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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.
Earnings functions are an important tool in labor economics as they allow to test a variety of labor market theories. Most empirical earnings functions research focuses on testing hypotheses about sign and magnitude for the variables of interest. In contrast, there is little attention for the explanation power of the econometric models employed. Measures for explanation power are of interest, however, for assessing how successful econometric models are in explaining the real world. Are researchers able to draw a complete picture of the determination of earnings or is there room for further theories leading to alternate econometric models? This article seeks to answer the question with a large microeconometric data set from Germany. Using linear regression estimated by OLS and R2 as well as adjusted R2 as measures for explanation power, the results show that up to 60 percent of wage variation can be explained using only observable variables.
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.
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).
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.
Unternehmen aus güterproduzierenden Industrien und Sektoren entdecken in immer stärkerem Maße das Differenzierungs- und Erlöspotenzial des Angebots ergänzender Dienstleistungen zur Erlangung von strategischen Wettbewerbsvorteilen. In vielen Branchen ist dies bereits ein notwendiger Bestandteil im Angebotsportfolios der Hersteller um sich zu positionieren und wettbewerbsfähig zu bleiben. Ein besonders prägnantes Beispiel stellt die Automobilbranche dar, die schon vor Jahren begonnen hat in ihr Geschäftsmodell um das Kernprodukt "Automobil" auch sog. produktbegleitende Dienstleistungen (wie beispielsweise Finanzierungsdienstleistungen) zu integrieren, um sich durch Erhöhung des Kundennutzens von den Angeboten der Mitbewerber zu differenzieren. Vor dem Hintergrund, dass Marketingkonstrukte, wie Marke, Reputation, Kundenloyalität, aber auch technische Spezifikationen wie Motorisierung, Ausstattung und Zubehör die Fahrzeugwahl beeinflussen, stellt sich die Autorin die Frage, inwiefern ein Zusatzangebot von reinen produktbegleitenden Dienstleistungen einen Einfluss auf die Marken- und Fahrzeugwahl beim Autokauf hat. In diesem Zusammenhang ist ein Forschungsziel der vorliegenden Untersuchung die Konzeption einer branchenunabhängigen Wertschöpfungskette für produktbegleitende Dienstleistungen, um eine Identifikation des strategischen Differenzierungspotenzials produktbegleitender Dienstleistungen zu ermöglichen. Den Bezugsrahmen der Forschungsarbeit wird dabei aus Perspektive des Endkonsumenten bei der Automobilkaufentscheidung konstruiert, um Aussagen zur Wahrnehmung existierender Angebote produktbegleitender Dienstleistungen den individuellen Phasen der Kaufentscheidung zuordnen zu können. Dies bildet das methodische Fundament dieses empirisch geprägten Forschungsbeitrags, um die folgende Frage der Untersuchung beantworten zu können: "Haben produktbegleitende Dienstleistungen einen Einfluss auf die Kaufwahrscheinlichkeit beim konsumentenseitigen Kaufentscheidungsprozess bei Automobilen im Segment des Privat-PKW?" Als Forschungsstrategie wird die Anwendung der Kausalanalyse gewählt, um anhand zwei aufeinander aufbauenden Primärerhebungen (quantitative Datenerhebung anhand eines Online-Fragebogens) potenzielle Autokäufer hinsichtlich ihres Wissens und ihrer Wahrnehmung bezüglich produktbegleitender Dienstleistungen der einzelnen Automobilherstellermarken zu untersuchen. Die Ergebnisse der Datenauswertung lassen die Schlussfolgerung zu, dass produktbegleitende Dienstleistungen zwar einen positiven Einfluss auf die Kaufentscheidung beim potentiellen Automobilkäufer ausüben, jedoch aufseiten der Automobilhersteller und -händler durchaus großes Verbesserungspotenzial bezüglich der Kommunikation von solchen Value-Added-Leistungen vorliegt. Die vorliegende Dissertationsschrift wurde am Lehrstuhl für Organisation und Strategisches Dienstleistungsmanagement verfasst und beim Fachbereich IV der Universität Trier eingereicht.
