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In a world of constant change, uncertainty has become a daily challenge for businesses. Rapidly shifting market conditions highlight the need for flexible responses to unforeseen events. Operations Management (OM) is crucial for optimizing business processes, including site planning, production control, and inventory management. Traditionally, companies have relied on theoretical models from microeconomics, game theory, optimization, and simulation. However, advancements in machine learning and mathematical optimization have led to a new research field: data-driven OM.
Data-driven OM uses real data, especially time series data, to create more realistic models that better capture decision-making complexities. Despite the promise of this new research area, a significant challenge remains: the availability of extensive historical training data. Synthetic data, which mimics real data, has been used to address this issue in other machine learning applications.
Therefore, this dissertation explores how synthetic data can be leveraged to improve decisions for data-driven inventory management, focusing on the single-period newsvendor problem, a classic stochastic optimization problem in inventory management.
The first article, "A Meta Analysis of Data-Driven Newsvendor Approaches", presents a standardized evaluation framework for data-driven prescriptive approaches, tested through a numerical study. Findings suggest model performance is not robust, emphasizing the need for a standardized evaluation process.
The second article, "Application of Generative Adversarial Networks in Inventory Management", examines using synthetic data generated by Generative Adversarial Networks (GANs) for the newsvendor problem. This study shows GANs can model complex demand relationships, offering a promising alternative to traditional methods.
The third article, "Combining Synthetic Data and Transfer Learning for Deep Reinforcement Learning in Inventory Management", proposes a method using Deep Reinforcement Learning (DRL) with synthetic and real data through transfer learning. This approach trains a generative model to learn demand distributions, generates synthetic data, and fine-tunes a DRL agent on a smaller real dataset. This method outperforms traditional approaches in controlled and practical settings, though further research is needed to generalize these findings.
Diese Arbeit präsentiert ein stochastisches Überlappungsmodell von
Generationen mit endogenen Gesundheitsinvestitionen und endogenem
Mortalitätsrisiko. Dieses Modell ermöglicht es, makroökonomische und
Auswirkungen von Gesundheitsreformen in Deutschland zu quantifizieren.
Zusätzlich werden Wohlfahrtsaspekte solcher Reformen beleuchtet. Zu Beginn
der Arbeit wird ein Ausgangsgleichgewicht dargestellt, welches die Situation in
Deutschland im Jahr 2020 abbildet. Hierbei sind Individuen entweder gesetzlich
oder privat krankenversichert. Die Versicherungen unterscheiden sich hinsichtlich
der Finanzierung sowie der Behandlungskosten und -qualität. Die Arbeit
untersucht den Übergang zu einem einheitlichen System, welches entweder
umlagefinanziert ist oder mit dem Kapitaldeckungsverfahren arbeitet. Die
Simulationsergebnisse deuten darauf hin, dass die gesetzliche
Krankenversicherung und somit einkommensabhängige Beiträge mit besseren
Versicherungseigenschaften verbunden sind, die die Verzerrungen bei der
Arbeitsangebotsmenge kompensieren können, jedoch auf Kosten eines höheren
moralischen Risikos gehen. Prämienmodelle hingegen führen zu einem höheren
Arbeitsangebot und besserem Vorsorge-Verhalten in Form von Ersparnissen oder
Gesundheitsinvestitionen. Ich stellen auch fest, dass obligatorische Selbstbehalte
das aggregierte Wohlergehen in Deutschland verringern würden, obwohl sie das
moralische Risiko reduzieren und private Gesundheitsinvestitionen erhöhen.
Schließlich ist der Übergang zu einer reinen privat Versicherung für
Übergangskohorten kostspielig, was auf eine Präferenz für kostengünstigere
umlagefinanzierte Prämien aufgrund von Effizienzüberlegungen hinweist.
