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This dissertation focuses on the link between labour market institutions and precautionary savings. It is evaluated whether private households react to changes in social insurance provision such as the income replacement in case of unemployment by increased savings for precautionary reasons. The dissertation consists of three self-contained chapters, each focusing on slightly different aspects of the topic. The first chapter titled "Precautionary saving and the (in)stability of subjective earnings uncertainty" empirically looks at the influence of future income uncertainty on household saving behavior. Numerous cross-section studies on precautionary saving use subjective expectations regarding the income variance one year ahead as a proxy for income uncertainty. Using such proxies observed only at one point in time, however, may give rise to biased estimates for precautionary wealth if expectations are not stable over time. Survey data from the Dutch DNB Household Survey suggest that subjective future income distributions are not stable over the mid-term. Moreover, in this study I contrast estimates of precautionary wealth using the variation coefficient observed at one point in time with those using a simple mid-term average. Estimates of precautionary wealth based on the average are about 40% to 80% higher than the estimates using the variation coefficient observed only once. In addition to that, wealth accumulation for precautionary reasons is estimated for different parts of the income distribution. The share of precautionary wealth is highest for households at the center of the income distribution. By linking saving behaviour with unemployment insurance, the following chapters then shed some light on an issue that has largely been neglected in the literature on labour market institutions so far. Whereas the third chapter models the relevance of unemployment insurance for income uncertainty and intertemporal decision making during institutional reform processes, chapter 4 seeks to establish empirically a relationship between saving behavior and unemployment insurance. Social insurance, especially unemployment insurance, provides agents with income insurance against not marketable income risks. Since the early 1990s, reform measures like more activating policies as suggested by the OECD Jobs Study in 1994 have been observed in Europe. In the third chapter it is argued that such changes in unemployment insurance reduce public insurance and increase income uncertainty. Moreover, a simple three period model is discussed which shows a link between a welfare state reform and agents' saving decisions as one possible reaction of agents to self-insure against income risk. Two sources of uncertainty seem to be important in this context: (1) uncertain results of the reform process concerning the replacement rate, and (2) uncertainty regarding the timing of information about the content of the reform. It can be shown that the precautionary motive for saving explains an increased accumulation of capital in times of reform activities. In addition to that, early information about the expected replacement rate increases agents' utility and reduces under and oversaving. Following the argument of the previous chapters, that an important feature of labour market institutions in modern welfare states is to provide cash transfers as income replacement in case of unemployment, it is hypothesised that unemployment benefits reduce the motive to save for precautionary reasons. Based on consumer sentiment data from the European Commission's Consumer Survey, chapter four finally provides some evidence that aggregate saving intentions are significantly influenced by unemployment benefits. It can be shown that higher benefits lower the intention to save.
This thesis deals with economic aspects of employees' sickness. In addition to the classical case of sickness absence, in which an employee is completely unable to work and hence stays at home, there is the case of sickness presenteeism, in which the employee comes to work despite being sick. Accordingly, the thesis at hand covers research on both sickness states, absence and presenteeism. The first section covers sickness absence and labour market institutions. Chapter 2 presents theoretical and empirical evidence that differences in the social norm against benefit fraud, so-called benefit morale, can explain cross country diversity in the generosity of statutory sick pay entitlements between developed countries. In our political economy model, a stricter benefit morale reduces the absence rate, with counteracting effects on the politically set sick pay replacement rate. On the one hand, less absence caused by a stricter norm, makes the tax-financed insurance cheaper, leading to the usual demand side effect and hence to more generous sick pay entitlements. On the other hand, being less likely to be absent due to a stricter norm, the voters prefer a smaller fee over more insurance. We document both effects in a sample of 31 developed countries, capturing the years from 1981 to 2010. In Chapter 3 we investigate the relationship between the existence of works councils and illness-related absence and its consequences for plants. Using individual data from the German Socio-Economic Panel (SOEP), we find that the existence of a works council is positively correlated with the incidence and the annual duration of absence. Additionally, linked employer-employee data (LIAB) suggests that employers are more likely to expect personnel problems due to absence in plants with a works council. In western Germany, we find significant effects using a difference-in-differences approach, which can be causally interpreted. The second part of this thesis covers two studies on sickness presenteeism. In Chapter 4, we empirically investigate the determinants of the annual duration of sickness presenteeism using the European Working Conditions Survey (EWCS). Work autonomy, workload and tenure are positively related to the number of sickness presenteeism days, while a good working environment comes with less presenteeism. In Chapter 5 we theoretically and empirically analyze sickness absence and presenteeism behaviour with a focus on their interdependence. Specifically, we ask whether work-related factors lead to a substitutive, a complementary or no relationship between sickness absence and presenteeism. In other words, we want to know whether changes in absence and presenteeism behaviour incurred by work-related characteristics point in opposite directions (substitutive), the same direction (complementary), or whether they only affect either one of the two sickness states (no relationship). Our theoretical model shows that the relationship between sickness absence and presenteeism with regard to work-related characteristics is not necessarily of a substitutive nature. Instead, a complementary or no relationship can emerge as well. Turning to the empirical investigation, we find that only one out of 16 work-related factors, namely the supervisor status, leads to a substitutive relationship between absence and presenteeism. Few of the other determinants are complements, while the large majority is either related to sickness absence or presenteeism.
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.
In politics and economics, and thus in the official statistics, the precise estimation of indicators for small regions or parts of populations, the so-called Small Areas or domains, is discussed intensively. The design-based estimation methods currently used are mainly based on asymptotic properties and are thus reliable for large sample sizes. With small sample sizes, however, this design based considerations often do not apply, which is why special model-based estimation methods have been developed for this case - the Small Area methods. While these may be biased, they often have a smaller mean squared error (MSE) as the unbiased design based estimators. In this work both classic design-based estimation methods and model-based estimation methods are presented and compared. The focus lies on the suitability of the various methods for their use in official statistics. First theory and algorithms suitable for the required statistical models are presented, which are the basis for the subsequent model-based estimators. Sampling designs are then presented apt for Small Area applications. Based on these fundamentals, both design-based estimators and as well model-based estimation methods are developed. Particular consideration is given in this case to the area-level empirical best predictor for binomial variables. Numerical and Monte Carlo estimation methods are proposed and compared for this analytically unsolvable estimator. Furthermore, MSE estimation methods are proposed and compared. A very popular and flexible resampling method that is widely used in the field of Small Area Statistics, is the parametric bootstrap. One major drawback of this method is its high computational intensity. To mitigate this disadvantage, a variance reduction method for parametric bootstrap is proposed. On the basis of theoretical considerations the enormous potential of this proposal is proved. A Monte Carlo simulation study shows the immense variance reduction that can be achieved with this method in realistic scenarios. This can be up to 90%. This actually enables the use of parametric bootstrap in applications in official statistics. Finally, the presented estimation methods in a large Monte Carlo simulation study in a specific application for the Swiss structural survey are examined. Here problems are discussed, which are of high relevance for official statistics. These are in particular: (a) How small can the areas be without leading to inappropriate or to high precision estimates? (b) Are the accuracy specifications for the Small Area estimators reliable enough to use it for publication? (c) Do very small areas infer in the modeling of the variables of interest? Could they cause thus a deterioration of the estimates of larger and therefore more important areas? (d) How can covariates, which are in different levels of aggregation be used in an appropriate way to improve the estimates. The data basis is the Swiss census of 2001. The main results are that in the author- view, the use of small area estimators for the production of estimates for areas with very small sample sizes is advisable in spite of the modeling effort. The MSE estimates provide a useful measure of precision, but do not reach in all Small Areas the level of reliability of the variance estimates for design-based estimators.
