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While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.
Distances affect economic decision-making in numerous situations. The time at which we make a decision about future consumption has an impact on our consumption behavior. The spatial distance to employer, school or university impacts the place where we live and vice versa. The emotional closeness to other individuals influences our willingness to give money to them. This cumulative thesis aims to enrich the literature on the role of distance for economic decision-making. Thereby, each of my research projects sheds light on the impact of one kind of distance for efficient decision-making.
Against the background of the increasingly discussed “Linguistic Saving Hypothesis” (Chen, 2013), I studied whether the targeted use of a present tense (close tense) and a future tense (distant tense) within the same language have an impact on intertemporal decision-making. In a monetarily incentivized laboratory experiment in Germany, I implemented two different treatments on intertemporal choices. The treatments differed in the tense in which I referred to future rewards. My results show that individuals prefer to a greater extent rewards which are associated with a present tense (close tense). This result is in line with my prediction and the first empirical support for the Linguistic Saving Hypothesis within one language. However, this result holds exclusively for males. Females seem to be unaffected by the linguistic manipulation. I discuss my findings in the context of “gender-as-culture” as well as their potential policy-implications.
Reformen bei Elterngeld und Ehegattensplitting könnten gleichstellungspolitische Impulse setzen
(2023)
Germany is characterised by large gender gaps in the labour market. Both the gender pay gap as well as the gender gap in working hours are among the highest in Europe. Family policy reforms such as increasing the parental leave period that is ear-marked for fathers as well as reducing the high marginal tax rates for secondary earners resulting from the joint taxation of married couples with full income splitting (“Ehegattensplitting”) could help to mitigate the existing gender gaps in the labour market. These reforms are also paramount due to the increasing labour scarcity stemming from the demographic change.
Elterngeld
(2023)
Modern health care systems are characterized by pronounced prevention and cost-optimized treatments. This dissertation offers novel empirical evidence on how useful such measures can be. The first chapter analyzes how radiation, a main pollutant in health care, can negatively affect cognitive health. The second chapter focuses on the effect of Low Emission Zones on public heath, as air quality is the major external source of health problems. Both chapters point out potentials for preventive measures. Finally, chapter three studies how changes in treatment prices affect the reallocation of hospital resources. In the following, I briefly summarize each chapter and discuss implications for health care systems as well as other policy areas. Based on the National Educational Panel Study that is linked to data on radiation, chapter one shows that radiation can have negative long-term effects on cognitive skills, even at subclinical doses. Exploiting arguably exogenous variation in soil contamination in Germany due to the Chernobyl disaster in 1986, the findings show that people exposed to higher radiation perform significantly worse in cognitive tests 25 years later. Identification is ensured by abnormal rainfall within a critical period of ten days. The results show that the effect is stronger among older cohorts than younger cohorts, which is consistent with radiation accelerating cognitive decline as people get older. On average, a one-standarddeviation increase in the initial level of CS137 (around 30 chest x-rays) is associated with a decrease in the cognitive skills by 4.1 percent of a standard deviation (around 0.05 school years). Chapter one shows that sub-clinical levels of radiation can have negative consequences even after early childhood. This is of particular importance because most of the literature focuses on exposure very early in life, often during pregnancy. However, population exposed after birth is over 100 times larger. These results point to substantial external human capital costs of radiation which can be reduced by choices of medical procedures. There is a large potential for reductions because about one-third of all CT scans are assumed to be not medically justified (Brenner and Hall, 2007). If people receive unnecessary CT scans because of economic incentives, this chapter points to additional external costs of health care policies. Furthermore, the results can inform the cost-benefit trade-off for medically indicated procedures. Chapter two provides evidence about the effectiveness of Low Emission Zones. Low Emission Zones are typically justified by improvements in population health. However, there is little evidence about the potential health benefits from policy interventions aiming at improving air quality in inner-cities. The chapter ask how the coverage of Low Emission Zones air pollution and hospitalization, by exploiting variation in the roll out of Low Emission Zones in Germany. It combines information on the geographic coverage of Low Emission Zones with rich panel data on the universe of German hospitals over the period from 2006 to 2016 with precise information on hospital locations and the annual frequency of detailed diagnoses. In order to establish that our estimates of Low Emission Zones’ health impacts can indeed be attributed to improvements in local air quality, we use data from Germany’s official air pollution monitoring system and assign monitor locations to Low Emission Zones and test whether measures of air pollution are affected by the coverage of a Low Emission Zone. Results