The cost of sin:the effect of social norms on audit pricing

In this paper we provide evidence for the effects of social norms on audit pricing by studying companies belonging to the alcohol, firearms, gambling, military, nuclear power, and tobacco industries,which are often described as “sin” companies. We hypothesize that the disparities between “sin” firms operations and prevailing social norms create an adverse context which heightens the client's business risk assessment by auditors and is, thereby, reflected in the pricing decisions for audit and consulting services. Having controlled for the impact of variables relating to client attributes, auditor attributes and engagement attributes, we demonstrate that audit firms charge significantly higher audit and consulting fees to companies that deviate from prevailing social norms. Additionally,we show that audit pricing levels within the “sin” group depend both on prevailing political views and on the level of “vice” exhibited by “sin” companies

Corporate social responsibility and earnings management in U.S. banks

Business decision making depends on financial reporting quality. In identifying the drivers of financial reporting quality, proxied by earnings management (EM), prior literature has drawn attention to the association between corporate EM practices and commitment to corporate social responsibility (CSR). Empirical evidence, however, provides inconclusive results regarding the direction of this association. Using simultaneous equations, we examine the bi-directional CSR-EM relationship in U.S. commercial banks. We demonstrate that, although banks that engage in EM practices are also actively involved in CSR, the reverse relationship is not significant. We provide implications for investors, analysts, business participants and regulators

Transplanting Anglo-American accounting oversight boards to a diverse institutional context

The introduction of accounting and auditing oversight boards (OBs) has been promoted on a global scale as a key component of the international financial architecture that has emerged over the past two decades. Such institutions, modeled on the Anglo-American tradition, are domestically organized and embedded within distinctively diverse institutional contexts. Their role is to ease agency problems, improve the quality of financial reporting, and help provide stability in the global financial system. We employ an institutional approach, located within the broader political economy framework of global capitalism, to examine the establishment and operation of the new regulatory regime in Greece. Greece, a member of the European Union, exhibits characteristics of a "delegative" democracy, i.e. a traditionally weak institutionalization, reform (in)capacity problems and a clientelistic political system. Our case study shows that the formation and operation of the newly-established system of oversight is conditioned by local political and economic constraints and, thus, does not automatically translate into concrete benefits for the quality of financial reporting. We also draw attention to the structural mismatch between a progressing globalized financial integration and the fragmented nature of the system of oversight, and illustrate that OBs' independence from local governments is an important but neglected issue

Error Correction for Wave Modelling

Installation and maintenance strategies regarding offshore wind farm operations involve extensive logistics, since the main focus is the right temporal and spatial placement of personnel and equipment, while taking into account forecasted meteorological and hydrodynamic conditions. In order for these operations to be successful weather windows characterized by certain permissive wave, wind and current conditions is of enormous importance, whereas unforeseen events result in high cost and risk in terms of safety.For that purpose, Deltares created Meteo Dashboard, an integrated software system that collects, stores, computes and presents measured and forecasted meteorological and hydrodynamic data for decision making of maintenance or installation activities in an offshore wind farm. The wind speed, as well as the air and water temperatures, result from a meteorological model and serve as an input for the numerical modelling (e.g. SWAN or Delft3D) of waves, water levels and current related parameters. To account for the inherited uncertainty, several error modelling techniques, such as Artificial Neural Networks (ANN), Copulas, Stochastic Interpolation (SI), ARMA models, and Linear Regression (REG), already run operational on Meteo Dashboard and can be implemented in order for the numerical model forecasts to be corrected. A number of the aforementioned techniques require training using historical or present time data, while others can be incorporated forthwith.In this research, a fully automated ARIMA model and different kinds of Bayesian Network (BN) models are incorporated in order to enhance the accuracy of the significant wave height (Hs) predictions even further. Both techniques are implemented using packages provided by the free software environment of R, namely the bnlearn and forecast. The implemented BN models differ in terms of training and structure, and provide overall the most satisfying accuracy in comparison to the rest of the error correction techniques, when tested with data retrieved from stations deployed in the Irish Sea (adjacent to the Gwynt-y-Mor and Rhyl Flats offshore wind farms) corresponding to the whole year of 2017 (from January 2017 – to January 2018).Supplementary, it is also shown that the BN models illustrate even more advantages when compared to the rest of the error correction techniques, since they provide information about the incorporated variables dependence relationship through their structures, while producing estimates for the underlying uncertainty of the phenomenon, by means of 95% confidence intervals extracted by the significant wave height (Hs) conditional distribution.Finally, all error correction models are tested in operational (online) mode, with real-time data from the aforementioned locations, with the newly implemented BN models producing results of enhanced accuracy, even in the absence of measurement

UPStream: Automated hydraulic design of pressurized water distribution networks

Hydraulic design of pressurized water distribution networks constitutes a time consuming process in engineering applications, requiring proper selection of pipe diameters so certain regulatory constrains are met. UPStream® is an open-source software, which combines EPANET’s computational engine and a simple hydraulic gradient-based recursive approach for selection of pipe diameters, to automatically design pressurized water distribution networks, based on user-defined pressure and flow velocity constraints. To the best of our knowledge, there is no available open-source software for this purpose, which allows for case-specific modifications/interventions by advanced users, as well as extensions to weight between alternative design strategies. Therefore, UPStream® is expected to serve as a useful tool/platform for educational/academic purposes, research, and engineering practice. Keywords: Water distribution networks, Hydraulic design, Pressurized pipe networks, MATLAB, EPANE

Regulatory enforcement, foreignness and language negativity: Evidence from SEC comment letters