This dissertation includes three research articles on the portfolio risks of private investors. In the first article, we analyze a large data set of private banking portfolios in Switzerland of a major bank with the unique feature that parts of the portfolios were managed by the bank, and parts were advisory portfolios. To correct the heterogeneity of individual investors, we apply a mixture model and a cluster analysis. Our results suggest that there is indeed a substantial group of advised individual investors that outperform the bank managed portfolios, at least after fees. However, a simple passive strategy that invests in the MSCI World and a risk-free asset significantly outperforms both the better advisory and the bank managed portfolios. The new regulation of the EU for financial products (UCITS IV) prescribes Value at Risk (VaR) as the benchmark for assessing the risk of structured products. The second article discusses the limitations of this approach and shows that, in theory, the expected return of structured products can be unbounded while the VaR requirement for the lowest risk class can still be satisfied. Real-life examples of large returns within the lowest risk class are then provided. The results demonstrate that the new regulation could lead to new seemingly safe products that hide large risks. Behavioral investors who choose products based only on their official risk classes and their expected returns will, therefore, invest into suboptimal products. To overcome these limitations, we suggest a new risk-return measure for financial products based on the martingale measure that could erase such loopholes. Under the mean-VaR framework, the third article discusses the impacts of the underlying's first four moments on the structured product. By expanding the expected return and the VaR of a structured product with its underlying moments, it is possible to investigate each moment's impact on them, simultaneously. Results are tested by Monte Carlo simulation and historical simulation. The findings show that for the majority of structured products, underlyings with large positive skewness are preferred. The preferences for variance and for kurtosis are ambiguous.
Chapter 2: Using data from the German Socio-Economic Panel, this study examines the relation-ship between immigrant residential segregation and immigrants" satisfaction with the neighbor-hood. The estimates show that immigrants living in segregated areas are less satisfied with the neighborhood. This is consistent with the hypothesis that housing discrimination rather than self-selection plays an important role in immigrant residential segregation. Our result holds true even when controlling for other influences such as household income and quality of the dwelling. It also holds true in fixed effects estimates that account for unobserved time-invariant influences. Chapter 3: Using survey data from the German Socio-Economic Panel, this study shows that immigrants living in segregated residential areas are more likely to report discrimination because of their ethnic background. This applies to both segregated areas where most neighbors are immigrants from the same country of origin as the surveyed person and segregated areas where most neighbors are immigrants from other countries of origin. The results suggest that housing discrimination rather than self-selection plays an important role in immigrant residential segregation. Chapter 4: Using data from the German Socio-Economic Panel (SOEP) and administrative data from 1996 to 2009, I investigate the question whether or not right-wing extremism of German residents is affected by the ethnic concentration of foreigners living in the same residential area. My results show a positive but insignificant relationship between ethnic concentration at the county level and the probability of extreme right-wing voting behavior for West Germany. However, due to potential endogeneity issues, I additionally instrument the share of foreigners in a county with the share of foreigners in each federal state (following an approach of Dustmann/Preston 2001). I find evidence for the interethnic contact theory, predicting a negative relationship between foreign-ers" share and right-wing voting. Moreover, I analyze the moderating role of education and the influence of cultural traits on this relationship. Chapter 5: Using data from the Socio-Economic Panel from 1998 to 2009 and administrative data on regional ethnic diversity, I show that ethnic diversity inhibits significantly people- political interest and participation in political organizations in West Germany. People seem to isolate themselves from political participation if exposed to more ethnic diversity which is particularly relevant with respect to the ongoing integration process of the European Union and the increasing transfer of legislative power from the national to European level. The results are robust if an instrumental variable strategy suggested by Dustmann and Preston (2001) is used to take into account that ethnic diversity measured on a local spatial level could be endogenous due to residential sorting. Interestingly, participation in non-political organizations is positively affected by ethnic diversity if selection bias is corrected for.
Das erste Kapitel "ECOWAS" capability and potential to overcome constraints to growth and poverty reduction of its member states" diskutiert die Analyse wirtschaftlicher und sozialer Barrieren für ökonomisches Wachstum " eine der Hauptelemente für Entwicklungs- und Armutsreduktionsstrategien in Entwicklungsländern. Die Form der länderspezifischen Analyse von Wachstumsbarrieren wurde nach dem Scheitern der auf alle Länder generalisierten Entwicklungsstrategie des Washington Consensus insbesondere durch den Ansatz der "Growth Diagnostics" der Harvard Professoren Hausman, Rodrik und Velasco eingeführt. Es zeigt sich jedoch, dass bisher der Fokus rein auf den länderspezifischen Analysen bzw. Strategieentwicklungen liegt. Diese Arbeit erweiterte die Diskussion auf die regionale Ebene, indem es beispielhaft an der Economic Community of West African States (ECOWAS) die länderspezifischen Wachstumsbarrieren mit den regionalen Wachstumsbarrieren vergleicht. Dies erfolgt mittels einer Darstellung der in Studien und Strategien bereits identifizierten, länderspezifischen Wachstumsbarrieren in den jeweiligen Ländern sowie mit der Auswertung der regionalen Strategien der ECOWAS. Dazu wird ermittelt, inwieweit auf der regionalen Ebene auch messbare Ergebnisse bei der Bekämpfung von Wachstumsbarrieren erzielt werden. Es zeigt sich, dass ,trotz der wirtschaftlichen und sozialen Diversität der Region, die ECOWAS den Großteil der in den Ländern identifizierten Wachstumsbarrieren ebenfalls auflistet und darüber hinaus sogar mit messbaren Ergebnissen dazu beiträgt, Veränderungen des Status Quo zu erreichen. Die Erweiterung des Ansatzes der Growth Diagnostics auf die regionale Ebene sowie die Erweiterung um das vergleichende Element von länderspezifischen und regionalen Wachstumsbarrieren zeigen sich als praktikabler Weg, Entwicklungsstrategien auf regionaler Ebene zu prüfen und subsidiär weiterzuentwickeln. Das zweite Kapitel "Simplifying evaluation of potential causalities in development projects using Qualitative Comparative Analysis (QCA)" diskutiert die Methode der qualitativen komperativen Analyse (QCA) als Evaluierungsmethodik für Projekte der Entwicklungszusammenarbeit. Hierbei stehen die adäquate Messung sowie die verständliche Darstellung der Wirkung von Entwicklungszusammenarbeit im Vordergrund. Dies ist ein Beitrag zu der intensiv geführten Diskussion, wie Wirkung von Hilfe in Entwicklungsländern gemessen und daraus für weitere Projekte gelernt werden kann. Mit der beispielhaften Anwendung der QCA auf einen Datensatz der deutschen Entwicklungszusammenarbeit im Senegal wird erstmalig diese Methode für die Entwicklungszusammenarbeit in der Praxis angewandt. Der Fokus liegt dabei auf der Überprüfung von bestimmten Programmtheorien, d.h. der Annahme bestimmter Zusammenhänge zwischen eingesetzten Mitteln, äußeren Umständen und den Projektergebnissen bei der Implementierung von Projekten. Während solche Programmtheorien in dem Großteil der Projektskizzen der deutschen Entwicklungszusammenarbeit enthalten sind, werden die wenigsten dieser Programmtheorien geprüft. Diese Arbeit zeigt QCA als eine effiziente Methode für diese Überprüfung. Eine eindeutige Bestätigung oder Falsifizierung