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The entry of a low-wage country into a world economy with pre-existing wage differentials puts the gains from trade in a former low-wage and then medium-wage country under pressure. If negotiations over the formation of a free trade area cover international transfers, there is a strong presumption that they bring about global free trade. Full compensation of the medium-wage country for the reduction in its gains from trade, however, does not necessarily occur. In the absence of international transfers the medium-wage country is never compensated when global free trade causes a reduction in its gains from trade, and it may in fact happen that the medium-wage country is not part of the equilibrium free trade area. Furthermore, the entry of a low-wage competitor may give the high-wage country an incentive to reap welfare gains in a tariff war at the expense of the medium-wage country, and capital may drain away from the medium-wage country to the high-wage country and, simultaneously, to the low-wage country., Der Eintritt eines Niedriglohnlandes in eine Weltwirtschaft mit bereits bestehenden Lohnunterschieden setzt die Handelsgewinne in einem vormals Niedriglohn- und dann Mittellohnland unter Druck. Wenn Verhandlungen über die Bildung einer Freihandelszone internationale Transferzahlungen mit einbeziehen, weist vieles darauf hin, dass sie zu globalem Freihandel führen. Eine vollständige Kompensation des Mittellohnlandes für die Minderung seiner Handelsgewinne erfolgt jedoch nicht zwangsläufig. Ohne internationale Transferzahlungen wird das Land mit mittlerem Lohnniveau nie entschädigt, wenn globaler Freihandel zu einer Verringerung seiner Handelsgewinne führt, und es kann tatsächlich vorkommen, dass das Land mit mittlerem Lohnniveau nicht Teil der Gleichgewichts-Freihandelszone ist. Darüber hinaus kann der Eintritt eines Niedriglohnkonkurrenten dem Hochlohnland einen Anreiz geben, in einem Zollkrieg auf Kosten des Mittellohnlandes Wohlfahrtsgewinne zu erzielen, und Kapital kann aus dem Mittellohnland in das Hochlohnland und gleichzeitig in das Niedriglohnland abließen.

This dissertation explores corporate social responsibility (CSR) and unethical corporate behavior (corporate social irresponsibility, CSI) in a financial context. The four research papers in this dissertation examine the relationship of CSR and CSI with financial performance in a portfolio context and analyze political, cultural, social, and firm-specific factors and their relationship with corporate scandals. This Dissertation also examines how efficient capital markets price corporate scandals and analyzes the relationship between CSR and CSI with corporate payout., Diese Dissertation befasst sich mit unternehmerischer Nachhaltigkeit (Corporate Social Responsibility, CSR) und unethischem Unternehmensverhalten (Corporate Social Irresponsibility, CSI) im Kontext finanzwirtschaftlicher Fragestellungen. Die vier Forschungsarbeiten dieser Dissertation untersuchen zum einen den Zusammenhang von CSR und CSI mit der finanziellen Performance in einem Portfoliokontext und betrachten politische, kulturelle, gesellschaftliche und unternehmensspezifische Faktoren und deren Beziehung mit Unternehmensskandalen. Weiterhin wird untersucht, wie effiziente Kapitalmärkte Unternehmensskandale bepreisen, sowie die Beziehung zwischen CSR und CSI mit Unternehmensausschüttung analysiert.

Diese Dissertation besteht aus einer Einleitung und drei empirischen Kapiteln, die sich mit verschiedenen Aspekten der Offenmarktgeschäfte der Bank of England in der Zwischenkriegszeit befassen. Offenmarktgeschäfte sind der Kauf und Verkauf von kurzfristigen Staatsanleihen. Die Einleitung definiert Instrumente und Ziele der Geldpolitik und beschreibt welche Folgen die veränderte Rolle Großbritanniens in der Welt nach dem 1. Weltkrieg für die Geldpolitik hatte. Das zweite Kapitel zeigt, wie Offenmarktgeschäfte die verfügbare Liquidität auf dem Londoner Geldmarkt erhöhen oder senken können. Dies erlaubt die kurzfristigen Marktzinsen relativ zum Leitzins zu steuern, was wiederum häufige Änderungen der Leitzinsen unnötig machte. Die empirische Analyse zeigt, dass Offenmarktgeschäfte die Wahrscheinlichkeit verändern können, dass Marktteilnehmer sich Geld bei der Diskontfazilität leihen müssen. Das dritte Kapitel zeigt, dass Offenmarktgeschäfte noch weitere Zwecke erfüllen. In der Finanzkrise von 1931 trugen Offenmarktgeschäfte dazu bei die größten Geschäftsbanken in London vor größerem Schaden zu bewahren. Der Verlust von Goldreserven wurde durch Offenmarktgeschäfte in großem Maße kompensiert und stabilisierte so die Liquidität der Geschäftsbanken. Das vierte Kapitel zeigt, dass Offenmarktgeschäfte zudem eine entscheidende Rolle bei der Stabilisierung der kurzfristigen Marktzinsen nach Kriegsausbruch 1939 spielten. Die empirische Analyse zeigt wie sorgfältig gewählte Laufzeiten von Offenmarktgeschäften dazu beigetragen haben, übermäßige Schwankungen der kurzfristigen Marktzinsen zu verhindern. Insgesamt deutet diese Dissertation darauf hin, dass die Bank of England in der Zwischenkriegszeit ähnlich einer modernen Zentralbank agierte. Kurzfristige Marktzinsen waren das operatives Ziel der Geldpolitik und nicht die Zentralbankgeldmenge. Im Jahr 1931 zog die Bank of England es vor die Geschäftsbanken zu stützen, auch wenn dies die Aufgabe des festen Wechselkurses bedeutete. This dissertation consists of an introductory chapter and three empirical chapters which deal with various aspects of open-market operations by the Bank of England during the interwar period. Open-market operations are the purchase and sale of Treasury bills. The introduction defines monetary policy implementation and describes the economic circumstances after World War I and outlines what consequences the changing role of Britain in the world had for monetary policy. The second chapter shows how open-market operations could add or drain liquidity in the London money market and help steer short-term market rates relative to the Bank rate, which made frequent changes in the Bank Rate unnecessary. The empirical analysis shows that open-market operations could change the probability of market participants having to borrow at the discount facility. The third chapter argues that in time of crisis the purpose of open-market operations goes further. During the financial crisis of 1931 open-market operations most likely helped to protect the largest clearing banks in London from severe harm. The empirical analysis shows how open-market operations offset the effect of reserves losses at an unprecedented scale and stabilized the liquidity of the London clearing banks. Chapter four examines the role of open-market operation after the outbreak of war in 1939. Open-market operations played a crucial role in stabilizing short-term market rates and preserving the London money market in its original form, most notably the London discount houses and clearing banks. The descriptive evidence shown suggests how carefully chosen maturities of open-market operations helped offset any undue disturbances to short-term market rates after the outbreak of war. Overall, this dissertation suggests that the Bank of England, not unlike modern central banks, targeted short-term market rates, not some monetary quantity, and chose banking stability over a fixed exchange rate in 1931.

Die Blockchain-Technologie revolutioniert die Interaktion zwischen Menschen durch Peer-to-Peer-Netzwerke, Kryptografie und Konsensalgorithmen. Trustless Trust ermöglicht sichere und transparente Transaktionen ohne Zwischenhändler. Trotz der zunehmenden Beliebtheit von Krypto-Assets und den damit verbundenen „Tokenomics“ hat die Öffentlichkeit immer noch kein umfangreiches Wissen über die Funktionsweisen dieser Technologie, und ein Großteil des Diskurses bleibt spekulativ. Das Hauptziel dieser Arbeit ist, die grundlegenden Prinzipien von Krytowährungen (Cryptos) und Non-Fungible Tokens (NFTs) zu untersuchen sowie eine Korrelation zwischen der Technologie und ihren Auswirkungen auf die Wirtschaft aus statistischer und wirtschaftlicher Sicht herzustellen. Um dieses Ziel zu erreichen, wird in den Kapiteln 2 und 3 der Einfluss der Blockchain-Technologie auf Ökonomie und Funktionsweise von Kryptowährungen anhand ökonometrischer Modelle und Clustering-Techniken untersucht. Kapitel 3 untersucht Kryptowirschaft und Blockchain-Funktionalität anhand empirischer Methoden, insbesondere für Coincreatoren und Investoren. Wir zeigen am Beispiel von Ethereum, dass die wirtschaftliche Leistung von Kryptowährungen durch die Gestaltung der ihnen zugrunde liegenden Blockchain-Technologie beeinflusst werden kann. Kapitel 4 untersucht die partiellen Korrelationen von Bitcoin-Renditen über neun verschiedene Zentralbörsen aus der Perspektive eines hochfrequenten, dynamischen Netzwerks. Die vorgeschlagene MHAR-CM liefert Kovarianzschätzungen, die die Besonderheiten der Kryptomärkte berücksichtigen. Das Kapitel zeigt Spillover- und Third-Party-Risiken zwischen diesen Börsen. Kapitel 5 verwendet eine Hedonische Bewertungsmethode, um den DAI Digital Art Index basierend auf dem NFT-Kunstmarkt zu konstruieren. Ein besonderer Fokus liegt auf der Nivellierung der Auswirkungen von Ausreißern mit einer einstufigen robusten Regressions-Huberisierung und einem dynamic conditional score model. Diese Arbeit verknüpft neue Technologien und Wirtschaft durch statistische Modellierung und Analyse. Durch die Bereitstellung empirischer Belege beobachten wir, wie die Blockchain-Technologie unsere Wahrnehmung von Geld, Kunst und anderen Branchen verändert. The emergence of distributed ledger technologies, such as blockchain, has revolutionized how individuals interact by enabling "trust-less trust" through peer-to-peer networks, cryptography, and consensus algorithms. This technology eliminates intermediaries and provides secure, transparent transaction methods. However, public understanding of this technology, along with "Tokenomics", remains limited, resulting in speculative discourse. The main objective of this thesis is to investigate the fundamental principles of cryptocurrencies (cryptos) and non-fungible tokens (NFTs) and establish a correlation between the technology and its economic impact from statistical and economic perspectives. To achieve this, Chapters 2 and 3 explore the influence of blockchain technology on the economic and functional performance of cryptos using econometric models and clustering techniques. Chapter 3 presents an empirical framework that offers insights to coin creators and investors regarding the interplay between cryptonomics, blockchain functionality, and market dynamics. The economic performance of cryptocurrencies, illustrated with Ethereum as an example, is shown to be affected by the design of their underlying blockchain technology. Chapter 4 examines partial correlations of Bitcoin returns across nine centralized exchanges from a high-frequency dynamic network perspective. The proposed MHAR-CM provides reasonable covariance estimates that account for the unique characteristics of crypto markets. This chapter uncovers spillover risk and counterparty risk among these exchanges. In Chapter 5, a hedonic regression approach is employed to construct the DAI digital art index for the NFT art market. Special emphasis is given to mitigating the impact of outliers using one-step robust regression Huberization and a dynamic conditional score model. The DAI index enhances our understanding of this emerging art market and facilitates observation of its macroeconomic trends. This thesis establishes a connection between emerging technologies and the economy through statistical modeling and analysis. By providing empirical evidence, we gain insights into how blockchain technology is transforming our perceptions of money, art, and various industries.

