Research Seminars

Household and ambient air pollution (HAAP), a major global health risk, is linked to a lower quality of life and is responsible for over six million premature annual deaths globally. We investigate country-level socioeconomic, environmental, energy, and health determinants of HAAP mortality rates, using regression analyses and global GIS mapping of predicted probabilities on high HAAP mortality risk. While related studies are predominantly country-specific based on micro-level factors, our study provides global evidence (n=150 countries) based on a broad range of macro-level indicators. Our findings reveal that rural access to clean cooking fuels and technology, as well as greater healthcare expenditure are critical for reducing HAAP deaths, whereas rurality and energy deprivation significantly increase mortality risks. While advanced economies show clear resilience to HAAP mortality risks, emerging and developing economies are disproportionately vulnerable. Contrary to related literature, our analyses also show that males are more at risk of HAAP mortality than females. Our results are robust to alternative model specifications and remain consistent over repeated samples. We further contextualise our global evidence with previous country-specific case studies on HAAP risks. Our research helps to appraise the progress towards achieving the UN Sustainable Development Goals 3, 5, and 7, addressing their associated targets and indicators, providing guidance for policymakers to strengthen efforts to reduce HAAP mortality and improve living conditions globally.

This paper examines how refugees' destinations and preferences evolve, focusing on Central and Eastern European countries. While our research findings are focussed on Bulgaria, Romania, and Hungary—regarded as ‘transit only countries’ prior to the Ukraine refugee crisis - we consider potential lessons to be drawn for more recent refugee inflows. Using a mixed-methods approach we show that prioritising safety significantly increases the likelihood of asylum seekers reconsidering a transit or temporary migration country as a settlement destination. Other influential factors include asylum conditions, migration costs, and educational background, with more educated individuals more likely to revise initial plans. Although our primary focus is on asylum seekers, we find that high migration costs affect decisions on destinations, suggesting a need to ‘recover’ investments through settlement in more stable or economi­cally attractive countries. The qualitative findings support the results, highlighting the role of legal stability, social networks, and perceived opportunity in shifting preferences for settlement. Finally, as the Czech Republic hosts most Ukrainian refugees per capita relative to its population, with a high share of women migrants, we add a reflection on the gendered aspects of migration, linking our research to the wider literature on the topic. 

We investigate whether departures from stationary intertemporal preferences, as identified in parametric estimations, reflect genuine nonstationarity in time preferences or arise from inconsistent or error-prone choice. Using data from a controlled lab experiment with a large number of intertemporal choices per subject, we applied nonparametric revealed preference tests to evaluate whether subjects’ behavior satisfies utility maximization and stationarity. We find that apparent violations of stationarity in parametric estimations are often better explained by misidentification due to inconsistency of choices with utility maximization or misspecification of the functional form, rather than by true nonstationary time preferences.

Job referrals through informal networks are an essential channel for disseminating information about the qualifications of job candidates. As such, they play a crucial role in determining the outcomes of hiring and promotion decisions. In this paper, we study gender biases in the referral process. We investigate this question through an online experiment in which university students are asked to nominate their highest-scoring classmates in either a math or a verbal task. Using administrative data, we reconstruct the students’ co-enrollment network. This allows us to identify who is chosen as well as everyone else who was not. In other words, we can measure the quality of the referrals and the characteristics of candidates who are better but not chosen. We find that participants are more likely to refer men than equally qualified women in the math task but not in the verbal task. This difference is partly explained by gender differences in network structure, i.e., who is linked with whom. However, equally important are gender biases in the referral of known contacts.

We study belief dynamics of an agent who repeatedly 'chooses' new beliefs, trading off costs from making worse decisions with benefits from anticipatory utility. We argue that some naiveté about past belief distortions is necessary to explain evidence on motivated reasoning and derive testable implications for belief dynamics when the agent naively treats each choice of beliefs as the first (and last) such choice. Such naiveté causes persistent insecurity and fragile optimism in important domains of life and dogmatic optimism in less important domains. It can also generate 'information avoidance' where a naive agent repeatedly, and indefinitely, postpones receiving information.

