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Consisting of three articles and a framework manuscript, this cumulative dissertation deals with sustainable compensation of chief executive officer (CEO) with a focus on climate-related aspects. Against the backdrop of the European action for sustainability and the EU Green Deal, the dissertation pays special attention to the consideration of climate-related aspects of corporate performance in CEO compensation. In this context, sustainable compensation is characterized by the consideration of long-term interests and sustainability of the company as well as by the inclusion of financial and non-financial aspects of environmental, social and governance performance (ESG) in compensation agreements. While this novel instrument of corporate governance aims to incentivize the implementation of sustainability-oriented corporate strategy, it is particularly important to unfold this incentive effect at the individual CEO level in view of their managerial discretion. The framework manuscript discusses the research objectives, the regulatory and theoretical background, the results of the dissertation and their implications in the context of regulation, research, and business practice. The essence of the dissertation are the three articles. The first article, "Determinants and effects of sustainable CEO compensation: a structured literature review of empirical evidence," examines the current state of empirical research based on 37 articles that were published between 1992 and 2018. Based on a multidimensional research framework, the structured literature review compiles past research findings, identifies contentual and methodological foci in the research area, and derives questions for future research. The second article, "Mapping the determinants of carbon-related CEO compensation: a multidimensional approach," addresses the topic from a conceptual perspective. Taking the existing work as a starting point, a conceptual framework is derived, which organizes the determinants of carbon-related CEO compensation at societal, organizational, group and individual levels of analysis. On this basis, eight propositions are presented that seek to distinguish between the determinants which support and challenge the implementation of carbon-related CEO compensation. The third article, "Climate change policies and carbon-related CEO compensation systems: an exploratory study of European companies," focuses on the use of CO2-oriented performance indicators in CEO compensation. The empirical-qualitative study analyzes corporate disclosure of the 65 largest companies in the EU for the years 2018 and 2019. The study addresses the use of CO2-oriented performance indicators in corporate strategy and CEO compensation. It also examines which compensation components are determined with the help of CO2-oriented performance indicators, which type of performance indicators are used, and whether CO2-intensive and less CO2-intensive companies differ in this regard.
Der Ausbau der erneuerbaren Energien als Ausprägung des klimaschutzpolitischen Substitutionsansatzes wird in Deutschland mithilfe verschiedener Gesetze gesteuert. Dabei haben sich in mehr als 30 Jahren umfangreiche Regelungsstrukturen herausgebildet. Besonders ausgeprägt ist dies im Stromsektor zu beobachten. Hier kön-nen ausgehend vom Kartellrecht über den Zwischenschritt des Stromeinspeisungsgesetzes bis zu den verschie-denen Fassungen des Erneuerbare-Energien-Gesetzes vielfältige Entwicklungslinien anhand ausgewählter kon-kreter Veränderungen aufgezeigt werden. Sowohl im Hinblick auf Änderungsdynamik wie -tiefe deutlich weni-ger ausgeprägt sind dagegen die Entwicklungslinien im Wärmesektor. Diese nehmen ihren gesetzlichen Ur-sprung erst 2009 mit dem Erneuerbare-Energien-Wärmegesetz, um dann zusammen mit den gebäudebezoge-nen Effizienzregelungen 2020 infolge eines umfassenden rechtlichen Konsolidierungsschritts im Gebäudeener-giegesetz zu münden.
Die Ausgestaltungsschritte im deutschen Erneuerbare-Energien-Recht sind auf vielfältige Weise mit den Ent-wicklungen im europäischen Rechtsrahmen zur Steuerung des Ausbaus der erneuerbaren Energien verwoben. Dies betrifft zunächst die Judikatur zu den primärrechtlichen Anforderungen an die Ausgestaltung mitglied-staatlicher Förderinstrumente, gilt aber besonders für die Entwicklungen im Sekundärrecht. Hier hat sich seit 2001 in mehreren Schritten eine immer detailliertere sekundärrechtliche Ordnung entwickelt. Dabei beinhalten die Entwicklungen der Erneuerbare-Energien-Richtlinien nicht nur eindimensional Steuerungs- und Bindungs-wirkungen von der supranationalen in Richtung der mitgliedstaatlichen Ebene. Vielmehr finden sich darin auch Entwicklungen zur Beschränkung der europarechtlichen Einflüsse, namentlich der Vorgaben zur Warenver-kehrsfreiheit und des Beihilferechts, die eine unmittelbare Reaktion der Mitgliedstaaten auf die Entscheidun-gen der europäischen Gerichte und der Europäischen Kommission darstellen.