Since the late 1960s, the rising volatility of financial markets in the US has troubled econometricians and bank managers alike. Both professions have found it increasingly difficult to forecast savings deposit flows. This article explores these challenges by focusing on two developments. First, it explores the internal adjustment process among econometric models of the savings deposit market. To achieve this aim, I use the so-called FMP (MPS) macro model used by the Federal Reserve Board since 1970 and the deposit forecast model of the Philadelphia Saving Fund Society (PSFS), the oldest and largest savings bank in the US. I find that economists failed to find timeless determinants for the market for savings deposits, partly because the determinants of expectation formation of households kept changing. Instead, economists relied on a large number of time-dependent dummy variables. Second, the article shows how the conditions of the market for savings deposits shaped the demand for macroeconomic forecast models. Here, I again use PSFS as a case study. I show that the demand for econometric models in the banking industry skyrocketed in the 1970s but abated somewhat in the 1980s. While the rising volatility led bank managers to seek sophisticated tools to predict deposit flows, the deregulation of the banking industry and the accompanying change in customer behavior devalued macro models as a reliable forecast technique for individual banks. Instead, it became crucial for banks to predict the future behavior of competing institutions.

The pre-modern economy had some particularities compared to today. For one, its most important sector, agriculture, was much more vulnerable to weather shocks. Secondly, the flow of goods and information was much more cumbersome and slower, and the uncertainties associated with the mobility of people, goods and money were manifold. This led to comparatively high risks and generally higher transaction costs compared to the intrinsic value of the goods. Recent research has shown that the economic behavior of many actors in the pre-modern era was not characterized by the “alterity” postulated by older research. Using examples from agriculture, (long-distance) trade and the financial system, we show that many economic actors used their experiences to form sensible expectations about the future and acted according to a sensible purpose-means ratio, just as they do today. In commerce in particular, mechanisms to reduce uncertainty took a similar form over large parts of Europe, supporting the mobility of people, goods and money. However, we are reluctant to postulate that their economic behavior may have been informed by rational expectations in the sense of modern economic theory because this concept requires that (incalculable) uncertainty might be transformed into (calculable) risks. Such an understanding of “rationality” as the absence of uncertainty does not appreciate the degree to which pre-modern economic activity remained incalculable due not only to changing market situations but also weather shocks, cattle diseases, plagues, shipwreck, wars, uprisings and other contingencies.

We investigate the extent to which (quasi-)colonial ties played a role in the procurement of jet aircraft by airlines in the Global South. Because we do not have access to archival data on the sensitive issue of aircraft procurement, we take an indirect empirical approach. Our investigation is based on a dataset including all Western jet aircraft delivered between 1952 and 1989. We ask if, to what extent and how long airlines from former British, French, Dutch, and US (quasi-)colonies tended to buy jets from their former or, respectively, most recent colonial master. We compare the (ex-ante) expected geographical distribution of politically unbiased jet deliveries to the (ex post) actual historical and potentially biased distribution. We find that colonial ties to former colonial masters from Europe especially mattered until the early/mid 1970s when, triggered by the two oil price crises, pure economic motives gained more significance in informing procurement decisions.

Bitcoin Pricing Kernels (PKs) are estimated using a novel data set from Deribit, the leading Bitcoin options exchange. The PKs, as the ratio between risk-neutral and physical density, dynamically reflect the change in investor preferences. Thus, the PKs improve the understanding of investor expectations and risk premiums in a new asset class. Bootstrap-based confidence bands are estimated in order to validate the results. Investors are heterogeneous in their risk profiles and preferences with respect to volatility and investment horizon. The empirical PKs turn out to be U-shaped for short-dated instruments and W-shaped for long-dated instruments. We find that investors are willing to pay a substantial risk premium to insure themselves against short-term price movements. The risk premium is smaller for longer-dated instruments and their traders are risk averse. The shape of the empirical PKs reveals the existence of a time-varying risk premium. The similarity between the shape of empirical PKs for Bitcoin and other markets that represent aggregate wealth shows that Bitcoin is becoming an established asset class. Deutsche Forschungsgemeinschaft Czech Science Foundation

The notion of a nation-specific inflation trauma among the German population is ubiquitous in the public debate in Germany and beyond. Because of its experience with hyperinflation in 1923, the German population fears rising prices and favors stability-oriented monetary as well as fiscal policy. It is less clear, however, whether this contemporary understanding of the German inflation trauma is as old as its historical point of reference. The majority of the literature presumes that such a traumatic disposition has persisted since 1923 and has been transposed intergenerationally (persistence thesis). Others, however, point to an ex-ante reconstruction of past experiences (reconstruction thesis). By employing an interdisciplinary approach of methodological triangulation drawing on both methods of history and political sciences, we provide new insights on the question of origin. Specifically, we examine the remembrance of hyperinflation in personal memoirs and the German Bundestag in regard to the monetary and fiscal policy lessons connected to memories of 1923. Doing so, we find support for the logic of reconstruction. We show that the hyperinflation was not remembered unambiguously, and that memories were not immediately linked to specific policy lessons. Only from the 1980s onwards, a process of discursive alignment occurred that mirrors the contemporary understanding of the inflation trauma. By providing this insight, our paper allows to better understand the historical origins of today’s popular memory and its political uses. Not Reviewed

This paper studies the effect of public child care on mothers’ career trajectories. To this end, we combine county-level data on child care coverage with detailed individual-level information from the German social security records and exploit a set of German reforms leading to a substantial temporal and spatial variation in child care coverage for children under the age of three. We conduct an event study approach that investigates the labor market outcomes of mothers in the years around the birth of their first child. We thereby explore career trajectories, both in terms of quantity and quality of employment. We find that public child care improves maternal labor supply in the years immediately following childbirth. However, the results on quality-related outcomes suggest that the effect of child care provision does not reach far beyond pure employment effects. These results do not change for mothers with different ‘career costs of children’., CEPA Discussion Papers; 64

The article processing charge was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 491192747 and the Open Access Publication Fund of Humboldt-Universität zu Berlin. Malnutrition continues to be a major problem with negative implications on economic and human development in many parts of the world, including in Sub-Saharan Africa (SSA). Strengthening promising underutilized crops that are nutrient dense, climate resilient, and locally adaptable is an instrumental approach to enhancing dietary diversity. Due to their nutritional and economic benefits, African Indigenous Vegetables (AIVs) have the potential to contribute to livelihoods and address challenges of food and nutrition insecurity. Despite their importance but due to their perishability, AIVs tend to suffer from high post-harvest losses (PHLs). Effective distribution systems along the value chain have the potential to reduce PHLs for AIVs. We therefore conducted a scoping review on transport systems and coordination in AIVs value chains in SSA. The objectives of this review were to summarize and analyze the focus of research in AIVs transport, to analyze the extent to which the literature synthesizes interactions of sub-components of the chains, and to identify knowledge gaps in AIVs transport literature. Based on the research foci, we categorize the reviewed articles into seven themes. Our analyses indicate that distance to agricultural market is a fundamental aspect of AIVs transportation, as it interacts with transport costs, market participation, produce quality, and profit efficiency. Results show that collective action is instrumental in the coordination of AIVs transportation and that it contributes to cost reduction. Following light exploration of determinants of choice of means of transport, we recommend further research in this area for improvement of transportation in AIVs value chains.