in chapter two confirm former results showing that the introduction of Low Emission Zones improved air quality significantly by reducing NO2 and PM10 concentrations. Furthermore, the chapter shows that hospitals which catchment areas are covered by a Low Emission Zone, diagnose significantly less air pollution related diseases, in particular by reducing the incidents of chronic diseases of the circulatory and the respiratory system. The effect is stronger before 2012, which is consistent with a general improvement in the vehicle fleet’s emission standards. Depending on the disease, a one-standard-deviation increase in the coverage of a hospitals catchment area covered by a Low Emission Zone reduces the yearly number of diagnoses up to 5 percent. These findings have strong implications for policy makers. In 2015, overall costs for health care in Germany were around 340 billion euros, of which 46 billion euros for diseases of the circulatory system, making it the most expensive type of disease caused by 2.9 million cases (Statistisches Bundesamt, 2017b). Hence, reductions in the incidence of diseases of the circulatory system may directly reduce society’s health care costs. Whereas chapter one and two study the demand-side in health care markets and thus preventive potential, chapter three analyzes the supply-side. By exploiting the same hospital panel data set as in chapter two, chapter three studies the effect of treatment price shocks on the reallocation of hospital resources in Germany. Starting in 2005, the implementation of the German-DRG-System led to general idiosyncratic treatment price shocks for individual hospitals. Thus far there is little evidence of the impact of general price shocks on the reallocation of hospital resources. Additionally, I add to the exiting literature by showing that price shocks can have persistent effects on hospital resources even when these shocks vanish. However, simple OLS regressions would underestimate the true effect, due to endogenous treatment price shocks. I implement a novel instrument variable strategy that exploits the exogenous variation in the number of days of snow in hospital catchment areas. A peculiarity of the reform allowed variation in days of snow to have a persistent impact on treatment prices. I find that treatment price increases lead to increases in input factors such as nursing staff, physicians and the range of treatments offered but to decreases in the treatment volume. This indicates supplier-induced demand. Furthermore, the probability of hospital mergers and privatization decreases. Structural differences in pre-treatment characteristics between hospitals enhance these effects. For instance, private and larger hospitals are more affected. IV estimates reveal that OLS results are biased towards zero in almost all dimensions because structural hospital differences are correlated with the reallocation of hospital resources. These results are important for several reasons. The G-DRG-Reform led to a persistent polarization of hospital resources, as some hospitals were exposed to treatment price increases, while others experienced reductions. If hospitals increase the treatment volume as a response to price reductions by offering unnecessary therapies, it has a negative impact on population wellbeing and public spending. However, results show a decrease in the range of treatments if prices decrease. Hospitals might specialize more, thus attracting more patients. From a policy perspective it is important to evaluate if such changes in the range of treatments jeopardize an adequate nationwide provision of treatments. Furthermore, the results show a decrease in the number of nurses and physicians if prices decrease. This could partly explain the nursing crisis in German hospitals. However, since hospitals specialize more they might be able to realize efficiency gains which justify reductions in input factors without loses in quality. Further research is necessary to provide evidence for the impact of the G-DRG-Reform on health care quality. Another important aspect are changes in the organizational structure. Many public hospitals have been privatized or merged. The findings show that this is at least partly driven by the G-DRG-Reform. This can again lead to a lack in services offered in some regions if merged hospitals specialize more or if hospitals are taken over by ecclesiastical organizations which do not provide all treatments due to moral conviction. Overall, this dissertation reveals large potential for preventive health care measures and helps to explain reallocation processes in the hospital sector if treatment prices change. Furthermore, its findings have potentially relevant implications for other areas of public policy. Chapter one identifies an effect of low dose radiation on cognitive health. As mankind is searching for new energy sources, nuclear power is becoming popular again. However, results of chapter one point to substantial costs of nuclear energy which have not been accounted yet. Chapter two finds strong evidence that air quality improvements by Low Emission Zones translate into health improvements, even at relatively low levels of air pollution. These findings may, for instance, be of relevance to design further policies targeted at air pollution such as diesel bans. As pointed out in chapter three, the implementation of DRG-Systems may have unintended side-effects on the reallocation of hospital resources. This may also apply to other providers in the health care sector such as resident doctors.
On January 1, 2015, Germany introduced a general statutory minimum wage of €8.50 gross per hour. This thesis analyses the effects of the minimum wage introduction in Germany as well as wage floors in the European context, contributing to national and international research.
The second chapter of this dissertation summarizes the short-run effects of the minimum wage reform found in previous studies.
