Information shocks and the empirical evaluation of training programs during unemployment spells

We study the role of notifications in the evaluation of training programs for unemployed workers. Using a unique administrative data set containing the dates when information is exchanged between job seekers and caseworkers, we address three questions: Do information shocks, such as notification of future training, have an effect on unemployment duration? What is the joint effect of notification and training programs on unemployment? Can ignoring information shocks lead to a large bias in the estimation of the effect of training programs? We discuss these issues through the lens of a job search model and then conduct an empirical analysis following a “random effects” approach to deal with selectivity. We find that notification has a strong positive effect on the training probability but a negative one on the probability of leaving unemployment. This “attraction” effect highlights the importance of accounting for notifications in the evaluation of active labor market policies.     

Metal prices made in China? A network analysis of industrial metal futures

In addition to being the world's greatest consumer and producer of industrial metals, China now also features the most actively traded industrial metal futures contracts worldwide. To examine China's role in the global price formation process of industrial metal futures markets, we use a sample of 29 futures contracts traded on exchanges in the United States, the United Kingdom, India, and China. We estimate vector autoregressive models and conduct variance decompositions, which are then visualized in the form of networks. The results indicate that China, despite its role as key actor in both real and financial industrial metal markets, is a price taker.     

Do data policy restrictions inhibit trade in services?

Review of World Economics - This paper examines whether restrictive data policies are related to trade in services. The authors have collected comparable information on a variety of policy measures...     

Analyzing companies' interactions with the Sustainable Development Goals through network analysis: Four corporate sustainability imperatives

The alignment between corporate strategies and the Sustainable Development Goals (SDGs) can be an indicator of long-term sustainability success. But which types of companies are most, and which are least, aligned with the SDGs? This paper scores how 67 economic activities—as a proxy for companies' operations and the goods or services they deliver—interact with 59 SDG targets. It then uses network analysis to define which activities are most and least aligned with the SDG Agenda. The results reveal four types of corporate activities, each having a strategic sustainability imperative: (i) “core activities” predominantly generate positive, while having few negative, impacts on the SDGs, challenging companies to scale their contributions to further align with the SDG Agenda; (ii) “mixed activities” have moderate/high degrees of both negative/positive impacts, posing a decoupling imperative; (iii) “opposed activities” provide few benefits yet cause significant adverse impacts, implying that companies must transform in order to better align with the SDGs; and (iv) “peripheral activities” have immaterial positive and negative impacts, creating an imperative to explore innovative avenues for creating SDG contributions. Detailed network graphs are presented that map companies' interactions with the SDGs and guide the creation of corporate sustainability strategies. Policy implications include the potential for using companies' activities as a lever for adopting a “nexus approach” to the SDGs.     

Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.     

Bargaining foundation for ratio equilibrium in public‐good economies

We provide a bargaining foundation for the concept of ratio equilibrium in public‐good economies. We define a bargaining game of alternating offers, in which players bargain to determine their cost shares of public‐good production and a level of public good. We study the stationary subgame perfect equilibrium (SSPE) without delay of the bargaining game. We demonstrate that when the players are perfectly patient, they are indifferent between the equilibrium offers of all players. We also show that every SSPE without delay in which the ratios offered by all players are the same leads to a ratio equilibrium. In addition, we demonstrate that all equilibrium ratios are offered by the players at some SSPE without delay. We use these results to discuss the case when the assumption of perfectly patient players is relaxed and the cost of delay vanishes.     

The Effects of Creative Culture on Real Earnings Management*

Creativity and innovation have been identified by senior executives as some of the most desired characteristics of corporate culture. Accordingly, managers strive to build these cultures within their organizations. However, research in psychology suggests that these attempts may have unintended negative consequences. In this study, I predict and find that managers in a more (versus less) innovative company culture will engage in higher levels of real earnings management (REM). I then test two construal level theory (CLT)-based interventions designed to reduce REM. As I predict, I find that in more innovative corporate cultures an intervention that makes downside risk more salient reduces REM, but an intervention that encourages managers to consider the “big-picture” impact of their decision reduces REM to a greater extent. Unexpectedly, I also find that the effect of the “big-picture” intervention reverses in a less innovative corporate culture leading to an increase in REM. My findings contribute to the emerging accounting literature regarding REM. I also extend the psychology literature investigating the link between opportunistic behavior and creativity, and I also expand research into how interventions based on CLT can affect judgment and decision making in an accounting context.     

The perception of risk among unauthorized migrants in Ghana

Abstract

In recent years, the number of unauthorized migrants trying to reach Europe by boat has increased. In an attempt to curtail this trend, European countries have increasingly deployed information campaigns regarding the risks involved in unauthorized migration. The assumption behind these campaigns is that a strong relation exists between the prevalence of high-risk migration and a lack of awareness of the involved dangers, and that the dissemination of ‘objective’ information would cause prospective migrants to refrain from leaving. Although regarded as a crucial tool in the management of migration, there is little evidence on their effectiveness. Based on four weeks of fieldwork in Ghana, this qualitative study has sought to fill this lacuna. By concentrating on both the circulation and perception of the available risk information in Ghana, this article explores the ways in which notions of risk affect the motivation and decision of unauthorized migrants to engage in high-risk behaviour. Thereby, it will be argued that unauthorized migrants are not the ignorant actors they are often portrayed to be, but that they make their decisions carefully and within a particular vulnerable, socioeconomic and cultural context.     

Global migration in the twentieth and twenty-first centuries: the unstoppable force of demography

Review of World Economics - This paper sheds light on the global migration patterns of the past 40 years, and produces migration projections for the 21st century. To do this, we build a simple...