Diese Dissertation umfasst drei Aufsätze zu Mindestlöhnen, zum Arbeitsangebot sowie zu öffentlichen Finanzen. Der Fokus liegt auf den Entwicklungen in Deutschland innerhalb der letzten zwei Jahrzehnte. Der erste Aufsatz untersucht Beschäftigungseffekte des Mindestlohns in einem Modell der Sucharbeitslosigkeit. Das Modell bildet Heterogenität auf Arbeitnehmer- und Arbeitgeberseite ab und schränkt die Richtung der Beschäftigungseffekte ein. Es erlaubt eine unterschiedliche Frequenz der Stellensuche von Beschäftigten und Arbeitslosen und modelliert die Rekrutierungsintensität der Unternehmen. Die Ergebnisse zeigen, dass die Arbeitslosigkeit eine nicht-monotone Funktion des Mindestlohns ist. Die Auswirkungen von verschiedenen Mindestlöhnen unterscheiden sich stark nach Arbeitsmarktsegmenten. Der zweite Aufsatz befasst sich mit Trends im Arbeitsangebotsverhalten in Deutschland. Dazu werden diskrete Wahlmodelle des Arbeitsangebots für die Jahre von 1998 bis 2018 geschätzt. Die implizierten Arbeitsangebotselastizitäten haben in den letzten zwei Jahrzehnten zugenommen, insbesondere für Paare und für alleinstehende Männer. Eine Zerlegungsanalyse zeigt, dass Veränderungen in der Demografie nur eine geringe Rolle bei der Verschiebung der Eigen- und Kreuzlohnelastizitäten von Männern spielen, da der größte Teil der Veränderungen durch Präferenzen oder Arbeitsmarktrestriktionen bedingt ist. Bei Frauen hingegen spielen demografische Veränderungen eine größere Rolle für den Anstieg der Elastizitäten. Der dritte Aufsatz befasst sich mit den deutschen Staatsfinanzen sowie mit Reformen aufgrund der Finanzkrise 2008/2009. Der Aufsatz stellt die makroökonomische Situation und die Entwicklung der Krise in Deutschland dar und beleuchtet die Bedeutung für die öffentlichen Finanzen. In dem Aufsatz werden zudem die Verteilungswirkungen der Reformen im Steuer- und Transfersystem mithilfe von Mikrosimulationen untersucht. This dissertation consists of three essays on the minimum wage, labour supply, and public finances. The selected essays focus on the German experience and developments over the last two decades. The first essay is an analysis of unemployment effects of the German minimum wage in an empirical equilibrium job search model. The estimated model with worker and firm heterogeneity does not restrict the sign of employment effects a priori; it allows for different job offer arrival rates for the employed and the unemployed and lets firms optimally choose their recruiting intensity. Results show that unemployment is a non-monotonic function of the minimum wage level, and effects differ strongly by labour market segment. The second essay is on the topic of labour supply elasticities in Germany. In order to analyse recent trends in labour supply in Germany, a static discrete choice model of unitary household labour supply is estimated for each year 1998 to 2018. Findings are that own-wage labour supply elasticities implied by the models have increased over the last two decades, especially for couples, and for single males. A decomposition analysis shows that compositional changes in demographics play only a minor role in the shift in males' own- and cross-wage elasticities, since most of the changes in elasticities are driven by preferences or labour market restrictions. For females, changes in composition play a bigger role in the rise of elasticities. The third essay reviews German public finances through the financial crisis 2008/2009. The essay starts with a presentation of the macroeconomic situation and how the crisis unfolded in Germany, before focusing on the situation of the public finances. Finally, the distributional effects of policy responses to the financial crisis are analysed on the individual level using microsimulation.

Leveraging two cohort-specific pension reforms, this paper estimates the forward-looking effects of an exogenous increase in the working horizon on (un)employment behaviour for individuals with a long remaining statutory working life. Using difference-in-differences and regression discontinuity approaches based on administrative and survey data, I show that a longer legal working horizon increases individuals’ subjective expectations about the length of their work life, raises the probability of employment, decreases the probability of unemployment, and increases the intensity of job search among the unemployed. Heterogeneity analyses show that the demonstrated employment effects are strongest for women and in occupations with comparatively low physical intensity, i.e., occupations that can be performed at older ages., CEPA Discussion Papers; 63

We investigate the impact of governmental restrictions on the short-term risk perception, as proxied by the going-in cap rate, of investors in regional and neighborhood shopping centers. We use the COVID-19 pandemic as a natural experiment and proxy for the length and severity of COVID-19 restrictions with the political affiliation of state governors. Using a sample of 40 metropolitan statistical areas (MSAs) across 27 states over the period of 2018 to 2021, we find that for states with Republican governors, which proxy for shorter and fewer COVID-19 restrictions, investors in regional malls required a lower going-in cap rate in the pandemic period than for states with Democratic governors. This effect does not exist for neighborhood shopping centers, whose tenants were not as affected by COVID-19 restrictions. Robustness checks suggest that our findings can be explained with mask mandates as one type of governmental restrictions, and that COVID-19 related restrictions do not impact the long-term risk perception of retail real estate investors. We furthermore find that the political attitudes of an MSA have an impact on investor risk perception.

In this article, we examine the accuracy and bias of market valuations in the U.S. commercial real estate sector using properties included in the NCREIF Property Index (NPI) between 1997 and 2021 and assess the potential of machine learning algorithms (i.e., boosting trees) to shrink the deviations between market values and subsequent transaction prices. Under consideration of 50 covariates, we find that these deviations exhibit structured variation that boosting trees can capture and further explain, thereby increasing appraisal accuracy and eliminating structural bias. The understanding of the models is greatest for apartments and industrial properties, followed by office and retail buildings. This study is the first in the literature to extend the application of machine learning in the context of property pricing and valuation from residential use types and commercial multifamily to office, retail, and industrial assets. In addition, this article contributes to the existing literature by providing an indication of the room for improvement in state-of-the-art valuation practices in the U.S. commercial real estate sector that can be exploited by using the guidance of supervised machine learning methods. The contributions of this study are, thus, timely and important to many parties in the real estate sector, including authorities, banks, insurers and pension and sovereign wealth funds.

Road Network Performance (RNP) impacts economic, ecological, and social sustainability. Nonetheless, models for road transport cost estimation often fail to account for the regional specificity of RNP. While the availability of suitable tools, data sources, and computational capacities to measure concrete RNP on a wide scale has steadily increased across a multitude of academic fields, it remains unclear why researchers and practitioners alike do not leverage them more heavily to improve estimations of transportation impact. This dissertation integrates achievements on the topic of location intelligence to develop and present efficient methodologies for incorporating diverse data sources to allow for better estimation of RNP and its impact on the economic and ecological dimensions of sustainability., Die Road Network Performance (RNP) wirkt sich auf die wirtschaftliche, ökologische und soziale Nachhaltigkeit aus. Dennoch berücksichtigen Modelle zur Schätzung von Straßenverkehrskosten häufig nicht die regionalen Besonderheiten der RNP. Während die Verfügbarkeit geeigneter Instrumente, Datenquellen und Rechenkapazitäten zur Messung konkreter RNP in großem Maßstab in einer Vielzahl von akademischen Bereichen stetig zugenommen hat, bleibt unklar, warum Forscher und Praktiker diese nicht stärker nutzen, um die Abschätzung der Auswirkungen des Verkehrs zu verbessern. In dieser Dissertation werden die Errungenschaften auf dem Gebiet der Standortintelligenz integriert, um effiziente Methoden für die Einbeziehung verschiedener Datenquellen zu entwickeln und zu präsentieren, die eine bessere Abschätzung der RNP und ihrer Auswirkungen auf die wirtschaftlichen und ökologischen Dimensionen der Nachhaltigkeit ermöglichen.

Research comprising this dissertation highlights that the changing retail landscape impacts the risk perception of investors in general-purpose shopping centers and asset pricing in the US American market. While threats emerging from an increased online and discount competition as well as the recent COVID-19 pandemic have been found to impact risk perception and asset pricing overall, the results also show that investors do not only price general uncertainties, but consider property-type and characteristic specific risks when valuing assets and making pricing decisions., Die Forschungsergebnisse dieser Dissertation verdeutlichen, dass die sich wandelnde Einzelhandelslandschaft die Risikowahrnehmung von Investoren in Einkaufszentren im US-amerikanischen Markt beeinflusst und sich auf die Vermögenspreisbildung auswirkt. Während Bedrohungen durch zunehmenden Online- und Discount-Wettbewerb sowie die COVID-19-Pandemie insgesamt die Risikowahrnehmung und Vermögenspreisbildung beeinflussen, zeigen die Ergebnisse darüber hinaus, dass Investoren bei der Bewertung von Vermögenswerten und Preisentscheidungen nicht nur allgemeine Unsicherheiten, sondern auch risikospezifische Merkmale und spezifische Eigenschaften der Liegenschaften berücksichtigen.