Zum Einfluss von Transformationen schiefer Verteilungen auf die Analyse mit imputierten Daten
(2015)
Die korrekte Behandlung fehlender Daten in empirischen Untersuchungen spielt zunehmend eine wichtige Rolle in der anwendungsorientierten, quantitativen Forschung. Als zentrales flexibles Instrument wurde von Rubin (1987) die multiple Imputation entwickelt, welche unter regulären Bedingungen eine korrekte Inferenz der eigentlichen Schätzungen ermöglicht. Eine Reihe von Imputationsmethoden beruht im Wesentlichen auf der Normalverteilungsannahme. In der Empirie wird diese Annahme normalverteilter Daten zunehmend kritisiert. So erweisen sich Variablen auf Grund ihrer sehr schiefen Verteilungen für die Imputation als besonders problematisch. In dieser Arbeit steht die korrekte Behandlung fehlender Werte mit der Intention einer validen Inferenz der eigentlichen Schätzung im Vordergrund. Ein Instrument ist die Transformation schiefer Verteilungen, um mit Hilfe der transformierten und approximativ normalverteilten Daten Imputationen unter regulären Bedingungen durchzuführen. In der Arbeit wird ein multivariater Ansatz eingeführt. Anschließend wird im Rahmen mehrerer Monte-Carlo-Simulationsstudien gezeigt, dass der neue Ansatz bereits bekannte Verfahren dominiert und sich die Transformation positiv auf die Analyse mit imputierten Daten auswirkt.
Fehlende Werte und deren Kompensation über Imputation stellen eine große Herausforderung für die Varianzschätzung eines Punktschätzers dar. Dies gilt auch in der Amtlichen Statistik. Um eine unverzerrte Varianzschätzung zu gewährleisten, müssen alle Komponenten der Varianz berücksichtigt werden. Hierzu wird häufig eine Zerlegung der Gesamtvarianz durchgeführt mit dem Ziel, detaillierte Informationen über ihre Komponenten zu erhalten und diese vollständig zu erfassen. In dieser Arbeit stehen Resampling-Methoden im Vordergrund. Es wird ein Ansatz entwickelt, wie neuere Resampling-Methoden, welche alle Elemente der ursprünglichen Stichprobe berücksichtigen, hinsichtlich der Anwendung von Imputation übertragen werden können. Zum Vergleich verschiedener Varianzschätzer wird eine Monte-Carlo-Simulationsstudie durchgeführt. Mit Hilfe einer Monte-Carlo-Simulation findet zudem eine Zerlegung der Gesamtvarianz unter verschiedenen Parameterkonstellationen statt.
Die vorliegende Meta-Analyse zeigt eindeutig, dass von Familienmitgliedern geführte Familienunternehmen eine schlechtere Performance aufweisen als Unternehmen, die von Managern geleitet werden, die der Inhaberfamilie nicht angehören. Basierend auf uni- und multivariaten Analysen von 270 wissenschaftlichen Publikationen aus 42 verschiedenen Ländern, wurde die Performance von Familienunternehmen im Vergleich zu Nicht-Familienunternehmen untersucht. Das erste robuste Ergebnis zeigt eindeutig, dass Familienunternehmen hinsichtlich der Performance Nicht-Familienunternehmen übertreffen. Dieses Ergebnis ist im Einklang mit den meisten Primärstudien und früheren Meta-Analysen. Das zweite Ergebnis dieser Arbeit kann dem "Finance"-Forschungszweig zugeordnet werden und basiert auf der Unterscheidung von Markt- und Accounting-Performance-Kennzahlen. Markt-Performance-Kennzahlen, welche durch Analysten errechnet werden, zeigen, dass Familienunternehmen Nicht-Familienunternehmen hinsichtlich der Performance unterlegen sind. Dieses Ergebnis steht im Gegensatz zu den Accounting-Performance-Kennzahlen, welche von den Familienunternehmen selbst in ihren von Wirtschaftsprüfern freigegebenen Bilanzen veröffentlicht wurden. Die dritte Forschungsfrage untersucht im Detail, ob die Zusammensetzung des Datensatzes in Primärstudien das Gesamtergebnis in eine bestimmte Richtung verzerrt. Das Ergebnis wird nicht durch Datensätzen mit Unternehmen, welche öffentlich gelistet, im produzieren Gewerbe tätig oder Technologie getriebene Unternehmen, sind getrieben. Kleine und Mittlere Unternehmen (KMU) veröffentlichen kleinere Kennzahlen und reduzieren somit die Höhe der abhängigen Variable. Das vierte Ergebnis gibt eine Übersicht über die Art und Weise der Beteiligung der Familie an der Aufsicht oder dem operativen Geschäft des Unternehmens. Dieses Ergebnis zeigt klar, dass Manager aus Familien einen signifikanten negativen Einfluss auf die Performance des Unternehmens haben. Dies kann auf die Erhaltung des Wohlstandes der Familienmitglieder zurückzuführen sein und somit spielen finanzielle Kennzahlen keine vordergründige Rolle. Die letzte Forschungsfrage untersucht, ob die Performance von Familienunternehmen im Vergleich zu Nicht-Familienunternehmen auch durch institutionelle Faktoren beeinflusst wird. In Europa zeigen die Familienunternehmen im Vergleich zu Nordamerika eine geringere Performance hinsichtlich der Kennzahlen. Das ist darauf zurückzuführen, dass europäische Unternehmen im Vergleich zu nordamerikanischen unterbewertet sind (Caldwell, 07.06.2014). Darüber hinaus zeigen Familienunternehmen im Vergleich zu Nicht-Familienunternehmen eine bessere Performance in eher maskulin geprägten Kulturen. Maskulinität, ist nach Hofstede, gekennzeichnet durch höhere Wettbewerbsorientierung, Selbstbewusstsein, Streben nach Wohlstand und klar differenzierte Geschlechterrollen. Rechtsregime hingegen (Common- oder Civil-Law) spielen im Performance-Zusammenhang von Familienunternehmen keine Rolle. Die Durchsetzbarkeit der Gesetze hat jedoch einen signifikanten positiven Einfluss auf die Performance von Familienunternehmen im Vergleich zu Nicht-Familienunternehmen. Dies ist damit zu begründen, dass die Kosten für Kredite in Länder mit einer sehr guten Durchsetzbarkeit von Gesetzen für Familienunternehmen geringer sind.