Der demografische Wandel im Zusammenhang mit einer alternden Bevölkerung sorgt dafür, dass Regierungen weltweit zur Reformierung ihrer Rentensysteme gezwungen werden. Ein beliebtes Mittel hierbei ist die Anhebung der Regelaltersgrenze. Diese Maßnahme ist jedoch in der Bevölkerung unbeliebt, weshalb hier nach alternativen Wegen gesucht wird, um frühzeitig in den Ruhestand einzutreten. Eine Möglichkeit, solchen angepassten Altersrentenregelungen zu entgehen, ist der Bezug einer Erwerbsminderungsrente. Deutschland schuf hier neue Anreize, in die Erwerbsminderung einzutreten, indem es die erwarteten Rentenzahlbeträge anhob. Dies ist der Ausgangspunkt der vorliegenden Arbeit, in der das Renteneintrittsverhalten und die daraus resultierenden makroökonomischen Effekte von Rentenreformen unter Verwendung eines allgemeinen Gleichgewichtsmodells untersucht werden. In diesem können Haushalte sowohl über den Zeitpunkt als auch die Art ihres Renteneintritts entscheiden, wobei sie zwischen einer Erwerbsminderungs- und einer Altersrente wählen können. Bei der Bewertung der tatsächlich realisierten Rentenreformen von 2007 und 2018 wird ersichtlich, dass die Anhebung der Regelaltersgrenze zu positiven Effekten sowohl mit Blick auf die Tragfähigkeit des Rentensystems als auch die gesamtwirtschaftliche Wohlfahrt geführt hätte. Die Realisierung dieser Gewinne wird jedoch durch die 2018 realisierte Anhebung der Zurechnungszeiten beinahe komplett zunichte gemacht. Allein die fiskalischen Auswirkungen, bei denen von Verhaltensreaktionen von Seiten der Haushalte abgesehen wird, würden fiskalische Kosten erzeugen, die ungefähr ein Drittel der zuvor generierten positiven Effekte eliminieren. Können die Haushalte komplett frei über ihre Ruhestandsentscheidung verfügen, verschwinden die zuvor generierten Wohlfahrtsgewinne sogar beinahe vollständig, und das Rentensystem sowie die makroökonomischen Größen befinden sich auf einem Niveau, das vergleichbar mit dem des Ausgangsgleichgewichts ist. Alternative Rentenreformen, basierend auf der Gesetzeslage von 2018, verdeutlichen, dass effektive Rentenpolitik nur dann funktionieren kann, wenn Alters- und Erwerbsminderungsrente als Gesamtpaket betrachtet werden. Hierdurch werden Erkenntnisse für die Gestaltung zukünftiger Rentenreformen gewonnen und die Bedeutung eines ganzheitlichen Ansatzes betont, der die verschiedenen Aspekte des Rentensystems berücksichtigt.
This thesis is about composite-based structural equation modeling. Structural equation modeling in general can be used to model both theoretical concepts and their relations to one another. In traditional factor-based structural equation modeling, these theoretical concepts are modeled as common factors, i.e., as latent variables which explain the covariance structure of their observed variables. In contrast, in composite-based structural equation modeling, the theoretical concepts can be modeled both as common factors and as composites, i.e., as linear combinations of observed variables that convey all the information between their observed variables and all other variables in the model. This thesis presents some methodological advancements in the field of composite-based structural equation modeling. In all, this thesis is made up of seven chapters. Chapter 1 provides an overview of the underlying model, as well as explicating the meaning of the term composite-based structural equation modeling. Chapter 2 gives guidelines on how to perform Monte Carlo simulations in the statistic software R using the package “cSEM” with various estimators in the context of composite-based structural equation modeling. These guidelines are illustrated by an example simulation study that investigates the finite sample behavior of partial least squares path modeling (PLS-PM) and consistent partial least squares (PLSc) estimates, particularly regarding the consequences of sample correlations between measurement errors on statistical inference. The third Chapter presents estimators of composite-based structural equation modeling that are robust in responding to outlier distortion. For this purpose, estimators of composite-based structural equation modeling, PLS-PM and PLSc, are adapted. Unlike the original estimators, these adjustments can avoid distortion that could arise from random outliers in samples, as is demonstrated through a simulation study. Chapter 4 presents an approach to performing predictions based on models estimated with ordinal partial least squares and ordinal consistent partial least squares. Here, the observed variables lie on an ordinal categorical scale which is explicitly taken into account in both estimation and prediction. The prediction performance is evaluated by means of a simulation study. In addition, the chapter gives guidelines on how to perform such predictions using the R package “cSEM”. This is demonstrated by means of an empirical example. Chapter 5 introduces confirmatory composite analysis (CCA) for research in “Human Development”. Using CCA, composite models can be estimated and assessed. This chapter uses the Henseler-Ogasawara specification for composite models, allowing, for example, the maximum likelihood method to be used for parameter estimation. Since the maximum likelihood estimator based on the Henseler-Ogasawara specification has limitations, Chapter 6 presents another specification of the composite model by means of which composite models can be estimated with the maximum likelihood method. The results of this maximum likelihood estimator are compared with those of PLS-PM, thus showing that this maximum likelihood estimator gives valid results even in finite samples. The last chapter, Chapter 7, gives an overview of the development and different strands of composite-based structural equation modeling. Additionally, here I examine the contribution the previous chapters make to the wider distribution of composite-based structural equation modeling.
Within three self-contained studies, this dissertation studies the impact and interactions between different macroeconomic policy measures in the context of financial markets empirically and quantitatively. The first study of this dissertation sheds light on the financial market effects of unconventional central bank asset purchase programs in the Eurozone, in particular sovereign bond asset purchase programs. The second study quantifies the direct implications of unconventional monetary policy on decisions by German public debt management regarding the maturity structure of gross issuance. The third study provides novel evidence on the role of private credit markets in the propagation of public spending toward private consumption in the U.S. economy. Across these three studies a set of different time-series econometric methods is applied including error correction models and event study frameworks to analyze contemporaneous interactions in financial and macroeconomic data in the context of unconventional monetary policy, as well as vector auto regressions (VARs) and local projections to trace the dynamic consequences of macroeconomic policies over time.
