Motivated by the recent surge in union drives, we present a theoretical model of the factors that influence unionization. An employee seeking to unionize their workplace assembles organizers to persuade coworkers to vote in favor. If unionization benefits workers, it is more likely to succeed when the organizers are credible. Credibility depends on the organizers not being overly biased and/or bearing significant organizational costs. Our theory explains why grassroots movements, rather than established unions, often succeed in organizing workplaces. Interestingly, the likelihood of successful unionization, when it benefits workers, is non-monotonic with respect to organizational costs. When such costs are low, a firm that opposes unionization and targets organizers may paradoxically increase the chances of success. However, the unionization drive is ineffective if the firm’s opposition is sufficiently strong, as this makes organizational costs prohibitive.

This study explores the factors influencing household overcrowding using longitudinal survey data from Germany spanning the years 1985 to 2022. As average square meters per capita have declined for urban tenants, we find that overcrowding rates have substantially increased since 2012: By 2022, 11% of the population lived in overcrowded housing (Eurostat definition), while up to 19% of individuals subjectively felt overcrowded. At the same time, under-occupation also rose, with 39% of dwellings objectively classified as under-occupied, and 16% of residents subjectively perceiving their homes as under-occupied. We demonstrate that the likelihood of entering, experiencing, and remaining in overcrowded housing increases in early adulthood and decreases over the life cycle. Moreover, we find that, after controlling for socio-demographic characteristics such as the number of children or a migration background, economic factors contribute relatively little to explaining the likelihood of living in an overcrowded household. In policy terms, our paper highlights a misallocation of housing space and the need for housing policies to target particular vulnerable groups at high risk of overcrowding.

History shows militarily dominant states that pursue imperialism, relying on their might to extort resources from weaker states. Occasionally, the latter revolt and the dominant state suffers some casualties. This paper explores imperialism along steady-growth paths. If the dominant state maximizes domestic welfare, it should eventually abandon imperialism because its safety costs asymptotically overrun its material benefits. To shed light on diametrically opposed historical records, I propose a model of endogenous ideology and war bias in which the political elite cares about self-image. If that concern is strong enough, the political elite gradually identifies with its country’s mission of hegemony and imperialism persists. It is first driven by material concerns and later by ideal ones. Despite its divergent preferences, the population of a dominant state generally has little interest to oppose imperialism.

Recently, there is a growing interest in understanding how individuals adapt to changing climate conditions and climate-induced extreme weather events. An underexplored question is whether and how climate-related natural hazards affect household saving behavior. For this purpose, we exploit a natural experiment stemming from the European Flood of August 2002. Combining micro data with geo-coded flood maps allows us to analyze the causal impact of flood exposure on household savings within a differences-in-differences setting. We find that flood exposure depresses household saving behavior in the medium run. The most likely explanation is moral hazard induced by massive government support for affected households.

One of the primary objectives of protests and demonstrations is to bring social, political, or economic issues to the attention of politicians and the wider population. While protests can have a mobilizing and persuading effect, they may reduce support for their cause if they are perceived as a threat to public order. In this study, we look at how local or spontaneously organised xenophobic demonstrations affect concerns about hostility towards foreigners and worries about immigration among natives in Germany. We use a regression discontinuity design to compare the attitudes of individuals interviewed in the days immediately before a large far-right demonstration and individuals interviewed in the days immediately after that demonstration. Our results show that large right-wing demonstrations lead to a substantial increase in worries about hostility towards foreigners of 13.7% of a standard deviation. In contrast, worries about immigration are not affected by the demonstrations, indicating that the protesters are not successful in swaying public opinion in their favour. In the heterogeneity analyses, we uncover some polarisation in the population: While worries about hostility against foreigners increase and worries about immigration decrease in left-leaning regions, both types of worries increase in districts where centre-right parties are more successful. Lastly, we also show that people become more politically interested in response to protests, mainly benefiting left-wing parties, and are more likely to wish to donate money to help refugees.

Behavioral economics has so far largely avoided discussing the psychological origins of preferences, as well as their relation to needs. This has not only restricted interdisciplinary exchange, but also significantly limits the predictive capabilities of models. For example, the revealed preference approach can only reliably predict repeating choices, while needing large amounts of observations for calibration. In this paper, I show how unifying preferences with the psychological concept of needs strengthens economic models, by developing a decision-making framework for well-being assessment and choice prediction. To present the direct merit of this approach, I show how this framework yields a systematic approximation scheme, which is able to solve limitations of current approaches by describing new alternatives, non-repeating choices, or otherwise unobservable desires. Meanwhile, the approximation scheme requires less observations on an individual level than current approaches. I achieve this by constructing a hierarchical dependency between human motivations and preferences through the language of needs. I show the basic feasibility of the approximation scheme through simulations on random populations. In practice, the framework is applicable in situations where individuals exert choices only once and measuring preferences is expensive, like evaluating policy proposals or predicting decisions under technological change

Current time allocation and household production models face three major weaknesses: First, they only describe the average time allocation. Thus, information about the order of activities is lost. Therefore, it is impossible to describe the influence of activities on later ones. Such interactions are likely pervasive, and can significantly alter behavior. Second, they are unable to describe the effort allocation of individuals, although effort influences one’s time allocation. Thereby, they are either unable or very limited in describing labor productivity or multitasking although individuals frequently multitask. Through the omission of interactions and effort allocation, current models yield biased descriptions of e.g. price and time elasticities. Third, they require strong assumptions, such as perfect foresight or periodic environments, and thus cannot describe behavior in unpredictable environments, like reactions to external shocks. In this paper, I provide a remedy for these shortcomings by developing a dynamical model of procedurally rational decision making. The basic idea of the model is a feedback loop between experienced utility, decision utility, and activities. In applications of the model, I show how introducing a work-leisure interaction and multitasking significantly changes elasticities and how nonmarginal external shocks cause short-term demand surges, none of which can be described by current time allocation models.