Selecting stochastic mortality models for the Italian population

The future revision of capital requirements and a market-consistent valuation of non-hedgeable liabilities lead to an increasing attention on forecasting longevity trends. In this field, many methodologies focus on either modeling mortality or pricing mortality-linked securities (as longevity bonds). Following Lee–Carter method (proposed in 1992), actuarial literature has provided several extensions in order to consider different trends observed in European data set (e.g., the cohort effect). The purpose of the paper is to compare the features of main mortality models proposed over the years. Model selection became indeed a primary task with the aim to identify the “best” model. What is meant by best is controversial, but good selection techniques are usually based on a good balance between goodness of fit and simplicity. In this regard, different criteria, mainly based on residual and projected rates analysis, are here used. For the sake of comparison, main forecasting methods have been applied to deaths and exposures to risk of male Italian population. Weaknesses and strengths have been emphasized, by underlying how various models provide a different goodness of fit according to different data sets. At the same time, the quality and the variability of forecasted rates have been compared by evaluating the effect on annuity values. Results confirm that some models perform better than others, but no single model can be defined as the best method.     

Measuring financial systemic stress for Turkey: A search for the best composite indicator

In this study, we aim to construct a single financial stress indicator (FSI) for Turkey adopting weekly data from between April 2005 and December 2016. To do so, we compose 15 different FSIs using 14 variables that will represent five different markets, i.e. the money market, the bond market, the foreign exchange market, the equity market and the banking sector. We aggregate these five different markets using a variety of techniques, including principal component analysis (PCA), basic portfolio theory, variance equal weights and the Bayesian dynamic factor model. We compare 15 different FSIs on the basis of their relation to, and the forecasting power of, different variables such as the growth rate of industrial production, the OECD business condition index and the OECD composite leading indicator for Turkey. Our results suggest that there is no simple best indicator for Turkey to measure financial systemic stress. Some indicators offer good forecasting power for economic growth while others have a stronger correlation with systemic risk. Therefore, we offer a final FSI for Turkey conducting a model averaging method via a rolling correlation based weighting scheme to benefit from the information content of all the FSIs and observe that the final FSI successfully indicates the tension periods.     

On the Decomposition by Subgroups of the Gini Index and Zenga's Uniformity and Inequality Indexes

Besides a brief historical outline of the Gini index decomposition proposals, we compare, in a subgroups framework, the decompositions of the Gini index and of the uniformity and inequality indexes recently proposed by Zenga. The two decompositions follow a similar scheme: in both cases the overall index can be at first expressed as a weighted average of convenient "cross" measures, with their own interpretation, and afterwards it is decomposed into a within and a between term by merely distinguishing measures evaluated within the same subgroup from the ones regarding different subgroups. This procedure does not depend on an a priori definition of the within or the between term and allows their contribution to be naturally evaluated preserving the structure of the index itself. In the last section the two decompositions are applied to the Italian net household wealth provided by the 2006 central Bank of Italy sample survey on household budgets.     

Sampling Procedures for Coordinating Stratified Samples: Methods Based on Microstrata

The aim of sampling coordination is to maximize or minimize the overlap between several samples drawn successively in a population that changes over time. Therefore, the selection of a new sample will depend on the samples previously drawn. In order to obtain a larger (or smaller) overlap of the samples than the one obtained by independent selection of samples, a dependence between the samples must be introduced. This dependence will emphasize (or limit) the number of common units in the selected samples. Several methods for coordinating stratified samples, such as the Kish & Scott method, the Cotton & Hesse method, and the Rivière method, have already been developed. Using simulations, we compare the optimality of these methods and their quality of coordination. We present six new methods based on permanent random numbers (PRNs) and microstrata. These new methods have the advantage of allowing us to choose between positive or negative coordination with each of the previous samples. Simulations are run to test the validity of each of them.     

What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry

Using a large plant level data set, this paper carries out an econometric analysis of the environmental performance of multinational firms in the gold mining industry worldwide. The aim of the analysis is to determine if, by looking at the actual environmental performance of firms (as opposed to inferring such behavior from location decisions), we can shed any light on important questions in the literature on firm location decisions: Do pollution havens exist in the gold mining industry? Do foreign controlled gold mines perform environmentally worse or better than their domestic counterparts? We develop different ways of measuring environmental performance within the context of a Bayesian stochastic production frontier approach. In particular, we derive different ways of measuring technical and environmental efficiency. When we implement these methods in our empirical work, we find that results are robust across different models and ways of measuring efficiency. We find that gold mines exhibit a wide range of environmental efficiencies; some are clearly more efficient than others. However, and most importantly for our questions, we find that this variation in efficiencies cannot be systematically related to mine characteristics such as whether they are foreign or domestically controlled or whether they are located in developed versus developing countries.     