dieser Theorien ist mittels dieser Methodik möglich. Dazu können die Ergebnisse bei den beiden einfacheren Formen der QCA, der crisp-set sowie der multi-value QCA, leicht nachvollziehbar vermittelt werden. Des Weiteren zeigt die Arbeit, dass QCA ebenfalls die Weiterentwicklung einer Programmtheorie ermöglicht, allerdings ist diese Weiterentwicklung nur begrenzt effizient und stark von den vorliegenden Daten sowie der Datenstruktur abhängig. Die Arbeit zeigt somit das Potential der QCA insbesondere für den Test von Programmtheorien auf und stellt die praktische Anwendung für mögliche Replizierung beispielhaft dar. Das dritte und letzte Kapitel der Doktorarbeit "The regional trade dynamics of Turkey: a panel data gravity model" analysiert den türkischen Handel, um die Veränderungen der letzten Jahrzehnte aufzuzeigen und daran zu diskutieren, inwieweit sich die Türkei als aufstrebendes Schwellenland von den bestehenden Handelsstrukturen loslöst. Diese Arbeit ist ein Beitrag zur Diskussion der sich Verschiebenden Machtkonstellationen durch das wirtschaftliche Aufholen der Schwellenländer. Bei der Türkei ist diese Diskussion zusätzlich interessant, da die Frage, ob die Türkei sich von der westlichen Welt, Nordamerika und Europa, abwendet, berücksichtigt wird. Mittels Dummy-Variablen für verschiedene Regionen in einem Gravitätsmodell werden die türkischen Handelsdaten zuerst insgesamt und nach Sektoren analysiert und die Veränderungen über verschieden Perioden des türkischen Außenhandels betrachtet. Es zeigt sich, dass in den türkischen Handelsbeziehungen eine Regionalisierung und eine Diversifizierung der Handelspartner stattfinden. Allerdings geht dies nicht mit einer Abkehr von westlichen Handelspartnern einher.
The main purpose of this dissertation is to solve the following question: How will the emergence of the Euro influence the currency composition of the NICs?monetary reserves? Taiwan and Thailand are chosen as our investigation subjects. There are two sorts of motives for central banks' reserve holdings, i.e., intervention-related motives and portfolio-related motives. The need for reserve holdings resulting from intervention-related motives are justified because of the costs resulting from exchange rate instability. On the other hand, we use the Tobin-Markowitz model to justify the need for monetary reserves held for portfolio-related motives. The operational implication of this distinction is the separation of monetary reserves into two tranches corresponding to different objectives. An analysis of a central bank's transaction balance is a money quality analysis. Such an analysis has to do with transaction costs and non-pecuniary rates of return. The facts point out, that the Euro's emergence will not change the fact that the USD will continue to be the major currency of transaction balances of the central banks in Taiwan and Thailand. In order to answer the question about diversification of monetary reserves as idle balance in the two NICs, we carry out an analysis of the portfolio approach, which is based on the basic ideas of the Tobin-Markowitz model. This analysis shows that Taiwan and/or Thailand respectively cannot reduce risk at a given rate of return or increase the rate of return at a given risk by diversifying their monetary reserves as idle balance from the USD to the Euro.
Why do some people become entrepreneurs while others stay in paid employment? Searching for a distinctive set of entrepreneurial skills that matches the profile of the entrepreneurial task, Lazear introduced a theoretical model featuring skill variety for entrepreneurs. He argues that because entrepreneurs perform many different tasks, they should be multi-skilled in various areas. First, this dissertation provides the reader with an overview of previous relevant research results on skill variety with regard to entrepreneurship. The majority of the studies discussed focus on the effects of skill variety. Most studies come to the conclusion that skill variety mainly affects the decision to become self-employed. Skill variety also favors entrepreneurial intentions. Less clear are the results with regard to the influence of skill variety on the entrepreneurial success. Measured on the basis of income and survival of the company, a negative or U-shaped correlation is shown. Within the empirical part of this dissertation three research goals are tackled. First, this dissertation investigates whether a variety of early interests and activities in adolescence predicts subsequent variety in skills and knowledge. Second, the determinants of skill variety and variety of early interests and activities are investigated. Third, skill variety is tested as a mediator of the gender gap in entrepreneurial intentions. This dissertation employs structural equation modeling (SEM) using longitudinal data collected over ten years from Finnish secondary school students aged 16 to 26. As indicator for skill variety the number of functional areas in which the participant had prior educational or work experience is used. The results of the study suggest that a variety of early interests and activities lead to skill variety, which in turn leads to entrepreneurial intentions. Furthermore, the study shows that an early variety is predicted by openness and an entrepreneurial personality profile. Skill variety is also encouraged by an entrepreneurial personality profile. From a gender perspective, there is indeed a gap in entrepreneurial intentions. While a positive correlation has been found between the early variety of subjects and being female, there are negative correlations between the other two variables, education and work related Skill variety, and being female. The negative effect of work-related skill variety is the strongest. The results of this dissertation are relevant for research, politics, educational institutions and special entrepreneurship education programs. The results are also important for self-employed parents that plan the succession of the family business. Educational programs promoting entrepreneurship can be optimized on the basis of the results of this dissertation by making the transmission of a variety of skills a central goal. A focus on teenagers could also increase the success as well as a preselection based on the personality profile of the participants. Regarding the gender gap, state policies should aim to provide women with more incentives to acquire skill variety. For this purpose, education programs can be tailored specifically to women and self-employment can be presented as an attractive alternative to dependent employment.
Part-time entrepreneurship has become increasingly popular and is a rather new field of research. Two important research topics are addressed in this dissertation: (a) the impact of culture on part-time and full-time entrepreneurship and (b) the motivational aspects of the transition from part-time to full-time entrepreneurship. Specifically, this dissertation advances prior research by highlighting the direct and indirect differential impact of macro-level societal culture on part-time and full-time entrepreneurship. Gender egalitarianism, uncertainty avoidance and future orientation have a significantly stronger impact on full-time than on part-time entrepreneurship. Furthermore the moderating impact of societal culture on micro-level relationships for both forms of entrepreneurship is explored. The age-old and well-established relationship between education and entrepreneurial activity is moderated by different forms of collectivism for part-time and full-time entrepreneurship. Regarding the motivation of part-time entrepreneurs to transition to full-time entrepreneurship, the entrepreneurial motives of self-realization and independence are significantly positively associated with the transition, whereas the entrepreneurial motives of income supplementation and recognition are significantly negatively associated with the transition. This dissertation advances academic research by indicating conceptual differences between part-time and full-time entrepreneurship in a multi country setting and by showing that both forms of entrepreneurship are impacted through different cultural mechanisms. Based on the findings, policy makers can identify the direct and indirect impact of societal culture on part-time and full-time entrepreneurship. As a result, policy makers can better target support and transition programs to foster entrepreneurial activity.