In this paper, we demonstrate that negative language is employed as a mechanism through which regulators express their differentiated level of concern and pass on stronger messages to riskier reviewees. We investigate the language tone employed by the internationally-influential U.S. Securities and Exchange Commission (SEC) in comment letters to foreign firms, which are considered riskier in comparison with their U.S. domestic counterparts. We find a significantly greater level of language negativity in comment letters addressed to foreign registrants. We furthershow that the negativity of language is more intense when foreign firms are domiciled in strong-law countries and when they do not apply U.S. GAAP. We offer implications for regulators, managers and market participants

Corporate Governance and Institutions \u2010 A Review and Research Agenda

Research Question/Issue Over the last decades, research on the relationship between national institutions, governance mechanisms, and firm outcomes has been increasing. This review aims at (i) analyzing extant research in this area, (ii) identifying influential current trends, and (iii) highlighting future avenues of research. Research Findings/Insights Using a content analysis of 165 articles published in top journals from accounting, finance, management, and organization disciplines, we explore research on institutions, corporate governance, and firm outcomes. Our results show that stronger national institutions aimed at protecting investors are mostly associated with better corporate governance and firm financial outcomes and that these relationships are moderated by some contingency factors. Theoretical/Academic Implications Our findings encourage scholars to further explore the relationship between national institutions, corporate governance, and firm outcomes by using theoretical frameworks and methods allowing them (i) to develop a "thicker" understanding of the national institutional context, (ii) to analyze powerful stakeholders' influence on the above relationships, and (iii) to better understand the role played by informal institutions. Practitioner/Policy Implications Our findings help policymakers and investors to (i) better understand how national institutions impact on both governance mechanisms and firm outcomes and (ii) develop policies or design governance mechanisms taking into consideration country-, industry-, and firm-level contingencies

Statistical models for improving significant wave height predictions in offshore operations

Installation and maintenance strategies regarding offshore wind farm operations involve extensive logistics. The main focus is the right temporal and spatial placement of personnel and equipment, while taking into account forecasted meteorological and ocean conditions. For these operations to be successful, weather windows characterized by certain permissive wave conditions are of enormous importance, whereas unforeseen events result in high cost and risk of safety. Numerical modelling of waves, water levels and current related variables has been used extensively to forecast ocean conditions. To account for the inherited model uncertainty, several error modelling techniques can be implemented for the numerical model forecasts to be corrected. In this study, various Bayesian Network (BN) models are incorporated, in order to enhance the accuracy of the significant wave height predictions and to be compared with other techniques, in conditions resembling the real-time nature of the application. The implemented BN models differ in terms of training and structure and provide overall the most satisfying performance. Supplementary, it is shown that the BN models illustrate significant advantages as both quantitative and conceptual tools, since they produce estimates for the underlying uncertainty of the phenomena, while providing information about the incorporated variables’ dependence relationships through their structure.Accepted author manuscriptApplied Probabilit

A Comprehensive Approach to the Design of a Renewable Energy Microgrid for Rural Ethiopia: The Technical and Social Perspectives

In view of Ethiopia’s significant renewable energy (RE) potential and the dynamic interactions among the components of the Water–Energy–Food (WEF) Nexus, we attempted to incorporate solar and small-scale hydropower into the optimal design of an environmentally friendly microgrid with the primary goal of ensuring the sustainability of irrigation water pumping, while taking advantage of existing infrastructure in various small administrative units (kebele). Any additional generated energy would be made available to the community for other needs, such as lighting and cooking, to support health and food security and improve the general quality of life. The novelty of the study stems from the utilization of in situ social data, retrieved during fieldwork interviews conducted in the kebele of interest, to ascertain the actual needs and habits of the local people. Based on these combined efforts, we were able to formulate a realistic energy demand plan for climatic conditions typical of Sub-Saharan Africa agricultural communities and analyze four different scenarios of the microgrid’s potential functionality and capital cost, given different tolerance levels of scheduled outages. We demonstrated that the RE-based microgrid would be socially and environmentally beneficial and its capital cost sensitive to the incorporation of individual or communal machines and appliances. Ultimately, the social impact investigation revealed the design would be welcomed by the local community, whose members already implement tailor-made solutions to support their agricultural activities. Finally, we argue that extended educational programs and unambiguous policies should be in place before any implementation to ensure the venture’s sustainability and functionality

Association of NADPH oxidase p22phox gene C242T, A640G and-930A/G polymorphisms with primary knee osteoarthritis in the Greek population

Osteoarthritis (OA) is the most common form of arthritis with still unknown pathogenic etiology and considerable contribution of genetic factors. Recently, a new emerging role of oxidative stress in the pathology of OA has been reported, lacking however elucidation of the underlying mechanism. Nicotinamide adenine dinucleotide phosphate (NADPH) oxidase being a complex enzyme produced by chondrocytes, presents the major source of reactive oxygen species and main contributor of increased oxidative stress. The present study aims to evaluate the association of NADPH oxidase p22phox gene C242T, A640G and -A930G polymorphisms with primary knee OA in the Greek population. One hundred fifty five patients with primary symptomatic knee OA participated in the study along with 139 matched controls. Genotypes were determined using polymerase chain reaction and restriction fragment length polymorphism technique. Allelic and genotypic frequencies were compared between both study groups. NADPH p22phox -A930G polymorphism was significantly associated with knee OA in the crude analysis (P = 0.018). No significant difference was detected for C242T and A640G polymorphisms (P > 0.05). The association between -A930G polymorphism and knee OA disappeared when the results were adjusted for obesity (P = 0.078, odds ratio 0.54, 95 % CI 0.272-1.071). The interaction between all three polymorphisms was not significant. The present study shows that NADPH oxidase p22phox gene C242T, A640G and -A930G polymorphisms are not risk factors for knee OA susceptibility in the Greek population. Further studies are needed to give a global view of the importance of this polymorphism in the pathogenesis of OA