The contribution of this dissertation is to empirically analyze the link between income distribution, sectoral financial balances, and the current account. Firstly, it examines the relationship between the personal and the functional income distribution which may have rather different implications for aggregate demand and the current account. Secondly, it analyzes the importance of different sectors of the economy for current account balances and tests whether households are able to fully pierce the institutional veils of the corporate and the government sector. Thirdly, it investigates how changes in the personal and the functional income distribution affect the saving and investment decisions of the household and the corporate sector, and hence the current account. Finally, it shows how different growth regimes are linked to different patterns of personal and functional income distribution, and how differences in wage bargaining institutions contribute to explaining these different patterns of income distribution.
Structural equation modeling (SEM) has been used and developed for decades across various domains and research fields such as, among others, psychology, sociology, and business research. Although no unique definition exists, SEM is best understood as the entirety of a set of related theories, mathematical models, methods, algorithms, and terminologies related to analyzing the relationships between theoretical entities -- so-called concepts --, their statistical representations -- referred to as constructs --, and observables -- usually called indicators, items or manifest variables.
This thesis is concerned with aspects of a particular strain of research within SEM -- namely, composite-based SEM. Composite-based SEM is defined as SEM involving linear compounds, i.e., linear combinations of observables when estimating parameters of interest.
The content of the thesis is based on a working paper (Chapter 2), a published refereed journal article (Chapter 3), a working paper that is, at the time of submission of this thesis, under review for publication (Chapter 4), and a steadily growing documentation that I am writing for the R package cSEM (Chapter 5). The cSEM package -- written by myself and my former colleague at the University of Wuerzburg, Florian Schuberth -- provides functions to estimate, analyze, assess, and test nonlinear, hierarchical and multigroup structural equation models using composite-based approaches and procedures.
In Chapter 1, I briefly discuss some of the key SEM terminology.
Chapter 2 is based on a working paper to be submitted to the Journal of Business Research titled “Assessing overall model fit of composite models in structural equation modeling”. The article is concerned with the topic of overall model fit assessment of the composite model. Three main contributions to the literature are made. First, we discuss the concept of model fit in SEM in general and composite-based SEM in particular. Second, we review common fit indices and explain if and how they can be applied to assess composite models. Third, we show that, if used for overall model fit assessment, the root mean square outer residual covariance (RMS_theta) is identical to another well-known index called the standardized root mean square residual (SRMR).
Chapter 3 is based on a journal article published in Internet Research called “Measurement error correlation within blocks of indicators in consistent partial least squares: Issues and remedies”. The article enhances consistent partial least squares (PLSc) to yield consistent parameter estimates for population models whose indicator blocks contain a subset of correlated measurement errors. This is achieved by modifying the correction for attenuation as originally applied by PLSc to include a priori assumptions on the structure of the measurement error correlations within blocks of indicators. To assess the efficacy of the modification, a Monte Carlo simulation is conducted. The paper is joint work with Florian Schuberth and Theo Dijkstra.
Chapter 4 is based on a journal article under review for publication in Industrial Management & Data Systems called “Estimating and testing second-order constructs using PLS-PM: the case of composites of composites”. The purpose of this article is threefold: (i) evaluate and compare common approaches to estimate models containing second-order constructs modeled as composites of composites, (ii) provide and statistically assess a two-step testing procedure to test the overall model fit of such models, and (iii) formulate recommendation for practitioners based on our findings. Moreover, a Monte Carlo simulation to compare the approaches in terms of Fisher consistency, estimated bias, and RMSE is conducted. The paper is joint work with Florian Schuberth and Jörg Henseler.
This thesis contributes to the understanding of the labor market effects of international trade, with a focus on the effects on wage and earnings inequality. The thesis draws on high-quality micro data and applies modern econometric techniques and theoretical concepts to improve our understanding of the distributional effects of international trade. The thesis focuses on the effects in Germany and the USA.
This dissertation deals with composite-based methods for structural equation models with latent variables and their enhancement. It comprises five chapters. Besides a brief introduction in the first chapter, the remaining chapters consisting of four essays cover the results of my PhD studies.Two of the essays have already been published in an international journal.
The first essay considers an alternative way of construct modeling in structural equation modeling.While in social and behavioral sciences theoretical constructs are typically modeled as common factors, in other sciences the common factor model is an inadequate way construct modeling due to its assumptions. This essay introduces the confirmatory composite analysis (CCA) analogous to confirmatory factor analysis (CFA). In contrast to CFA, CCA models theoretical constructs as composites instead of common factors. Besides the theoretical presentation of CCA and its assumptions, a Monte Carlo simulation is conducted which demonstrates that misspecifications of the composite model can be detected by the introduced test for overall model fit.
The second essay rises the question of how parameter differences can be assessed in the framework of partial least squares path modeling. Since the standard errors of the estimated parameters have no analytical closed-form, the t- and F-test known from regression analysis cannot be directly used to test for parameter differences. However, bootstrapping provides a solution to this problem. It can be employed to construct confidence intervals for the estimated parameter differences, which can be used for making inferences about the parameter difference in the population. To guide practitioners, guidelines were developed and demonstrated by means of empirical examples.
