e. affordable surrogates are possible already for moderate sample sizes. So far, interpolation problems were regarded as separate problems. The new approach uses the structural similarities of a mutual problem class innovatively for surrogate modeling. Concepts from response surface methods, variable-fidelity modeling, design of experiments, image registration and statistical shape analysis are connected in an interdisciplinary way. Generic surrogate modeling is not restricted to aerodynamic simulation. It can be applied, whenever expensive simulations can be assigned to a larger problem class, in which structural similarities are expected.
Stress and pain are common experiences in human lives. Both, the stress and the pain system have adaptive functions and try to protect the organism in case of harm and danger. However, stress and pain are two of the most challenging problems for the society and the health system. Chronic stress, as often seen in modern societies, has much impact on health and can lead to chronic stress disorders. These disorders also include a number of chronic pain syndromes. However, pain can also be regarded as a stressor itself, especially when we consider how much patients suffer from long-lasting pain and the impact of pain on life quality. In this way, the effects of stress on pain can be fostered. For the generation and manifestation of chronic pain symptoms also learning processes such as classical conditioning play an important role. Processes of classical conditioning can also be influenced by stress. These facts illustrate the complex and various interactions between the pain and the stress systems. Both systems communicate permanently with each other and help to protect the organism and to keep a homeostatic state. They have various ways of communication, for example mechanisms related to endogenous opioids, immune parameters, glucocorticoids and baroreflexes. But an overactivation of the systems, for example caused by ongoing stress, can lead to severe health problems. Therefore, it is of great importance to understand these interactions and their underlying mechanisms. The present work deals with the relationship of stress and pain. A special focus is put on stress related hypocortisolism and pain processing, stress induced hypoalgesia via baroreceptor related mechanisms and stress related cortisol effects on aversive conditioning (as a model of pain learning). This work is a contribution to the wide field of research that tries to understand the complex interactions of stress and pain. To demonstrate the variety, the selected studies highlight different aspects of these interactions. In the first chapter I will give a short introduction on the pain and the stress systems and their ways of interaction. Furthermore, I will give a short summary of the studies presented in Chapter II to V and their background. The results and their meaning for future research will be discussed in the last part of the first chapter. Chronic pain syndromes have been associated with chronic stress and alterations of the HPA axis resulting in chronic hypocortisolism. But if these alterations may play a causal role in the pathophysiology of chronic pain remains unclear. Thus, the study described in Chapter II investigated the effects of pharmacological induced hypocortisolism on pain perception. Both, the stress and the pain system are related to the cardiovascular system. Increase of blood pressure is part of the stress reaction and leads to reduced pain perception. Therefore, it is important for the usage of pain tests to keep in mind potential interferences from activation of the cardiovascular system, especially when pain inhibitory processes are investigated. For this reason we compared two commonly and interchangeably used pain tests with regard to the triggered autonomic reactions. This study is described in chapter III. Chapter IV and V deal with the role of learning processes in pain and related influences of stress. Processes of classical conditioning play an important role for symptom generation and manifestation. In both studies aversive eyeblink conditioning was used as a model for pain learning. In the study described in Chapter IV we compared classical eyeblink conditioning in healthy volunteers to patients suffering from fibromyalgia, a chronic pain disorder. Also, differences of the HPA axis, as part of the stress system, were taken in account. The study of Chapter V investigated effects of the very first stress reaction, particularly rapid non-genomic cortisol effects. Healthy volunteers received an intravenous cortisol administration immediately before the eyeblink conditioning. Rapid effects have only been demonstrated on a cellular level and on animal behavior so far. In general, the studies presented in this work may give an impression of the broad variety of possible interactions between the pain and the stress system. Furthermore, they contribute to our knowledge about theses interactions. However, more research is needed to complete the picture.