Non-probability sampling is a topic of growing relevance, especially due to its occurrence in the context of new emerging data sources like web surveys and Big Data.
This thesis addresses statistical challenges arising from non-probability samples, where unknown or uncontrolled sampling mechanisms raise concerns in terms of data quality and representativity.
Various methods to quantify and reduce the potential selectivity and biases of non-probability samples in estimation and inference are discussed. The thesis introduces new forms of prediction and weighting methods, namely
a) semi-parametric artificial neural networks (ANNs) that integrate B-spline layers with optimal knot positioning in the general structure and fitting procedure of artificial neural networks, and
b) calibrated semi-parametric ANNs that determine weights for non-probability samples by integrating an ANN as response model with calibration constraints for totals, covariances and correlations.
Custom-made computational implementations are developed for fitting (calibrated) semi-parametric ANNs by means of stochastic gradient descent, BFGS and sequential quadratic programming algorithms.
The performance of all the discussed methods is evaluated and compared for a bandwidth of non-probability sampling scenarios in a Monte Carlo simulation study as well as an application to a real non-probability sample, the WageIndicator web survey.
Potentials and limitations of the different methods for dealing with the challenges of non-probability sampling under various circumstances are highlighted. It is shown that the best strategy for using non-probability samples heavily depends on the particular selection mechanism, research interest and available auxiliary information.
Nevertheless, the findings show that existing as well as newly proposed methods can be used to ease or even fully counterbalance the issues of non-probability samples and highlight the conditions under which this is possible.
Flexibility and spatial mobility of labour are central characteristics of modern societies which contribute not only to higher overall economic growth but also to a reduction of interregional employment disparities. For these reasons, there is the political will in many countries to expand labour market areas, resulting especially in an overall increase in commuting. The picture of the various, unintended long-term consequences of commuting on individuals is, however, relatively unclear. Therefore, in recent years, the journey to work has gained high attention especially in the study of health and well-being. Empirical analyses based on longitudinal as well as European data on how commuting may affect health and well-being are nevertheless rare. The principle aim of this thesis is, thus, to address this question with regard to Germany using data from the Socio-Economic Panel. Chapter 2 empirically investigates the causal impact of commuting on absence from work due to sickness-related reasons. Whereas an exogenous change in commuting distance does not affect the number of absence days of those individuals who commute short distances to work, it increases the number of absence days of those employees who commute middle (25 " 49 kilometres) or long distances (50 kilometres and more). Moreover, our results highlight that commuting may deteriorate an individual- health. However, this effect is not sufficient to explain the observed impact of commuting on absence from work. Chapter 3 explores the relationship between commuting distance and height-adjusted weight and sheds some light on the mechanisms through which commuting might affect individual body weight. We find no evidence that commuting leads to excess weight. Compensating health behaviour of commuters, especially healthy dietary habits, could explain the non-relationship of commuting and height-adjusted weight. In Chapter 4, a multivariate probit approach is used to estimate recursive systems of equations for commuting and health-related behaviours. Controlling for potential endogeneity of commuting, the results show that long distance commutes significantly decrease the propensity to engage in health-related activities. Furthermore, unobservable individual heterogeneity can influence both the decision to commute and healthy lifestyle choices. Chapter 5 investigates the relationship between commuting and several cognitive and affective components of subjective well-being. The results suggest that commuting is related to lower levels of satisfaction with family life and leisure time which can largely be ascribed to changes in daily time use patterns, influenced by the work commute.
This dissertation looked at both design-based and model-based estimation for rare and clustered populations using the idea of the ACS design. The ACS design (Thompson, 2012, p. 319) starts with an initial sample that is selected by a probability sampling method. If any of the selected units meets a pre-specified condition, its neighboring units are added to the sample and observed. If any of the added units meets the pre-specified condition, its neighboring units are further added to the sample and observed. The procedure continues until there are no more units that meet the pre-specified condition. In this dissertation, the pre-specified condition is the detection of at least one animal in a selected unit. In the design-based estimation, three estimators were proposed under three specific design setting. The first design was stratified strip ACS design that is suitable for aerial or ship surveys. This was a case study in estimating population totals of African elephants. In this case, units/quadrant were observed only once during an aerial survey. The Des Raj estimator (Raj, 1956) was modified to obtain an unbiased estimate of the population total. The design was evaluated using simulated data with different levels of rarity and clusteredness. The design was also evaluated on real data of African elephants that was obtained from an aerial census conducted in parts of Kenya and Tanzania in October (dry season) 2013. In this study, the order in which the samples were observed was maintained. Re-ordering the samples by making use of the Murthy's estimator (Murthy, 1957) can produce more efficient estimates. Hence a possible extension of this study. The computation cost resulting from the n! permutations in the Murthy's estimator however, needs to be put into consideration. The second setting was when there exists an auxiliary variable that is negatively correlated with the study variable. The Murthy's estimator (Murthy, 1964) was modified. Situations when the modified estimator is preferable was given both in theory and simulations using simulated and two real data sets. The study variable for the real data sets was the distribution and counts of oryx and wildbeest. This was obtained from an aerial census that was conducted in parts of Kenya and Tanzania in October (dry season) 2013. Temperature was the auxiliary variable for two study variables. Temperature data was obtained from R package raster. The modified estimator provided more efficient estimates with lower bias compared to the original Murthy's estimator (Murthy, 1964). The modified estimator was also more efficient compared to the modified HH and the modified HT estimators of (Thompson, 2012, p. 319). In this study, one auxiliary variable is considered. A fruitful area for future research would be to incorporate multi-auxiliary information at the estimation phase of an ACS design. This could, in principle, be done by using for instance a multivariate extension of the product estimator (Singh, 1967) or by using the generalized regression estimator (Särndal et al., 1992). The third case under design-based estimation, studied the conjoint use of the stopping rule (Gattone and Di Battista, 2011) and the use of the without replacement of clusters (Dryver and Thompson, 2007). Each of these two methods was proposed to reduce the sampling cost though the use of the stopping rule results in biased estimates. Despite this bias, the new estimator resulted in higher efficiency gain in comparison to the without replacement of cluster design. It was also more efficient compared to the stratified design which is known to reduce final sample size when networks are truncated at stratum boundaries. The above evaluation was based on simulated and real data. The real data was the distribution and counts of hartebeest, elephants and oryx obtained in the same census as above. The bias attributed by the stopping rule has not been evaluated analytically. This may not be direct since the truncated network formed depends on the initial unit sampled (Gattone et al., 2016a). This and the order of the bias however, deserves further investigation as it may help in understanding the effect of the increase in the initial sample size together with the population characteristics on the efficiency of the proposed estimator. Chapter four modeled data that was obtained using the stratified strip ACS (as described in sub-section (3.1)). This was an extension of the model of Rapley and Welsh (2008) by modeling data that was obtained from a different design, the introduction of an auxiliary variable and the use of the without replacement of clusters mechanism. Ideally, model-based estimation does not depend on the design or rather how the sample was obtained. This is however, not the case if the design is informative; such