The third essay answers the question of how ordinal categorical indicators can be dealt with in partial least squares path modeling. A new consistent estimator is developed which combines the polychoric correlation and partial least squares path modeling to appropriately deal with the qualitative character of ordinal categorical indicators. The new estimator named ordinal consistent partial least squares combines consistent partial least squares with ordinal partial least squares. Besides its derivation, a Monte Carlo simulation is conducted which shows that the new estimator performs well in finite samples. Moreover, for illustration, an empirical example is estimated by ordinal consistent partial least squares.
The last essay introduces a new consistent estimator for polynomial factor models.
Similarly to consistent partial least squares, weights are determined to build stand-ins for the latent variables, however a non-iterative approach is used.
A Monte Carlo simulation shows that the new estimator behaves well in finite samples.
The present thesis analyzes whether and - if so - under which conditions mergers result in merger-specific efficiency gains. The analysis concentrates on manufacturing firms in Europe that participate in horizontal mergers as either buyer or target in the years 2005 to 2014.
The result of the present study is that mergers are idiosyncratic processes. Thus, the possibilities to define general conditions that predict merger-specific efficiency gains are limited.
However, the results of the present study indicate that efficiency gains are possible as a direct consequence of a merger. Efficiency changes can be measured by a Total Factor Productivity (TFP) approach. Significant merger-specific efficiency gains are more likely for targets than for buyers. Moreover, mergers of firms that mainly operate in the same segment are likely to generate efficiency losses. Efficiency gains most likely result from reductions in material and labor costs, especially on a short- and mid-term perspective. The analysis of conditions that predict efficiency gains indicates that firm that announce the merger themselves are capable to generate efficiency gains in a short- and mid-term perspective. Furthermore, buyers that are mid-sized firms are more likely to generate efficiency gains than small or large buyers. Results also indicate that capital intense firms are likely to generate efficiency gains after a merger.
The present study is structured as follows.
Chapter 1 motivates the analysis of merger-specific efficiency gains. The definition of conditions that reasonably likely predict when and to which extent mergers will result in merger-specific efficiency gains, would improve the merger approval or denial process.
Chapter 2 gives a literature review of some relevant empirical studies that analyzed merger-specific efficiency gains. None of the empirical studies have analyzed horizontal mergers of European firms in the manufacturing sector in the years 2005 to 2014. Thus, the present study contributes to the existing literature by analyzing efficiency gains from those mergers.
Chapter 3 focuses on the identification of mergers. The merger term is defined according to the EC Merger Regulation and the Horizontal Merger Guidelines. The definition and the requirements of mergers according to legislation provides the framework of merger identification.
Chapter 4 concentrates on the efficiency measurement methodology. Most empirical studies apply a Total Factor Productivity (TFP) approach to estimate efficiency. The TFP approach uses linear regression in combination with a control function approach. The estimation of coefficients is done by a General Method of Moments approach.
The resulting efficiency estimates are used in the analysis of merger-specific efficiency gains in chapter 5. This analysis is done separately for buyers and targets by applying a Difference-In-Difference (DID) approach.
Chapter 6 concentrates on an alternative approach to estimate efficiency, that is a Stochastic Frontier Analysis (SFA) approach. Comparable to the TFP approach, the SFA approach is a stochastic efficiency estimation methodology. In contrast to TFP, SFA estimates the production function as a frontier function instead of an average function. The frontier function allows to estimate efficiency in percent.
Chapter 7 analyses the impact of different merger- and firm-specific characteristics on efficiency changes of buyers and targets. The analysis is based on a multiple regression, which is applied for short-, mid- and long-term efficiency changes of buyers and targets.
Chapter 8 concludes.
This dissertation consists of three contributions. Each addresses one specific aspect of intergenerational income mobility and is intended to be a stand-alone analysis. All chapters use comparable data for Germany and the United States to conduct country comparisons. As there are usually a large number of studies available for the United States, this approach is useful for comparing the empirical results to the existing literature.
The first part conducts a direct country comparison of the structure and extent of intergenerational income mobility in Germany and the United States. In line with existing results, the estimated intergenerational income mobility of 0.49 in the United States is significantly higher than that of 0.31 in Germany. While the results for the intergenerational rank mobility are relatively similar, the level of intergenerational income share mobility is higher in the United States than in Germany. There are no significant indications of a nonlinear run of intergenerational income elasticity. A final decomposition of intergenerational income inequality shows both greater income mobility and stronger progressive income growth for Germany compared to the United States. Overall, no clear ranking of the two countries can be identified. To conclude, several economic policy recommendations to increase intergenerational income mobility in Germany are discussed.
The second part examines the transmission channels of intergenerational income persistence in Germany and the United States. In principle, there are two ways in which well-off families may influence the adult incomes of their children: first through direct investments in their children's human capital (investment effect ), and second through the indirect transmission of human capital from parents to children (endowment effect ). In order to disentangle these two effects, a descriptive as well as a structural decomposition method are utilized. The results suggest that the investment effect and the endowment effect each account for approximately half of the estimated intergenerational income elasticity in Germany, while the investment effect is substantially more influential in the United States with a share of around 70 percent. With regard to economic policy, these results imply that equality of opportunity for children born to poor parents cannot be reached by the supply of financial means alone. Conversely, an efficient policy must additionally substitute for the missing direct transmission of human capital within socio-economically weak families.
