The Tragedy of the Commons and Inflation Bias in the Euro Area

Central bank credit has expanded dramatically in some of the Euro Area member countries since the beginning of the financial crisis. This paper makes two contributions to understand this stylized fact. First, we discuss a simple model of monetary policy that includes (i) a credit channel and (ii) a common pool problem in a monetary union. We illustrate that the interaction of the two elements leads to an inflation bias that is independent of the standard time-inconsistency bias. Secondly, we present an institutional analysis that is consistent with the view of fragmented monetary policy and empirical evidence that illustrates the heterogeneity of central bank credit expansion.     

Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.     

The Value of Product Attributes,Brands and Private Labels: An Analysis of Frozen Seafood in Germany

It is well known that the price of a food in general and fish in particular is a function of a number of attributes such as species, product form, processing form and size. However, limited attention has been given to the influence of private labels, production method, eco‐labels and promotions. We use a unique dataset which identifies these attributes in the German seafood market. We estimate a hedonic price function, and our results highlight the importance of brand and labels for seafood prices in Germany. Our results also suggest that private label products are discounted by 20%, while branded products achieve substantial price premiums, as do fish products from aquaculture.     

Firm heterogeneity, productivity and spatially bounded knowledge externalities

In this paper, we argue that conceptually disentangling the ‘context versus composition’ aspects of regional growth is a multilevel issue. By applying multilevel models (also called random-effects models), we show (1) the importance of considering firm-specific characteristics simultaneously with region-specific characteristics, as we find that a large part of what is traditionally assigned to the impact of the region should be assigned to firm-specific characteristics and (2) that existing single-level methodologies can be problematic, as they are vulnerable to the charge of estimating significance levels that are too liberally assigned and promote exaggerations. This is illustrated empirically by showing that single-level approaches would lead to the conclusion that innovation spillovers are highly significant in a setting of Dutch urban growth differentials, while multilevel analyses shows less liberally assigned significance levels. We conclude that multilevel-effect models better fit research questions that combine firm and spatial characteristics simultaneously, especially because they allow firm-specific characteristics to be differently linked to their regional contexts.     

Transatlantic wage gaps and the migration decision: Europe–Canada in the 1920s

As has been seen in other contexts, workers in similar occupations earned much higher wages in Canada than Europe during the 1920s. This observation and related aspects of immigration are addressed with a life-cycle model of the migration decision. The characteristics of immigrants from five European countries: Ireland, Italy, the Netherlands, Poland, and Sweden, are explored in a way that sheds light not just on those population flows but on the process of immigration generally. We draw on passenger manifests from immigrant ships for information on the individual migrants. Simulations, based partly on the these manifests, reveal that the costs of migration, borrowing constraints, concern for status, and country-specific taste preferences account for key immigrant characteristics, and help explain the large wage differentials that persisted despite Canada’s relatively open immigration policy.     

THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL

We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.     

Consumers’ Perceptions of Corporate Social Responsibility: Scale Development and Validation

Researchers and companies are paying increasing attention to corporate social responsibility (CSR) programs and the reaction to them by consumers. Despite such corporate efforts and an expanding literature exploring consumers’ response to CSR, it remains unclear how consumers perceive CSR and which “Gestalt” consumers have in mind when considering CSR. Academics and managers lack a tool for measuring consumers’ perceptions of CSR (CPCSR). This research explores CPCSR and develops a measurement model. Based on qualitative data from interviews with managers and consumers, the authors develop a conceptualization of CPCSR. Subsequently, model testing and validating occurs on three large quantitative data sets. The conceptualization and the measurement scale can assist companies to assess CPCSR relative to their performance. They also enable managers in identifying shortcomings in CSR engagement and/or communication. Finally, the paper discusses implications for marketing practice and future research.