as the ACS design. In this case, the procedure that was used to obtain the sample was incorporated in the model. Both model-based and design-based simulations were conducted using artificial and real data. The study and the auxiliary variable for the real data was the distribution and counts of elephants collected during an aerial census in parts of Kenya and Tanzania in October (dry season) and April (wet season) 2013 respectively. Areas of possible future research include predicting the population total of African elephants in all parks in Kenya. This can be achieved in an economical and reliable way by using the theory of SAE. Chapter five compared the different proposed strategies using the elephant data. Again the study variable was the elephant data from October (dry season) 2013 and the auxiliary variable was the elephant data from April (wet season) 2013. The results show that the choice of particular strategy to use depends on the characteristic of the population under study and the level and the direction of the correlation between the study and the auxiliary variable (if present). One general area of the ACS design that is still behind, is the implementation of the design in the field especially on animal populations. This is partly attributed by the challenges associated with the field implementation, some of which were discussed in section 2.3. Green et al. (2010) however, provides new insights in undertaking the ACS design during an aerial survey such as how the aircraft should turn while surveying neighboring units. A key point throughout the dissertation is the reduction of cost during a survey which can be seen by the reduction in the number of units in the final sample (through the use of stopping rule, use of stratification and truncating networks at stratum boundaries) and ensuring that units are observed only once (by using the without replacement of cluster sampling technique). The cost of surveying an edge unit(s) is assumed to be low in which case the efficiency of the ACS design relative to the non-adaptive design is achieved (Thompson and Collins, 2002). This is however not the case in aerial surveys as the aircraft flies at constant speed and height (Norton-Griffiths, 1978). Hence the cost of surveying an edge unit is the same as the cost of surveying a unit that meets the condition of interest. The without replacement of cluster technique plays a greater role of reducing the cost of sampling in such surveys. Other key points that motivated the sections in the dissertation include gains in efficiency (in all sections) and practicability of the designs in the specific setting. Even though the dissertation focused on animal populations, the methods can as well be implemented in any population that is rare and clustered such as in the study of forestry, plants, pollution, minerals and so on.
Financing of Small and Medium-Sized Enterprises in Europe - Financing Patterns and 'Crowdfunding'
(2015)
Small and medium-sized enterprises (SMEs) play a vital role for the innovativeness, economic growth and competitiveness of Europe. One of the most pressing problems of SMEs is access to finance to ensure their survival and growth. This dissertation uses both quantitative and qualitative exploratory research methods and increases with its holistic approach the transparency in SME financing. The results of a cluster analysis including 12,726 SMEs in 28 European countries reveal that SME financing in Europe is not homogenous but that different financing patterns exist which differ according to the number of financing instruments used and the combinations thereof. Furthermore, the SME financing types can be profiled according to their firm-, product-, industry- and country-specific characteristics. The results of this analysis provide some support for prior findings that smaller, younger and innovative SMEs suffer from a financing gap which cannot be closed with traditional financing instruments. One alternative to close this financing gap is crowdfunding. Even though crowdfunding has shown tremendous growth rates over the past few years, little is known about the determinants of this financing alternative. This dissertation systematically analyses the existing scientific literature on crowdfunding as an alternative in SME financing and reveals existing research gaps. Afterwards, the focus is on the role of investor communication as a way to reduce information asymmetries of the crowd in equity-based crowdfunding. The results of 24 interviews with market participants in equity-based crowdfunding reveal that crowd investors seem to replace personal contacts with alternative ways of communicating, which can be characterized as pseudo-personal (i.e., by using presentation videos, social media and investor relations channels). In addition, it was found that third party endorsements (e.g., other crowd investors, professional investors, customers and platforms) reduce the information asymmetries of crowd investors and hence, increase the likelihood of their investment.
The equity premium (Mehra and Prescott, 1985) is still a puzzle in the sense that there are still no convincing explanations for the size of the equity premium. In this dissertation, we study this long-standing puzzle and several possible behavioral explanations. First, we apply the IRR methodology proposed by Fama and French (1999) to achieve large firm level data on the equity premia for N = 28,256 companies in 54 countries around the world. Second, by using preferences data from the INTRA study (Rieger et. al., 2014), we could test the relevant risk factors together with time cognition to explain the equity premium. We document the failure of the Myopic Loss Aversion hypothesis by Benartzi and Thaler (1995) but provides rigorous empirical evidence to support the behavioral theory of ambiguity aversion to account for the equity premium. The observations shed some light on the new approach of integrating risk and ambiguity (together with time preferences) into a more general model of uncertainty, in which both risk premium and ambiguity premium play roles in asset pricing models.
Monetary Policy During Times of Crisis - Frictions and Non-Linearities in the Transmission Mechanism
(2017)
For a long time it was believed that monetary policy would be able to maintain price stability and foster economic growth during all phases of the business cycle. The era of the Great Moderation, often also called the Volcker-Greenspan period, beginning in the mid 1980s was characterized by a decline in volatility of output growth and inflation among the industrialized countries. The term itself is first used by Stock and Watson (2003). Economist have long studied what triggered the decline in volatility and pointed out several main factors. An important research strand points out structural changes in the economy, such as a decline of volatility in the goods producing sector through better inventory controls and developments in the financial sector and government spending (McConnell2000, Blanchard2001, Stock2003, Kim2004, Davis2008). While many believed that monetary policy was only 'lucky' in terms of their reaction towards inflation and exogenous shocks (Stock2003, Primiceri2005, Sims2006, Gambetti2008), others reveal a more complex picture of the story. Rule based monetary policy (Taylor1993) that incorporates inflation targeting (Svensson1999) has been identified as a major source of inflation stabilization by increasing transparency (Clarida2000, Davis2008, Benati2009, Coibion2011). Apart from that, the mechanics of monetary policy transmission have changed. Giannone et al. (2008) compare the pre-Great Moderation era with the Great Modertation and find that the economies reaction towards monetary shocks has decreased. This finding is supported by Boivin et al. (2011). Similar to this, Herrera and Pesavento (2009) show that monetary policy during the Volcker-Greenspan period was very effective in dampening the effects of exogenous oil price shocks on the economy, while this cannot be found for the period thereafter. Yet, the subprime crisis unexpectedly hit worldwide economies and ended the era of Great Moderation. Financial deregulation and innovation has given banks opportunities for excessive risk taking, weakened financial stability (Crotty2009, Calomiris2009) and led to the build-up of credit-driven asset price bubbles (SchularickTaylor2012). The Federal Reserve (FED), that was thought to be the omnipotent conductor of price stability and economic growth during the Great Moderation, failed at preventing a harsh crisis. Even more, it did intensify the bubble with low interest rates following the Dotcom crisis of the early 2000s and misjudged the impact of its interventions (Taylor2009, Obstfeld2009). New results give a more detailed explanation on the question of latitude for monetary policy raised by Bernanke and suggest the existence of non-linearities in the transmission of monetary policy. Weise (1999), Garcia and Schaller (2002), Lo and Piger (2005), Mishkin (2009), Neuenkirch (2013) and Jannsen et al. (2015) find that monetary policy is more potent during times of financial distress and recessions. Its effectiveness during 'normal times' is much weaker or even insignificant. This prompts the question if these non-linearities limit central banks ability to lean against bubbles and financial imbalances (White2009, Walsh2009, Boivin2010, Mishkin2011).