The third part explicitly focuses on the intergenerational income mobility among daughters. The restriction to men is commonly made in the empirical literature due to women‘s lower labor market participation. While most men work full-time, the majority of (married) women still work only part-time or not at all. Especially with the occurrence of assortative mating, daughters from well-off families are likely to marry rich men and might decide to reduce their labor supply as a result. Thus, the individual labor income of a daughter might not be a good indicator for her actual economic status. The baseline regression analysis shows a higher intergenerational income elasticity in Germany and a lower intergenerational income elasticity in the United States for women as compared to men. However, a separation by marital status reveals that in both countries unmarried women exhibit a higher intergenerational income elasticity than unmarried men, while married women feature a lower intergenerational income elasticity than married men. The reason for the lower mobility of unmarried women turns out to be a stronger human capital transmission from fathers to daughters than to sons. The higher mobility of married women is driven by a weaker human capital transmission and a higher labor supply elasticity with respect to spousal income for women as compared to men. In order to further study the effects of assortative mating, the subsample of married children is analyzed by different types of income. It shows that the estimated intergenerational income elasticity of children's household incomes is even higher than that of their individual incomes. This can be seen as an indication for strong assortative mating. If household income is interpreted as a measure of children‘s actual economic welfare, there are barely any differences between sons and daughters. The intergenerational income elasticity of spousal income with respect to parental income is again relatively high, which in turn supports the hypothesis of strong assortative mating. The elasticity of the sons-in-law with respect to their fathers-in-law in Germany is even higher than that of the sons with respect to their own fathers.
Economists (should) care about regions! On the one hand this is true because macroeconomic shocks have vastly different effects across regions. The pressing topics of robotization
and artificial intelligence, Brexit, or U.S. tariffs will affect Würzburg differently than Berlin,
implying varying interests among its population, firms and politicians. On the other hand,
shocks in individual regions, such as inventions, bankruptcies or the attraction of a major
plant can, through trade and input-output linkages, magnify to aggregate effects of macroe-
conomic importance. Yet, regional heterogeneities in Germany and the complicated network
of linkages that connect regions are still not well documented nor understood. A fact that
is especially true for local labor markets that are of core interest to regional policy makers
and that also feature substantial heterogeneity.
This thesis provides a thorough quantification of such heterogeneities and an in-depth analysis of the sources and mechanisms that drive these differences.
The main subject of this dissertation is the analysis of the impact of the creation of the Eurozone on its member countries. This analysis comprises two studies that analyze this research agenda from different perspectives.
The first study compares the monetary policy of the ECB with the respective monetary policy of selected central banks of the European Monetary System (EMS). More precisely, conditional on aggregate demand and supply shocks, are there differences in the systematic central bank reaction function of the ECB and the four most important central banks of the EMS (Germany, France, Italy and Spain).
The second study analyzes the built-up of internal and external imbalances in Spain, i.e., on the housing market and in the current account, during the run-up to the financial crisis in 2007/08. The analysis differentiates between domestic Spain-specific factors and foreign Eurozone-factors that led to the macroeconomic imbalances.
The third and last study develops a price-theoretic credit supply model. In order to validate the model empirically, a credit market is estimated on the basis of data from the German credit market for enterprises. Finally, the results from the empirical exercise are compared to the predictions of the theoretic model.
Methodologically, all studies draw heavily on time series methods such as (multi-country) vector autoregressions (VARs) and time series regressions.
This dissertation is concerned with the empirical investigation of the link between globalization and labor market outcomes as well as the determinants of governmental redistribution, with a special focus on the effects of culture and diversity on the welfare state. In recent years, globalization has been criticized for adverse structural effects, e.g. increasing employment volatility and higher inequality.
Following the introduction, the second chapter investigates the relationship between growing import penetration and manufacturing employment growth in 12 OECD countries between 1995 and 2011, accounting for various model specifications, different measures of import penetration, and alternative estimation strategies. The application of the latest version of the World Input-Output Database (WIOD), which has only recently become available, enables measurement of the effect of increases in imported intermediates according to their country of origin. The findings emphasize a weak positive overall impact of growing trade on manufacturing employment. However, while intermediate inputs from China and the new EU members are substitutes for manufacturing employment in highly developed countries, imports from the EU-27 complement domestic manufacturing production. The three-level mixed model utilized implies that the hierarchical structure of the data plays only a minor role, and controlling for endogeneity leaves the results unchanged.
The findings point to ambiguous effects of globalization on labor market outcomes which increase the demand for equalizing public policies. Accordingly, the following chapter examines the relationship between income inequality and redistribution, accounting for the shape of the income distribution, different development levels, and subjective perceptions. Cross-national inequality datasets that have become available only recently allow for the assessment of the link for various sample compositions and several model specifications. The empirical results confirm the Meltzer-Richard hypothesis, but suggest that the relationship between market inequality and redistribution is even stronger when using perceived inequality measures. The findings emphasize a decisive role of the middle class, while also identifying a negative impact of top incomes. The Meltzer-Richard effect is less pronounced in developing economies with less sophisticated political rights, illustrating that it is the political channel through which higher inequality translates into more redistribution.
