Portfolio performance gauging in discrete time using a Luenberger productivity indicator

This paper proposes a pragmatic, discrete time indicator to gauge the performance of portfolios over time. Integrating the shortage function (Luenberger, 1995) into a Luenberger portfolio productivity indicator (Chambers, 2002), this study estimates the changes in the relative positions of portfolios with respect to the traditional Markowitz mean-variance efficient frontier, as well as the eventual shifts of this frontier over time. Based on the analysis of local changes relative to these mean-variance and higher moment (in casu, mean-variance-skewness and mean-variance-skewness-kurtosis) frontiers, this methodology allows to neatly separate between on the one hand performance changes due to portfolio strategies and on the other hand performance changes due to the market evolution. This methodology is empirically illustrated using a mimicking portfolio approach (22 and 23) using US monthly data from January 1931 to August 2007.     

Vertical Disintegration: A Dynamic Markovian Approach

In a model where a monopolistic downstream firm (assembler) negotiates simultaneously with each of its intermediate‐input suppliers the prices of the complementary components which enter its product, we analyze the process by which the assembler separates from its suppliers as a Markov Perfect equilibrium. Due to a negative strategic effect (the prices and profits of independent suppliers decrease when their number increases), the assembler’s marginal return from keeping an upstream subsidiary is lower than the market value of an independent supplier. Separation is immediate when the downstream firm’s initial number of upstream subsidiaries is below a critical level. It is progressive in the reverse case and eventually leads to a mixed strategy whereby the assembler keeps all the remaining subsidiaries with some probability, and sells all them off in one go with the complementary probability.     

On the unique features of post-disaster humanitarian logistics

Logistic activity can be thought of as a socio-technical process whereby a social network of individuals orchestrates a series of technical activities using supporting systems such as transportation and communications. To understand the functioning of the entire system requires proper consideration of all its components. We identify seven key components: the objectives being pursued, the origin of the commodity flows to be transported, knowledge of demand, the decision-making structure, periodicity and volume of logistic activities, and the state of the social networks and supporting systems. Based on our analysis of the differences between commercial and humanitarian logistics, we pinpoint research gaps that need to be filled to enhance both the efficiency of humanitarian logistics and the realism of the mathematical models designed to support it.We argue that humanitarian logistics is too broad a field to fit neatly into a single definition of operational conditions. At one end of the spectrum we find humanitarian logistic efforts of the kind conducted in long-term disaster recovery and humanitarian assistance, where operational efficiency – akin to commercial logistics – is a prime consideration. At the other, post-disaster humanitarian logistic operations involved in disaster response and short-term recovery activities represent a vastly different operational environment, often in chaotic settings where urgent needs, life-or-death decisions and scarce resources are the norm. The huge contrast between these operational environments requires that they be treated separately.     

An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longitudinal perspective

This article presents an application of a bibliometric and visual study of the research carried out on a social science subfield, concretely the consumer behaviour research (CBR), from a longitudinal perspective (period 1966–2008). The study combines performance analysis and science mapping for detecting and visualizing conceptual subdomains. Quantitative and qualitative measures are used in order to identify the most prominent themes. Quantitative data are used to put together very related concepts (themes or clusters of topics), while qualitative indicators (as those based on citations) are used to measure the quality and/or impact of the detected themes. The study also uses bibliometric maps to show in a visual way the associations between the main concepts treated by the CBR community. The maps provide insight into the structure of the CBR, visualize the division of the field into several subfields, and indicate the relationships between these subfields. Co-word analysis is the bibliometric technique used to identify the main themes. All this allows us to quantify and visualize the thematic evolution of the CBR. It also helps to both experts and novices to understand the current state of the art of the CBR and to predict where future research could lead.     

Inter-market competition for NYSE-listed securities under decimals

Blume and Goldstein (J Finance 52:221–244, 1997) suggest that quote competition between trading venues may diminish following tick size reductions. We test this suggestion by studying the competitive landscape in the NYSE-listed stocks before and after decimalization. We find that NBBO (National Best Bid and Offer) participation by non-NYSE venues declines following decimalization consistent with the prediction. At the same time, the importance of quote competitiveness in attracting order flow increases. In addition, although not as active in determining and maintaining the best quotes under decimals, non-NYSE venues become more active in price discovery. Finally, decimalization leads to lower trading costs and to smaller differences in trading costs across trading venues.     

