G20: dealing with too-big-to-fail banks, corporate tax avoidance, and development

Overview: This issue of the G20 Monitor addresses the ‘too big to fail’ dilemma of major financial institutions, combating tax evasion and avoidance through ‘base erosion and profit shifting’ (BEPS), and a report from the ‘G20 and Development’ conference hosted by the G20 Studies Centre and Griffith University. Key findings Systemic banking crises are rare, and their cost fades from memory, not least for policy-makers. The challenge is to establish a sensible trade-off between reducing the ex-post cost of TBTF, while minimising the ex-ante costs of doing so. A number of contradictions have emerged within the OECD-led push against Base Erosion and Profit Shifting (BEPS) - the result of creative company tax strategies. These include: whether tax avoidance and evasion via international profit shifting and the use of tax havens is really all that new, how big the problem actually is, and what can meaningfully be done about it. The biggest contribution that the G20 can make to progressing the BEPS agenda may be in pushing for the ‘power of transparency in minimising aggressive tax planning strategies’

G20 2014: reform of the international organisations, financial regulation, trade, accountability and anti-corruption

This issue of the G20 Monitor discusses the reform of international economic institutions, financial regulation, and the trade, accountability and anti-corruption agendas at the forthcoming Brisbane G20 Summit. It also provides a summary of the key ideas from the ‘G20 Conference: Strengthening Accountability and Effectiveness’ hosted by the Lowy Institute. Key findings: If the G20 is truly to be the world’s premier forum for international economic cooperation, fostering the reform of international economic institutions needs to be a fundamental objective. Ex ante regulatory impact assessments are an important tool for strengthening financial regulation and fostering financial stability globally. Trade, anti-corruption, and the accountability of the G20 are important agenda items for the forthcoming Brisbane Summit and go to the heart of the G20’s aim to boost growth and resilience

Infrastructure, tax, energy

This issue of the Monitor focuses on the role of the G20 in infrastructure, tax and energy governance. The Monitor opens with a reflection on a conference jointly hosted by the Reserve Bank of Australia, the Productivity Commission and the Lowy Institute, titled ‘Financial Flows and Infrastructure Financing’. There is also a note on trade. Key findings Ensuring that the right public infrastructure projects are selected is more important than the question of how they will be financed. As such, the G20 should designate appropriate project selection as the foundation stone of its infrastructure agenda. The MDBs can make a major contribution to reducing the global infrastructure gap, provided their actions begin with the principle of additionality. Private sector involvement is a desirable secondary goal and should be promoted wherever business finance produces a more efficient approach, but it should not supersede the MDBs’ preoccupation with an investment strategy built around value for money. Focusing on infrastructure investment for macroeconomic growth can, but does not automatically, benefit people living in extreme poverty, Australia needs to use its outreach program to talk to LICs about the possible prioritisation of infrastructure investment within the G20 agenda. Australia’s G20 presidency is a rare and time-bound opportunity to influence the process guiding tax reforms around base erosion and profit shifting. Better tax compliance and transparency will help to address poverty and inequality globally and within Asia and the Pacific. The G20 has a number of energy issues on its work program, including energy efficiency, yet it has not adequately addressed the prior need for a revision of the global energy governance framework itself. The G20 should push for an elevation of the International Energy Agency into a truly global forum that brings together all the major energy producers and consumers on equal basis

Larval migration in PERL chambers as an in vitro model for percutaneous infection stimulates feeding in the canine hookworm Ancylostoma caninum

<p>Abstract</p> <p>Background</p> <p><it>Ancylostoma caninum </it>third-stage larvae are the non-feeding infective stage of this parasite and are able to infect potential hosts via different infection routes. Since percutaneous infection is one of the most important routes and skin penetration is the first step into parasitic life, an existing <it>in vitro </it>model for percutaneous migration was modified and evaluated. The main parameter used to evaluate migration was the migration ratio (migrated larvae as a percentage of total number of larvae recovered). Additionally, the skin lag was calculated, expressing the percentage of larvae remaining in the skin and therefore not being recovered. Since initiation of feeding is proposed to be an important step in the transition from free-living to parasitic <it>A. caninum </it>larvae, feeding assays were performed with <it>in vitro </it>percutaneously migrated larvae. Additionally, infective larvae of <it>A. caninum </it>were activated via serum-stimulation and feeding behaviour was analysed and compared between percutaneously migrated and serum-stimulated larvae.</p> <p>Results</p> <p>Maximum skin migration levels of infective larvae were observed at temperatures above 32°C when larvae were placed on the epidermal side of skin for more than 12 hours. The medium beneath the skin had no effect on migration ratio, and no significant difference between the migration ratios through fresh and frozen/thawed skin was observed.</p> <p>Maximum feeding levels of 93.2% were observed for percutaneously migrated larvae after 48 h incubation, whereas serum-stimulated larvae reached the maximum of 91.0% feeding larvae after 24 h.</p> <p>Conclusions</p> <p>The PERL chamber system was optimised and standardised as an <it>in vitro </it>model for percutaneous migration. The larvae recovered after percutaneous migration showed characteristic signs of activation similar to that of serum-stimulated larvae. The observed difference in time course of resumption of feeding indicates that percutaneously migrated larvae are not identical to serum-stimulated larvae, which are currently representing the model for early parasitic stages.</p