Intertemporal choices are affected by both discount rate and utility curvature. We investigate how the two aspects of time preference are affected by the size of the total budget using an intertemporal allocation task. At the aggregate level as well as at the individual level, we find magnitude effects both on the discount rate and on intertemporal substitutability (i.e., utility curvature). Individuals are more patient when dealing with larger budgets and also regard larger budgets to be more fungible. The latter effect suggests that the degree of asset integration is increasing in the stake. Nederlandse Organisatie voor Wetenschappelijk Onderzoek http://dx.doi.org/10.13039/501100003246 Deutsche Forschungsgemeinschaft Humboldt-Universität zu Berlin (1034)

Bribery is a complex and critical issue in higher education (HE), causing severe economic and societal harm. Traditionally, most scholarship on HE corruption has focused on institutional factors in developing countries and insights into the psychological and motivational factors that drive HE bribery on the micro-level mechanisms are virtually non-existent. To close this research gap, this study investigates the connection between study-related burnout and university students’ willingness to offer bribes to their lecturers to pass important exams. Conducting a vignette-based quasi-experimental replication study with 624 university students in Germany, Belgium, and the Netherlands we find that university students in three countries differentiate sharply between different shades of bribery and that a majority accept using emotional influence tactics to pass (failed) exams. In contrast, offering a helping hand or money (i.e., darker shades of bribery) to their lecturer was less acceptable. Study-related burnout is associated with a higher likelihood of engaging in these darker shades of bribery and students’ commitment to the public interest is but a weak factor in preventing unethical behavior. In summary, this study provides solid empirical evidence that university students are likely to use emotional influence tactics violating both the ethical codes of conduct and the formalized bureaucratic procedures of HE examination, particularly if they suffer from study-related burnout. However, the accelerating effect of burnout on bribery is conditional in that it only holds for darker shades of bribery. HE institutions may benefit from implementing the four-eye principle and from launching awareness campaigns that enable lecturers to better recognize these tactics and engage students in creating a transparent environment for testing, grading, and collaboration that is resistant to bribery. Supplementary Information The online version contains supplementary material available at 10.1007/s11162-021-09669-1.

The thesis extends the real estate literature by exploring extreme loss risk factors of REITs and the economics of green retrofit measures in an analytical, systematic, and critical manner. The results on the one hand aim to provide a new framework for rendering modern real estate risk management more resilient to extreme risks. On the other hand, the dissertation provides insights into practice relevant climate risk mitigation., Die Dissertation erweitert die Immobilienliteratur, indem sie extreme Verlustrisikofaktoren von REITs und die Wirtschaftlichkeit grüner Sanierungsmaßnahmen analytisch, systematisch und kritisch untersucht. Die Ergebnisse zielen einerseits darauf ab, einen neuen Rahmen zu schaffen, um das moderne Immobilienrisikomanagement widerstandsfähiger gegenüber extremen Risiken zu machen. Andererseits gibt die Dissertation Einblicke in praxisrelevante Klimarisikominderung.

The challenges facing the reinsurance industry remain considerable. For the reinsurance sector, 2022 was marked not only by the ongoing coronavirus pandemic and claims due to natural disasters but also by the war in Ukraine, the energy crisis and inflation. The Cologne Research Centre for Reinsurance analyses the latest developments in the reinsurance market and, where appropriate, monitors these through research projects. In the process, the Research Centre for Reinsurance links its research activities with practices in the reinsurance sector. Hereby, and facilitated through organisation of the annual Cologne Reinsurance Symposium and the Annual Meeting of the Sponsoring Group Reinsurance [Förderkreis Rückversicherung], a bi-directional transfer of knowledge between theory and practice is pursued. Unfortunately the Cologne Reinsurance Symposium for 2022 had to be cancelled due to COVID-19. The content of these two scientific events, as well as the completed research projects, are incorporated into scholarship and instruction at the Institute of Insurance Studies, rounding out practice-oriented training in the field of reinsurance. There are eight researchers and four professors currently on the staff of the Cologne Research Centre for Reinsurance. Thereby, all material and personnel costs are fully financed by third-party funds provided by the Sponsoring Group Reinsurance. This funding helped facilitate the doctorate of Mr Frank Cremer, among other things. At the 14th Annual Meeting of the Sponsoring Group Reinsurance held in 2021, the decision was taken to continue to provide financial support to the non-profit organisation ‘Hilfe für Guinea e.V.’ Through its annual donation to this project, the Cologne Research Centre for Reinsurance fulfils the criterion of ‘social commitment’ required of an official research focus. The donation will benefit the La Lumière Scolaire project. This project finances the construction and operation of schools for the children of disabled and homeless people in Guinea. The Cologne Research Centre for Reinsurance is accredited as an official research focus of the Cologne University of Applied Sciences., Publikationen der Kölner Forschungsstelle Rückversicherung; 2/2023

This thesis is designed to shed light on novel aspects of the housing market, which is influenced in recent years by different trends. The data quality and quantity increased rapidly through Big Data, which affects fundamental and non-fundamental variables of the housing market. Furthermore, Artificial Intelligence and Machine Learning, which pave the way for more efficient and fine-grained market analysis and property valuations and eXplainable Machine Learning (XAI), which brings explainability to the complex hidden mechanics of ML approaches. This dissertation finds a way to blur the boundaries of well-established and newly designed approaches, which is not only important for housing markets but is also transferable to other fields of research., Diese Arbeit beleuchtet neue Aspekte des Wohnungsmarktes, welcher in den letzten Jahren von verschiedenen Trends beeinflusst wurde. Die Datenqualität und -quantität hat durch Big Data stark zugenommen, was sich auf fundamentale und nicht-fundamentale Variablen des Wohnungsmarktes auswirkt. Darüber hinaus ebnen künstliche Intelligenz und Machine Learning den Weg für effizientere Marktanalysen und Immobilienbewertungen sowie für eXplainable Machine Learning (XAI), das die komplexen Mechanismen von Machine Learning-Ansätzen erklärbar macht. In dieser Dissertation wird ein Weg gefunden, die Grenzen zwischen etablierten und neu entwickelten Ansätzen zu verwischen, was nicht nur für Wohnungsmärkte wichtig ist, sondern auch auf andere Forschungsbereiche übertragbar ist.

Self-efficacy reflects the self-belief that one can persistently perform difficult and novel tasks while coping with adversity. As such beliefs reflect how individuals behave, think, and act, they are key for successful entrepreneurial activities. While existing literature mainly analyzes the influence of the task-related construct of entrepreneurial self-efficacy, we take a different perspective and investigate, based on a representative sample of 1,405 German business founders, how the personality characteristic of generalized self-efficacy influences start-up performance as measured by a broad set of business outcomes up to 19 months after business creation. Outcomes include start-up survival and entrepreneurial income, as well as growth-oriented outcomes such as job creation and innovation. We find statistically significant and economically important positive effects of high scores of self-efficacy on start-up survival and entrepreneurial income, which become even stronger when focusing on the growth-oriented outcome of innovation. Furthermore, we observe that generalized self-efficacy is similarly distributed between female and male business founders, with effects being partly stronger for female entrepreneurs. Our findings are important for policy instruments that are meant to support firm growth by facilitating the design of more target-oriented offers for training, coaching, and entrepreneurial incubators., CEPA Discussion Papers; 61

Diese Dissertation umfasst drei Studien. Die erste Studie untersucht Overprecision („Überpräzision“). Ich untersuche, wie Menschen Spannweitenschätzungen vornehmen. Teilnehmende müssen die Größe der Spannweite (Präzision) mit der Wahrscheinlichkeit, dass sie den wahren Wert einschließt (Richtigkeit) balancieren. Die Ergebnisse zeigen, dass Menschen inhärente individuelle Vorlieben für Präzision zu haben scheinen. Gleichzeitig werden vorhersagbar zusätzliche Informationen genutzt, um die Richtigkeit der Schätzungen zu erhöhen. Dafür wird entweder Präzision geopfert, oder die Spannweitenschätzung insgesamt verschoben. Die Richtigkeit der Schätzung wird jedoch nicht maximiert, sondern ein Teil für höhere Präzision aufgegeben. Die zweite Studie untersucht, wie sich die Übersetzung von Finanzberichterstattung auf die Wahrnehmung einer Firma als attraktives Investment auswirkt. Sie beleuchtet drei verschiedene Kanäle: Lesbarkeit, Stimmung, und Präzision der Veröffentlichung. In einem Umfrageexperiment lesen Kleinanleger deutsche und englische Prognoseberichte deutscher Firmen. Die Ergebnisse zeigen, dass die deutschen Berichte als besser lesbar wahrgenommen werden. Im Gegensatz zu vorheriger Literatur ist die Lesbarkeit nicht mit einer höheren Investmentattraktivität korreliert. Allein die Stimmung des Textes zeigt eine Korrelation mit höherer Attraktivität. Die dritte Studie untersucht, wie das Angebot von formativen Onlinetests die Leistungen von Studierenden in der Klausur beeinflusst. Sie untersucht zudem, ob die Leistung sich unterscheidet, je nachdem ob die Studierenden zeitlich begrenzten Zugang zu den Tests haben oder ob sie jederzeit auf die Tests zugreifen können. Ein Experiment, welches es ermöglicht den kausalen Intention-to-treat-Effekt zu bestimmen, zeigt, dass die formativen Onlinetests die Studienleistung erhöhen können, allerdings nur für Studierende, welche sich nicht freiwillig für die Tests gemeldet hatten und in der kontinuierlichen Lerngruppe waren., This dissertation comprises three papers. The first study examines overprecision. I examine how people provide range estimates, a challenging task that requires people to balance the width of the range (i.e., its precision) with the probability of the range covering the true value (i.e., accuracy). I find that people appear to have inherent individual preferences for a certain level of precision. At the same time, they appear to predictably incorporate additional information in order to increase accuracy by either sacrificing precision or shifting their ranges altogether. Still, they do not seem to maximise accuracy, but are willing to expend some of it to provide more precise estimates. The second study examines how the translation of financial disclosures changes investors’ perceptions of firms as an attractive investment. It examines three possible channels: readability, tone, and precision of the underlying disclosure. In a survey experiment, retail investors read forecast reports of German firms, provided in German and English. The findings indicate that the German versions are easier to read. Contrary to prior literature, the easier readability does not translate into higher investment attractiveness. Solely tone appears to be correlated with investment attractiveness. The third study analyses how offering formative online assessments influences student performance in the final exam. It further examines whether students perform differently depending on whether they have time-restricted access to the assessments, or whether they can access the assessments at any time. An experiment which allows for the identification of the causal intention-to-treat effect shows that offering formative online assessments can enhance student performance, but only for students who do not opt for taking the test voluntarily and who are in a continuous learning environment.