Background: This study investigates the potential relationship between obesity and self-ranking of poverty, as a proxy for self-awareness and happiness. To the best of our knowledge, this issue has not been previously explored based on self-ranking of poverty when income is controlled. Method: Ordered Probit Regressions. We propose a new measure for the influence of western social values and norms associated with discrimination against obese women. Results: Based on a follow-up survey after two years, findings demonstrate a drop in the projected probability of self-ranking as “not poor” with the BMI from 0.73 to 0.37 (females) – 0.48 (males) when the level of income is controlled. Similar outcomes are obtained when the independent variables are lagged and thus avoid endogeneity concerns. Finally, additional outcomes support the conclusion that the lagged BMI Granger-cause self-ranking of poverty for women, but not for men. Findings support the awareness of more obese women to lower prospects of finding a job. Conclusion: Since according to twin studies, approximately 80% of obesity emanates from genetic factors, research findings stress the need to educate the public against prejudices on the grounds of obesity. In particular, our study seeks to evoke awareness among potential employers, which, in turn, might motivate avoidance of, or at least reduction in, an implicit wage penalty against obese women.

Allowing voters to trade votes for money may generate either negative or positive externalities: A voter is harmed (benefited) if voters she agrees with end up with reduced (increased) voting power. However, the plausibility of each kind of externality crucially depends on the electoral rule in place (i.e., on the way votes are aggregated into a political outcome). Focusing on a private-values setting with two alternatives and on the family of qualified majority rules (ranging from a simple majority to unanimity), we first argue that trade: a) cannot generate any negative externalities in the interim stage for any rational voter (and, ex post, to any non-trader) if and only if a unanimity rule is in place, and b) can generate positive externalities to agents under any qualified majority rule. That is, under unanimity rule, vote trading is less objectionable in normative and/or welfare-related terms than under any other electoral system. We conduct a laboratory experiment to test these predictions and show that despite the fact that vote-trading improves utilitarian welfare under unanimity rule, several subjects are worse off compared to when vote-trading is not allowed. This raises important caveats regarding its use even under this most favorable institutional setting.

This paper aims to assess the social welfare benefits of open access competition for long distance passenger rail in Europe, using GB data as a case study, importantly taking into account not only benefits to passengers through lower fares and increased frequency, but impacts on total costs and impacts on government finances. This takes the cost analysis beyond Stead et. al. (2019), first by extending the analysis into an overall social cost benefit analysis with broader policy implications; and second by permitting more up-to-date and more years of data to assess cost differences between the incumbent and open access operators, taking into account that open access volumes have grown in the meantime.

This presentation explores the use of microsimulation modeling to inform health policy, drawing on the work of Bryan Tysinger and the Schaeffer Center team. It will introduce key models—including the Future Elderly Model (FEM) and Future Adult Model (FAM)—used to simulate individual trajectories in health, healthcare utilization, and economic outcomes. Applications discussed will range from evaluating obesity treatments and dementia risk reduction to analyzing rural health disparities and pandemic mortality. Attendees will also get a preview of new research directions and learn how collaborative modeling can support evidence-based policymaking and effective communication with stakeholders.

The large influx of refugees over recent decades challenges many Western countries to devise effective policies for long-term integration. A key policy question is whether refugee children should be directly integrated into native schools or initially separated into migrant schools. In the Netherlands, refugee children arriving at primary-school age are taught either in integrated or separated schools depending on their randomly assigned municipality, whereas all secondary-school-aged arrivals are initially separated. We exploit this setting in a novel difference-in-differences framework, leveraging rich administrative data. Results indicate that on average, integrated primary schooling increases cultural assimilation as measured by hormonal-contraceptive usage but decreases educational outcomes at age 18. The negative educational effects are restricted to children from disadvantaged backgrounds, whereas the positive assimilation effects are strongest for children from advantaged backgrounds.

