Contribution Margin - a Model of Performance Evaluation of Banks' Profit Centers

My reason for embarking upon this project lies first and foremost in the fact that my responsibilities in the bank are inextricably bound to the concerns of managing the bank's operating performance; more specifically, to the planning and control of the performance of various responsibility centers within it to the end of meeting target objectives. I found a further impetus in my involvement in the current process of the bank's reorganization which is aimed at aligning the bank's structure to the organization standards valid in EU commercial banks. Such a massive-scale decentralization process has uncovered the need for introducing certain models of monitoring the bank's responsibility centers. This paper serves a double purpose, namely, its topic coincides with the material I need to prepare for the exam which is part of the symposium in Pforzheim I participated in and also with the contents of the course on Managerial Accounting. Secondly, with this paper I am also meeting the seminar paper requirement at the 'Management' postgraduate program. This paper is divided in two major sections, which coincide with the two major angles from which I have looked at the topic at hand, namely, the theoretical angle and the practical one built on the example of Slavonska banka d.d. Osijek. In the theoretical part I have looked in some detail into the concept and meaning of responsibility accounting as well as into the issue of the establishment of responsibility centers (henceforth: RC) in commercial banks. The second part purports to shape and apply the model of managerial control of the contribution margin for performance evaluation of the bank’s profit centers (henceforth: PC). I would also like to take this opportunity to extend my thanks to all of my colleagues postgraduates who have contributed in one way or another to the completion of this paper.bank’s profit centers, bank's responsibility centers, bank's operating performance, Managerial Accounting

Requirements for benefit assessment in Germany and England – overview and comparison

Photograph of coin found by Stivvie Thomas by metal-detecting in fields south of Willy Howe

Book review: unexplored dimensions of discrimination edited by Tito Boeri, Eleonora Patacchini and Giovanni Peri

What mechanisms serve to maintain the gender pay gap and what other forms of discrimination persist in the labour market? In Unexplored Dimensions of Discrimination, editors Tito Boeri, Eleonora Patacchini and Giovanni Peri provide a comprehensive, empirically-driven interrogation of various facets of discrimination through data obtained from the USA, Spain and Italy. Ria Ivandic welcomes the book for opening up a highly important academic dialogue on previously unexamined aspects of labour market discrimination

Degradation of Orange G Through Persulfate Activated Nanoscale Zerovalent Iron Composites and Boron-Doped Diamond Electrodes

Properly treated wastewater is necessary for water reuse and to avoid unnecessary impacts on the environment. The poultry industry utilizes large amounts of water for poultry processing. The need for innovative ways to treat organic contaminants in the poultry wastewater industry is especially necessary due to increased poultry consumption. The U.S. Department of Agriculture projected Americans would consume approximately 92 pounds of chicken per person in 2017.1 Dissolved air flotation (DAF) is currently used in poultry wastewater treatment, but DAF does not remove organic contaminants efficiently per effluent standards. Implementation of processes that degrade contaminants directly would benefit the poultry industry economically. Potential organic treatment options are nanoscale zerovalent iron (nZVI) composites that activate persulfate to degrade contaminants by sulfate radical generation and boron-doped diamond electrode (BDDE) electrochemical oxidation processes that mineralize organic content through hydroxyl radical electro-generation. These processes have shown potential in decolorization of Orange G (OG) dye contaminant through UV/Vis spectroscopy and decreasing oxygen necessary for oxidation of OG through Chemical Oxygen Demand (COD) testing. Standard and lyophilized 1:5 mass ratio nZVI/biochar composites showed decolorization and COD concentration decreases for 30-mintute experimental runs. 30-minute and 120-minute BDDE experiments utilizing a current density of 2-mA/cm2 and varying OG starting concentrations indicated potential for OG decolorization through azo bond breaking and decreased COD readings by OH radical oxidation of organic content. Ultimately, industrial poultry wastewater will be used to test organic contaminant degradation through both nZVI/biochar composites and BDDE

Home is not a safe place for everyone: domestic abuse between partners increased during lockdown

What has happened to the prevalence and nature of domestic abuse during lockdown? Crime economists Ria Ivandic and Tom Kirchmaier collaborated with the Strategic Insights Unit (SIU), from the Metropolitan Police, to answer this question by analysing data from calls to the police and recorded crime in London

Does the number of candidates increase turnout? Causal evidence from two-round elections

A long-lasting question in comparative politics is whether the number of candidates/parties increases turnout. Existing observational studies on the topic find mixed results. We thus apply a regression discontinuity design to data 13,910 legislative and cantonal electoral districts in France since 1978. In the two-round system used in these elections, the candidates who pass a certain vote threshold in the first round can participate in the second round. We use this discontinuity to estimate the causal effect of having a third candidate in the second round: it increases turnout by 3.5% points and the share of valid votes by 7.3% points. We confirm these findings with survey data from the 2012 legislative election. Further, we investigate the mechanism and find evidence supporting the alienation theory, according to which individuals whose preferences do not resonate with the preferences of any of the candidates are likely to abstain

Gender gaps from labor market shocks

Job loss leads to persistent adverse labor market outcomes, but assessments of gender differences in labor market recovery are lacking. We utilize plant closures in Denmark to estimate gender gaps in labor market outcomes and document that women face an increased risk of unemployment and lose a larger share of their earnings in the two years following job displacement. When accounting for observable differences in human capital across men and women, half of the gender gap in unemployment remains. In a standard decomposition framework, we document that childcare imposes an important barrier to women's labor market recovery regardless of individual characteristics

Changing patterns of domestic abuse during Covid-19 lockdown

The effects of preventing a COVID-19 health crisis have had unintended consequences on domestic abuse (DA) victimization. We contribute to the literature on domestic abuse in lockdown by providing insight on how changing patterns of domestic abuse can explain differences in magnitudes reported across studies. We examine the patterns of domestic abuse during the COVID-19 lockdown in Greater London and find that the lockdown changed the nature of reporting and the type of relationship the abuse occurs within. While abuse by current partners as well as family members increased on average by 8.1% and 17.1% respectively over the lockdown period, abuse by ex-partners declined by 11.4%. These findings show that reporting the average change in domestic abuse during lockdown can be misleading when designing a policy response. Moreover, we show that all the increase in domestic abuse calls is driven by third party reporting, particularly evident in areas with high density. This suggests that under reporting is present in the lockdown, particularly in households where the abuse cannot be reported by an outsider. Although these findings pertain to the COVID-19 lockdown, they also highlight the role that victim exposure and proximity has in affecting domestic abuse

Comparing conventional and machine-learning approaches to risk assessment in domestic abuse cases

We compare predictions from a conventional protocol-based approach to risk assessment with those based on a machine-learning approach. We first show that the conventional predictions are less accurate than, and have similar rates of negative prediction error as, a simple Bayes classifier that makes use only of the base failure rate. A random forest based on the underlying risk assessment questionnaire does better under the assumption that negative prediction errors are more costly than positive prediction errors. A random forest based on two-year criminal histories does better still. Indeed, adding the protocol-based features to the criminal histories adds almost nothing to the predictive adequacy of the model. We suggest using the predictions based on criminal histories to prioritize incoming calls for service, and devising a more sensitive instrument to distinguish true from false positives that result from this initial screening