Marketing Innovation in Rural Small Food Industries in Iran

Marketing innovation is essential for small industries to transform products into profit; therefore, understanding its nature and determinants is of utmost importance. This study aimed at understanding marketing innovation and its determinants in the 60 small food industries in the rural areas of Tehran province, Iran. Using a census sampling method, 111 managers of these firms were interviewed. Results showed that the firms’ performance in marketing innovation is generally weak, and a higher level of radical innovation in marketing is perceived compared to the incremental innovation. Also, a cause-and-effect relationship exists between both product and organizational innovations and marketing innovation. Furthermore, while incremental marketing innovation was negatively influenced by formal R&D unit, product diversification, and the manager’s years of experience, radical marketing innovation was affected by the capacity of production, product diversification, and managers’ age and education. The study concluded that in order to boost marketing innovation, innovation should be made also in products and organization. In addition, in order to facilitate the process of marketing innovation, practical and updated training for managers encouraging incremental innovation in marketing, product diversification, and improving R&D activities in the studied firms should be regarded.     

How a Reduction of Standard Working Hours Affects Employment Dynamics

December 1, 1996 a new law was implemented in Portugal to gradually reduce the standard workweek from 44 to 40 h. We study how this mandatory reduction affected employment through job creation and job destruction. There was considerable regional, sectoral and firm-size variation in the share of workers who were affected by the working hours reduction. We exploit this variation to assess the impact of the workweek reduction. We find evidence that the working hours reduction had a positive effect on employment through a fall in job destruction.     

“Economic Capital Allocation Derived from Risk Measures”, Eddy Van den Borre,January 2003

Abstract

The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent times because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Despite the number of papers published in recent years, a comprehensive review has not yet been developed.

This paper attempts to be the starting point for that review, highlighting the importance of recently published research—most of the references cited span the last 10 years—and covering the main methodologies that have been applied to the projection of mortality rates in the United Kingdom and the United States. A comparative review of techniques used in official population projections, actuarial applications, and the most influential scientific approaches is provided. In the course of the review an attempt is made to identify common themes and similarities in methods and results.

In both official projections and actuarial applications there is some evidence of systematic overestimation of mortality rates. Models developed by academic researchers seem to reveal a trade-off between the plausibility of the projected age pattern and the ease of measuring the uncertainty involved. The Lee-Carter model is one approach that appears to solve this apparent dilemma.

There is a broad consensus across the resulting projections: (1) an approximately log-linear relationship between mortality rates and time, (2) decreasing improvements according to age, and (3) an increasing trend in the relative rate of mortality change over age. In addition, evidence suggests that excessive reliance on expert opinion—present to some extent in all methods—has led to systematic underestimation of mortality improvements.     

The impact of coding time on the estimation of school effects

Multilevel growth curve models are becoming invaluable in educational research because they model changes in student outcomes efficiently. The coding of the time variable in these models plays a crucial role as illustrated in this study for the case of a three-level quadratic growth curve model. This paper shows clearly how the choice of a time coding affects school effects estimates and their interpretation. A new definition for school effects for growth curve models with random intercepts and slopes is proposed. This study recommends that the choice of a time coding should not only be based on the ease of interpretation and model convergence but also on its consequences on the student status and growth parameter estimates. The current application illustrates that in general the school effects for student growth in well-being and language achievement in secondary school, are greater for student growth than for student status.     

Preference for Restorative Situations: Interactive Effects of Attentional State,Activity-in-Environment,and Social Context

This study extends research on psychological restoration by encompassing a broad set of restorative situations available to urban residents. Preferences are assessed for mundane restorative situations comprising leisure activity, setting, and social context, given different levels of attentional fatigue. Attentional fatigue, activity-setting, and social context were experimentally manipulated. The settings for activities were home, park, city center, and transit. Participants (N = 70) read scenarios describing an attentional state and rated their preference for the situations. Results show interactive effects of attentional state with activity-setting and with social context. The park was most preferred given attentional fatigue. Results confirm that while residents may particularly value urban nature for restoration, their urban context also provides other mundane but attractive restorative situations.