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.
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.
Die vorliegende empirische Untersuchung nimmt eine gezielte Betrachtung der Auswirkungen des Working Capital Managements als Ganzem sowie seiner Teilkomponenten für die operative Profitabilität und das Bonitätsrating (d.h. im Ergebnis über seine Bedeutung für die Innen- und die Außenfinanzierung) deutscher mittelständischer Unternehmen vor. Darüber hinaus wird untersucht, in wie weit größenspezifische Unterschiede bei der Wirkung der einzelnen Komponenten des Working Capital Managements auf die operative Profitabilität und das Bonitätsrating bestehen, ob also die Stärke der ggf. zu beobachtenden Effekte für kleinere Unternehmen anders ausgeprägt ist als für größere Unternehmen. Zudem wird untersucht, ob sich die Stärke der zu beobachtenden Effekte in unterschiedlichen konjunkturellen Rahmenbedingungen jeweils verändert, um Erkenntnisse darüber zu gewinnen, ob und in wie weit Working Capital Management zur Verbesserung der Krisenresistenz mittelständischer Unternehmen beitragen kann.
Weltweit untersuchen viele Wissenschaftler die Ursachen für die Entstehung und Ausdehnung industrieller Cluster. Die Ergebnisse dieser Bemühungen sind in zahlreichen empirischen Studien dokumentiert worden. Die Mehrheit der Arbeiten legt ihren Fokus auf die Entwicklung einer präzisen Messmethodik für die Konzentrationsstärke. Hierzu ist ein breites Instrumentarium an Maßzahlen bereits verfügbar und lässt sich je nach Forschungsziel erkenntnisbringend einsetzen. Dennoch bleibt die Trennung zwischen unterschiedlichen geographischen Grundmustern unzureichend. Insbesondere trifft dies auf unterschiedliche Typen der Konzentration zu. Die vorliegende Arbeit bietet eine umfassende Konzentrationsanalyse des Wirtschaftsstandorts Deutschland auf unterschiedlichen regionalen und sektoralen Aggregationsebenen. Dabei verfolgt sie das Ziel, durch eine detaillierte Untersuchung der räumlichen Verteilungsmuster der wirtschaftlichen Aktivität einen Beitrag zur Erklärung der Ansiedlungsstrukturen der einzelnen Wirtschaftszweige zu leisten. Hierfür wird eine gänzlich neue Methodik entwickelt, die das Identifizieren einer breiteren Palette an geographischen Grundmustern sowohl statisch als auch dynamisch zulässt. Da die Unterscheidung zwischen verschiedenen Typen der Konzentration bisher kaum Gegenstand wissenschaftlicher Untersuchung war, stößt der hier verfolgte Ansatz auf ein relativ neues Forschungsfeld vor. Die Existenz unterschiedlicher Typen bzw. Formen der Konzentration beruht auf einer einfachen Überlegung: Neben städtisch konzentrierten Wirtschaftszweigen muss es zwangsläufig auch ländlich konzentrierte Wirtschaftszweige geben. Hiervon ausgehend werden sieben geographische Grundmuster identifiziert. Neben dem dispersen und dem zufälligen Grundmuster wird zwischen fünf verschiedenen Typen der Konzentration unterschieden. Die Identifikation der einzelnen Grundmuster erfolgt auf Basis des Rangkorrelationskoeffizienten von Goodman-Kruskal. Dem entwickelten Ansatz wird mithilfe bivariater Konfidenzregionen eine exakte und durch statistische Signifikanz fundierte Aussagekraft verliehen. Des Weiteren wird im Rahmen der Arbeit festgestellt, dass ein Vernachlässigen der unterschiedlichen geographischen Grundmuster in inhaltlich irreführenden und fragwürdigen Konzentrationsvergleichen münden kann. Parallel dazu werden acht Indizes zur Erfassung der Konzentrationsstärke behandelt. Sie werden hinsichtlich der Datenanforderungen in drei Gruppen unterteilt und im Hinblick auf ihre Verlässlichkeit und Aussagekraft ausführlich untersucht. Die empirische Konzentrationsanalyse belegt für alle drei Gruppen, dass die durchschnittliche Konzentration der deutschen Wirtschaftsgruppen von 1995 bis 2010 kontinuierlich gefallen ist. Darüber hinaus wird in der Arbeit gezeigt, dass die Wirtschaftszweige in Deutschland sehr unterschiedlichen Konzentrationstypen folgen und dass weder die traditionellen noch die komplexen, distanzbasierten Maßzahlen imstande sind, zwischen verschiedenen Typen der Konzentration zu unterscheiden.