We propose a general framework that links social-media network structures with the concept of retail investors' attention to improve financial forecasting. We construct asset-level networks based on social-media co-mentions, leveraging information about retail investors' attention. Our contribution is twofold: First, the weighted adjacency matrix associated with this network provides an intuitive and parsimonious way to model spillover effects in volatility models, extending the notion of retail investors' attention to the multivariate case. Second, the dynamics of the overall network structure may provide predictive power for macro-level risk indicators. Preliminary results suggest that financial social networks are particularly useful for forecasting asset-level volatility.

Symbolic regression (SR) is an estimation method aimed at finding simple, interpretable equations in a fully data-driven manner. We investigate under which settings SR algorithms are expected to recover a "true" model. SR is formulated as a solution to a model selection problem, and we formalize the discussion on whether true model recovery is achievable. For the case of estimating an unknown nonlinear conditional expectation function, exhaustive symbolic regression (ESR) is conjectured to select the true model in large samples, provided the true model is contained in the search space and a consistent model selection criterion is used. Within the PAC-learning framework, ESR can be framed as a structural risk minimization (SRM) problem, and we argue that ESR is non-uniformly PAC-learnable under mild assumptions. Various applications of SR to economics and finance are proposed.

We examine the CEO career consequences following shareholder activism in their companies. To address endogeneity, we employ a control function approach, using expected mutual fund flow-induced sales and purchases as exclusion restrictions. We show that CEOs targeted by activists are more likely to be dismissed earlier and less likely to retain internal executive board positions than non-targeted CEOs. We also find significant decreases in their remuneration, while their outside board seats remain unaffected. These effects vary across campaign hostility, activist types, and CEOs’ ex-ante resistance. Hostile campaigns and campaigns involving hedge funds impose more adverse career effects, though anticipated CEO resistance deters activism and mitigates negative effects from hedge fund involvement in non-hostile campaigns.

The Paris-Lyon line is the busiest High-Speed Line in Europe and has been open to competition in open access since December 18, 2021. The main objective of the paper is to explore the effects for users with respect to price and frequency compare with the existing literature. The analysis is based on a large database (n = 1243) collected by web scraping from September 2019 to October 2022. The method relies on a descriptive analysis with a similar route without competition (Paris-Bordeaux) in the comparison group. The results highlight an increase of frequency by 15% and a decrease in price by 23%. The prices charged by the newcomer are lower than those of the incumbent (−30% to −50%). The comparison with the control route suggests a positive effect on price that moderates the economic catch-up effect following the COVID-19 pandemic in an inflationary context. More specifically, SNCF appears to take a wait and see attitude to competitive pressure from Trenitalia. It has moderated its prices since the new offer was introduced and has maintained its trains.

Microsimulation models have become indispensable tools in evaluating the dynamic impact of policy interventions across Europe, the United States and other countries. This seminar introduces the principles and advantages of policy microsimulation, with a particular focus on the European Future Elderly Model (EUFEM).

EUFEM enables the integration of longitudinal and cross-sectional data to simulate the consequences of policy interventions in healthcare, labor markets, and social protection systems.

Drawing on results from recent applications—including disease burden estimation, LTC policies and prevention startegies—this talk illustrates how EUFEM supports policy evaluation in a controlled, data-rich environment. Particular attention will be paid to methodological choices, validation strategies, and the challenges of aligning health and economic models with real-world applications, e.g. in heart disease, diabetes, obesity and other areas.

This paper examines post-Global Financial Crisis changes in the relevance of bank capitalization and firms’ unrated status in determining bank-firm matching in the U.S. syndicated loan market. Since 2010, the expansion of the bond market and persistently low interest rates have weakened the traditional ties between unrated firms and well-capitalized banks. Improved bond market access reduces the incentive for unrated firms to borrow from well-capitalized banks, while lower-capitalized banks, in search of higher yields, increasingly lend to these firms. Notably, during the COVID-19 crisis, matching with well-capitalized banks did not influence unrated firms’ credit access, as stricter capital requirements had enhanced the lending capacity of lower-capitalized banks.