Das Erneuerbare-Energien-Recht ist zudem eingebettet in das übergreifende Umweltenergie- und Klima-schutzrecht. Mit der sowohl auf europäischer als auch deutscher Ebene im Werden befindlichen umfassenden Klimaschutzordnung lassen sich ebenso wie mit dem sich fortlaufend ändernden Instrumentenmix zahlreiche Wechselwirkungen feststellen. Der mit der neuen Klimaschutz-Governance geschaffene prozedurale Rahmen etabliert ein System von Klimaschutzzielen, Evaluierungs- und Nachsteuerungsvorgaben. Dieser ist aber mit dem Erneuerbare-Energien-Recht und dessen Zielen nur lose verbunden. Detaillierungsgrad und Steuerungs-wirkung der europäischen und der deutschen Klimaschutz-Governance unterscheiden sich dabei deutlich, was auch mit den stärkeren Koordinationsbedürfnissen im eher vertikal orientierten supranationalen Regelungs-verbund begründet ist.
Dass die Entwicklung im Erneuerbare-Energien-Recht in absehbarer Zeit zu einem Endpunkt gelangen könnten, ist nicht zu erwarten. Dies wird deutlich, wenn die tatsächlichen Herausforderungen der Transformation und aktuell diskutierte Themenfelder für die weitere Fortschreibung dieses Rechtsbereichs betrachtet werden. Dabei sind die verschiedenen Dimensionen der Integration erneuerbarer Energien zur Vertiefung der System-transformation ebenso von Bedeutung, wie Regelungen zu Akzeptanz und Teilhabe sowie zur Beantwortung der Verteilungsfragen einerseits und eine Reduktion des Komplexitätsumfangs im Recht anderseits.
Die Digitalisierung ermöglicht es, die Anwendung von Scoring Systemen auf verschiedene Lebensbereiche auszuweiten und Verhalten von Kunden und Konsumenten vorherzusagen und zu steuern. Gezielt eingesetzte Incentives, die an einen bestimmten Score geknüpft sind, werden häufig genutzt, um das gewünschte Verhalten zu erreichen. Um die Erkenntnisse zur Wahrnehmung von Scoring Systemen zu erweitern, wurde in dieser Studie die Einstellung zu Scoring Systemen erfasst und untersucht, inwieweit potenzielle individuelle und funktionelle Einflussfaktoren auf die Einstellung wirken. Dafür wurde eine Online Umfrage mit 125 Teilnehmenden aus Deutschland umgesetzt. Zu Erfassung der Einstellung wurde je ein Scoring Szenario inklusive Incentives für die Bereiche Gesundheit, Mobilität und Finanzen konstruiert, das die Teilnehmenden bewerten sollten. Die Incentives wurden als funktionelle Faktoren zusammengefasst, und es wurde vermutet, dass sie die Einstellung zu Scoring beeinflussen. Als individuelle Faktoren wurden einmal die Selbsteinschätzung Scoring-relevanten Verhaltens festgelegt und einmal die Persönlichkeitsvariable Narzissmus. Es wurde davon ausgegangen, dass beide Variablen einen Einfluss auf die Einstellung haben und einen positiven Zusammenhang aufweisen. Bei der Überprüfung der Hypothesen zeigte sich, dass sowohl die Incentives als auch die Selbsteinschätzung einen signifikanten Einfluss auf die Einstellung zu Scoring haben. Für den Einfluss von Narzissmus konnten keine signifikanten Ergebnisse gefunden werden. Für die Faktoren Alter, Geschlecht und Erfahrung mit Scoring wurde ebenfalls ein Einfluss vermutet, weshalb eine zusätzliche explorative Analyse für diese Faktoren durchgeführt wurde, bei der allerdings keine signifikanten Ergebnisse zustande kamen. Des Weiteren zeigte sich, dass Scoring auch über verschiedene Szenarien hinweg insgesamt als eher negativ bewertet wird. Die eingesetzten Incentives wurden ebenfalls als negativ bewertet.
