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Leadership plays an important role for the efficient and fair solution of social dilemmas but the effectiveness of a leader can vary substantially. Two main factors of leadership impact are the ability to induce high contributions by all group members and the (expected) fair use of power. Participants in our experiment decide about contributions to a public good. After all contributions are made, the leader can choose how much of the joint earnings to assign to herself; the remainder is distributed equally among the followers. Using machine learning techniques, we study whether the content of initial open statements by the group members predicts their behavior as a leader and whether groups are able to identify such clues and endogenously appoint a “good” leader to solve the dilemma. We find that leaders who promise fairness are more likely to behave fairly, and that followers appoint as leaders those who write more explicitly about fairness and efficiency. However, in their contribution decision, followers focus on the leader’s first-move contribution and place less importance on the content of the leader’s statements.
Access to digital finance
(2024)
Financing entrepreneurship spurs innovation and economic growth. Digital financial platforms that crowdfund equity for entrepreneurs have emerged globally, yet they remain poorly understood. We model equity crowdfunding in terms of the relationship between the number of investors and the amount of money raised per pitch. We examine heterogeneity in the average amount raised per pitch that is associated with differences across three countries and seven platforms. Using a novel dataset of successful fundraising on the most prominent platforms in the UK, Germany, and the USA, we find the underlying relationship between the number of investors and the amount of money raised for entrepreneurs is loglinear, with a coefficient less than one and concave to the origin. We identify significant variation in the average amount invested in each pitch across countries and platforms. Our findings have implications for market actors as well as regulators who set competitive frameworks.
High growth firms (HGFs) are important for job creation and considered to be precursors of economic growth. We investigate how formal institutions, like product- and labor-market regulations, as well as the quality of regional governments that implement these regulations, affect HGF development across European regions. Using data from Eurostat, OECD, WEF, and Gothenburg University, we show that both regulatory stringency and the quality of the regional government influence the regional shares of HGFs. More importantly, we find that the effect of labor- and product-market regulations ultimately depends on the quality of regional governments: in regions with high quality of government, the share of HGFs is neither affected by the level of product market regulation, nor by more or less flexibility in hiring and firing practices. Our findings contribute to the debate on the effects of regulations by showing that regulations are not, per se, “good, bad, and ugly”, rather their impact depends on the efficiency of regional governments. Our paper offers important building blocks to develop tailored policy measures that may influence the development of HGFs in a region.
The last years have been affected by Covid-19 and the international emergency mecha-nism to deal with health-related threats. The effects of this period manifested differ-ently worldwide, depending on matters such as international relations, national policies, power dynamics etc. Additionally, the impact of this time will likely have long-term effects which are yet to be known. This paper gives a critical overview of the Public Health Emergency of International Concern (PHEIC) mechanism in the context of Covid-19. It does so by explaining the legal framework for states of emergency, specifically in the context of a PHEIC, while considering its restrictions and limitations on human rights. It further outlines issues in the manifestation of global protections and limitations on human rights during Covid-19. Lastly, considering the likelihood of future PHEICs and the known systemic obstructions, this paper offers ways to im-prove this mechanism from a holistic, non-zero-sum perspective.
Das Dokument "Forschungsdatenmanagement bei personenbezogenen Daten - eine Handreichung" versammelt zentrale Inhalte, Verweise und Vorgehensweisen für Forscher*innen, die in einer Studie personenbezogene Daten erheben und diese verarbeiten, archivieren oder veröffentlichen wollen. Die Handreichung verweist an den entsprechenden Abschnitten auf weiterführende Materialien wie insbesondere die Handreichung „Datenschutz“ des Rats für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften (RatSWD).
Carbon dioxide removal from the atmosphere is becoming an important option to achieve net zero climate targets. This paper develops a welfare and public economics perspective on optimal policies for carbon removal and storage in non-permanent sinks like forests, soil, oceans, wood products or chemical products. We derive a new metric for the valuation of non-permanent carbon storage, the social cost of carbon removal (SCC-R), which embeds also the conventional social cost of carbon emissions. We show that the contribution of CDR is to create new carbon sinks that should be used to reduce transition costs, even if the stored carbon is released to the atmosphere eventually. Importantly, CDR does not raise the ambition of optimal temperature levels unless initial atmospheric carbon stocks are excessively high. For high initial atmospheric carbon stocks, CDR allows to reduce the optimal temperature below initial levels. Finally, we characterize three different policy regimes that ensure an optimal deployment of carbon removal: downstream carbon pricing, upstream carbon pricing, and carbon storage pricing. The policy regimes differ in their informational and institutional requirements regarding monitoring, liability and financing.
Urban pollution
(2022)
We use worldwide satellite data to analyse how population size and density affect urban pollution. We find that density significantly increases pollution exposure. Looking only at urban areas, we find that population size affects exposure more than density. Moreover, the effect is driven mostly by population commuting to core cities rather than the core city population itself. We analyse heterogeneity by geography and income levels. By and large, the influence of population on pollution is greatest in Asia and middle-income countries. A counterfactual simulation shows that PM2.5 exposure would fall by up to 36% and NO2 exposure up to 53% if within countries population size were equalized across all cities.
Predicting entrepreneurial development based on individual and business-related characteristics is a key objective of entrepreneurship research. In this context, we investigate whether the motives of becoming an entrepreneur influence the subsequent entrepreneurial development. In our analysis, we examine a broad range of business outcomes including survival and income, as well as job creation, expansion and innovation activities for up to 40 months after business formation. Using self-determination theory as conceptual background, we aggregate the start-up motives into a continuous motivational index. We show – based on a unique dataset of German start-ups from unemployment and non-unemployment – that the later business performance is better, the higher they score on this index. Effects are particularly strong for growth oriented outcomes like innovation and expansion activities. In a next step, we examine three underlying motivational categories that we term opportunity, career ambition, and necessity. We show that individuals driven by opportunity motives perform better in terms of innovation and business expansion activities, while career ambition is positively associated with survival, income, and the probability of hiring employees. All effects are robust to the inclusion of a large battery of covariates that are proven to be important determinants of entrepreneurial performance.
On Track to Success?
(2022)
Many countries consider expanding vocational curricula in secondary education to boost skills and labour market outcomes among non-university-bound students. However, critics fear this could divert other students from more profitable academic education. We study labour market returns to vocational education in England, where until recently students chose between a vocational track, an academic track and quitting education at age 16. Identification is challenging because self-selection is strong and because students’ next-best alternatives are unknown. Against this back- drop, we leverage multiple instrumental variables to estimate margin-specific treatment effects, i.e., causal returns to vocational education for students at the margin with academic education and, separately, for students at the margin with quitting education. Identification comes from variation in distance to the nearest vocational provider conditional on distance to the nearest academic provider (and vice-versa), while controlling for granular student, school and neighbourhood characteristics. The analysis is based on population-wide administrative education data linked to tax records. We find that the vast majority of marginal vocational students are indifferent be- tween vocational and academic education. For them, vocational enrolment substantially decreases earnings at age 30. This earnings penalty grows with age and is due to wages, not employment. However, consistent with comparative advantage, the penalty is smaller for students with higher revealed preferences for the vocational track. For the few students at the margin with no further education, we find merely tentative evidence of increased employment and earnings from vocational enrolment.