In today's world, social media is a major source of information for many people. However, not all information on social media is accurate, and misinformation can spread quickly, especially on important topics like climate change. This study aims to examiner how social media message formats (text, picture and video) affect climate change perception and behaviours. A mixed-method study with participants from UK and Mexico was conducted. The study found that misinformation reduces the credibility of social media posts in all formats (text, picture, video). Accurate posts about climate change prompted people to think about taking action to protect the environment. In contrast, misinformation posts made some people believe that climate change is not caused by humans and therefore not their problem to fix. Finally, it was found that higher social media literacy generally helps people recognise misinformation, especially in pictures. However, surprisingly, those with higher social media literacy might find video misinformation more credible. The study significantly advances our understanding of the interplay between message formats, misinformation, and social media's impact on climate change perceptions.

We show that external suppliers are critical for facilitating machinery investments and capturing the skill bias of new machines. Linking firm data on capital investments, buyer-supplier transactions, and worker skills in Belgium, we find that the adoption of new machinery by manufacturing firms strongly increases the skills demanded from external suppliers. By contrast, the machines do not alter the skill mix of in-house employment. The skill bias of external suppliers reflects machine integration initially and machine-complementary services eventually. External integrators are especially important for smaller manufacturing firms, and the skill bias of investment depends on the capital type and application sector. Our findings help reconcile recent firm-level studies of in-house employment with long-standing theories of capital-skill complementarities

This paper develops a welfare and public economics perspective on optimal policies for carbon removal and storage (CDR) in permanent and non-permanent sinks. Non-permanent CDR reduces mitigation costs, even though the stored carbon is released into the atmosphere eventually. It may serve as bridge technology until permanent CDR becomes available. In contrast to permanent removals, non-permanent CDR does not reduce the optimal long-run temperature level. Its valuation differs from the social cost of carbon since a social cost of carbon removal arises from marginal damages caused by emissions released from non-permanent storage. We discuss three policy regimes that ensure optimal deployment of non-permanent CDR in terms of their informational and institutional requirements for monitoring, liability, and financing.

This paper investigates whether tax evasion can be beneficial for an optimal income tax schedule. Past theoretical discussions have presented mixed outcomes as to whether allowing taxpayers to opt into uncertainty could indeed enhance overall tax revenues. In this study, we conducted an original real effort experiment in an online labor market with almost 1,000 participants to test this hypothesis empirically. Our findings show significant positive labor supply responses to the opportunity to evade (increased labor supply by 37%). More importantly, the expected tax revenue significantly and substantially increased by up to more than 50%. Strikingly, this effect persists when comparing effective tax rates: Lowering effective tax rates through probabilistic enforcement (the opportunity to evade) is more efficient than simply lowering statutory tax rates. Our findings suggest that the opportunity for tax evasion can increase tax revenues beyond what a corresponding decrease in nominal rates would achieve.

Exploiting the 1848 revolution in the Austrian Empire, I study how a sudden institutional change impacts economic development. In contrast to much existing research, which focuses on the rule of law and the security of property rights, I argue that the main impact occurred through the expansion of the upper-tail useful human capital (Mokyr, 2005) following the revolution. While the revolution was defeated, important liberalizing reforms persisted in the areas of (i) the press, (ii) technical education and (iii) knowledge-promoting voluntary associations – the information space, for short. Pushing back against the existing consensus that the revolution had no discernible impact on the empire’s economic development, I combine newly collected data on the pre-1848 and post-1848 information space with data on the use and location of steam engines in 1841–1863 to establish the causal link between the post-1848 reforms and the diffusion of this important industrial technology.

