Banks’ deferred tax assets during the financial crisis

Review of Quantitative Finance and Accounting - Prior studies have demonstrated that the net deferred tax liabilities of industrial firms are valued by market participants in a manner consistent...     

Bagging bundle benefits in broadband and media mergers: Lessons from Sky/Vodafone for antitrust analysis

The historic precedents in telecommunications antitrust findings have tended towards finding harm to competition when network operators integrate downstream and bundle the provision of applications and services. The reason for this is that market power in network provision is thought to be extended into the applications market(s). More recently however, proposed mergers have been between telecommunications and media distribution firms, both of whom have some degree of market power, already sell their own services in bundles, and who may or may not have been offering combined bundles already via contractual agreements. Examples include Sky/Vodafone in New Zealand, and Time Warner/AT&T in the United States as well as Vodafone/Unitymedia in Germany and Media Capital/Altice in Portugal. These complex proposed arrangements pose challenges to competition authorities, whose legal and procedural rules and precedents, especially those defining the relevant markets affected by the merger or vertical integration activity, have been developed from the analysis of simpler cases. These precedents may not be sufficient to analyse current cases, characterized by multiple products catering to heterogeneous consumer preferences, and consumers are not constrained to buying only one variant of the products in each of the upstream and downstream markets.We illustrate the challenges by way of a case study of the proposed merger between Sky and Vodafone, declined by the New Zealand Commerce Commission in February 2017. Limitations in existing market definition processes and the evaluation of market power where bundling already occurs risk overlooking complex demand-side interactions that influence the profitability and efficiency of various structural and contractual strategic choices. We propose that classic merger and antitrust analysis based on econometric cost-benefit analysis can be augmented by using simulation and numerical analysis of a range of bundle offers expected to be relevant in decision-making. We develop a simple model and use it to illustrate how it may be used to inform broadband and content mergers, and other complex antitrust cases, such the assessment of the effects of two-sided markets and firm pricing decisions.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

New Evidence on Housing Wealth and Consumption Channels

The Journal of Real Estate Finance and Economics - This paper provides new evidence on the effect of housing wealth on consumption by focusing on the impact of home-equity extraction. We develop a...     

INSURANCE‐INDUCED MORAL HAZARD: A DYNAMIC MODEL OF WITHIN‐YEAR MEDICAL CARE DECISION MAKING UNDER UNCERTAINTY

This study quantifies the moral hazard effect of health insurance on medical expenditure by estimating a dynamic model of within‐year medical care consumption that allows for insurance selection, endogenous health transitions, and individual uncertainty about medical care prices in an environment where insurance has nonlinear cost‐sharing features. The results suggest that moral hazard accounts for 53.1%, on average, of total annual medical expenditure when insured. This estimate is significantly different, and generally larger, than that produced by an alternative model that is representative of the annual medical care decision‐making models commonly found in the literature.     

Costs and potential funding of expanded public pension coverage in Asia

Public pension burdens in most emerging Asian economies are still relatively small. However, there are a number of reasons to believe that they will increase markedly in the coming years. First, many Asian economies will face rapidly ageing populations, which will raise pension and other old‐age‐related spending dramatically. Second, as economies develop, political pressures to expand the coverage of public pensions and raise pension benefits will likely increase. The first objective of this paper is to identify the potential fiscal burden of public pensions in 23 emerging Asian economies, based on econometric models and forecasts of GDP and demographic trends. Using two different methodologies yields estimated increases in the average share of public pension expenditures in GDP of 1.0 percentage point and 3.6 percentage points by 2030 compared with current levels. We believe the latter estimate is more realistic. The second objective is to recommend policies to provide adequate funding for public pension needs, including enhancing the efficiency of social insurance programs, improving the balance of revenues and expenditures, implementing more explicit fiscal rules and frameworks, and establishing stronger fiscal surveillance at the national and regional levels.