We show that the introduction of the minimum wage had a positive effect on wages at the bottom of the distribution. Yet, there was still a significant amount of non-compliance shortly after the reform. Additionally, previous evidence points to small negative employment effects mainly driven by a reduction in mini-jobs. Contrary to expectations, though, there were no effects on poverty and general inequality found in the short run. This is mostly due to the fact that working hours were reduced and the increase of hourly wages was therefore not reflected in monthly wages.
The third chapter identifies whether the job losses predicted in ex-ante studies materialized in the short run and, if so, which type of employment was affected the most. To identify the effects, this chapter (as well as chapter four) uses a regional difference-in-difference approach to estimate the effects on regular employment (part- and full-time) and mini-jobs.
Our results suggest that the minimum wage has slightly reduced overall employment, mainly due to a decline in mini-jobs.
The fourth chapter has the same methodological approach as the previous one. Its motivated by the fact that women are often overrepresented among low-wage employees. Thus, the primary research question in this chapter is whether the minimum wage has led to a narrowing of the gender wage gap. In order to answer that, we identify the effects on the wage gap at the 10th and 25th percentiles and at the mean of the underlying gender-specific wage distributions. Our results imply that for eligible employees the gender wage gap at the 10th percentile decreased by 4.6 percentage points between 2014 and 2018 in high-bite regions compared to low-bite regions. We estimate this to be a reduction of 32% compared to 2014. Higher up the distribution – i.e. at the 25th percentile and the mean – the effects are smaller and not as robust.
The fifth chapter keeps the gender-specific emphasis on minimum wage effects. However, in contrast to the rest of the dissertation, it widens the scope to other European Union countries. Following the rationale of the previous chapter, women could potentially benefit particularly from a minimum wage. However, they could also be more prone to suffer from the possibly induced job losses or reductions in working hours. Therefore, this chapter summarizes existing evidence from EU member states dealing with the relationship between wage floors and the gender wage gap. In addition, it provides a systematic summary of studies that examine the impact of minimum wages on employment losses or changes in working hours that particularly affect women. The evidence shows that higher wage floors are often associated with smaller gender wage gaps. With respect to employment, women do not appear to experience greater employment losses than men per se. However, studies show that the minimum wage has a particular impact on part-time workers. Therefore, it cannot be ruled out that the negative correlation between the minimum wage and the gender wage gap is related to the job losses of these lower-paid, often female, part-time workers. This working arrangement should therefore be specially focused on in the context of minimum wages.
Process-based integrated assessment models (IAMs) project long-term transformation pathways in energy and land-use systems under what-if assumptions. IAM evaluation is necessary to improve the models’ usefulness as scientific tools applicable in the complex and contested domain of climate change mitigation. We contribute the first comprehensive synthesis of process-based IAM evaluation research, drawing on a wide range of examples across six different evaluation methods including historical simulations, stylised facts, and model diagnostics. For each evaluation method, we identify progress and milestones to date, and draw out lessons learnt as well as challenges remaining. We find that each evaluation method has distinctive strengths, as well as constraints on its application. We use these insights to propose a systematic evaluation framework combining multiple methods to establish the appropriateness, interpretability, credibility, and relevance of process-based IAMs as useful scientific tools for informing climate policy. We also set out a programme of evaluation research to be mainstreamed both within and outside the IAM community.
Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.
Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as '1.5 °C scenarios', with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define 'medium' and 'high' upper bounds that delineate between their 'reasonable', 'challenging' and 'speculative' use by mid century. We do not find any 1.5 °C scenarios that stay within all medium upper bounds on the five mitigation levers. Scenarios most frequently 'over use' CDR with geological storage as a mitigation lever, whilst reductions of energy demand and carbon intensity of energy production are 'over used' less frequently. If we allow mitigation levers to be employed up to our high upper bounds, we are left with 22 of the SR1.5 1.5 °C scenarios with no or low overshoot. The scenarios that fulfil these criteria are characterised by greater coverage of the available mitigation levers than those scenarios that exceed at least one of the high upper bounds. When excluding the two scenarios that exceed the SR1.5 carbon budget for limiting global warming to 1.5 °C, this subset of 1.5 °C scenarios shows a range of 15–22 Gt CO2 (16–22 Gt CO2 interquartile range) for emissions in 2030. For the year of reaching net zero CO2 emissions the range is 2039–2061 (2049–2057 interquartile range).