While risky choice under time pressure is a topic that has attracted much attention in the literature, the effects of time pressure on risk attitudes seem to be poorly understood. In this paper we present evidence from an economic experiment where participants have to allocate an experimental income to two risky assets, with and without time pressure. We assume Rank Dependent Utility preferences, where risk attitudes are captured by both the utility curvature and the probability weighting function. Using the allocation data, we fit structural models which allow us to disentangle the effect of time pressure on the two components of risk attitudes. We then correlate the risk attitudes to various demographic and personality traits.

In this paper, we estimate the rise in smoking prevalence in East Germany caused by exposure to West German TV, with a focus on gender differences. We leverage survey data on smoking prevalence from 1989 (before the fall of the Berlin Wall) and 2002 (twelve years following reunification) and exploit exogenous variation in exposure to the West German TV signal to identify the causal effect. We document that exposure to West German TV increases smoking prevalence, but this rise is concentrated entirely among women, with a negligible impact on men. Our estimates imply a 10.5 percentage point increase in the probability of smoking among women and a 70.7% increase in the number of cigarettes smoked. These findings are robust across various tests and suggest that the convergence in smoking rates between men and women will likely lead to an increase in women's mortality and healthcare costs.

This paper provides a comprehensive assessment of the impact of education finance on students’ long-term outcomes and the mechanisms through which these effects operate. For identification, I exploit an intergovernmental transfer reform in Norway, which generated exogenous variation in school funding based on the school-aged demographic composition at the local level in the mid1980s. The main takeaway is that exposure to an additional $100 per pupil in education funding over nine years of primary and lower-secondary school leads to nearly $250 in higher annual earnings. This effect corresponds to an Internal Rate of Return (IRR) greater than 6% and a Marginal Value of Public Funds (MVPF) ranging from 1.5 to 2.5. The increase in earnings is mediated by higher educational attainment, higher likelihood of obtaining a degree in high-paying fields, and improved cognitive abilities. The effect is larger and more significant for students from low-educated parents and those at the lower end of the earnings distribution, while no significant impact is found for students with at least one college-educated parent. At the municipal level, the funding shock led to an increase in teacher hiring without affecting capital expenditures.

Cost of medicines is on an exponential rise and the pressure towards speedy access to medicines comes from all directions: pharmaceutical industry, patients, clinicians, politicians, and ultimately, the public. In Europe, standard reimbursement of a medicine typically requires efficacy approval from the European Medicines Agency (EMA), clinical and cost-effectiveness assessment of a Health Technology Assessment (HTA) body, and decision by a national regulator. With the intention to provide speedy access, efficacy evidence standards are often lowered in the name of hope that the given medicine may bring about clinically meaningful benefit nonetheless. This shift brings significant uncertainty into clinical and pharmaco-economic assessments, and ultimately into decision-making.
Using the example of a cost-utility analysis of an advance therapy medicinal product (ATMP) for spinal muscular atrophy, I will illustrate a prototypical case of modelling uncertainties. These uncertainties include the use of incomplete data sets, short-term data cut-offs used for long-term extrapolations, or challenges with discounting rates for benefits and costs of chronic conditions. Further challenges include modelling based on data from single arm trials, modelling with numerical values without statistical significance, label approved by EMA for a wider population than included in the clinical trials, or the question of selective approach to the inclusion of indirect costs.
This shift leads to a number of open normative questions such as: who is to pay for the cost of uncertainty? How should we set up willingness-to-pay-thresholds? What will be the role of the new European regulation on HTA (2021/2282)? How to prevent the public from paying thrice: for basic research of medicines, for the actual patented treatment, and for post-market evidence generation?