Recently, much attention has been devoted to the measurement of macroeconomic (expectation) uncertainty and its impact on aggregate economic fluctuations. This paper presents a new qualitative measure of macroeconomic expectation uncertainty based on data from a German online survey of consumer expectations. I document that the survey design works well. Elicited expectation uncertainty is related to data volatility and conventional measures of uncertainty as expected. Its dependency on socioeconomic factors is in line with previous evidence based on quantitative uncertainty measures. The new measure offers a very efficient way of eliciting expectation uncertainty and can be used to obtain uncertainty measures on many different expectations at low cost.

In a knowledge-based economy, scientists in research organizations play a key role as producers of new academic knowledge; however, they are also responsible for commercializing this knowledge. Thus, universities and public research organizations have experienced substantial organizational changes, which have come along with various managerial challenges. Unfortunately, the results of these reorganization efforts are far behind expectations: most patents never get licensed, the growth of spin-offs is far behind that of other start-ups, and scientists still view commercialization as a burden or something “nice to have,” rather than essential. This dissertation argues that a change in behavior among scientists and executives will only occur if commercialization is successfully anchored as part of the organizational structure and hence new behavioral routines are stimulated. Therefore, this dissertation aims to expand and deepen the understanding of the behavior of individuals involved in the commercialization of academic knowledge. It uses insights on organizational behavior and human resource management to obtain a profound understanding of the individuals involved. In this dissertation, the topic is examined from four different angles. First, this dissertation examines previous literature on commercialization to identify determinants that have been proven to increase or decrease the commercialization of academic knowledge in research organizations. This review reveals 97 determinants, which are categorized along six commercialization channels and the following five classes: environmental, individual, institutional, organizational, and technological. Second, this dissertation explores the phenomenon of serial patentees, providing insights into how commercial support infrastructure should be adopted according to the kind and timing of academic inventors’ prior patent experiences. Third, this dissertation addresses how the bounded rationality of scientists hinders them from finding the best industry partner for their commercial activities; then, it develops a supervised learning approach to support decision making in industry partner selection. Finally, it empirically addresses the question of how university knowledge transfer offices enable the intrinsic motivation of their employees through satisfying their three psychological needs (for relatedness, competence, and autonomy), developing a framework of university- and organizational-level antecedents. Depending on the research question, a variety of different methods and data are used. The chapters encompass a meta-analysis based on 99 published articles, a survival analysis based on recurrent patenting data, an explorative qualitative approach based on four case studies, and the testing of a supervised learning approach using cooperation and company data. The findings of this dissertation provide valuable insights for decision makers in research organizations, transfer professionals, and policy makers who seek a solid micro-foundation for the behavior of individuals involved in the commercialization of research results. These insights can be used to design organizational contexts and support that truly change their commercial behavior and routines., In einer wissensbasierten Ökonomie kommt Wissenschaftler*innen in Forschungseinrichtungen eine besondere Rolle, als Produzente*innen und Verwerter*innen von akademischem Wissen, zu. Daher haben Universitäten und öffentliche Forschungseinrichtungen in den letzten Jahren gravierende organisatorische Veränderungen durchlaufen, die mit verschiedensten Managementherausforderungen einhergehen. Jedoch sind die Ergebnisse dieser Reorganisationsbemühungen weit hinter den Erwartungen, beispielsweise wird der Großteil der Patente nie lizenziert, Spin-offs wachsen wesentlich langsamer als andere Start-Ups und viele Wissenschaftler*innen betrachten die Kommerzialisierung immer noch als zusätzliche Belastung oder als „nice-to-have“ anstatt als wesentliche Aufgabe. Im Rahmen dieser Dissertation wird argumentiert, dass eine Verhaltensänderung bei Wissenschaftler*innen und anderen beteiligten Individuen nur dann eintreten wird, wenn Kommerzialisierung als Teil der Organisationsstruktur verankert wird und neue Verhaltensroutinen etabliert werden. Daher ist das Ziel dieser Arbeit das Verständnis für die Beweggründe und das Verhalten der an der Kommerzialisierung beteiligten Personen zu erweitern und zu vertiefen. Dazu werden die Erkenntnisse aus den Gebieten des Organisationsverhaltens und des Personalmanagements genutzt, um die beteiligten Individuen besser zu verstehen und Handlungsempfehlungen abzuleiten. Die vorliegende Dissertation untersucht die genannte Problematik in den folgenden Kapiteln aus vier verschiedenen Blickwinkeln. Zunächst wird die bisherige Literatur zur Kommerzialisierung untersucht, um jene Erfolgsfaktoren zu ermitteln, die nachweislich die Kommerzialisierung von akademischem Wissen steigern. Dabei werden 97 Erfolgsfaktoren identifiziert, welche entlang von sechs Transferkanälen und fünf Dimensionen klassifiziert werden: externe, individuelle, institutionelle, organisatorische und technologische Faktoren. Daraufhin wird das Phänomen der seriellen Patentierer*innen untersucht und Empfehlungen für eine verbesserte Unterstützungsinfrastruktur abgeleitet, je nach Art und Zeitpunkt der früheren Patenterfahrungen der Patentierer*innen. Als Nächstes befasst sich diese Dissertation mit der Frage, wie die begrenzte Rationalität von Wissenschaftler*innen sie daran hindert, den geeignetsten Industriepartner für ihre kommerziellen Aktivitäten zu finden. Dazu wird ein auf maschinellem Lernen beruhender Ansatz entwickelt und getestet. Dieser unterstützt die Entscheidungsfindung bei der Auswahl von Industriepartnern. Schließlich wird empirisch der Frage nachgegangen, wie die intrinsische Motivation Mitarbeitenden in Transferbüros gefördert werden kann. Im Ergebnisse stehen die notwendigen Vorläufer intrinsischer Motivation auf Universitäts- und Organisationsebene. Je nach Fragestellung werden in dieser Dissertation unterschiedliche Methoden und Daten verwendet. Dies umfasst eine Meta-Analyse auf Basis von 99 veröffentlichten Artikeln sowie eine Ereigniszeitanalyse auf der Grundlage von Patent-, Publikations- und Personaldaten. Zudem verfolgt eine Studie einen qualitativen Ansatz auf der Grundlage von vier Fallstudien und es wird ein „Supervised learning approach“ auf Basis von Kooperations- und Unternehmensdaten entwickelt. Die Ergebnisse dieser Dissertation liefern wertvolle Erkenntnisse für Entscheidungsträger in Forschungsorganisationen, Transferfachleute und politische Entscheidungsträger, die daran interessiert sind, organisatorische Kontexte und Unterstützungsprogramme, auf Basis von fundierten Erkenntnissen über die Mikro-Prozesse der an der Kommerzialisierung beteiligten Personen, zu gestalten.

We propose to treat survey-based density expectations as compositional data when testing either for heterogeneity in density forecasts across different groups of agents or for changes over time. Monte Carlo simulations show that the proposed test has more power relative to both a bootstrap approach based on the KLIC and an approach which involves multiple testing for differences of individual parts of the density. In addition, the test is computationally much faster than the KLIC-based one, which relies on simulations, and allows for comparisons across multiple groups. Using density expectations from the ECB Survey of Professional Forecasters and the U.S. Survey of Consumer Expectations, we show the usefulness of the test in detecting possible changes in density expectations over time and across different types of forecasters.

Leading academics have repeatedly called for research in the field of Information Systems (IS) to address one of the major issues of mankind: global warming. One area in which IS research can contribute to this challenge is the design of digital solutions to support decision-making for more sustainable practices. Addressing this call for research, I engaged in an extensive research agenda on how to design User Interfaces (UI) so that they support user decisions for regional – an thus, commonly more sustainable – products and services. This cumulative dissertation presents the results of this research. I found a very suitable object of study in the electricity market – and thanks to the sector’s characteristics, findings should be easily transferable to other contexts. At first, the thesis provides a look at the sector which is currently disrupted by digitization, decarbonization, and decentralization. Subsequently, the consumer perspective is taken to assess whether consumers value regionality when buying electricity. In a next step, this work investigates how regional design elements (i.e., trust cues) are used on UIs in practice. Thereafter, I present the results from multiple experiments in which participants engaged with regional trust cues on UIs. In these experiments, various objective and subjective measures for user attitudes and behavior were collected. I present empirical evidence that regional trust cues positively affect these measures. Throughout, implications for research, practitioners, policy makers, but also the broader society are drawn from this work. I conclude with offering an outlook on recent developments surrounding regional design elements on UI in research and practice., Führende Wissenschaftler haben wiederholt gefordert, dass die Forschung im Bereich der Informationssysteme (IS) eines der größten Probleme der Menschheit adressieren sollte: die globale Erwärmung. Ein Bereich, in dem die IS-Forschung einen Beitrag zu dieser Herausforderung leisten kann, ist die Entwicklung digitaler Lösungen zur Unterstützung der Entscheidungsfindung für nachhaltigere Praktiken. Diesem Aufruf folgend, habe ich mich auf eine umfassende Forschungsreise begeben, um herauszufinden, wie digitale Nutzerschnittstellen (UI) so gestaltet werden können, dass sie die Entscheidungen der Benutzenden im Hinblick auf die Auswahl regionaler Produkte und Dienstleistungen unterstützen. Mit der vorliegenden kumulativen Dissertation präsentiere ich die Ergebnisse dieses Vorhabens. Der Strommarkt stellt dafür ein sehr passendes Forschungsobjekt dar – und dank der Eigenschaften des Sektors sollten die Ergebnisse auf andere Kontexte übertragbar sein. Zunächst wirft die Arbeit einen Blick auf den Sektor, der derzeit einen tiefgreifenden Umbruch befeuert durch Digitalisierung, Dekarbonisierung und Dezentralisierung durchläuft. Anschließend wird die Verbraucherperspektive eingenommen, um zu analysieren, ob Verbrauchende beim Stromkauf Wert auf Regionalität legen. In einem nächsten Schritt wird untersucht, wie regionale Gestaltungselemente auf UIs in der Praxis eingesetzt werden. Danach stelle ich die Ergebnisse mehrerer Experimente vor, in denen sich die Teilnehmenden mit regionalen Designelementen auf UIs auseinandersetzten. In diesen Experimenten wurden objektive und subjektive Messgrößen für Verhalten und Einstellung der Nutzenden erhoben. Ich präsentiere empirische Belege dafür, dass sich regionale Designelemente positiv auf diese Messgrößen auswirken. In dieser Arbeit werden Implikationen für Forschung, Praxis, Politik wie auch für die Gesellschaft im Allgemeinen diskutiert. Ich schließe mit einem Ausblick auf die jüngsten Entwicklungen rund um regionale Designelemente auf UIs in Forschung und Praxis.