Retirement, fertility and sexuality are three key life stage events that are embedded in the framework of population economics in this dissertation. Each topic implies economic relevance. As retirement entry shifts labour supply of experienced workers to zero, this issue is particularly relevant for employers, retirees themselves as well as policymakers who are in charge of the design of the pension system. Giving birth has comprehensive economic relevance for women. Parental leave and subsequent part-time work lead to a direct loss of income. Lower levels of employment, work experience, training and career opportunities result in indirect income losses. Sexuality has decisive influence on the quality of partnerships, subjective well-being and happiness. Well-being and happiness, in turn, are significant key determinants not only in private life but also in the work domain, for example in the area of job performance. Furthermore, partnership quality determines the duration of a partnership. And in general, partnerships enable the pooling of (financial) resources - compared to being single. The contribution of this dissertation emerges from the integration of social and psychological concepts into economic analysis as well as the application of economic theory in non-standard economic research topics. The results of the three chapters show that the multidisciplinary approach yields better prediction of human behaviour than the single disciplines on their own. The results in the first chapter show that both interpersonal conflict with superiors and the individual’s health status play a significant role in retirement decisions. The chapter further contributes to existing literature by showing the moderating role of health within the retirement decision-making: On the one hand, all employees are more likely to retire when they are having conflicts with their superior. On the other hand, among healthy employees, the same conflict raises retirement intentions even more. That means good health is a necessary, but not a sufficient condition for continued working. It may be that conflicts with superiors raise retirement intentions more if the worker is healthy. The key findings of the second chapter reveal significant influence of religion on contraceptive and fertility-related decisions. A large part of research on religion and fertility is originated in evidence from the US. This chapter contrasts evidence from Germany. Additionally, the chapter contributes by integrating miscarriages and abortions, rather than limiting the analysis to births and it gains from rich prospective data on fertility biography of women. The third chapter provides theoretical insights on how to incorporate psychological variables into an economic framework which aims to analyse sexual well-being. According to this theory, personality may play a dual role by shaping a person’s preferences for sex as well as the person’s behaviour in a sexual relationship. Results of econometric analysis reveal detrimental effects of neuroticism on sexual well-being while conscientiousness seems to create a win-win situation for a couple. Extraversions and Openness have ambiguous effects on romantic relationships by enhancing sexual well-being on the one hand but raising commitment problems on the other. Agreeable persons seem to gain sexual satisfaction even if they perform worse in sexual communication.
International private equity development is highly volatile with increasing global diversification. This thesis examines the transaction patterns of cross-border private equity investment with a particular focus on the affinity of country pairs. Analysis is based on a comprehensive dataset of 99 countries over 25 years. A three-dimensional gravity model analysis covering source and host country over time exposes the effects of the country determinants: economic mass, economic distance, banking system, corporate endowment, as well as legal, political, and institutional system on the transactions. A new method is developed to examine countries in their dual roles as investor and target. This approach verifies their global importance as source and host, and also makes possible an analysis of overall private equity investment. For private equity-specific multi-investor deals, a scheme is designed to measure cross-border activity with more precision by participation, proportional deal participation, and deal flow. The analysis identifies intense level of affinity between country pairs and reveals that no single country is ideal for private equity activity. Instead, the findings show that the specific push and pull factors within each country constellation define the optimal country as trading partner. The results verify a correlation between cross-border deals and economic masses and reduced economic distance of countries. Geographic distance and cultural similarities, such as language and legal system, intensify the likelihood of initiating transactions. International trade-oriented countries with a high level of development lower the entrance barriers and increase the chances of deal success. A well-funded financial system for the investor and an efficient and competitive banking system of target countries enhance the probability of investment between countries. Also relevant for the likelihood of starting cross-border deals are low corporate tax burdens and advanced scientific competitiveness, and a well-developed stock market in the investor country. Fundamental to frequency and likelihood of success are well-established, high standards of a country- social, political, and legal systems with widespread confidence in the rules of society. In particular, the reliability of contract enforcement, with proven quality of regulations that promote private sector development, proves to be crucial for deal success.
The demand for reliable statistics has been growing over the past decades, because more and more political and economic decisions are based on statistics, e.g. regional planning, allocation of funds or business decisions. Therefore, it has become increasingly important to develop and to obtain precise regional indicators as well as disaggregated values in order to compare regions or specific groups. In general, surveys provide the information for these indicators only for larger areas like countries or administrative divisions. However, in practice, it is more interesting to obtain indicators for specific subdivisions like on NUTS 2 or NUTS 3 levels. The Nomenclature of Units for Territorial Statistics (NUTS) is a hierarchical system of the European Union used in statistics to refer to subdivisions of countries. In many cases, the sample information on such detailed levels is not available. Thus, there are projects such as the European Census, which have the goal to provide precise numbers on NUTS 3 or even community level. The European Census is conducted amongst others in Germany and Switzerland in 2011. Most of the participating countries use sample and register information in a combined form for the estimation process. The classical estimation methods of small areas or subgroups, such as the Horvitz-Thompson (HT) estimator or the generalized regression (GREG) estimator, suffer from small area-specific sample sizes which cause high variances of the estimates. The application of small area methods, for instance the empirical best linear unbiased predictor (EBLUP), reduces the variance of the estimates by including auxiliary information to increase the effective sample size. These estimation methods lead to higher accuracy of the variables of interest. Small area estimation is also used in the context of business data. For example during the estimation of the revenues of specific subgroups like on NACE 3 or NACE 4 levels, small sample sizes can occur. The Nomenclature statistique des activités économiques dans la Communauté européenne (NACE) is a system of the European Union which defines an industry standard classification. Besides small sample sizes, business data have further special characteristics. The main challenge is that business data have skewed distributions with a few large companies and many small businesses. For instance, in the automotive industry in Germany, there are many small suppliers but only few large original equipment manufacturers (OEM). Altogether, highly influential units and outliers can be observed in business statistics. These extreme values in connection with small sample sizes cause severe problems when standard small area models are applied. These models are generally based on the normality assumption, which does not hold in the case of outliers. One way to solve these peculiarities is to apply outlier robust small area methods. The availability of adequate covariates is important for the accuracy of the above described small area methods. However, in business data, the auxiliary variables are hardly available on population level. One of several reasons for that is the fact that in Germany a lot of enterprises are not reflected in business registers due to truncation limits. Furthermore, only listed enterprises or companies which trespass specific thresholds are obligated to publish their results. This limits the number of potential auxiliary variables for the estimation. Even though there are issues with available covariates, business data often include spatial dependencies which can be used to enhance small area methods. Next to spatial information based on geographic characteristics, group-specific similarities like related industries based on NACE codes can be used. For instance, enterprises from the same NACE 2 level, e.g. sector 47 retail trade, behave more similar than two companies from different NACE 2 levels, e.g. sector 05 mining of coal and sector 64 financial services. This spatial correlation can be incorporated by extending the general linear mixed model trough the integration of spatially correlated random effects. In business data, outliers as well as geographic or content-wise spatial dependencies between areas or domains are closely linked. The coincidence of these two factors and the resulting consequences have not been fully covered in the relevant literature. The only approach that combines robust small area methods with spatial dependencies is the M-quantile geographically weighted regression model. In the context of EBLUP-based small area models, the combination of robust and spatial methods has not been considered yet. Therefore, this thesis provides a theoretical approach to this scientific and practical problem and shows its relevance in an empirical study.
