Non‐additivity in Accounting Valuation: Theory and Applications

This paper has three objectives. First, to introduce a theoretical solution to the issue of non‐additivity between assets in place, relying on an accounting‐based valuation approach. Second, to explain how such an approach can be implemented empirically by measuring synergies between assets. Third, to present the properties of this non‐additive valuation technique. We use Choquet capacities, that is, non‐additive aggregation operators, to measure the interactions between assets and apply our methodology to a sample of US firms from the capital goods industry. To operationalize our approach we examine the relationships between synergies—captured by Choquet capacities—and the market‐to‐book ratio (proxying for growth options), and show how interactions between assets are consistently linked to a firm’s market‐to‐book ratio. We also measure firm‐specific productive efficiency relative to the industry and firm size. For large firms, efficiency, as defined by our approach, is positively associated with higher future operating cash flows. For small firms, efficiency is positively associated with higher future sales growth. We document that the non‐additive approach appears to be better able to identify expected relationships between efficiency and future performance than a simpler approach based on the market‐to‐book ratio.     

Trading volume,return variability and short-term momentum

We propose short-term averages of daily stock-level trading volume and return variability as proxies for latent corporate news flow. Conditioning momentum strategies on these two proxies give a significant boost to winner-minus-loser alphas. Regardless of the portfolio formation and holding periods, price drift is larger after elevated levels of volume and variability, supporting the view that prices underreact to news. This pattern is not driven by micro-cap stocks and it is robust to corrections for systematic risk factors and stock characteristics such as liquidity and credit quality.     

Antecedents and Consequences of Eco‐Control Deployment: Evidence from Canadian Manufacturing Firms

Environmental issues have become an important consideration for a growing number of organizations. Eco‐control may represent a valuable tool to help organizations address such issues. The aim of this study is to provide an overview of the eco‐control practices adopted by Canadian organizations and to understand the antecedents and consequences of their adoption. More specifically, this study examines (i) the extent to which eco‐control practices are deployed within organizations, (ii) the factors and motivations that lead organizations to implement eco‐control practices, and (iii) the impact of adoption on firms’ managerial and operational environmental actions as well as on environmental and economic performance. Using survey data from a sample of 249 Canadian manufacturing firms, this article shows that environmental missions, environmental policies, environmental strategic planning, environmental budgets and environmental performance indicators are the most frequently adopted eco‐control practices among the investigated firms, while environmental incentives seem to be less frequently adopted. The results of this study also suggest that competitive and ethical motivations as well as size, environmental exposure and stakeholder pressure are all important factors in explaining eco‐control practice adoption by Canadian manufacturing firms. Moreover, the results of this study show that organizations that have undertaken more intensive managerial and operational environmental actions have also adopted more intensive eco‐control practices. Organizations adopting more intensive eco‐control practices perform better both environmentally and economically performance than firms adopting less intensive eco‐control practices.     

Understanding strategic bidding in multi‐unit auctions: a case study of the Texas electricity spot market

We examine the bidding behavior of firms in the Texas electricity spot market, where bidders submit hourly supply schedules to sell power. We characterize an equilibrium model of bidding and use detailed firm‐level data on bids and marginal costs to compare actual bidding behavior to theoretical benchmarks. Firms with large stakes in the market performed close to the theoretical benchmark of static profit maximization. However, smaller firms utilized excessively steep bid schedules significantly deviating from this benchmark. Further analysis suggests that payoff scale has an important effect on firms' willingness and ability to participate in complex, strategic market environments.     

Testing the compounding structure of the CP-INARCH model

A statistical test to distinguish between a Poisson INARCH model and a Compound Poisson INARCH model is proposed, based on the form of the probability generating function of the compounding distribution of the conditional law of the model. For first-order autoregression, the normality of the test statistics’ asymptotic distribution is established, either in the case where the model parameters are specified, or when such parameters are consistently estimated. As the test statistics’ law involves the moments of inverse conditional means of the Compound Poisson INARCH process, the analysis of their existence and calculation is performed by two approaches. For higher-order autoregressions, we use a bootstrap implementation of the test. A simulation study illustrating the finite-sample performance of this test methodology in what concerns its size and power concludes the paper.     