Random forest classification as a tool in epidemiological modelling: Identification of farm-specific characteristics relevant for the occurrence of Fasciola hepatica on German dairy farms

Fasciola hepatica is an internal parasite of both human and veterinary relevance. In order to control fasciolosis, a multitude of attempts to predict the risk of infection such as risk maps or forecasting models have been developed. These attempts mainly focused on the influence of geo-climatic and meteorological features. Predicting bovine fasciolosis on farm level taking into account farm-specific settings yet remains challenging. In the present study, a new methodology for this purpose, a data-driven machine learning approach using a random forest classification algorithm was applied to a cross-sectional data set of farm characteristics, management regimes, and farmer aspects within two structurally different dairying regions in Germany in order to identify factors relevant for the occurrence of F. hepatica that could predict farm-level bulk tank milk positivity. The resulting models identified farm-specific key aspects in regard to the presence of F. hepatica. In study region North, farm-level production parameters (farm-level milk yield, farm-level milk fat, farm-level milk protein), leg hygiene, body condition (prevalence of overconditioned and underconditioned cows, respectively) and pasture access were identified as features relevant in regard to farm-level F. hepatica positivity. In study region South, pasture access together with farm-level lameness prevalence, farm-level prevalence of hock lesions, herd size, parity, and farm-level milk fat appeared to be important covariates. The stratification of the analysis by study region allows for the extrapolation of the results to similar settings of dairy husbandry. The local, region-specific modelling of F. hepatica presence in this work contributes to the understanding of on-farm aspects of F. hepatica appearance. The applied technique represents a novel approach in this context to model epidemiological data on fasciolosis which allows for the identification of farms at risk and together with additional findings in regard to the epidemiology of fasciolosis, can facilitate risk assessment and deepen our understanding of on-farm drivers of the occurrence of F. hepatica

Do all roads lead to Rome? The potential of different approaches to diagnose Aelurostrongylus abstrusus infection in cats

An infection with the cat lungworm, Aelurostrongylus abstrusus, can be subclinical, but it can also cause severe respiratory clinical signs. Larvae excretion, antibody levels, clinical assessment findings of the respiratory system and diagnostic imaging findings were recorded and compared for six cats with experimental aelurostrongylosis. In five cats, patency started 33–47 days post infection (pi), but two cats excreted larvae only in long intervals and low numbers. Positive ELISA results were observed in four cats with patent aelurostrongylosis, starting between five days before and 85 days after onset of patency. One seropositive cat remained copromicroscopically negative. Mild respiratory signs were observed in all cats examined. A computed tomographic (CT) examination of the lungs displayed distinct alterations, even in absence of evident clinical signs or when larvae excretion was low or negative. The thoracic radiograph evaluation correlated with the CT results, but CT was more distinctive. After anthelmintic treatment in the 25th week post infection, pulmonary imaging findings improved back to normal within 6–24 weeks. This study shows that a multifaceted approach, including diagnostic imaging, can provide a clearer diagnosis and monitoring of disease progression. Furthermore, a CT examination provides an alternative to post mortem examination and worm counts in anthelmintic efficacy studies

A machine learning approach using partitioning around medoids clustering and random forest classification to model groups of farms in regard to production parameters and bulk tank milk antibody status of two major internal parasites in dairy cows

Fasciola hepatica and Ostertagia ostertagi are internal parasites of cattle compromising physiology, productivity, and well-being. Parasites are complex in their effect on hosts, sometimes making it difficult to identify clear directions of associations between infection and production parameters. Therefore, unsupervised approaches not assuming a structure reduce the risk of introducing bias to the analysis. They may provide insights which cannot be obtained with conventional, supervised methodology. An unsupervised, exploratory cluster analysis approach using the k–mode algorithm and partitioning around medoids detected two distinct clusters in a cross-sectional data set of milk yield, milk fat content, milk protein content as well as F. hepatica or O. ostertagi bulk tank milk antibody status from 606 dairy farms in three structurally different dairying regions in Germany. Parasite–positive farms grouped together with their respective production parameters to form separate clusters. A random forests algorithm characterised clusters with regard to external variables. Across all study regions, co–infections with F. hepatica or O. ostertagi, respectively, farming type, and pasture access appeared to be the most important factors discriminating clusters (i.e. farms). Furthermore, farm level lameness prevalence, herd size, BCS, stage of lactation, and somatic cell count were relevant criteria distinguishing clusters. This study is among the first to apply a cluster analysis approach in this context and potentially the first to implement a k–medoids algorithm and partitioning around medoids in the veterinary field. The results demonstrated that biologically relevant patterns of parasite status and milk parameters exist between farms positive for F. hepatica or O. ostertagi, respectively, and negative farms. Moreover, the machine learning approach confirmed results of previous work and shed further light on the complex setting of associations a between parasitic diseases, milk yield and milk constituents, and management practices