Chapter (4) extends the framework developed in the preceding chapter by studying the effects of culture and diversity on governmental redistribution for a large sample of countries. To disentangle culture from institutions, the analysis employs regional instruments as well as data on linguistic differences, the frequency of blood types, and the prevalence of the pathogen Toxoplasma Gondii. Redistribution is higher in countries with (1) loose family ties and individualistic attitudes, (2) a high prevalence of trust and tolerance, (3) low acceptance of unequally distributed power and obedience, and (4) a prevalent belief that success is the result of luck and connections. Apart from their direct effects, these traits also exert an indirect impact by influencing the transmission of inequality to redistribution. Finally, the findings indicate that redistribution and diversity in terms of culture, ethnic groups, and religion stand in a non-linear relationship, where moderate levels of diversity impede redistribution and higher levels offset the generally negative effect.
As a consequence of the financial crisis in 2008/09, some economists have expressed doubts about the adequacy of theoretical models, especially those that claim to model financial markets and banks. Because of these doubts, some economists are following a new paradigm based on a monetary theory rather than a commodity theory. The main difference between these two views is that in the commodity theory money does not play an essential role, whereas in a money economy every transaction is settled with money. It is therefore essential to clarify whether a theory that includes money comes to other conclusions than a theory that leaves money out.
Based on this problem, the second chapter compares the conclusions from the commodity logic of the financial system - modeled by the loanable funds theory - with the monetary logic. Following the review of the conclusions, I describe three theories about banks. The so-called endogenous money creation theory, in which the central banks control the lending of banks through prices, describes our world best.
In the third chapter, I use the endogenous money creation theory for modelling the bank credit market. In this model, banks act according to profit maximization, whereby income from lending business is generated and the costs of credit default risk and refinancing costs (including regulatory requirements) are incurred. These are the determinants of the supply of credit, which meets the demand for credit on the credit market. Credit demand is determined by borrowers who borrow from banks for consumption or investment purposes. The interplay between loan supply and demand for credit results in the equilibrium loan interest rate and the equilibrium loan volume that banks grant to non-banks. The supply and demand sides interacting on the credit market are empirically estimated for Germany over the period 1999-2014 based on the theoretical model using a disequilibirum framework, showing that the determinants from the theoretical model are statistically significant.
Building on the theoretical banking model, the fourth chapter extends the model to include the bond market. In contrast to the description in the commodity theory, the bank loan market and the bond market are fundamentally different. On the one hand, banks create money according to the endogenous money creation theory. Once the money is in circulation, non-banks can redistribute it by either using it for the purchase of goods or borrowing it for longer periods. Due to the focus on the financial system in this dissertation, the case is considered in which money is lent over the longer term. The motive of the suppliers in the bond market, i.e. those who want to lend money, is similar to that of banks, driven by profit maximization. Suppliers can generate income from interest on bonds. Costs arise from the opportunity costs of holding money as deposits, the credit default of the debtor and price losses due to changes in interest rates. The logic described is based on the idea that banks create money, i.e. they are originators of money, and the money is redistributed on the bond market and thus used several times. The two markets are linked on both the supply and demand sides. On the one hand, banks refinance themselves on the bond market in order to reduce the maturity transformation resulting from lending. In addition, consumers of credit have the option of requesting either bank loans or loans on the bond market.
After the description of the theoretical framework of the financial system consisting of the banking and bond market, the fifth chapter follows the application of the model for Quantitative Easing. It should be noted here that Quantitative Easing already influences the behaviour of credit consumers and suppliers when the central bank announces it. The four major central banks (Bank of Japan, Bank of England, Federal Reserve Bank and European Central Bank) have used the unconventional instrument of buying up bonds due to the continuing recession and the already low short-term interest rates. In the theoretical model, the central bank already influences bond market rates through the announcement, resulting in decreasing risk premiums, as the central bank acts as a lender of confidence, decreasing interest expectations (at least in the short term) and decreasing long-term interest rates overall. These three hypotheses are tested using empirical methods for the Euro area.
This dissertation contributes to the empirical analysis of economic development. The continuing poverty in many Sub-Saharan-African countries as well as the declining trend in growth in the advanced economies that was initiated around the turn of the millennium raises a number of new questions which have received little attention in recent empirical studies. Is culture a decisive factor for economic development? Do larger financial markets trigger positive stimuli with regard to incomes, or is the recent increase in their size in advanced economies detrimental to economic growth? What causes secular stagnation, i.e. the reduction in growth rates of the advanced economies observable over the past 20 years? What is the role of inequality in the growth process, and how do governmental attempts to equalize the income distribution affect economic development? And finally: Is the process of democratization accompanied by an increase in living standards? These are the central questions of this doctoral thesis.