Informal hierarchies among workers in low‐skill food manufacturing jobs

This article examines the creation of informal workplace hierarchies in the context of recent changes in the UK labour market. Previous studies have identified that deskilling of jobs has removed formal hierarchies among many production workers, and that informal hierarchies based upon factors such as contractual status have formed in their place. The aim of this article is to examine how changes in the labour force mean that new informal hierarchies have developed among migrant and immigrant workers who take these jobs through an agency. Research consisted of 50 semi‐structured interviews, coupled with lengthy observation of both work and social settings, at three food manufacturers. The article finds that language and cultural issues create a complex informal hierarchy not only between directly employed and agency workers, but also among and within different groups of migrant and immigrant agency workers.     

ON THE PARAMETERIZATION OF TECHNIQUES FOR REPRESENTING REGIONAL ECONOMIC STRUCTURES

This paper is concerned with two parameterized methods of regionalising input–output coefficients: the Flegg et al. Location Quotient (FLQ) and its augmented version (AFLQ). For applying the two techniques, a parameter δ has to be estimated. In this regard, the paper faces two matters that are still open in the literature: the existence of a range of δ that can be used in different regions and the estimation of the most appropriate value of δ. For this aim, a Monte Carlo simulation has been carried out in order to generate ‘true’ multiregional I-O tables randomly. From the simulation, analyses based on probability distributions and regression were also carried out. Finally, these simulation results have been compared with those of an empirical case. Results confirm that there is actually a range of values of δ within which the best δ is more likely to fall. For the FLQ, this range is centred on 0.3 with an associated probability of 33% (if the width of the range is set at 0.1), whereas, for the AFLQ, the relevant range is between 0.3 and 0.4 with a probability by 38%. Finally, this paper provided a way to estimate the best δ for a given region, without knowing the relevant and detailed economic structure at sectoral level.     

Testing inter-group ranking heterogeneity: do patient characteristics matter for prioritization of quality improvements in healthcare service?

In many research contexts, such as social science, marketing, education, psychology and medicine, it is frequently of interest to compare two or more groups of subjects (e.g. people of different gender, age or nationality), who are asked to rank a set of alternatives according to their personal liking or opinion, for investigating the presence of group effect. The common investigation aim is to detect customers with homogeneous preferences (or priorities) in order to serve each group as properly as possible. Several approaches have been proposed in the literature for testing ranking heterogeneity among groups of subjects. This paper focuses on an approach considering diversity as a generalization of the notion of variation and investigates the performance of a testing procedure for ranking heterogeneity based on the index of segregation power. The performance of the testing procedure has been investigated via a Monte Carlo simulation study under several scenarios, differing for group size, number of ranked alternatives and system of hypothesis. Furthermore, using a real data set, the testing procedure is exploited for investigating whether patient age and gender matter for patient prioritization of quality improvement in healthcare service.     

Drivers,adoption, and evaluation of sustainability practices in Italian wine SMEs

Based on a survey with 64 small and medium‐sized enterprises (SMEs) in two Italian wine regions, this study aims to (a) identify key drivers and barriers of the adoption of sustainability and (b) compare the adoption and evaluation (use, financial/labor investments, and satisfaction) of sustainability practices in four management domains (marketing, chain, operational, and innovation). Results show that internal drivers were considered to be more important than external drivers. Economic sustainability‐oriented drivers scored significantly lower than drivers related to other dimensions, such as environmental sustainability and heritage. Key barriers refer to labor and investments costs, as well as concerns about greenwashing. Although there are substantial differences in adoption and evaluation of sustainability practices within and between management domains, this study confirms their widespread adoption in wineries. Among users, satisfaction levels outweigh the perceived investments. Except for innovation management practices, financial investments are considered to be lower than labor investments. Positive correlations between use‐satisfaction (within each management domain) and between investments or satisfaction levels (between management domains) further lend support for producers' adoption of multiple practices. At sustainability dimension level, heritage is negatively correlated with the evaluation indicators, indicating that it may act as a potential barrier to some sustainability practices. Segmentation analysis identified a low (30%) and high sustainability clusters (70%), which differ significantly in terms of sustainability perceptions and drivers, adoption, and evaluation of practices, as well as company characteristics. Future research needs to validate the findings on SMEs, compare our measures with more objective evaluation indicators, future adoption rates, and multidimensional sustainability practices.     

The role of organizational cultures in information‐systems security management: A goal‐setting perspective

The aim of this research is to investigate the role of strong organizational cultures in setting information‐systems security goals. In doing so, we explore and discuss the concept of culture within three financial organizations with different social and organizational structures, and seek to demonstrate the importance of having a cohesive culture in efficiently setting information‐security goals. The relationship between goal setting, culture strength, and performance is also discussed, as there have been studies that indirectly indicate that such a relationship may exist. The contribution of this work to interpretive information‐systems research consists of its study of culture and goal setting in a security‐management context, and its grounding within an interpretive epistemology. In addition, this research promotes an interdisciplinary and interorganizational theory to foster dialogue that transcends industry‐specific contexts and explores different organizational practices that can improve leadership's role in human life.     