Previous evidence on the sunk cost fallacy primarily comes from laboratory or online experiments in which the sunk cost consists of a single upfront payment. In this paper, we study sunk cost effects in a highly relevant field context (exercising), where sunk costs may be dispersed over time and influence habit formation. In particular, we investigate how a (random) two-month discount on the membership fee affects the exercising behavior of new members of a large fitness chain and test whether individuals mentally account for the timing of this discount, i.e., the dispersion of sunk costs over time. The experimental design allows us to exclude any selection into discounted memberships and thereby isolate potential sunk cost effects. Despite a highly powered design, we do not find any evidence of sunk cost effects. These results cast doubt on the relevance of the sunk cost fallacy in the health domain. They also suggest that the common practice of offering discounts on membership fees does not undermine habit formation.

Despite the vast medical literature on the health effects of menopause, its economic implications remain understudied. During women's reproductive years, hormones like estrogen are protective of health. Menopause, associated with a gradual yet pronounced decrease in estrogen, induces a distinct change in women’s health trajectory that may have an impact on employment. This paper uses detailed data on the reported natural age of menopause for women in the Health and Retirement Study (HRS) to estimate the impact of menopause on health and employment. To address issues in identification that arise when analyzing menopause, such as confounding factors and measurement error, this paper uses the genetic predisposition for the timing of menopause, specifically the associated polygenic risk score (PGS), as an instrument for the reported age of natural menopause. There are three principal findings. First, consistent with the medical literature, crossing the menopause threshold there is an economically substantive and statistically significant acceleration in health conditions. The decline in health is more than triple that for pre-menopause years. Second, menopause is associated with a substantial reduction in the likelihood of working for pay by just under 2 percentage points every year after menopause, which accumulates to an 18 percentage point reduction in ten years. Combining these estimates, the associated IV estimate of the impact of health on employment indicates that the diagnosis of an additional medical condition reduces the likelihood of working for pay by between 49 to 77 percentage points depending on the exact specification. This is a substantial effect given that 78% of women work for pay prior to menopause. The key take-away is that essentially an additional diagnosis of a medical condition results in exit from employment for middle age to older women.

This study explores how, when income inequality is perceived to arise from both effort and luck, excuses (self-serving belief distortions) can influence acceptance of inequality. In a controlled laboratory setting involving a real-effort task, participants make redistribution decisions between themselves and a partner. The study varied the degree of uncertainty about the role of effort and luck in determining initial earnings endowments. Belief elicitations indicate that increased uncertainty caused participants to be more likely to attribute their partner’s success to luck. Furthermore, the use of excuses (attributing others’ outcomes to luck) was found to reduce willingness to redistribute earnings to their partners. These findings highlight how excuses about the role of luck versus effort may contribute to the persistence of inequality even if many individuals have meritocratic principles, and how variation in the degree of uncertainty about the causes of inequality, across individuals or societies, may contribute to different degrees of biased beliefs and inequality. The paper also shows evidence of excuses in another sense: According to a structural model of fairness views, individuals tend to adopt a fairness view – egalitarian, meritocratic, or libertarian – to justify an allocation that benefits themselves.

Does having children make you lose your mind? This study investigates the causal relationship between the number of children and the risk of dementia among parents, addressing longstanding questions about how parenthood shapes cognitive health in later life. Using comprehensive administrative data for all parents born in Sweden between 1920 and 1950, we derive completed fertility from multi-generational registers and identify dementia onset through in-patient registers and cause-of-death records. To estimate causal effects, we apply instrumental variable (IV), leveraging quasi-experimental variation from offspring sex composition and twin births, and within-family designs in survival models. Baseline associations reveal a U-shaped gradient between the number of children and dementia risk, with significantly higher risks for childless individuals and those with more than three children. However, IV and within-sibling estimates indicate no adverse effects of having multiple children on dementia risk, and suggest that parenthood generally reduces dementia risk. These findings challenge recent studies that report accelerated cognitive decline with higher parity, suggesting that observed risks are driven by confounding factors. Further analyses explore potential mediators, including educational attainment, labor market outcomes, and social/geographical proximity to offspring, highlighting how midlife motherhood penalties attenuate the protective effects of parenthood for women.