Climate Change and Asset Prices: Are Corporate Carbon Disclosure and Performance Priced Appropriately?

This paper empirically assesses the relevance of information on corporate climate change disclosure and performance to asset prices, and discusses whether this information is priced appropriately. Findings indicate that corporate disclosures of quantitative greenhouse gas (GHG) emissions and, to a lesser extent, carbon performance are value relevant. We use hand‐collected information on quantitative GHG emissions for 433 European companies and build portfolios based on GHG disclosure and performance. We regress portfolios on a standard four factor model extended for industry effects over the years 2005 to 2009. Results show that investors achieved abnormal risk‐adjusted returns of up to 13.05% annually by exploiting inefficiently priced positive effects of (complete) GHG emissions disclosure and good corporate climate change performance in terms of GHG efficiency. Results imply that, firstly, information costs involved in carbon disclosure and management do not present a burden on corporate financial resources. Secondly, investors should not neglect carbon disclosure and performance when making investment decisions. Thirdly, during the period analysed, financial markets were inefficient in pricing publicly available information on carbon disclosure and performance. Mandatory and standardised information on carbon performance would consequently not only increase market efficiency but result in better allocation of capital within the real economy.     

CPA credential perceptions: a case study of Hispanic accountants

One of the recommendations of The Pathways Commission report was to increase the number of diverse entrants into the accounting profession. While the Commission’s recommendation is commendable, the lack of diversity in the accounting profession is not a new problem. Hence, the accounting profession has attempted to address the underrepresentation of minority Certified Public Accountants (CPAs) for many years. To this end, organizations such as American Institute of CPAs (AICPA), National Association of Black Accountants (NABA), Association of Latino Professionals in Finance and Accounting (ALPFA), and the Ph.D. Project have provided different types of support to alleviate the problem. However, the numbers are still disturbingly low. This is particularly true for Hispanic accountants. Therefore, the purpose of this study was to examine Hispanic accountants’ perception of the CPA credential. While the results indicate that gender, exam affordability, and job incentives are positively associated with the likelihood of being a CPA, the 150-hour requirement was not perceived as a hindrance for certification.     

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.     

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.     

Wheat variety yield data: Do commercial and public performance tests provide the same information?

Wheat yields from reported performance test results are of economic importance to wheat producers, since their profits depend on selecting the optimal variety for their location. However, our data shows differences in absolute and relative wheat yields between commercial and public wheat breeding program's performance test data in Kansas. Newly available data are used to test if the difference in yields arose from potential selectivity bias, and to determine the contribution of private and public wheat breeding programs to varietal yield improvement during 2007–2012. Both Heckman selection models and multiple regression showed no statistical evidence of the potential presence of selectivity bias rather, managerial practices, agronomic conditions, field location, and inherent genetic traits of the seed variety were identify as the source of yield differences.     

Employee satisfaction trajectories and their effect on customer satisfaction and repatronage intentions

Does improving employee happiness affect customer outcomes? The current study attempts to answer this question by examining the impact of employee satisfaction trajectories (i.e., systematic changes in employee satisfaction) on customer outcomes. After accounting for employees’ initial satisfaction levels, the analyses demonstrate the importance of employee satisfaction trajectories for customer satisfaction and repatronage intentions, as well as identify customer-employee contact as a necessary conduit for their effect. From a macro perspective, employee satisfaction trajectories strongly impact customer satisfaction for companies with significant employee–customer interaction, but not for companies without such interaction. From a micro perspective, employee satisfaction trajectories influence customer repatronage intentions for frequent customers, but not for infrequent customers. These effects are robust to controlling for previous customer evaluations and recent employee evaluations. Overall, these findings extend the dominant view of examining static, employee satisfaction levels and offer important implications for the management of the organizational frontline.