Contributions published at Department of Economics (Florian Scheuer)

This open access textbook introduces the emerging field of Development Engineering and its constituent theories, methods, and applications. It is both a teaching text for students and a resource for researchers and practitioners engaged in the design and scaling of technologies for low-resource communities. The scope is broad, ranging from the development of mobile applications for low-literacy users to hardware and software solutions for providing electricity and water in remote settings. It is also highly interdisciplinary, drawing on methods and theory from the social sciences as well as engineering and the natural sciences. The opening section reviews the history of “technology-for-development” research, and presents a framework that formalizes this body of work and begins its transformation into an academic discipline. It identifies common challenges in development and explains the book’s iterative approach of “innovation, implementation, evaluation, adaptation.” Each of the next six thematic sections focuses on a different sector: energy and environment; market performance; education and labor; water, sanitation and health; digital governance; and connectivity. These thematic sections contain case studies from landmark research that directly integrates engineering innovation with technically rigorous methods from the social sciences. Each case study describes the design, evaluation, and/or scaling of a technology in the field and follows a single form, with common elements and discussion questions, to create continuity and pedagogical consistency. Together, they highlight successful solutions to development challenges, while also analyzing the rarely discussed failures. The book concludes by reiterating the core principles of development engineering illustrated in the case studies, highlighting common challenges that engineers and scientists will face in designing technology interventions that sustainably accelerate economic development. Development Engineering provides, for the first time, a coherent intellectual framework for attacking the challenges of poverty and global climate change through the design of better technologies. It offers the rigorous discipline needed to channel the energy of a new generation of scientists and engineers toward advancing social justice and improved living conditions in low-resource communities around the world.

In this paper, the author analyzes different political regimes (empires, nation-states, and democracies) in a number of institutional and economic dimensions: tendency towards geographical expansionism or fragmentation, cultural heterogeneity, focus of public spending, and a number of other variables. He uses this setup to analyze the coexistence and interactions between empires, nation-states, and democracies. While these interactions are source of instability, he argues that modern economic development tends to doom empires that were once the dominant form of political regime in history.

We estimate the effect of a female employee giving birth and taking parental leave on small firms and coworkers in Denmark using a dynamic difference-in-differences design. We find little evidence that parental leave take-up has negative effects on firms and coworkers overall. This is because most firms are very effective in compensating for the worker on leave by hiring temporary workers and by increasing other employees’ hours. In contrast, we do find evidence that parental leave has negative effects on a small subsample of firms which are less able to use their existing employees to compensate for absent workers.

Recent years have witnessed the rise of digital platforms that allow economic agents to arrange ever more fine-grained contracts. This article zooms in on labour-based platforms that permit the hire of labour in a just-in-time fashion (and are part of the broader trend towards on-demand work). Its principal contributions correspond to its three sections. First, the article exposes the frequently overlooked diversity of labour-based platforms. While the debate typically focuses on powerful platform companies, which arguably constitute distinct economic entities, other platforms resemble mere marketplaces or ordinary employers. Second, it argues that staying alert to this diversity is vital because violations of labour justice take different forms across the three types of platforms. The underlying cause, however, is identical: their relative powerlessness renders workers vulnerable to domination and exploitation. Finally, the article examines three strategies for addressing this threat: turning platforms into worker-run co-ops, introducing stricter regulation, and improving outside job opportunities. While each strategy is most suitable in certain contexts, and all three are complementary, the article argues that the last strategy is most significant. This feeds into its overall conclusion: we should always discuss labour-based platforms with an eye towards the broader labour market.

Previous research finds that the greater geographic mobility of foreign than native-born workers following economic shocks helps to facilitate local labor market adjustment to shifting regional economic conditions. We examine the role that immigration may have played in enabling U.S. commuting zones to respond to manufacturing job loss caused by import competition from China. Although population headcounts of the foreign-born fell by more than those of the native-born in regions exposed to the China trade shock, the overall contribution of immigration to labor market adjustment in this episode was small. Because most U.S. immigrants arrived in the country after manufacturing regions were already mature, few took up jobs in industries that would later see increased import penetration from China. The foreign-born share of the working-age population in regions with high trade exposure was only three-fifths that in regions with low exposure. Immigration thus appears more likely to aid adjustment to cyclical shocks, in which job loss occurs in regions that had recent booms in hiring, rather than facilitating adjustment to secular regional decline, in which hiring booms occurred in the more distant past.

Poor psychological health is associated with Takotsubo cardiomyopathy, cardiac syndrome X, coronary microcirculatory dysfunction, peripheral artery disease, or spontaneous coronary artery dissection. Data regarding pessimism, cardiovascular disease (CVD) events and mortality and all-cause mortality remained inconclusive. This systematic review and meta-analysis aim to provide an overview of the association between pessimism, CVD outcomes and mortality. A systematic search of electronic databases was conducted from inception through July 2022 for studies evaluating pessimism and adverse outcomes. A total of 17 studies published between 1966 and July 2022 met our inclusion criteria, for a total of 232,533 individuals. Pooled hazard ratios were calculated in random-effects meta-analyses. Based on pooled analysis of adjusted HRs, pessimism was associated with adjusted HR of 1.13 (95% CI 1.07-1.19) for all-cause mortality with minimal heterogeneity (I2 = 28.5%). Based on pooled analysis of adjusted HRs, pessimism was associated with adjusted HR of 1.30 (95% CI 0.43-3.95) for CHD mortality, adjusted HR of 1.41 (95% CI 1.05-1.91) for CVD mortality, and adjusted HR of 1.43 (95% CI 0.64-3.16) for stroke. In conclusion, pessimism seems to be significantly associated with a higher risk for and poorer outcomes from CVD events than optimistic styles. There are genetic and other bases for these life approaches, but behavioral, cognitive and meditative interventions can modify patients' level of pessimism, hopefully leading to better medical outcomes. Testing this theory would yield highly useful and practical data for clinical care.

