Corporate investment and stock market valuation

We study the driving forces behind the positive association observed between corporate investment and stock market valuation, and how they interact with managerial equity incentives and informativeness of investment. We build a dynamic model where managers use investment choices to influence investors' opinions about firms' future prospects and increase the market valuation. The incentives to manipulate the valuation processes increase with managerial equity incentives and informativeness of investment. Our empirical findings support the model's predictions that the tendency of using investment to boost market valuation is stronger when managerial stock ownership is high or when earnings quality is low (i.e., there is strong reliance on investment for information).     

Local volatility under rough volatility

Several asymptotic results for the implied volatility generated by a rough volatility model have been obtained in recent years (notably in the small-maturity regime), providing a better understanding of the shapes of the volatility surface induced by rough volatility models, supporting their calibration power to SP500 option data. Rough volatility models also generate a local volatility surface, via the so-called Markovian projection of the stochastic volatility. We complement the existing results on implied volatility by studying the asymptotic behavior of the local volatility surface generated by a class of rough stochastic volatility models, encompassing the rough Bergomi model. Notably, we observe that the celebrated “1/2 skew rule” linking the short-term at-the-money skew of the implied volatility to the short-term at-the-money skew of the local volatility, a consequence of the celebrated “harmonic mean formula” of [Berestycki et al. (2002). Quantitative Finance, 2, 61–69], is replaced by a new rule: the ratio of the at-the-money implied and local volatility skews tends to the constant $1/(H+3/2)$ (as opposed to the constant 1/2), where H is the regularity index of the underlying instantaneous volatility process.     

Enhancing bank transparency: Financial reporting quality,fraudulent peers and social capital

This study examines the role of social norms in financial markets by relating bank transparency to social capital. Using comprehensive data on commercial banks, we provide empirical evidence that high social capital contributes to more transparent financial reporting, thereby enabling more precise risk assessments and promoting financial stability. We find that the effect of social capital is more pronounced when commercial banks are more complex and disclosure incentives of bank managers are strong. Our results suggest that more opaque reporting by peers explains lower transparency but financial misreporting is less contagious when social capital is high. Our study suggests that social capital can effectively improve reporting transparency when other mechanisms are not effective, thus securing financial system stability.     

Farmers’ organizations and sustainable development: An introduction

This special issue features 14 new research papers investigating the role of farmers’ organizations (e.g., collective action, self-help groups, producer companies/organizations, and cooperatives) in supporting sustainable development. The key findings include: (1) farmer groups and cooperatives promote farmers’ adoption of good farm management practices, new agricultural technologies and sustainable farming practices, although not substantially improving farm yield; (2) outsourcing services provided by agricultural cooperatives help to increase the technical efficiency of crop production; (3) cooperative membership enhances members’ bargaining power and enables them to sell their products at higher prices; (4) cooperatives motivate rural laborers to work in off-farm sectors, while self-help groups empower rural women in decision-making; (5) internet use improves agricultural cooperatives’ economic, social, and innovative performances; (6) direct administrative intervention supporting cooperative development may lead to the emergence of shell cooperatives; (7) participation in forest farmer organizations enables wood value chain upgrading; (8) increasing the cooperative size in terms of income, equity, and assets increases the profitability of savings and credit cooperatives; and (9) creating cross-border cooperation between cooperatives generates benefits for all parties involved. These findings can inspire the design of policies aimed to support farmers’ organizations in achieving sustainable development goals.     

Taxation of unhealthy food consumption and the intensive versus extensive margin of obesity

International Tax and Public Finance - If an individual’s health costs are U-shaped in weight with a minimum at some healthy level and if the individual has both self-control problems and...     

Random encounters and information diffusion about product quality

This paper explores how social interactions among consumers shape markets. In a two-country model, consumers meet and exchange information about the quality of the goods. As information spreads, demand evolves, affecting the prices and quantities manufactured by profit-maximizing firms. We show that market prices with informational frictions reach the duopoly price with full information at the limit. However, this convergence can take different paths depending on the size asymmetry between countries. In particular, when the country producing the low-quality good is relatively large, the single market does not immediately turn into a duopoly and can be temporarily trapped in a situation of price instability where no Nash equilibrium in pure (but only in mixed) strategies exists and prices can fluctuate between their monopoly and duopoly levels. It follows that the classical price-reducing effects of international trade may take longer to appear. In view of an intense globalization process, understanding how social meetings affect market outcomes is critical for understanding the performance of international economic integration.     

The optimality of public–private partnerships under financial and fiscal constraints

The government may delegate two sequential tasks (e.g., building and operating an infrastructure) to the same or different agents (i.e., partnership vs. sequential contracts). Agents are risk-neutral but face financial constraints, whereas the government's contractual capacity may be limited by the renegotiation-proofness and fiscal constraints. By relying on history-dependent incentives, the partnership contract corrects moral hazard more effectively than sequential contracts. Thus, it is socially preferred unless bundling different tasks deteriorates the agent's financial conditions. Our results shed new light on the role of firms' financial and government's fiscal conditions in driving the cost–benefit analysis of public–private partnerships.     

What drives a donor? A machine learning-based approach for predicting responses of nonprofit direct marketing campaigns

Direct marketing campaigns are one of the main fundraising sources for nonprofit organizations and their effectiveness is crucial for the sustainability of the organizations. The response rate of these campaigns is the result of the complex interaction between several factors, such as the theme of the campaign, the month in which the campaign is launched, the history of past donations from the potential donor, as well as several other variables. This work, applied on relevant data gathered from the World Wide Fund for Nature Italian marketing department, undertakes different data mining approaches in order to predict future donors and non-donors, thus allowing for optimization in the target selection for future campaigns, reducing its overall costs. The main challenge of this research is the presence of thoroughly imbalanced classes, given the low percentage of responses per total items sent. Different techniques that tackle this problem have been applied. Their effectiveness in avoiding a biased classification, which is normally tilted in favor of the most populated class, will be highlighted. Finally, this work shows and compares the classification results obtained with the combination of sampling techniques and Decision Trees, ensemble methods, and Artificial Neural Networks. The testing approach follows a walk-forward validation procedure, which simulates a production environment and reveals the ability to accurately classify each future campaign.     

Factors determining the degree of gender equality within the European Union

Quality & Quantity - This paper aims to identify the major determinants of the structural differences in gender equality for EU countries, using tools from partial order theory on a system of 6...     

Modelling the switch from hail insurance to antihail nets

We analyse the impact of the antihail net promotion on the actuarial soundness of the hail insurance market. Specifically, we present a simple model showing that, in the presence of an imperfect insurance market, incentives for antihail nets could cause low-risk farmers to exit the insurance market more likely than high-risk ones. This induces a typical adverse selection problem. The theoretical model predictions are corroborated by an empirical investigation. Based on a fixed-effect conditional logit regression, we show that a higher per-hectare output value and a location strongly affected by hail both increase the chance that a plot is hedged through antihail nets.