Carbon dioxide removal from the atmosphere is becoming an important option to achieve net zero climate targets. This paper develops a welfare and public economics perspective on optimal policies for carbon removal and storage in non-permanent sinks like forests, soil, oceans, wood products or chemical products. We derive a new metric for the valuation of non-permanent carbon storage, the social cost of carbon removal (SCC-R), which embeds also the conventional social cost of carbon emissions. We show that the contribution of CDR is to create new carbon sinks that should be used to reduce transition costs, even if the stored carbon is released to the atmosphere eventually. Importantly, CDR does not raise the ambition of optimal temperature levels unless initial atmospheric carbon stocks are excessively high. For high initial atmospheric carbon stocks, CDR allows to reduce the optimal temperature below initial levels. Finally, we characterize three different policy regimes that ensure an optimal deployment of carbon removal: downstream carbon pricing, upstream carbon pricing, and carbon storage pricing. The policy regimes differ in their informational and institutional requirements regarding monitoring, liability and financing., CEPA Discussion Papers; 62

I propose a novel approach to uncover business cycle reports’ priorities and relate them to economic fluctuations. To this end, I leverage quantitative business-cycle forecasts published by leading German economic research institutes since 1970 to estimate the proportions of latent topics in associated business cycle reports. I then employ a supervised approach to aggregate topics with similar themes, thus revealing the proportions of broader macroeconomic subjects. I obtain measures of forecasters’ subject priorities by extracting the subject proportions’ cyclic components. Correlating these priorities with key macroeconomic variables reveals consistent priority patterns throughout economic peaks and troughs. The forecasters prioritize inflation-related matters over recession-related considerations around peaks. This finding suggests that forecasters underestimate growth and overestimate inflation risks during contractive monetary policies, which might explain their failure to predict recessions. Around troughs, forecasters prioritize investment matters, potentially suggesting a better understanding of macroeconomic developments during those periods compared to peaks.

In the Digital Age the world is experiencing an immense growth of advanced digital technologies such as robotics, big data analytics, virtual reality, or artificial intelligence. Hundreds if not thousands of new applications and social media tools are introduced every day changing how people gain and process information, how they communicate or learn but more importantly how people think and solve problems. These all present a huge challenge for all leaders especially senior ones. Thus, this dissertation reveals senior leaders’ perspective to find out how digitalization of teamwork and decision-making changes trust relations at interpersonal level. Moreover, it sheds light on the role of moral trust on eliminating possible gaps in interpersonal trust. The research employs descriptive analysis of theoretical background and compares it to empirical data collected from practitioners; senior and junior leaders in multinational military environment at NATO´s standing and deployed HQs. Based on the findings, this dissertation offers a coaching tool which can be employed in designing leadership training or individual leadership coaching concepts.

This dissertation consists of three chapters which are self-contained. However, there is a common denominator between all three chapters. Each chapter looks at unintended indirect effects of policy interventions. Chapter 1 is a continuation of my dissertation proposal (Spils, 2018) and explores the long-run effects of reducing the number of STEM-hours in high school. Chapter 2 studies the effect of a buyer’s bias for an insurance product on the market equilibrium. Chapter 3 investigates the economic effects of wearing a face mask in the laboratory during various well-known tasks from the literature.

In recent years, three sovereign catastrophe risk pools have developed worldwide, offering climate insurance against natural disasters in emerging and developing economies: • Caribbean Catastrophe Risk Insurance Facility (CCRIF) in the Caribbean • African Risk Capacity (ARC) in Africa • Pacific Catastrophe Risk Insurance Company (PCRIC) in the Pacific region These pools have emerged against the backdrop of limited fiscal room for manoeuvre in emerging and developing economies. Increases in tax revenues or capital allocations are scarcely possible in these economies. Moreover, debt on the capital market often ends in debt relief, and this can jeopardise refinancing. Ultimately, the only measure remaining is to provide donations and aid that can be made available by the G7 countries, the World Bank or the World Health Organization, among others., Publikationen der Kölner Forschungsstelle Rückversicherung; 14/2020

The SearchEngine is an open source project providing an integrated framework for diverse matching activities, especially the linkage of large scale firm data by fuzzy criteria like company names and addresses. At its core, it utilizes an efficient candidate retrieval mechanism implementing a word respectively token driven heuristic. Every record in one table becomes a search term to retrieve similar candidate records in the base table according to a search strategy replacing blocking strategies of conventional matching efforts. Because similarity is inherently established by the candidate selection, it is only required to filter false positives by using the meta data export file derived from the matching heuristic to implement a machine learning approach. This paper discusses the general foundation of the heuristic and the algorithm while two detailed walkthroughs of company linkages show practical examples.

Calls for supporting sustainability through more and better research rest on an incomplete understanding of scientific evidence use. We argue that a variety of barriers to a transformative impact of evidence arises from diverse actor motivations within different stages of evidence use. We abductively specify this variety in policy and practice arenas for three actor motivations (truth-seeking, sense-making, and utility-maximizing) and five stages (evidence production, uptake, influence on decisions, effects on sustainability outcomes, and feedback from outcome evaluations). Our interdisciplinary synthesis focuses on the sustainability challenge of reducing environmental and human health risks of agricultural pesticides. It identifies barriers resulting from (1) truth-seekers’ desire to reduce uncertainty that is complicated by evidence gaps, (2) sense-makers’ evidence needs that differ from the type of evidence available, and (3) utility-maximizers’ interests that guide strategic evidence use. We outline context-specific research–policy–practice measures to increase evidence use for sustainable transformation in pesticides and beyond., Ambio, 52 (2), ISSN:0044-7447, ISSN:1654-7209

The R&D policy instrument mix concept has become increasingly important for understanding how public R&D support drives firm-level R&D. To-date, empirical studies have conceptualised the instrument mix as a static unit, whereby firms receive multiple policy instruments at one point in time. However, firms can also receive multiple instruments in a sequence, over time. While sequencing is well rehearsed theoretically, this remains a major gap in the empirical literature. Our study evaluates, for the first time, how R&D policy instrument mix sequencing impacts firm-level R&D. We construct a unique dataset, containing almost 25,000 firm-year observations over a 17-year period for Ireland. Our analysis focuses on R&D grants, R&D tax credits, and publicly-supported academic-industry collaborations, and develops two novel approaches to measure R&D policy instrument mix sequencing. Our results suggest that R&D policy instrument mix sequencing is highly effective at driving firmlevel R&D, but that some sequences are more effective than others. These findings highlight opportunities to realise superior policy outcomes through targeted sequencing.

Organizational change often fails due to employees' resistance to change resulting in unforeseen expenses, delays, or other disruptions in organizations. In our experiment, we compare behavioral interventions—a pro-change default rule and a pro-change recommendation—with a costly pay raise to foster supportive behavior. In regard to the pure nudge used (default), we support its effectiveness in enhancing change-related success. In line with our model and based on the assumption of low decision confidence in change settings, we find that a preference nudge (recommendation) lacks a corresponding effect. In addition, we find that a pay raise has a positive effect that is likely to be triggered by positive reciprocity. If this pay raise fails to materialize, we report supporting evidence for negative reciprocity. We compare the effect sizes for these nudges and the pay raise and provide insights for the relative cost-effectiveness of such nudges compared to a pay raise for organizational change. We conclude with managerial implications. in press

This dissertation is composed of three chapters on macroeconomics and banking. The main objective of these chapters is to analyze how the banking sector affects the macroeconomy. In Chapter 1 I explore how the optimal capital requirement varies with the level of competition in the banking sector. In Chapter 2 I investigate how banking competition affects the business cycle and the transmission of uncertainty shocks. Finally, in Chapter 3 I analyze the business cycle implications of macroprudential regulation.