We provide an axiomatic characterization of Bayesian updating, viewed as a mapping from prior beliefs and new information to posteriors, which is disentangled from any reference to preferences. Bayesian updating is characterized by Non-Innovativeness (events considered impossible in the prior remain impossible in the posterior), Dropping (events contradicted by new evidence are considered impossible in the posterior), and Proportionality (for other events, the posterior simply rescales the prior’s probabilities proportionally). The result clarifies the differences between the normative Bayesian benchmark, alternative models, and actual human behavior.

Transitivity is perhaps the most fundamental choice axiom and, therefore, almost all economic models assume that preferences are transitive. The empirical literature has regularly documented violations of transitivity, but these violations pose little problem as long as they are simply a result of somewhat-noisy decision making and not a reflection of the deterministic part of individuals’ preferences. However, what if transitivity violations reflect individuals’ genuinely nontransitive preferences? And how can we separate nontransitive preferences from noise-generated transitivity violations – a problem that so far appears unresolved? Here we tackle these fundamental questions on the basis of a newly developed, non-parametric method which uses response times and choice frequencies to distinguish genuine preferences from noise. We extend the method to allow for nontransitive choices, enabling us to identify the share of weak stochastic transitivity violations that is due to nontransitive preferences. By applying the method to two different datasets, we document that a sizeable proportion of transitivity violations reflect nontransitive preferences. Specifically, in the two datasets, 19% and 14% of all cycles of alternatives for which preferences are revealed involve genuinely nontransitive preferences. These violations cannot be accounted for by any noise or utility specification within the universe of random utility models.

The potential benefits and mechanistic effects of working memory training (WMT) in children are the subject of much research and debate. We show that after five weeks of school-based, adaptive WMT 6–9 year-old primary school children had greater activity in prefrontal and striatal brain regions, higher task accuracy, and reduced intra-individual variability in response times compared to controls. Using a sequential sampling decision model, we demonstrate that this reduction in intra-individual variability can be explained by changes to the evidence accumulation rates and thresholds. Critically, intra-individual variability is useful in quantifying the immediate impact of cognitive training interventions, being a better predictor of academic skills and well-being 6–12 months after the end of training than task accuracy. Taken together, our results suggest that attention control is the initial mechanism that leads to the long-run benefits from adaptive WMT. Selective and sustained attention abilities may serve as a scaffold for subsequent changes in higher cognitive processes, academic skills, and general well-being. Furthermore, these results highlight that the selection of outcome measures and the timing of the assessments play a crucial role in detecting training efficacy. Thus, evaluating intra-individual variability, during or directly after training could allow for the early tailoring of training interventions in terms of duration or content to maximise their impact.

Background: Whenever vaccines for a new pandemic or widespread epidemic are developed, demand greatly exceeds the available supply of vaccine doses in the crucial, initial phases of vaccination. Rationing protocols must then fulfill a number of ethical principles balancing equal treatment of individuals and prioritization of at-risk and instrumental subpopulations. For COVID-19, actual rationing methods used a territory-based first allocation stage based on proportionality to population size, followed by locally-implemented prioritization rules. The results of this procedure have been argued to be ethically problematic. Methods: We use a formal-analytical approach arising from the mathematical social sciences which allows to investigate whether any allocation methods (known or unknown) fulfill a combination of (ethical) desiderata and, if so, how they are formulated algorithmically. Results: Strikingly, we find that there exists one and only one method that allows to treat people equally while giving priority to those who are worse off. We identify this method down to the algorithmic level and show that it is easily implementable and it exhibits additional, desirable properties. In contrast, we show that the procedures used during the COVID-19 pandemic violate both principles. Conclusions: Our research delivers an actual algorithm that is readily applicable and improves upon previous ones. Since our axiomatic approach shows that any other algorithm would either fail to treat people equally or fail to prioritize those who are worse off, we conclude that ethical principles dictate the adoption of this algorithm as a standard for the COVID-19 or any other comparable vaccination campaigns.

Do financial crises radicalize voters? We study Germany’s 1931 banking crisis, collecting new data on bank branches and firm-bank connections. Exploiting cross-sectional variation in precrisis exposure to the bank at the center of the crisis, we show that Nazi votes surged in locations more affected by its failure. Radicalization in response to the shock was exacerbated in cities with a history of anti-Semitism. After the Nazis seized power, both pogroms and deportations were more frequent in places affected by the banking crisis. Our results suggest an important synergy between financial distress and cultural predispositions, with far-reaching consequences.

Serial dictatorships have emerged as the canonical simple mechanisms in the literature on the allocation of indivisible goods without transfers. They are the only neutral and group-strategy-proof mechanisms in environments in which agents have no outside options and hence no individual rationality constraints (Svensson in Soc Choice Welfare 16:557–567, 1999). Accounting for outside options and individual rationality constraints, our main result constructs the class of group-strategy-proof, neutral, and non-wasteful mechanisms. These mechanisms are also Pareto efficient and we call them binary serial dictatorships. The abundance of the outside option - anybody who wants can opt out to get it - is crucial for our result.