While the benefits of common and public goods are shared, they tend to be scarce when contributions are provided voluntarily. Failure to cooperate in the provision or preservation of these goods is fundamental to sustainability challenges, ranging from local fisheries to global climate change. In the real world, such cooperative dilemmas occur in multiple interactions with complex strategic interests and frequently without full information. We argue that voluntary cooperation enabled across multiple coalitions (akin to polycentricity) not only facilitates greater generation of non-excludable public goods, but may also allow evolution toward a more cooperative, stable, and inclusive approach to governance. Contrary to any previous study, we show that these merits of multi-coalition governance are far more general than the singular examples occurring in the literature, and are robust under diverse conditions of excludability, congestability of the non-excludable public good, and arbitrary shapes of the return-to-contribution function. We first confirm the intuition that a single coalition without enforcement and with players pursuing their self-interest without knowledge of returns to contribution is prone to cooperative failure. Next, we demonstrate that the same pessimistic model but with a multi-coalition structure of governance experiences relatively higher cooperation by enabling recognition of marginal gains of cooperation in the game at stake. In the absence of enforcement, public-goods regimes that evolve through a proliferation of voluntary cooperative forums can maintain and increase cooperation more successfully than singular, inclusive regimes.

Car-sharing platforms provide access to a shared rather than a private fleet of automobiles distributed in the region. Participation in such services induces changes in mobility behaviour as well as vehicle ownership patterns that could have positive environmental impacts. This study contributes to the understanding of the total mobility-related greenhouse gas emissions reduction related to business-to-consumer car-sharing participation. A comprehensive model which takes into account distances travelled annually by the major urban transport modes as well as their life-cycle emissions factors is proposed, and the before-and-after analysis is conducted for an average car-sharing member in three geographical cases (Netherlands, San Francisco, Calgary). In addition to non-operational emissions for all the transport modes involved, this approach considers the rebound effects associated with the modal shift effect (substituting driving distances with alternative modes) and the lifetime shift effect for the shared automobiles, phenomena which have been barely analysed in the previous studies. As a result, in contrast to the previous impact assessments in the field, a significantly more modest reduction of the annual total mobility-related life-cycle greenhouse gas emissions caused by car-sharing participation has been estimated, 3-18% for three geographical case studies investigated (versus up to 67% estimated previously). This suggests the significance of the newly considered effects and provides with the practical implications for improved assessments in the future.

This paper investigates the relationships between economic growth, investment in human capital and income equality in Turkey. The conclusion drawn based on the data from the OECD and the World Bank suggests that economic growth can improve income equality depending on the expenditures undertaken by the government. As opposed to the standard view that economic growth and income inequality are positively related, the findings of this paper suggest that other factors such as education and healthcare spending are also driving factors of income inequality in Turkey. The proven positive impact of investment in education and health care on income equality could aid policymakers who aim to achieve fairer income equality and economic growth, in investment decisions.

We develop a model of electoral selection and accountability in the presence of mainstream and alternative media outlets. In addition to standard high and low competence types, the incumbent may be an aspiring autocrat, who controls the mainstream media and will cause substantial harm if not removed from office. Alternative media can help voters identify and remove aspiring autocrats and can enable voters to focus on honest mainstream media assessments of incumbents' competence. But malicious alternative media that peddle false conspiracy theories about the incumbent and the mainstream media can induce voters to mistakenly remove nonautocratic incumbents, which in turn demotivates incumbent effort and undermines accountability. The alternative media is most dangerous when it is sufficiently credible that voters pay attention to it, but sufficiently likely to be malicious that it undermines accountability.

The popularity of modern portfolio theory has decreased among practitioners because of its unfavorable out-of-sample performance. Estimation errors tend to affect the optimal weight calculation noticeably, especially when a large number of assets is considered. To overcome these issues, many methods have been proposed in recent years, although most only address a small set of practically relevant questions related to portfolio allocation. This study therefore sheds light on different covariance estimation techniques, combines them with sparse model approaches, and includes a turnover constraint that induces stability. We use two datasets - comprising 319 and 100 companies of the S&P 500, respectively - to create a realistic and reproducible data foundation for our empirical study. To the best of our knowledge, this study is the first to show that it is possible to maintain the low-risk profile of efficient estimation methods while automatically selecting only a subset of assets and further inducing low portfolio turnover. Moreover, we provide evidence that using the LASSO as the sparsity-generating model is insufficient to lower turnover when the involved tuning parameter can change over time.

We study how news personalization affects policy polarization. In a two-candidate electoral competition model, an attention-maximizing infomediary aggregates information about candidate valence into news, whereas voters decide whether to consume news, trading off the expected utility gain from improved expressive voting against the attention cost. Broadcast news attracts a broad audience by offering a symmetric signal. Personalized news serves extreme voters with skewed signals featuring own-party bias and occasional big surprise. Rational news aggregation yields policy polarization even if candidates are office-motivated. Personalization makes extreme voters the disciplining entity for equilibrium polarization and increases polarization through occasional big surprise.