Kooperationen sind in den unterschiedlichsten Industrien und Wirtschaftszweigen ein fester Bestandteil zur Entwicklung von Unternehmensstrategien und vielfach die Reaktion auf branchenspezifische wie auch -übergreifende Bedingungen des Unternehmensumfeldes. Durch das Eingehen von Kooperationen wird sich erhofft Zugang zu Ressourcen zu gewinnen, Marktbarrieren zu umgehen, Kostensenkungspotenziale durch Synergieeffekte zu realisieren, spezifisches Know-how zu erlangen, Informations- und Wissenstransfer zu ermöglichen oder integrativ Kompetenzen in einem technologisierten Umfeld aufzubauen. Angesichts seit Jahren steigender weltweiter Tourismusausgaben für Urlaubsreisen, einem zunehmendem Wettbewerbsdruck zwischen Reisezielen und touristischen Anbietern sowie branchenspezifisch hoher Krisenanfälligkeit sind Kooperationen auch in der Tourismuswirtschaft omnipräsent. Vor dem Hintergrund sich wandelnder Aufgaben traditioneller Tourismusorganisationen (Touristen Info) einerseits sowie der den Kooperationen inhärenten Spannung zwischen Zusammenarbeit und Wettbewerb der beteiligten Akteure (Leistungsträger, Stakeholder) andererseits, steht im Mittelpunkt dieser Untersuchung die Frage: "Kooperationen von Destinationen: zufällige Einzelphänomen oder Entscheidungen eines strategischen Destinationsmanagements?" Dabei beschränkt sich der Untersuchungsgegenstand nicht auf Kooperationen zwischen Leistungsträgern innerhalb einer Destination, sondern setzt jene Kooperationen in den Fokus, die sowohl zwischen konkurrierenden Touristenorganisationen als auch zwischen Touristenorganisationen und nicht-originär touristischen Unternehmen zu beobachten sind. Ziel der Arbeit ist die theorie- und empiriegeleitete Exploration von Zielsystemen und Erfolgsfaktoren, um so einen Beitrag zum effektiven Kooperationsmanagement von Tourismusorganisationen liefern zu können. Somit positioniert sich diese Arbeit im Kontext der wirtschaftswissenschaftlichen Kooperationsforschung im strategischen Dienstleistungs- sowie Tourismus- und Destinationsmanagement. Basierend auf einem kritisch-reflektierenden Literaturüberblick wird ein konzeptioneller Bezugsrahmen entwickelt und die verfolgte qualitative Forschungsstrategie einer Fallanalyse in ein konkretes empirisches Untersuchungsdesign umgesetzt: die im Rahmen der Datenerhebung geführten Experteninterviews mit Geschäftsführern ausgewählter Unternehmen wurden transkribiert und mittels einer strukturierenden Inhaltsanalyse untersucht. Neben der Konzeption einer Systematisierung zu Kooperationen im Destinationskontext dienen die zentralen empirischen Ergebnisse der Identifikation neun eigenständiger Zielkategorien sowie sieben Erfolgsfaktoren. Davon abgeleitetes wird ein phasenorientiertes Entscheidungsmodell für Entscheidungsträger im Destinationsmanagement entwickelt.
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).
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.
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.
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 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.
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.