Resilience to the financial crisis in customer-supplier networks

Inspired by the Capital Asset Pricing Model (CAPM) beta, we construct customer and supplier betas to separately investigate potentially different properties of downstream and upstream linkages. With the adjacency matrix acting as a ‘filter’ to extract each company's return covariances with its trading partners, the cross-sectional dependence contained in the customer-supplier network is summarized by our betas. We explore how these two betas are related to a company's resilience to the financial crisis of 2008–2009. We observe that a higher customer beta is generally associated with more resilience during the crisis. Therefore, investors could construct the customer beta to gain insights into the relative negative impact of a potential crisis on a stock's performance.     

Statistical Inference,Learning and Models in Big Data

The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context. Statistical ideas are an essential part of this, and as a partial response, a thematic program on statistical inference, learning and models in big data was held in 2015 in Canada, under the general direction of the Canadian Statistical Sciences Institute, with major funding from, and most activities located at, the Fields Institute for Research in Mathematical Sciences. This paper gives an overview of the topics covered, describing challenges and strategies that seem common to many different areas of application and including some examples of applications to make these challenges and strategies more concrete.     

Cost-effectiveness of droxidopa in patients with neurogenic orthostatic hypotension: post-hoc economic analysis of Phase 3 clinical trial data

Objective:

Falls are associated with neurogenic orthostatic hypotension (nOH) and are an economic burden on the US healthcare system. Droxidopa is approved by the US FDA to treat symptomatic nOH. This study estimates the cost-effectiveness of droxidopa vs standard of care from a US payer perspective.

Methods:

A Markov model was used to predict numbers of falls and treatment responses using data from a randomized, double-blind trial of patients with Parkinson’s disease and nOH who received optimized droxidopa therapy or placebo for 8 weeks. The severity of falls, utility values, and injury-related costs were derived from published studies. Model outcomes included number of falls, number of quality-adjusted life-years (QALYs), and direct costs. Incremental cost-effectiveness ratios (ICERs) were calculated. Outcomes were extrapolated over 12 months.

Results:

Patients receiving droxidopa had fewer falls compared with those receiving standard of care and gained 0.33 QALYs/patient. Estimated droxidopa costs were $30,112, with estimated cost savings resulting from fall avoidance of $14,574 over 12 months. Droxidopa was cost-effective vs standard of care, with ICERs of $47,001/QALY gained, $24,866 per avoided fall with moderate/major injury, and $1559 per avoided fall with no/minor injury. The main drivers were fall probabilities and fear of fall-related inputs.

Limitations:

A limitation of the current study is the reliance on falls data from a randomized controlled trial where the placebo group served as the proxy for standard of care. Data from a larger patient population, reflecting ‘real-life’ patient use and/or comparison with other agents used to treat nOH, would have been a useful complement, but these data were not available.

Conclusion:

Using Markov modeling, droxidopa appears to be a cost-effective option compared with standard of care in US clinical practice for the treatment of nOH.     

Public–private wage differentials in Turkey: public policy or market dynamics?

We evaluate public–private sector wage differentials by gender in Turkey between the years 2005 and 2013. Using micro data from Household Labor Force Surveys we find a positive premium for low wage earners and a penalty of working in the public sector at the higher end of the distribution. Although the penalty has not disappeared, the price effect has increased at both ends of the distribution. The increase at the lower tail is attributed to a higher price effect in the public sector, whereas at the higher tail it has been a result of a relatively uneven wage increase in the private sector along the distribution, rather than an explicit public wage policy.     

Common and Private Values of the Firm in Tax Competition

We develop a simple model of interregional tax competition to explore how the balance between common and region-specific aspects of a project's value affects the magnitudes of tax breaks offered by governments, when the firm possesses private information on the region-specific values. We examine cases in which the tax applies to both the common and private values and to each component separately. The model predicts that when the common and observable part of the value of a project increases relative to the variance of the region-specific private values, the stringency of competition reduces the equilibrium tax rate. Conversely, if the competing regions are sufficiently different, bidding is less aggressive. One interpretation of the results is that firms that are observed to be large get better tax breaks. The intuition is closely related to the Bertrand model of differentiated product market competition.