This dissertation includes an introduction and five empirical papers focusing on the educational and career decision-making process of individuals in Germany. The five papers embrace different determinants of educational and career decisions including school performance, social background, leisure activities as well as professional expectations, and contribute to the existing literature in this research area. Chapter 2 of this dissertation begins by analysing the nexus between students’ time allocation and school performance in terms of grades and satisfaction with their own performance in mathematics, the German language and a first foreign language, as well as overall achievement. This chapter looks at the heterogeneity of three important extracurricular activities: student jobs, sports and participation in music. Moreover, the heterogeneity of each activity is addressed by accounting for different types of the particular activity and differences in the number of years the activity has been pursued. For this purpose, data from the German SOEP, as a representative panel survey of private households and people in Germany, in particular cross-sectional survey data of 3388 students who are about 17 years old and enrolled in a German secondary school, were used. The main findings are that having a job as a student is negatively correlated with school performance, whereas participation in sports and music is positively correlated. However, the results reveal heterogeneity in each activity, especially with respect to intensity. Chapter 3 addresses the concrete post-school decision of school students, in particular whether to study or to enter the German VET system (Vocational Education and Training). It focuses on individual risk preferences and the social background of individuals and how these determinants affect the ultimate decision to enrol in university or to start an apprenticeship given the same level of qualification. For the empirical approach data from the German SOEP were used, in particular information on individuals' educational decisions between 2007 and 2013. The results indicate that (i) individual risk preferences do not have an overall effect on the real transition; (ii) privileged individuals are more likely to take up higher education; and (iii) compared to highly educated parents, parents without an academic background are less likely to guide their children into tertiary education, regardless of how much they support their children with their school work. Chapter 4 deals with the reconsideration of educational decisions in terms of early contract cancellations in VET. In particular, the effects of a second job on the intention to cancel a VET contract early are analysed for apprentices in Germany. For the empirical approach the representative German firm-level study "BIBB Survey Vocational Training from the Trainee's Point of View 2008", conducted by the Federal Institute for Vocational Education and Training (BIBB), is used. The survey contains 5901 apprentices that were interviewed during their second year of apprenticeship (205 schools, 340 classes, and 15 common occupations). Furthermore, it includes the design, procedures, basic conditions, and quality criteria of apprenticeships. The applied probit regressions show a higher intention to quit if apprentices require a secondary job to cover their living costs. In Chapter 5, new data on 191 apprentices from a vocational school, located in a northern German federal state, are used to validate the empirical results of Chapter 4. This chapter presents new insights into secondary-job-related burdens during apprenticeship. Due to limitations in the data, the applied empirical approach in Chapter 4 lacks to analyse how holding multiple jobs increases the intention to leave an apprenticeship early. Therefore, Chapter 5 includes the investigations of burdens related to the second job. The results indicate a lower intention to quit the apprenticeship if an apprentice holds a second job to cover living costs. However, secondary jobs are linked to lower quality of training, which, on the other hand, increases the intention to leave the apprenticeship early. Furthermore, the probability of secondary-job-related burdens increases with the number of working hours. Chapter 6 concludes the thesis by investigating subjective determinants of early contract cancellations in VET. It examines ten questions on what apprentices want to achieve and how unfulfilled expectations affect the intention to leave the apprenticeship early. The findings of this investigation contributes to the existing research on early contract cancellation. The questions considered include information on the performance, personal development, career development and prospects or position in society and their meaning to apprentices. For the research approach, the "BIBB Survey Vocational Training from the Trainee's Point of View 2008" is considered again. The probit and ordered probit regressions applied show significant effects of job characteristics that represent job security. The expectation of being retained after an apprenticeship and the encouragement to consistently train further decrease the intention to leave the apprenticeship early. Furthermore, women appear to be more affected by job security signals than men, but they also sort more often into occupations with lower retention probabilities. Consequently, this result may be an indication of occupational segregation rather than a sign of differences between sexes.