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.
Service innovation has increasingly gained acknowledgement to contribute to economic growth and well-being. Despite this increased relevance in practice, service innovation is a developing research field. To advance literature on service innovation, this work analyzes with a qualitative study how firms manage service innovation activities in their organization differently. In addition, it evaluates the influence of top management commitment and corporate service innovativeness on service innovation capabilities of a firm and their implications for firm-level performance by conducting a quantitative study. Accordingly, the main overall research questions of this dissertation are: 1.) How and why do firms manage service innovation activities in their organization differently? 2.) What influence do top management commitment and corporate service innovativeness have on service innovation capabilities of a firm and what are the implications for firm-level performance? To respond to the first research question the way firms manage service innovation activities in their organization is investigated and by whom and how service innovations are developed. Moreover, it is examined why firms implement their service innovation activities differently. To achieve this a qualitative empirical study is conducted which included 22 semi-structured interviews with 15 firms in the sectors of construction, financial services, IT services, and logistics. Addressing the second research question, the aim is to improve the understanding about factors that enhance firm-level performance through service innovations. Deploying a dynamic capabilities perspective, a quantitative study is performed which underlines the importance of service innovation capabilities. More specifically, a theoretical framework is developed that proposes a positive relationship of top management commitment and corporate service innovativeness with service innovation capabilities and a positive relationship between service innovation capabilities and the firm-level performance indicators market performance, competitive advantage, and efficiency. A survey with double respondents from 87 companies from the sectors construction, financial services, IT services, and logistics was conducted to test the proposed theoretical framework by applying partial least squares structural equation modeling (PLS-SEM).
For the first time, the German Census 2011 will be conducted via a new method the register based census. In contrast to a traditional census, where all inhabitants are surveyed, the German government will mainly attempt to count individuals using population registers of administrative authorities, such as the municipalities and the Federal Employment Agency. Census data that cannot be collected from the registers, such as information on education, training, and occupation, will be collected by an interview-based sample survey. Moreover, the new method reduces citizens' obligations to provide information and helps reduce costs significantly. The use of sample surveys is limited if results with a detailed regional or subject-matter breakdown have to be prepared. Classical estimation methods are sometimes criticized, since estimation is often problematic for small samples. Fortunately, model based small area estimators serve as an alternative. These methods help to increase the information, and hence the effective sample size. In the German Census 2011 it is possible to embed areas on a map in a geographical context. This may offer additional information, such as neighborhood relations or spatial interactions. Standard small area models, like Fay-Herriot or Battese-Harter-Fuller, do not account for such interactions explicitly. The aim of our work is to extend the classical models by integrating the spatial information explicitly into the model. In addition, the possible gain in efficiency will be analyzed.
Legalisation cannot be fully explained by interest politics. If that were the case, the attitudes towards legalisation would be expected to be based on objective interests and actual policies in France and Germany would be expected to be more similar. Nor can it be explained by institutional agency, because there are no hints that states struggle with different normative traditions. Rather, political actors seek to make use of the structures that already exist to guar-antee legitimacy for their actions. If the main concern of governmental actors really is to accumulate legitimacy, as stated in the introduction, then politicians have a good starting position in the case of legalisation of illegal foreigners. Citizens" negative attitudes towards legalisation cannot be explained by imagined labour market competition; income effects play only a secondary role. The most important explanatory factor is the educational level of each individual. Objective interests do not trigger attitudes towards legalisation, but rather a basic men-tal predisposition for or against illegal immigrants who are eligible for legalisation. Politics concerning amnesties are thus not tied to an objectively given structure like the socio-economic composition of the electorate, but are open for political discretion. Attitudes on legalising illegal immigrants can be regarded as being mediated by beliefs and perceptions, which can be used by political agents or altered by political developments. However, politicians must adhere to a national frame of legitimating strategies that cannot be neglected without consequences. It was evident in the cross-country comparison of political debates that there are national systems of reference that provide patterns of interpretation. Legalisation is seen and incorporated into immigration policy in a very specific way that differs from one country to the next. In both countries investigated in this study, there are fundamental debates about which basic principles apply to legalisation and which of these should be held in higher esteem: a legal system able to work, humanitarian rights, practical considerations, etc. The results suggest that legalisation is "technicized" in France by describing it as an unusual but possible pragmatic instrument for the adjustment of the inefficient rule of law. In Germany, however, legalisation is discussed at a more normative level. Proponents of conservative immigration policies regard it as a substantial infringement on the rule of law, so that even defenders of a humanitarian solution for illegal immigrants are not able to challenge this view without significant political harm. But the arguments brought to bear in the debate on legalisation are not necessarily sound because they are not irrefutable facts, but instruments to generate legitimacy, and there are enough possibilities for arguing and persuading because socio-economic factors play a minor role. One of the most important arguments, the alleged pull effect of legalisation, has been subjected to an empirical investigation. In the political debate, it does not make any dif-ference whether this is true or not, insofar as it is not contested by incontrovertible findings. In reality, the results suggest that amnesties indeed exert a small attracting influence on illegal immigration, which has been contested by immigration friendly politicians in the French par-liament. The effect, however, is not large; therefore, some conservative politicians may put too much stress on this argument. Moreover, one can see legalisation as an instrument to restore legitimacy that has slipped away from immigration politics because of a high number of illegally residing foreigners. This aspect explains some of the peculiarities in the French debate on legalisation, e.g. the idea that the coherence of the law is secured by creating exceptional rules for legalising illegal immigrants. It has become clear that the politics of legalisation are susceptible to manipulation by introducing certain interpretations into the political debate, which become predominant and supersede other views. In this study, there are no signs of a systematic misuse of this constellation by any certain actor. However, the history of immigration policy is full of examples of symbolic politics in which a certain measure has been initiated while the actors are totally aware of its lack of effect. Legalisation has escaped this fate so far because it is a specific instrument that is the result of neglecting populist mechanisms rather than an ex-ample of a superficial measure. This result does not apply to policies concerning illegal immi-gration in general, both with regard to concealing a lack of control and flexing the state- muscles.