Über 10 Jahre nach der Finanzkrise von 2007 und 2008 blicken Regulierung, Forschung und Praxis auf weitreichende Veränderungen in den regulatorischen Anforderungen und Lehren aus der Vergangenheit zurück. Dennoch zeigen sich immer wieder Bankenkrisen, die trotz der regulatorischen Dynamik in den vergangenen Jahren nicht aufgefangen werden konnten. Oftmals resultierten sie aus Managemententscheidungen, die im Ergebnis eine Verstetigung systemischer Risiken erzeugten. Hierbei rückte das individuelle Verhalten von Entscheidungsträgern in den Fokus. Die Finanzkrise hat bewiesen, dass Krisen durch viele Faktoren aber insbesondere durch fehlgeleitete Entscheidungen entstehen können. Durch diese vernetzte sich die Bankenwelt immer mehr und die systemischen Risiken erreichten ein ungeahntes Ausmaß. Ein Prozess, der zuletzt 2007 und 2008 durch die irrational hohen Investitionen in Mortgage-Backed Securities zu erkennen war. Diese Dissertation stiftet über gleich drei papers Mehrwerte für Regulierung, Forschung und Praxis. Im Resultat entstehen durch diese Dissertation neue Steuerungsimpulse, um das Risikobewusstsein der Entscheidungsträger zu schärfen., More than 10 years after the financial crisis of 2007 and 2008, regulation, research, and practice can look back on the far-reaching changes in the regulatory requirements as well as the lessons learned. Nevertheless, despite recent regulatory initiatives, banking crises continue to emerge, often as a result of management decisions that perpetuate systemic risks. The focus of this dissertation is on the individual behavior of decision makers. The financial crisis proved that crises can be caused by many factors, especially misguided decisions. Because of the heavy interconnectedness of the banking sector, systemic risks have reached unprecedented levels. This process was last observed in 2007 and 2008 with irrationally high investments in mortgage-backed securities. This dissertation added value to regulation, research, and practice by generating new steering impulses to sharpen decision makers’ awareness of risk.

Die vorliegende Dissertation stellt empirische Untersuchungen über den Zusammenhang von städtischem Leben und dessen ökonomische Kosten, insbesondere für die Umwelt, an. Dabei werden zum einen bestehende Forschungslücken des Einflusses von Bevölkerungsdichte auf die Luftqualität geschlossen und zum anderen innovative Politikmaßnahmen im Verkehrsbereich untersucht, die Ballungsräume nachhaltiger gestalten sollen. Im Zentrum der Betrachtungen stehen Luftverschmutzung, Staus und Verkehrsunfälle, die für Fragen der allgemeinen Wohlfahrt bedeutend sind und erhebliche Kostenfaktoren für urbanes Leben darstellen. Von ihnen ist ein beträchtlicher Anteil der Weltbevölkerung betroffen. Während im Jahr 2018 bereits 55% der Menschen weltweit in Städten lebten, soll dieser Anteil bis zum Jahr 2050 ungefähr 68% betragen. Die vier in sich geschlossenen Kapitel dieser Arbeit lassen sich in zwei Abschnitte aufteilen: In den Kapiteln 2 und 3 werden neue kausale Erkenntnisse über das komplexe Zusammenspiel von städtischen Strukturen und Luftverschmutzung erbracht. Kapitel 4 und 5 untersuchen anschließend politische Maßnahmen zur Förderung nicht-motorisierter Verkehrsmittel und deren Einfluss auf Luftqualität sowie Staugeschehen und Verkehrsunfälle., The present dissertation conducts empirical research on the relationship between urban life and its economic costs, especially for the environment. On the one hand, existing gaps in research on the influence of population density on air quality are closed and, on the other hand, innovative policy measures in the transport sector are examined that are intended to make metropolitan areas more sustainable. The focus is on air pollution, congestion and traffic accidents, which are important for general welfare issues and represent significant cost factors for urban life. They affect a significant proportion of the world's population. While 55% of the world's people already lived in cities in 2018, this share is expected to reach approximately 68% by 2050. The four self-contained chapters of this thesis can be divided into two sections: Chapters 2 and 3 provide new causal insights into the complex interplay between urban structures and air pollution. Chapters 4 and 5 then examine policy measures to promote non-motorised transport and their influence on air quality as well as congestion and traffic accidents.

Every day, we interact with each other in various markets and economic mechanisms. The rules that shape these markets and mechanisms shape our economic interactions. In particular, rules create incentives that govern economic interactions. The design of rules then allows us to shape economic incentives to pursue different market outcomes. This thesis is dedicated to studying the design of markets and mechanisms, their rules, incentives and goals in three applications: blockchains, mechanism design with inequality, and mechanism design with partially verifiable information.

According to the theoretical freedom-of-choice literature and a growing body of experiments, the economic value of a decision right is reflected not only in its instrumental value, but also in an additional intrinsic value. Building upon findings from previous experiments, I use a novel two-stage laboratory experiment to examine (i) whether individuals value decision rights intrinsically, (ii) how intrinsic valuation depends on structural determinants of the related decision, and (iii) why individuals value decision rights that have no instrumental benefits. I find decision rights to have intrinsic value which is conditioned by stake size, risk, and domain. Intrinsic-value assignment is positively correlated with a preference for self-determination and –in the domain of losses– with a preference for non-interference of others. Aversion to paternalism is no significant motive behind the intrinsic valuation of decision rights.

This study examines whether staged project management is beneficial or harmful for making product innovations. Using a unique firm survey for Japan, we find that firms that employed staged project management had a higher likelihood of introducing new products to the market. Additional estimations show that the positive effect of staged project management on product innovation is stronger when firms provided feedback at the interim stages. In contrast, whether and how firms set milestones was not associated with the likelihood of product innovation. The marginal effect of feedback was larger for new-to-market product innovation than for new-to-firm product innovation, and the feedback from non-R&D organizations within the firm in the initial stages was particularly beneficial for the introduction of new-to-market products. Our findings suggest that staged project management is beneficial for product innovation, but its effectiveness depends on how firms set milestones and feedback as well as the nature of innovation.

In a field experiment with 341 participants, we study whether social comparisons, either in isolation or in combination with a climate-related moral appeal, can change the use of public and car-related transportation. We do so in the context of a mobility budget offered to employees of a large German company as an alternative to a company car. The budget can be used to pay for both leisure and commuting trips, and for various modes of transport. Behavioral interventions in this setting are of particular interest, since companies are constrained to significantly alter financial benefits to employees yet strive to lower carbon emissions via a shift to low-emission transport modes. We find strong evidence for a reduction in car-related mobility in response to the combined treatment, driven by reduced expenditures for taxi and UBER rides. This is accompanied by substitution towards micromobility, but not towards public transport. Furthermore, we do not find any effects of the social comparison alone. Our results demonstrate that norm-based nudges are able to change transportation behavior, at least temporarily.

Much economic analysis derives policy recommendations based on social welfare criteria intended to model the preferences of a policy maker. Yet, little is known about policy maker's normative views in a way amenable to this use. In a behavioral experiment, we elicit German legislators' social welfare criteria unconfounded by political economy constraints. When resolving preference conflicts across individuals, politicians place substantially more importance on least-favored than on most-favored alternatives, contrasting with both common aggregation mechanisms and the equal weighting inherent in utilitarianism and the Kaldor-Hicks criterion. When resolving preference conflicts within individuals, we find no support for the commonly used "long-run criterion" which insists that choices merit intervention only if the lure of immediacy may bias intertemporal choice. Politicians' and the public's social welfare criteria largely coincide.

The full-information rational expectations (FIRE) assumption is at the core of modern macroeconomics. We revisit recent evidence which rejects FIRE based on survey data. It relates forecast errors to news at different levels of aggregation. The evidence based on consensus forecasts testifies against the full-information assumption, the evidence based on data for individual forecasters against rational expectations. In contrast to earlier survey evidence that was largely dismissed as irrelevant, the recent evidence is likely to have a lasting impact for two reasons. First, the global financial crisis of 2007/08 has led to a certain uneasiness with the state of macro and a readiness to embrace new ideas. Second, the recent literature has put forward a number of promising alternative models of the expectation-formation process. We review these at the end of the paper.

Many decisions in organizations, politics, and economics are made collectively by groups. Often, other people who are not part of the decision-making process are affected by the resulting outcomes. Therefore, it is important to understand how individual group members are held accountable for the collective decision. In a recent paper, Bartling et al. (2015) analyzed the attribution of responsibility for collective decisions in a sequential voting game, in which three decision makers sequentially decide on an equal or unequal allocation implemented for themselves and three other recipients. They found that the pivotal decision maker was punished significantly more than non-pivotal decision makers. However, it remains unclear what other factors influence the attribution of responsibility for collective decisions. Therefore, this study extends the work of Bartling et al. (2015) in two ways: first, the decision right is assigned through one of two different (legitimate) mechanisms, and second, one allocation is already preselected as the default. The assignment of individual responsibility is measured by eliciting the punishment choices of the recipients. Interestingly, the legitimacy of the group-building mechanism has no significant effect on the assigned responsibility. However, choosing the default is associated with less punishment, as long as other punishment motives are not controlled for. Additionally, the main result of Bartling et al. (2015), that the pivotal decision maker is punished significantly more, could not be replicated. Instead, the unkindness of a decision determines the punishment behavior of recipients.