This thesis analyses how European merger control law is applied to the energy sector and to which extent its application may facilitate the liberalisation of the electricity, natural gas and petroleum industries so that only these concentrations will be cleared that honour the principles of the liberalisation directives. After having discussed the complex micro- and macro-economic considerations which accompany any concentration of business activities, this thesis discusses the merger control regime of the European Community (EC) so as to establish whether the merger control under either Art. 66 Treaty Establishing the European Coal and Steal Community (ECSCT), the case law under Art. 101 and 102 Treaty on the functioning of the European Union (TFEU) and (Art. 81 and Art. 82 Treaty Establishing the European Economic Community (ECT), as it was introduced by the Commission and reviewed by the CJEU, the original Merger Regulation (MR1989) or the amended Merger Regulation of 1997 (MR1997) or the amended Merger Regulation of 2004 (MR2004) facilitate the liberalisation of European electricity and gas markets. Said liberalisation was introduced by the Internal Electricity Market Directive (IEMD), the Hydrocarbons Licensing Directive and the Internal Gas Market Directive (IGMD). The paper focuses on the contestable idea that regulatory amendments - especially the introduction of third party access by means of the directives - only form a first necessary condition for attaining economic alterations whereas pro-active conduct of the marketers is the second and decisive one in order to increase the competitive performance of the European energy supply industries. The analysis is supported by a second argument which relates closely to the ambivalent nature of concentrations: A concentration may be used to increase the process of market opening and the expansion into new markets by pooling of scarce resources. It may also be used as a retro -active means so as to create national champions, increase barriers to market entry of new competitors, enable cross-subsidisation so as to expand dominant positions on heretofore competitive up- and downstream markets.
Detecting and Assessing Road Damages for Autonomous Driving Utilizing Conventional Vehicle Sensors
(2021)
Environmental perception is one of the biggest challenges in autonomous driving to move inside complex traffic situations properly. Perceiving the road's condition is necessary to calculate the drivable space; in manual driving, this is realized by the human visual cortex. Enabling the vehicle to detect road conditions is a critical and complex task from many perspectives. The complexity lies on the one hand in the development of tools for detecting damage, ideally using sensors already installed in the vehicle, and on the other hand, in integrating detected damages into the autonomous driving task and thus into the subsystems of autonomous driving. High-Definition Feature Maps, for instance, should be prepared for mapping road damages, which includes online and in-vehicle implementation. Furthermore, the motion planning system should react based on the detected damages to increase driving comfort and safety actively. Road damage detection is essential, especially in areas with poor infrastructure, and should be integrated as early as possible to enable even less developed countries to reap the benefits of autonomous driving systems. Besides the application in autonomous driving, an up-to-date solution on assessing road conditions is likewise desirable for the infrastructure planning of municipalities and federal states to make optimal use of the limited resources available for maintaining infrastructure quality. Addressing the challenges mentioned above, the research approach of this work is pragmatic and problem-solving. In designing technical solutions for road damage detection, the researchers conduct applied research methods in engineering, including modeling, prototyping, and field studies. They utilize design science research to integrate road damages in an end-to-end concept for autonomous driving while drawing on previous knowledge, the application domain requirements, and expert workshops. This thesis provides various contributions to theory and practice. The investigators design two individual solutions to assess road conditions with existing vehicle sensor technology. The first solution is based on calculating the quarter-vehicle model utilizing the vehicle level sensor and an acceleration sensor. The novel model-based calculation measures the road elevation under the tires, enabling common vehicles to assess road conditions with standard hardware. The second solution utilizes images from front-facing vehicle cameras to detect road damages with deep neural networks. Despite other research in this area, the algorithms are designed to be applicable on edge devices in autonomous vehicles with limited computational resources while still delivering cutting-edge performance. In addition, the analyses of deep learning tools and the introduction of new data into training provide valuable opportunities for researchers in other application areas to develop deep learning algorithms to optimize detection performance and runtime. Besides detecting road damages, the authors provide novel algorithms for classifying the severity of road damages to deliver additional information for improved motion planning. Alongside the technical solutions, they address the lack of an end-to-end solution for road damages in autonomous driving by providing a concept that starts from data generation and ends with servicing the vehicle motion planning. This includes solutions for detecting road damages, assessing their severity, aggregating the data in the vehicle and a cloud platform, and making the data available via that platform to other vehicles. Fundamental limitations in this dissertation are due to boundaries in modeling. The pragmatic approach simplifies reality, which always distorts the degree of truth in the result.
The wide accessibility of the Internet and web-based programs enable an increased volume of online interventions for mental health treatment. In contrast to traditional face-to-face therapy, online treatment has the potential to overcome some of the barriers such as improved geographical accessibility, individual time planning, and reduced costs. The availability of clients’ treatment data fuels research to analyze the collected data to obtain a better understanding of the relationship among symptoms in mental disorders and derive outcome and symptom predictions. This research leads to predictive models that can be integrated into the online treatment process to assist clinicians and clients.