To facilitate the empirical analysis of the determinants of economic growth, this dissertation introduces a new method to compute classifications in the field of social sciences. The approach is based on mathematical algorithms of machine learning and pattern recognition. Whereas the construction of indices typically relies on arbitrary assumptions regarding the aggregation strategy of the underlying attributes, utilization of Support Vector Machines transfers the question of how to aggregate the individual components into a non-linear optimization problem.
Following a brief overview of the theoretical models of economic growth provided in the first chapter, the second chapter illustrates the importance of culture in explaining the differences in incomes across the globe. In particular, if inhabitants have a lower average degree of risk-aversion, the implementation of new technology proceeds much faster compared with countries with a lower tendency towards risk. However, this effect depends on the legal and political framework of the countries, their average level of education, and their stage of development.
The initial wealth of individuals is often not sufficient to cover the cost of investments in both education and new technologies. By providing loans, a developed financial sector may help to overcome this shortage. However, the investigations in the third chapter show that this mechanism is dependent on the development levels of the economies. In poor countries, growth of the financial sector leads to better education and higher investment levels. This effect diminishes along the development process, as intermediary activity is increasingly replaced by speculative transactions. Particularly in times of low technological innovation, an increasing financial sector has a negative impact on economic development. In fact, the world economy is currently in a phase of this kind. Since the turn of the millennium, growth rates in the advanced economies have experienced a multi-national decline, leading to an intense debate about "secular stagnation" initiated at the beginning of 2015. The fourth chapter deals with this phenomenon and shows that the growth potentials of new technologies have been gradually declining since the beginning of the 2000s.
If incomes are unequally distributed, some individuals can invest less in education and technological innovations, which is why the fifth chapter identifies an overall negative effect of inequality on growth. This influence, however, depends on the development level of countries. While the negative effect is strongly pronounced in poor economies with a low degree of equality of opportunity, this influence disappears during the development process. Accordingly, redistributive polices of governments exert a growth-promoting effect in developing countries, while in advanced economies, the fostering of equal opportunities is much more decisive.
The sixth chapter analyzes the growth effect of the political environment and shows that the ambiguity of earlier studies is mainly due to unsophisticated measurement of the degree of democratization. To solve this problem, the chapter introduces a new method based on mathematical algorithms of machine learning and pattern recognition. While the approach can be used for various classification problems in the field of social sciences, in this dissertation it is applied for the problem of democracy measurement. Based on different country examples, the chapter shows that the resulting SVMDI is superior to other indices in modeling the level of democracy. The subsequent empirical analysis emphasizes a significantly positive growth effect of democracy measured via SVMDI.
Within three self-contained chapters, this dissertation provides new insights into the macroeconomic consequences of income inequality from a global perspective. Following an introduction, which summarizes the main findings and offers a brief overview of trends in income distribution, Chapter 2 evaluates the relationship between the labor share of income and the evolution of aggregate demand. Chapter 3 analyzes the link between income inequality and aggregate saving; and Chapter 4 directly estimates the effect of inequality and public redistribution on economic growth.
In recent decades the international migration has increased worldwide. The influx of people from different cultures and ethnic groups poses new challenges to the labor market and the welfare state of the host countries and causes changes in the social fabric. In general, immigration benefits the economy of the host country. However, these gains from immigration are unevenly distributed among the native population. Natives who are in direct competition with the new workers expect wage losses and a higher probability of getting unemployed, whereas remaining natives foresee either no feedback effects or even wage gains. On the other hand, the tax and transfer system benefits disproportionally from an influx of highly skilled immigrants. Examinations of 20 European countries in 2010 show that a higher proportion of low-skilled immigrants in the immediate neighborhood of the natives increases the difference in the demand for redistribution between high-skilled and low-skilled natives. Thus, high-skilled natives are more opposed to an expansion of the governmental redistribution. On the one hand, a higher proportion of low-skilled immigrants generates a higher fiscal burden on the welfare state. On the other hand, high-skilled natives' wages increase due to an influx of low-skilled immigrants, since relative supply of high-skilled labor increases.
In addition to the economic impact of immigration, the inflow of new citizens is accompanied by natives' fear of changes in the social environment as well as in symbolic values, such as cultural identity or natives' set of values. The latter might generate negative attitudes towards immigrants and increase the demand for a more restrictive immigration policy. On the other hand, more interethnic contact due to a higher ethnic diversity could reduce natives' information gaps, prejudices and stereotypes. This, in turn, could enhance more tolerance and solidarity towards immigrants among natives. Examinations of 18 European countries in 2014 show that more interethnic contact during everyday life reduces both the natives' social distance from immigrants and their fear of social upheaval by the presence of immigrants. However, natives' social distance from immigrants has no effect on their preference for redistribution, but their perceived threat to the national culture and social life by the presence of immigrants has a significantly negative impact on their demand for redistribution. Thus, natives’ concern about the preservation of symbolic norms and values affects the solidarity channel of their redistribution preference.