Transportation of commodities strongly affects the economic activities and welfare of today’s societies. However, freight transportation also causes relevant negative effects such as greenhouse gas emissions, noise and congestion. In general, freight transport demand models, which determine the number of trips between predefined origins and destinations and split according to different modes and/or vehicles, provide a crucial input for assessing positive and negative effects (by, e.g., cost-benefit analysis) of, e.g., policy measures and infrastructure investments. Nonetheless, the vast majority of existing comprehensive interregional freight transport demand models reveal a significant shortcoming as they treat logistics decisions in a rudimentary manner. Although logistics decisions and especially shipment size choice are broadly considered to be a valuable contribution to the realistic representation of interregional freight transport demand, most of current interregional freight transport demand models solely use observed transports as decision objects to estimate basic mode choice models. This is due to limited data availability. To address the challenges, this cumulative dissertation proposes an approach for shipment size modeling that is based upon the framework of total logistics costs which mathematically expresses the logistical calculus of the respective decision-makers. This microeconomic framework has two desirable properties: First, it ensures a behavioral-sensitive modeling in order to determine shipment size and enables the mapping of stakeholders’ reactions to external influences such as policy measures. Second, this framework contains only a limited number of key strategic parameters making it an appropriate choice due to the limited data availability. Obviously, the model constitutes a theoretical abstraction and thus is not able to fully account for the actual circumstances in reality. For this reason, methods originating from market research are used to develop a few homogeneous segments from a multiplicity of influencing factors. Using such an approach accounts for heterogeneity in an efficient and feasible manner. Generally, the scientific contribution of this cumulative dissertation at hand can be structured into different thematic clusters: First, deductive shipment size models based on the minimization of total logistics costs lead to the development of stable behavioral models. The latter are characterized by high explanatory power and only use a limited number of strategic parameters. This also accounts for the combined mode choice and shipment size choice model, where both decisions are connected by a multidimensional logit model. The second major contribution of this dissertation is to enrich the stable shipment size choice models by adding homogeneous segments derived using relevant characteristics of commodities and decision-makers. In a nutshell, the integration of data-driven segments into the shipment size choice models significantly increases the models’ explanatory power while decreasing their complexity. Moreover, data-driven segments are more powerful than classifications by public authorities regarding their in-sample and out-of-sample performance. Third, a machine-learning approach called the naïve Bayes classifier is used to exploit the shipment size choice and segmentation model derived from the survey in order to apply it to the population of interest. In the course of this approach, a simulation study demonstrates an increase of shipment sizes due to an increased penetration of ICT (information and communication technology). An additional simulation study deals with the effects of automation in transport and logistics on shipment size formation. The last major contribution deals with the transferability of the model’s results between Germany and France. Key strategic parameters for shipment size formation as well as segment composition reveal only small structural discrepancies. In summary, this cumulative dissertation bridges a substantial methodological gap of current interregional freight transport demand models by integrating a suitable key logistics decision and thus improves state-of-the-art cost-benefit analysis for transportation planning purposes in various ways. More specifically, the proposed modeling approach for shipment size choice, as crucial logistics decision, allows efficient exploitation of scarce data, which is a ubiquitous challenge in freight transport demand modeling. Further, the findings gained by applying data-driven segmentation techniques to shipment size choice reveal that freight-transport-related survey designs and commodity classifications provided by public authorities need to be revised. Finally, the successful transfer of the findings to a French dataset provides evidence that the modeling approach can be extensively applied to comprehensive interregional freight transport demand models., Der Güterverkehr hat einen großen Einfluss auf die wirtschaftlichen Aktivitäten und den Wohlstand heutiger Gesellschaften. Jedoch bringt der Güterverkehr auch negative Effekte wie Treibhausgasemissionen, Lärm und Stau mit sich. Um positive und negative Effekte von Maßnahmen wie Infrastrukturinvestitionen, beispielsweise mittels einer Kosten-Nutzen-Analyse, zu bewerten, liefern Güterverkehrsnachfragemodelle einen äußerst wichtigen Beitrag, da sie zur verkehrsmittelfeinen Ermittlung von Verkehrsströmen auf Relationsebene dienen. Allerdings weist die überwiegende Mehrheit an aktuell eingesetzten überregionalen Güterverkehrsnachfragemodellen eine beträchtliche Schwachstelle auf, da sie logistische Entscheidungen nur rudimentär behandeln. Obwohl logistische Entscheidungen, insbesondere die Losgrößenwahl, allgemein als wertvolle Stellgrößen für eine realistische Abbildung der Güterverkehrsnachfrage gelten, werden in aktuell eingesetzten Güterverkehrsnachfragemodellen meist lediglich Verkehrsmittelwahlmodelle anhand von beobachteten Frachtaufträgen als Entscheidungsobjekt verwendet und nicht die beste Option in einem umfangreichen Belieferungsprozess modelliert. Diese Diskrepanz lässt sich vor allem durch einen Faktor erklären: eine limitierte Datenverfügbarkeit. Die vorliegende kumulative Dissertation befasst sich mit diesen herausfordernden Gegebenheiten. Dabei wird ein Modellierungsansatz zur Losgrößenwahl erarbeitet, der auf dem Prinzip der „Total Logistics Costs“-Minimierung und damit auf der Abbildung des logistischen Trade-offs zwischen Lagerhaltungs- und Transportkosten beruht. Dieses mikroökonomische Gerüst liefert einerseits die Basis für eine verhaltenssensitive Modellierung. Sie ermöglicht es, Reaktionen auf Veränderungen, etwa bedingt durch politische Maßnahmen, abzubilden. Andererseits zeichnet sich dieser Ansatz durch eine überschaubare Anzahl an Einflussfaktoren und somit realisierbaren Datenanforderungen aus. Nichtsdestotrotz können durch eine theoretische Abstraktion nicht sämtliche reale Gegebenheiten abgebildet werden. Hierbei kommen Methoden zum Tragen, die ihren Ursprung in der Marktforschung haben: die Bildung weniger verhaltenshomogener Gruppen aus einer Vielzahl an möglichen Einflussfaktoren. Dieses Vorgehen erlaubt es, der Heterogenität, die nicht durch den Verhaltenskern der „Total Logistics Costs“ abgefangen werden kann, in effizienter und praktikabler Art und Weise Rechnung zu tragen. Grundsätzlich kann der wissenschaftliche Beitrag der vorliegenden kumulativen Dissertation in unterschiedliche Aspekte gegliedert werden. Zuerst ist zu nennen, dass deduktive Losgrößenmodelle anhand der „Total Logistics Costs“-Minimierung zu stabilen Verhaltensmodellen führen, die sich durch einen hohen Erklärungsgehalt auszeichnen und mit wenigen strategischen Modellparametern auskommen. Diese Erkenntnisse gelten auch für ein kombiniertes Verkehrsmittel- und Losgrößenwahlmodell, das mittels eines mehrdimensionalen Logit-Modells geschätzt wird. Den zweiten großen Beitrag stellt die Anreicherung der stabilen Losgrößenwahlmodelle mit aus Mikrodaten abgeleiteten Segmenten dar. Dabei wird durchgängig eine signifikante Erhöhung des Erklärungsgehalts bei gleichzeitiger Komplexitätsreduktion durch die verwendeten Segmentierungsverfahren erreicht. Darüber hinaus verbessern datengetriebene Segmentierungen die in-sample und out-of-sample Performance im Vergleich zur offiziellen Standardklassifikation von Gütern. Drittens wird der Naïve Bayes Klassifikator aus dem Bereich des Machine Learning verwendet: Dieser ermöglicht den operativen Einsatz des Losgrößenwahlmodells mit datengetriebenen, homogenen Segmenten und somit zielgenaue politikrelevante Untersuchungen. Dabei wird mittels einer Simulationsstudie aufgezeigt, dass eine weitere Durchdringung von Informations-und Kommunikationstechnologie die gewählte Transportlosgröße tendenziell ansteigen lässt. In einer weiteren Simulationsstudie werden die Auswirkungen von Automatisierung im Transport und die des Umschlags auf die Losgrößenwahl untersucht. Der letzte grundlegende Beitrag dieser Dissertation besteht aus dem Vergleich von Modellergebnissen zwischen Deutschland und Frankreich und der Evaluation ihrer Übertragbarkeit. Sowohl die Einflüsse der strategischen Losgrößenparameter als auch die Zusammensetzung und der Einfluss der latenten Segmente weisen nur geringe strukturelle Abweichungen auf. Zusammenfassend ist festzuhalten, dass die vorliegende kumulative Dissertation eine wesentliche methodische Lücke von derzeitig verwendeten überregionalen Güterverkehrsnachfragemodellen schließt. Sie ermöglicht die Integration einer elementaren logistischen Entscheidung in überregionale Güterverkehrsnachfragemodelle und dadurch Bewertungsmethoden wie die Kosten-Nutzen-Analyse für transportplanerische Zwecke in mehrfacher Hinsicht zu verbessern. Der vorgestellte Ansatz ist trotz der allgegenwärtigen Datenrestriktionen in der Lage die Losgrößenwahl als zentrale logistische Entscheidung zu modellieren und somit die vorhandenen Daten effizient zu nutzen. Darüber hinaus zeigen die Ergebnisse der datengetriebenen Segmentierungsmethoden, dass eine Überarbeitung von güterverkehrsspezifischen Erhebungen und Standardklassifikationen im Bereich des Güterverkehrs angedacht werden sollte. Abschließend wird durch die erfolgreiche, länderübergreifende Ausweitung des Modellierungsansatzes eine unmittelbare Anwendung in überregionalen, umfassenden Güterverkehrsnachfragemodellen gestützt.