This dissertation discusses different aspects of the development of predictive modeling in online treatment: Categorization of predictive models, data analyses for predictive purposes, and model evaluation. Specifically, the categorization of predictive models and barriers against the uptake of mental health treatment are discussed in the first part of this dissertation. Data analysis and predictive modeling are emphasized in the second part by presenting methods for inference and prediction of mood as well as the prediction of treatment outcome and costs. Prediction of future and current mood can be beneficial in many aspects. Inference of users’ mood levels based on unobtrusive measures or diary data can provide crucial information for intervention scheduling. Prediction of future mood can be used to assess clients’ response to the treatment and expected treatment outcome. Prediction of the expected treatment costs and outcomes for different treatment types allows simultaneous optimization of these objectives and to increase the cost-effectiveness of the treatment. In the third part, a systematic predictive model evaluation incorporating simulation analyses is demonstrated and a method for model parameter estimation for computationally limited devices is presented.
This dissertation aims to overcome the current challenges of predictive model development and its use in online treatment. The development of predictive models for varies data collected in online treatment is demonstrated and how these models can be applied in practice. The derived results contribute to computer science and mental health research with client individual data analysis, the development ofpredictive models, and their statistical evaluation.
Network analysis methods have long been used in the social sciences. About 25 years ago, these methods gained popularity in various other domains and many real-world phenomena have been modeled using networks. Well-known examples include (online) social networks, economic networks, web graphs, metabolic networks, infrastructure networks, and many more.
Technological development made it possible to store and process data on a scale not imaginable decades ago — a development that also includes network data. A particular characteristic of network data is that, unlike standard data, the objects of interest, called nodes, have relationships to (possibly all) other objects in the network. Collecting empirical data is often complicated and cumbersome, hence, the observed data are typically incomplete and might also contain other types of errors. Because of the interdependent structure of network data, these errors have a severe impact on network analysis methods.
This cumulative dissertation is about the impact of erroneous network data on centrality measures, which are methods to assess the position of an object, for example a person, with respect to all other objects in a network. Existing studies have shown that even small errors can substantially alter these positions. The impact of errors on centrality measures is typically quantified using a concept called robustness.
The articles included in this dissertation contribute to a better understanding of the robustness of centrality measures in several aspects. It is argued why the robustness needs to be estimated and a new method is proposed. This method allows researchers to estimate the robustness of a centrality measure in a specific network and can be used as a basis for decision making. The relationship between network properties and the robustness of centrality measures is analyzed. Experimental and analytical approaches show that centrality measures are often more robust in networks with a larger average degree. The study of the impact of non-random errors on the robustness suggests that centrality measures are often more robust if missing nodes are more likely to belong to the same community compared to missingness completely at random. For the development of imputation procedures based on machine learning techniques, a process for the evaluation of node embedding methods is proposed.
Die vorliegende Arbeit untersucht das Reiseverhalten verschiedener Generationen in Deutschland (68er, Babyboomer, Generation X und Generation Y) anhand der Kohortenanalyse. Mit Hilfe des Intrinsic Estimators und der Rohdaten der Reiseanalyse für die Jahre 1971 bis 2012 wurden Kohorten-, Alters- und Periodeneffekte für die verschiedenen Merkmale des Reiseverhaltens geschätzt. Deutliche Unterschiede zwischen den Generationen, die unabhängig von Alter und Jahr bestand haben sollten, wurden in Bezug auf die Wahl des Verkehrsträgers, der Unterkunft, der Reiseart und der Destination identifiziert. Bei anderen Merkmalen gab es hingegen weniger oder nur geringe Generationenunterschiede. Die Ergebnisse ermöglichen einen genaueren Blick in die Zukunft des Reisens und geben wichtige Hinweise für die tourismuswirtschaftliche Praxis.
My dissertation embraces four empirical papers addressing socio-economic issues relevant to policy-makers and society as a whole. These papers cover important aspects of human life including health at birth, life satisfaction, unemployment periods and retirement decisions, and are intended to provide a contribution to the respective research areas. The analyses are carried out applying advanced econometric methods and are based on data sets consisting of survey data as well as administrative records.