Entrepreneurship is a process of discovering and exploiting opportunities, during which two crucial milestones emerge: in the very beginning when entrepreneurs start their businesses, and in the end when they determine the future of the business. This dissertation examines the establishment and exit of newly created as well as of acquired firms, in particular the behavior and performance of entrepreneurs at these two important stages of entrepreneurship. The first part of the dissertation investigates the impact of characteristics at the individual and at the firm level on an entrepreneur- selection of entry modes across new venture start-up and business takeover. The second part of the dissertation compares firm performance across different entrepreneurship entry modes and then examines management succession issues that family firm owners have to confront. This study has four main findings. First, previous work experience in small firms, same sector experience, and management experience affect an entrepreneur- choice of entry modes. Second, the choice of entry mode for hybrid entrepreneurs is associated with their characteristics, such as occupational experience, level of education, and gender, as well as with the characteristics of their firms, such as location. Third, business takeovers survive longer than new venture start-ups, and both entry modes have different survival determinants. Fourth, the family firm- decision of recruiting a family or a nonfamily manager is not only determined by a manager- abilities, but also by the relationship between the firm- economic and non-economic goals and the measurability of these goals. The findings of this study extend our knowledge on entrepreneurship entry modes by showing that new venture start-ups and business takeovers are two distinct entrepreneurship entry modes in terms of their founders" profiles, their survival rates and survival determinants. Moreover, this study contributes to the literature on top management hiring in family firms: it establishes family firm- non-economic goals as another factor that impacts the family firm- hiring decision between a family and a nonfamily manager.
The classic Capital Asset Pricing Model and the portfolio theory suggest that investors hold the market portfolio to diversify idiosyncratic risks. The theory predicts that expected return of assets is positive and that reacts linearly on the overall market. However, in reality, we observe that investors often do not have perfectly diversified portfolios. Empirical studies find that new factors influence the deviation from the theoretical optimal investment. In the first part of this work (Chapter 2) we study such an example, namely the influence of maximum daily returns on subsequent returns. Here we follow ideas of Bali et al. (2011). The goal is to find cross-sectional relations between extremely positive returns and expected average returns. We take account a larger number of markets worldwide. Bali et al. (2011) report with respect to the U.S. market a robust negative relation between MAX (the maximum daily return) and the expected return in the subsequent time. We extent substantially their database to a number of other countries, and also take more recent data into account (until end of 2009). From that we conclude that the relation between MAX and expected returns is not consistent in all countries. Moreover, we test the robustness of the results of Bali et al. (2011) in two time-periods using the same data from CRSP. The results show that the effect of extremely positive returns is not stable over time. Indeed we find a negative cross-sectional relation between the extremely positive returns and the average returns for the first half of the time series, however, we do not find significant effects for the second half. The main results of this chapter serve as a basis for an unpublished working paper Yuan and Rieger (2014b). While in Chapter 2 we have studied factors that prevent optimal diversification, we consider in Chapter 3 and 4 situations where the optimal structure of diversification was previously unknown, namely diversification of options (or structured financial products). Financial derivatives are important additional investment form with respect to diversification. Not only common call and put options, but also structured products enable investors to pursue a multitude of investment strategies to improve the risk-return profile. Since derivatives become more and more important, diversification of portfolios with dimension of derivatives is of particularly practical relevance. We investigate the optimal diversification strategies in connection with underlying stocks for classical rational investors with constant relative risk aversion (CRRA). In particular, we apply Monte Carlo method based on the Black-Scholes model and the Heston model for stochastic volatility to model the stock market processes and the pricing of the derivatives. Afterwards, we compare the benchmark portfolio which consists of derivatives on single assets with derivatives on the index of these assets. First we compute the utility improvement of an investment in the risk-free assets and plain-vanilla options for CRRA investors in various scenarios. Furthermore, we extend our analysis to several kinds of structured products, in particular capital protected notes (CPNs), discount certificates (DCs) and bonus certificates (BCs). We find that the decision of an investor between these two diversification strategies leads to remarkable differences. The difference in the utility improvement is influenced by risk-preferences of investors, stock prices and the properties of the derivatives in the portfolio. The results will be presented in Chapter 3 and are the basis for a yet unpublished working paper Yuan and Rieger (2014a). To check furthermore whether underlyings of structured products influence decisions of investors, we discuss explicitly the utility gain of a stock-based product and an index-based product for an investor whose preferences are described by cumulative prospect theory (CPT) (Chapter 4, compare to Yuan (2014)). The goal is that to investigate the dependence of structured products on their underlying where we put emphasis on the difference between index-products and single-stock-products, in particular with respect to loss-aversion and mental accounting. We consider capital protected notes and discount certificates as examples, and model the stock prices and the index of these stocks via Monte Carlo simulations in the Black-Scholes framework. The results point out that market conditions, particularly the expected returns and volatility of the stocks play a crucial role in determining the preferences of investors for stock-based CPNs and index-based CPNs. A median CPT investor prefers the index-based CPNs if the expected return is higher and the volatility is lower, while he prefers the stock-based CPNs in the other situation. We also show that index-based DCs are robustly more attractive as compared to stock-based DCs for CPT investors.
Surveys are commonly tailored to produce estimates of aggregate statistics with a desired level of precision. This may lead to very small sample sizes for subpopulations of interest, defined geographically or by content, which are not incorporated into the survey design. We refer to subpopulations where the sample size is too small to provide direct estimates with adequate precision as small areas or small domains. Despite the small sample sizes, reliable small area estimates are needed for economic and political decision making. Hence, model-based estimation techniques are used which increase the effective sample size by borrowing strength from other areas to provide accurate information for small areas. The paragraph above introduced small area estimation as a field of survey statistics where two conflicting philosophies of statistical inference meet: the design-based and the model-based approach. While the first approach is well suited for the precise estimation of aggregate statistics, the latter approach furnishes reliable small area estimates. In most applications, estimates for both large and small domains based on the same sample are needed. This poses a challenge to the survey planner, as the sampling design has to reflect different and potentially conflicting requirements simultaneously. In order to enable efficient design-based estimates for large domains, the sampling design should incorporate information related to the variables of interest. This may be achieved using stratification or sampling with unequal probabilities. Many model-based small area techniques require an ignorable sampling design such that after conditioning on the covariates the variable of interest does not contain further information about the sample membership. If this condition is not fulfilled, biased model-based estimates may result, as the model which holds for the sample is different from the one valid for the population. Hence, an optimisation of the sampling design without investigating the implications for model-based approaches will not be sufficient. Analogously, disregarding the design altogether and focussing only on the model is prone to failure as well. Instead, a profound knowledge of the interplay between the sample design and statistical modelling is a prerequisite for implementing an effective small area estimation strategy. In this work, we concentrate on two approaches to address this conflict. Our first approach takes the sampling design as given and can be used after the sample has been collected. It amounts to incorporate the survey design into the small area model to avoid biases stemming from informative sampling. Thus, once a model is validated for the sample, we know that it holds for the population as well. We derive such a procedure under a lognormal mixed model, which is a popular choice when the support of the dependent variable is limited to positive values. Besides, we propose a three pillar strategy to select the additional variable accounting for the design, based on a graphical examination of the relationship, a comparison of the predictive accuracy of the choices and a check regarding the normality assumptions.rnrnOur second approach to deal with the conflict is based on the notion that the design should allow applying a wide variety of analyses using the sample data. Thus, if the use of model-based estimation strategies can be anticipated before the sample is drawn, this should be reflected in the design. The same applies for the estimation of national statistics using design-based approaches. Therefore, we propose to construct the design such that the sampling mechanism is non-informative but allows for precise design-based estimates at an aggregate level.