Closing the emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries. They need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant, short-term measures informed by interactions with country experts. These good practice policies are rolled out globally between now and 2030 and combined with carbon pricing thereafter. We implement this scenario with an ensemble of global integrated assessment models. We show that the Bridge scenario closes two-thirds of the emissions gap between NDC and 2 °C scenarios by 2030 and enables a pathway in line with the 2 °C goal when combined with the necessary long-term changes, i.e. more comprehensive pricing measures after 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 52%–88% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation.
Interest in evaluating the effects of continuous treatments has been on the rise recently. To facilitate the estimation of causal effects in this setting, the present paper introduces entropy balancing for continuous treatments (EBCT) by extending the original entropy balancing methodology of Hainmüller (2012). In order to estimate balancing weights, the proposed approach solves a globally convex constrained optimization problem, allowing for much more computationally efficient implementation compared to other available methods. EBCT weights reliably eradicate Pearson correlations between covariates and the continuous treatment variable. This is the case even when other methods based on the generalized propensity score tend to yield insufficient balance due to strong selection into different treatment intensities. Moreover, the optimization procedure is more successful in avoiding extreme weights attached to a single unit. Extensive Monte-Carlo simulations show that treatment effect estimates using EBCT display similar or lower bias and uniformly lower root mean squared error. These properties make EBCT an attractive method for the evaluation of continuous treatments. Software implementation is available for Stata and R.
The crises of both the climate and the biosphere are manifestations of the imbalance between human extractive, and polluting activities and the Earth’s regenerative capacity. Planetary boundaries define limits for biophysical systems and processes that regulate the stability and life support capacity of the Earth system, and thereby also define a safe operating space for humanity on Earth. Budgets associated to planetary boundaries can be understood as global commons: common pool resources that can be utilized within finite limits. Despite the analytical interpretation of planetary boundaries as global commons, the planetary boundaries framework is missing a thorough integration into economic theory. We aim to bridge the gap between welfare economic theory and planetary boundaries as derived in the natural sciences by presenting a unified theory of cost-benefit and cost-effectiveness analysis. Our pragmatic approach aims to overcome shortcomings of the practical applications of CEA and CBA to environmental problems of a planetary scale. To do so, we develop a model framework and explore decision paradigms that give guidance to setting limits on human activities. This conceptual framework is then applied to planetary boundaries. We conclude by using the realized insights to derive a research agenda that builds on the understanding of planetary boundaries as global commons.
The large majority of climate change mitigation scenarios that hold warming below 2 °C show high deployment of carbon dioxide removal (CDR), resulting in a peak-and-decline behavior in global temperature. This is driven by the assumption of an exponentially increasing carbon price trajectory which is perceived to be economically optimal for meeting a carbon budget. However, this optimality relies on the assumption that a finite carbon budget associated with a temperature target is filled up steadily over time. The availability of net carbon removals invalidates this assumption and therefore a different carbon price trajectory should be chosen. We show how the optimal carbon price path for remaining well below 2 °C limits CDR demand and analyze requirements for constructing alternatives, which may be easier to implement in reality. We show that warming can be held at well below 2 °C at much lower long-term economic effort and lower CDR deployment and therefore lower risks if carbon prices are high enough in the beginning to ensure target compliance, but increase at a lower rate after carbon neutrality has been reached.
Economic agents often irrationally base their decision-making on irrelevant information. This research analyzes whether men and women react to futile information about past outcomes. For this purpose, we run a laboratory experiment (Study 1) and use field data (Study 2). In both studies, the behavior of men is consistent with falsely assumed negative autocorrelation, often referred to as gambler’s fallacy Women’s behavior aligns with falsely assumed positive autocorrelation, a notion of the hot hand fallacy. On the aggregate, the two fallacies cancel out. Even when individuals are, on average, rational, the biases in the decision-making of subgroups might cause inefficient outcomes. In a mediation analysis, we find that a) the agents stated perceived probabilities of future outcomes are not blurred by irrelevant information and b) about 40 % of the observed biases are driven by differences in the perceived attractiveness of available choices caused by the irrelevant information.
Charities typically ask potential donors repeatedly for a donation. These repeated requests might trigger avoidance behavior. Considering that, this paper analyzes the impact of offering an ask avoidance option on charitable giving. In a proposed utility framework, the avoidance option decreases the social pressure to donate. At the same time, it induces feelings of gratitude toward the fundraiser, which may lead to a reciprocal increase in donations. The results of a lab experiment designed to disentangle the two channels show no negative impact of the option to avoid repeated asking on donations. Instead, the full model indicates a positive impact of the reciprocity channel. This finding suggests that it might be beneficial for charities to introduce an ask avoidance option during high-frequency fundraising campaigns.