The joint paper with Alessandro Palma and Daniela Vuri "Prenatal Air Pollution Exposure and Neonatal Health" in Chapter 2 investigates the causal impact of prenatal exposure to air pollution on neonatal health in Italy in the 2000s combining detailed information on mother’s residential location from birth certificates with PM10 concentrations from air pollution monitors. Variation in local weekly rainfall is exploited as an instrumental variable for non-random air pollution exposure. Using quasi-experimental variation in rainfall shocks allows to identify the effect of PM10, ruling out potential bias due to confounder pollutants. The paper estimates the effect of exposure for both the entire pregnancy period and separately for each trimester to test whether the neonatal health effects are driven by pollution exposure during a particular gestation period. This information enhances our understanding of the mechanisms at work and help prevent pregnant mothers from most dangerous exposure periods. Additionally, the effects of prenatal exposure to PM10 are estimated by maternal labor market status and maternal education level to understand how the pollution burden is shared across different population groups. This decomposition allows to identify possible mechanisms through which environmental inequality reinforces the negative impact of early-life exposure to air pollution. This study finds that average PM10 and days with PM10 level above the hazard limit reduce birth weight, gestational age, and measures of overall newborn health. Effects are largest for third trimester exposure and for low-income and less educated mothers. These findings imply that further policy efforts are needed to fully protect fetuses from the adverse effects of air pollution and to mitigate the environmental inequality of health at birth.
The joint paper with Christian Pfeifer "Life Satisfaction in Germany After Reunification: Additional Insights on the Pattern of Convergence" in Chapter 3 updates previous findings on the total East-West gap in overall life satisfaction and its trend by using data from the German Socio-Economic Panel for the years 1992 to 2013. Additionally, the effects are separately analyzed for men and women as well as for four birth cohorts. The results indicate that reported life satisfaction is, on average, significantly lower in East than in West German federal states and that part of the raw East-West gap is due to differences in household income and unemployment status. The conditional East-West gap decreased in the first years after the German reunification and remained quite stable and sizable since the mid-nineties. The results further indicate that gender differences are small. Finally, the East-West gap is significantly smaller and shows a trend towards convergence for younger birth cohorts.
The joint paper with Christian Pfeifer "Unemployment Benefits Duration and Labor Market Outcomes: Evidence from a Natural Experiment in Germany" in Chapter 4 explores the effects
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of a major reform of unemployment benefits in Germany on the labor market outcomes of individuals with some health impairment. The reform induced a substantial reduction in the potential duration of regular unemployment benefits for older workers. This work analyzes the reform in a wider framework of institutional interactions, which allows to distinguish between its intended and unintended effects. The results based on routine data collected by the German Statutory Pension Insurance and a Difference-in-Differences design provide causal evidence for a significant decrease in the number of days in unemployment benefits and increase in the number of days in employment. However, they also suggest a significant increase in the number of days in unemployment assistance, granted upon exhaustion of unemployment benefits. Transitions to unemployment assistance represent an unintended effect, limiting the success of a policy change that aims to increase labor supply via reductions in the generosity of the unemployment insurance system.
The single-authored paper "How Older Workers Respond to Raised Early Retirement Age: Evidence from a Kink Design in Germany" in Chapter 5 explores how an increase in the early retirement age affects labor force participation of older workers. The analysis is based on a social security reform in Germany, which raised the early retirement age over several birth cohorts to boost employment of older people and ultimately alleviate the burden on the public pension system. Detailed administrative data from the Federal Employment Agency allow to distinguish between employment and unemployment as well as disability pensions and retirement benefits claims. Using a Regression Kink design in a quasi-experimental framework, I show that the raised early retirement age had positive employment effects and negative effects on retirement benefits claims. The reform did not affect unemployment benefits or disability pensions claims. My results also show that some population groups are more sensitive to a reduction in retirement options and more likely to seek benefits from other government programs. In this respect, I find that workers in manufacturing sector respond to the raised early retirement age by claiming benefits from the disability insurance program designed to compensate for reduced earnings capacity due to severe health problems. The treatment heterogeneity analysis further suggests that high-wage workers are more likely to delay exits from employment, which is in line with incentives but might also indicate an increased inequality within the affected birth cohorts induced by the reform. Finally, women seem to rely on alternative sources of income such as retirement benefits for women, or spouse's or partner's income not observed in the data. All things considered, workers did not adjust to the increased early retirement age by substituting early retirement with other government programs but rather responded to the reform in line with the policy intent. At the same time, the findings point to heterogeneous behavioral responses across different population groups. This implies that raising the early retirement age is an effective policy tool to increase employment only among older people who have the real choice to delay employment exits. Therefore, reforms that raise statutory ages should ensure social support for workers only marginally attached to the labor market or not able to work longer due to potential health problems or other circumstances.