Associations of production characteristics with the on-farm presence of Fasciola hepatica in dairy cows vary across production levels and indicate differences between breeds

Fasciola hepatica is one of the economically most important endoparasites in cattle production. The aim of the present work was to evaluate the relevance of production level on the associations of on-farm presence of F. hepatica with farm-level milk yield, milk fat, and milk protein in Holstein cows, a specialised dairy breed, and in Simmental cows, a dual purpose breed. Furthermore, we investigated whether differential associations were present depending on breed. Data from 560 dairy farms across Germany housing 93,672 cows were analysed. The presence of F. hepatica antibodies was determined via ELISA on bulk tank milk samples. Quantile regression was applied to model the median difference in milk yield, milk fat, and milk protein depending on the interaction of breed and fluke occurrence. Whereas a reduction in milk yield (-1,206 kg, p < 0.001), milk fat (-22.9 kg, p = 0.001), and milk protein (-41.6 kg, p <0.001) was evident on F. hepatica positive German Holstein farms, only milk fat (-33.8 kg, p = 0.01) and milk protein (-22.6 kg, p = 0.03) were affected on F. hepatica positive German Simmental farms. Subsequently, production traits were modelled within each of the two breeds for low, medium, and high producing farms in the presence of F. hepatica antibodies and of confounders. On Holstein farms, the presence of F. hepatica seropositivity was associated with lower production, while on German Simmental farms such an association was less evident. This work demonstrates that production level is relevant when assessing the associations between the exposure to F. hepatica with production characteristics. Moreover, both models indicate a breed dependence. This could point towards a differential F. hepatica resilience of specialised dairy breeds in comparison with dual purpose breeds

Creating triple-wins for health, equity and environmental sustainability: elements of good practice based on learning from the INHERIT case studies

This report draws out dimensions of good practice for building this triple-win, based on learning from the INHERIT project’s 15 case studies. In the context of the project, good practice refers to ways that support changing contexts and create conditions to enable behaviour change to reach the triple-win. This report summarises key information for consideration by governmental and non-governmental policy-makers and practitioners planning to work across sectors to achieve the triple-win through behaviour change at every level. INHERIT researchers have focused their evaluations of the 15 INHERIT case studies on implementation, intersectoral cooperation, impacts and cost benefits. The researchers have taken dimensions of good practice from INHERIT research to be those elements that appear to be promising or necessary in the contexts in which the INHERIT cases studies are implemented. The extent to which these elements of good practice can be generalised to other contexts merits consideration in developing future initiatives towards creating synergies across sectors. INHERIT researchers have drawn out lessons learned from information gathered in evaluations about triggers for the initiatives, key elements for implementation, success factors in intersectoral cooperation, what could have been done better, what should be done in the future, and the most important learnings from the evaluation of outcomes, costs and benefits

Creating triple-wins for health, equity and environmental sustainability: elements of good practice based on learning from the INHERIT case studies

This report draws out dimensions of good practice for building this triple-win, based on learning from the INHERIT project’s 15 case studies. In the context of the project, good practice refers to ways that support changing contexts and create conditions to enable behaviour change to reach the triple-win. This report summarises key information for consideration by governmental and non-governmental policy-makers and practitioners planning to work across sectors to achieve the triple-win through behaviour change at every level. INHERIT researchers have focused their evaluations of the 15 INHERIT case studies on implementation, intersectoral cooperation, impacts and cost benefits. The researchers have taken dimensions of good practice from INHERIT research to be those elements that appear to be promising or necessary in the contexts in which the INHERIT cases studies are implemented. The extent to which these elements of good practice can be generalised to other contexts merits consideration in developing future initiatives towards creating synergies across sectors. INHERIT researchers have drawn out lessons learned from information gathered in evaluations about triggers for the initiatives, key elements for implementation, success factors in intersectoral cooperation, what could have been done better, what should be done in the future, and the most important learnings from the evaluation of outcomes, costs and benefits