An individual's upward mobility over time or in relation to his or her parents determines his or her attitude towards the welfare state as well as the transfer of his or her opinions to his or her own children. With regard to intergenerational income mobility, Germany shows a value in the international midfield; higher than the United States (lower mobility) and lower than the Scandinavian countries (higher mobility). For example, if a father's lifetime income increases by 10 percent, his son's lifetime income increases by 4.9 percent in the United States and by 3.1 percent in Germany. Additionally, in Germany, fathers' lifetime income tends to show a higher impact on their sons' income if their incomes are higher. In the United States, fathers' lifetime incomes have a stronger influence on their sons' income at the lower and the upper end of the income distribution compared to the middle.
Taking a closer look at the intragenerational wage mobility and wage inequality in Germany, the development at the current edge is rather sobering. Since 2000 there is a steady decline in wage mobility. Furthermore, wage mobility in the services sector has been significantly lower than in the manufacturing sector since the beginning of the 2000s. This result is mainly driven by the decrease of wage mobility in the health care and social services sector. Moreover, a worker's unemployment spells and occupation have become more important in the meantime. Since 2006 the increase in the German wage inequality has markedly slowed down and wage growth between 2006 and 2013 has been even polarized, i.e. wages at the lower and at the upper end of the wage distribution have increased more than wages in the middle. However, this development can be partly attributed to the computerization and automation of the production processes. Although, there was substitution of manual routine tasks between 2001 and 2013, cognitive routine tasks are still more pronounced in the middle and at the upper end of the wage distribution. Furthermore, the latter experienced an increase in wage mobility since 2000. On the other hand, manual non-routine tasks are localized disproportionally in the middle and at the lower end of the wage distribution. Thus, the wage gains of these occupations at the lower end were compensated for by the wage losses in the middle.
This book produces three main results. First, from publicly available statistics, it can be inferred that the interest rate risk from on-balance sheet term transformation of banks in Germany exceeds the euro area average and is bound to increase even further. German banks push for shorter-term funding and hardly counteract the increased demand for longer-term loans. Within Germany, savings banks and cooperative banks are particularly engaged. Second, the supervisory interest rate shock scenarios are found to be increasingly detached both from the historic and the forecasted development of interest rates in Germany. In particular, German banks have been exposed to fewer and smaller adverse changes of the term structure. This increasingly limits the informative content of mere exposure measures such as the Basel interest rate coefficient when used as risk measures as is common practice in banking supervision and economic research. An impact assessment further supports the conclusion that the least that is required is a more comprehensive set of shock scenarios. Third and finally, there is a reasonable theoretical rationale and there is strong empirical evidence for banks' search for yield in interest rate risk. In addition to the established positive link between the term spread and the taking of interest rate risk by banks an additional negative link can be explained theoretically and there is significant empirical evidence for its existence and relevance. There is even a threshold of income below which banks' search for yield in interest rate risk surfaces openly.
The dissertation deals with the market and welfare effects of different business practices and the firm's incentives to use them: resale price maintenance, revenue sharing of a platform operator, membership fees to buyers using a platform and patent licensing.
In the second chapter we investigate the incentives of two manufacturers with common retailers to use resale price maintenance (RPM). Retailers provide product specific services that increase demand and manufacturers use minimum RPM to compete for favorable services for their products. Minimum RPM increases consumer pricesby voiding retailer price competition and can create a prisoner’s dilemma for manufacturers without increasing, and possibly even decreasing the overall service level. If manufacturer market power is asymmetric, minimum RPM tends to distort the allocation of sales services towards the high-priced products of the manufacturer with more market power. These results challenge the service argument as an efficiency defense for minimum RPM.
The third chapter deals with trade platforms whose operators not only allow third party sellers to offer their products to consumers, but also offer products themselves. In this context, the platform operator faces a hold-up problem if he uses classical two-part tariffs only (which previous literature on two-sided markets has focused on) as potential competition between the platform operator and sellers reduces platform attractiveness. Since some sellers refuse to join the platform, some products that are not known to the platform operator will not be offered at all. We discuss the effects of different platform tariffs on this hold-up problem. We find that revenue-based fees lower the platform operator's incentives to compete with sellers, increasing platform attractiveness. Therefore, charging such proportional fees can be profitable, what may explain why several trade platforms indeed charge proportional fees.
The fourth chapter investigates the optimal tariff system in a model in which buyers are heterogeneous. A platform model is presented in which transactions are modeled explicitly and buyers can differ in their expected valuations when they decide to join the platform. The main effect that the model identifies is that the participation decision sorts buyers according to their expected valuations. This affects the pricing of sellers. Furthermore diffing form the usual approach, in which buyers are ex-ante homogeneous, the platform does not internalize the full transaction surplus. Hence it does not implement the socially efficient price on the platform, also it has control of the price with the transaction fee.
The fifth chapter investigates the effects of licensing on the market outcome after the patent has expired. In a setting with endogenous entry, a licensee has a head start over the competition which translated into a first mover advantage if strategies are strategic substitutes. As competitive strategies quantities and informative advertising are considered explicitly. We find that although licensing increases the joint profit of the patentee and licensee, this does not necessarily come from a reduction in consumer surplus or other firms profits. For the case of quantity competition we show that licensing is welfare improving. For the case of informative advertising, however, we show that licensing increases prices and is thus detrimental to consumer surplus.