Incremental costs associated with myocardial infarction and stroke in patients with type 2 diabetes mellitus: an overview for economic modeling

Objective:

To identify cost estimates related to myocardial infarction (MI) or stroke in patients with type 2 diabetes mellitus (T2DM) for use in economic models.

Methods:

A systematic literature review was conducted. Electronic databases and conference abstracts were screened against inclusion criteria, which included studies performed in patients who had T2DM before experiencing an MI or stroke. Primary cost studies and economic models were included. Costs were converted to 2012 pounds sterling.

Results:

Fifty-four studies were identified: 13 primary cost studies and 41 economic evaluations using secondary sources for complication costs. Primary studies provided costs from 10 countries. Estimates for a fatal event ranged from £2482–£5222 for MI and from £4900–£6694 for stroke. Costs for the year a non-fatal event occurred ranged from £5071–£29,249 for MI and from £5171–£38,732 for stroke. Annual follow-up costs ranged from £945–£1616 for an MI and from £4704–£12,926 for a stroke. Economic evaluations from 12 countries were identified, and costs of complications showed similar variability to the primary studies.

Discussion:

The costs identified within primary studies varied between and within countries. Many studies used costs estimated in studies not specific to patients with T2DM. Data gaps included a detailed breakdown of resource use, which affected the ability to compare data across countries.

Conclusions:

In the development of economic models for patients with T2DM, the use of accurate estimates of costs associated with MI and stroke is important. When country-specific costs are not available, clear justification for the choice of estimates should be provided.     

Easing the assessment of emerging technologies in technology observatories. Findings about patterns of dissemination of emerging technologies on the internet

This paper considers the Web as a big data container that can be used by Technology Observatories and administrations to track emerging issues and more specifically emerging technologies. It considers information that is available on the Internet for free from different sources, and proposes a framework that can be useful to characterise them and to detect patterns of dissemination. This framework is made up of 30 metrics obtained from different kinds of sources (general web, patents, scholars?…). Some of them are obtained directly as the number of hits retrieved by queries on a search engine, and other ones calculated by means of ratios. This paper contains the development of a complete case that utilises this framework to characterise emerging technologies included in the well-known Hype Cycle for Emerging Technologies, in this case the 2015 release¹ and to analyze patterns of dissemination of these technologies on the Internet.     

An Exploratory Study on Nonlinear Causality Among the MILA Markets

According to conventional portfolio theory, an increase in the interconnectedness of international financial markets may reduce the potential for constructing diversified portfolios. This article explores the implications of the creation of the Latin American Integrated Market (MILA)¹ over the dependence structure of its members using correlation and cointegration analysis as well as linear and nonlinear Granger causality tests. The creation of MILA aimed to enhance the integration process that Latin American financial markets “naturally” present while still providing diversification opportunities to investors. The results of our empirical analysis suggest that such objective is being achieved. Evidence of a rise in cross-country linear correlations and their linear causal relationship supports the idea of an increasing financial integration process in the region, while the absence of cointegration and the weakening of the nonlinear causal relationship favors the creation of diversified regional portfolios. These findings provide valuable insights for investment portfolio designers, regulators, and supervisors.     

Visual displays: analytical study and applications to graphs and real data

Principal axis methods such as principal component analysis (PCA) and correspondence analysis (CA) are useful for identifying structures in data through interesting planar graphic displays. However, some kinds of data sets can be dealt alternatively with PCA or CA. This paper focuses on methods, such as PCA and CA, and on visual displays. Our aim is to illustrate the implications for a potential user of selecting either method, and its advantages and disadvantages, from an applied point of view. This is a matter covered broadly in textbooks and elsewhere considering theoretical arguments. Our purpose is to contribute to the comparison between these methods, over the same data set, in order to illustrate them for the practitioner. In the first part of this paper we present a novel analytical study of a binary matrix associated with a non-oriented axis-symmetric graph and show that CA outperforms standardized PCA for the reconstitution and visualization of such kind of graphs. In the second part we present a case using real data dealing with the distribution of employees in different economic sectors for the countries of the European Union, analyzed by means of standardized PCA and two-way CA, in order to see the differences between the two methods in practice.     

Altruism and the Economic Values of Environmental and Social Policies

Altruism is a type of non-use value which can have different definitions depending on the type of goods entering the utility function of the altruists and their expectations about the contributions of others. The purpose of this paper is to measure the trade-offs between different types of altruist values originating from social and environmental policies. Environmental policies are concerned with reducing health effects from a power plant while social policies involve both the attainment of public facilities for education and leisure and an increase in the income of the affected population. The empirical application utilizes a choice experiment technique which allows for valuation of multiple goods. Health effects are decomposed into the values of the risk of becoming ill, the duration of the episodes and the limitations imposed by illness. Altruist values are elicited from a population that is not affected by pollution. Results show that altruism is significant for policies directed to reducing health effects and improving the income level of the affected population, whereas there is egoism for a policy aimed at improving public facilities in the polluted suburb. The value of altruism is significantly influenced by the expectations of net benefits to be received by the affected population.     

RESPONDING TO DISRUPTIONS IN THE SUPPLY NETWORK‐FROM DORMANT TO ACTION

Managing risks in supply networks is a complex task; more so in those supply networks where the core competence lies in dealing with natural disasters, complex emergencies, and large‐scale attacks—namely those of humanitarian, and military organizations where the price of failure can be counted in terms of the loss of life rather than, simply, reduced profits. This conceptual article examines the capabilities of these supply networks to manage such disruptions, based on their resource configuration in a dormant preparation state. The article concludes by presenting how different types of supply networks can manage large‐scale disruptions.     

Linking corporate productivity to foreign direct investment: An empirical assessment

This paper examines whether foreign firms generate productivity spillovers. Despite the relevance of this question to public policy, previous studies have failed to find consistent and conclusive evidence to support the existence of positive spillovers. Using previously unexploited firm-level data over the 1994–1999 period, we attempt to contribute to the literature on productivity spillovers from FDI by analysing the Portuguese manufacturing industry. The results indicate that foreign firms in the same industry of the observed firms (horizontal spillovers) and linkages between foreign firms and their local suppliers or customers (vertical spillovers) do not impact significantly on firms’ productivity. Moreover, we detected no differences on productivity spillovers associated to firm-specific characteristics.     

The impact of the institutional environment on the value relevance of fair values

Most prior studies attribute valuation discounts on certain fair valued assets to measurement error or bias. We argue that institutional differences across countries (e.g., information environment or market sophistication) affect investors’ ability to process and impound fair value information in their valuation. We predict that the impact of the institutional environment on value relevance is particularly pronounced for reported fair values of assets designated at fair value through profit or loss (hereafter, “FVO assets”), for which investor experience is lowest and complexity is highest. Using a global sample of IFRS banks, we find that FVO assets are generally less value relevant than held-for-trading assets (HFT) and available-for-sale assets (AFS). By partitioning countries into market- and bank-based economies to proxy for institutional differences, we find that the valuation discount on FVO assets is more pronounced in bank-based economies. Additional tests suggest that this valuation discount is attenuated by a richer firm-level information environment and the presence of institutional investors with fair value experience.