Issues in the analysis of co-authorship networks

Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines.     

A CLOSER LOOK AT VALUE PREMIUM: LITERATURE REVIEW AND SYNTHESIS

This paper provides a systematic review of value premium literature that examines the performance difference between value and growth stocks and the possible reasons for it. We compare and synthesize the results from the different regional stock markets and different sample periods. The literature is categorized according to stock selection criteria that are based on either individual valuation ratios, such as E/P, B/P, D/P, S/P, CF/P, and enterprise value-based multiples, or composite value criteria that aim to capture more than one dimension of relative value simultaneously or combine them with other classification criteria. We also compare the efficacy of various selection criteria to each other and synthesize the literature on the explanations for the value anomalies. The overall evidence shows that the best criterion varies over time and across the markets. The relative efficacy of different valuation criteria also seems to depend on numerous methodological choices. Recent studies have given mild evidence that combining traditional valuation ratios either with each other or with some financial statement variables could at least in some cases enhance the value premium, although very few studies have provided transparent comparisons between the results based on individual valuation ratios and those based on composite value criteria.     

Print versus electronic surveys: a comparison of two data collection methodologies

This paper compares the responses of consumers who submitted answers to a survey instrument focusing on Internet purchasing patterns both electronically and using traditional paper response methods. We present the results of a controlled experiment within a larger data collection effort. The same survey instrument was completed by 416 Internet customers of a major office supplies company, with approximately 60% receiving the survey in paper form and 40% receiving the electronic version. In order to evaluate the efficacy of electronic surveys relative to traditional, printed surveys we conduct two levels of analysis. On a macro-level, we compare the two groups for similarity in terms of fairly aggregate, coarse data characteristics such as response rates, proportion of missing data, scale means and inter-item reliability. On a more fine-grained, micro-level, we compare the two groups for aspects of data integrity such as the presence of data runs and measurement errors. This deeper, finer-grained analysis allows an examination of the potential benefits and flaws of electronic data collection.Our findings suggest that electronic surveys are generally comparable to print surveys in most respects, but that there are a few key advantages and challenges that researchers should evaluate. Notably, our sample indicates that electronic surveys have fewer missing responses and can be coded/presented in a more flexible manner (namely, contingent coding with different respondents receiving different questions depending on the response to earlier questions) that offers researchers new capabilities.     

Mixed-effects models for health care longitudinal data with an informative visiting process: A Monte Carlo simulation study

Electronic health records are being increasingly used in medical research to answer more relevant and detailed clinical questions; however, they pose new and significant methodological challenges. For instance, observation times are likely correlated with the underlying disease severity: Patients with worse conditions utilise health care more and may have worse biomarker values recorded. Traditional methods for analysing longitudinal data assume independence between observation times and disease severity; yet, with health care data, such assumptions unlikely hold. Through Monte Carlo simulation, we compare different analytical approaches proposed to account for an informative visiting process to assess whether they lead to unbiased results. Furthermore, we formalise a joint model for the observation process and the longitudinal outcome within an extended joint modelling framework. We illustrate our results using data from a pragmatic trial on enhanced care for individuals with chronic kidney disease, and we introduce user-friendly software that can be used to fit the joint model for the observation process and a longitudinal outcome.     

Are Mainstream and Heterodox Economists Different? An Empirical Analysis

We explore the differences between mainstream and heterodox economists based on the responses to a questionnaire from a representative sample of Italian economists. Using different definitions for mainstream and heterodox economics, we compare the individual and academic characteristics of the economists belonging to these groups. We measure the within and between disagreement for each group and we test whether belonging to one or the other group predicts differences in economists' opinions on economic policy. Results show that: 1) mainstream and heterodox economists differ as to individual and academic characteristics and political views; 2) the disagreement within heterodox economics is lower than within mainstream economics; 3) some of commonly used ways of grouping heterodox and mainstream schools of thought have little explicative power in relation to individual opinions; 4) on critical economic policies, the opinions of heterodox and mainstream economists are significantly different even after controlling for a number of individual characteristics, including political opinions.     

Government instruments to support the commercialization of university research: Lessons from Canada

Increased efforts are made in most industrialized countries to promote the commercialization of university research, for instance, through spin-off firm formation. Many studies have investigated the initiatives set up in the university sector that aim to support and facilitate the commercialization of research, such as technology transfer offices (TTO). However, few studies have looked at the increasing number of instruments introduced from the government. This paper reviews the Canadian support structure at federal level that aims to support the commercialization of publicly funded research. Two types of programs can be identified. Firstly, programs made to induce structural reforms within the university sector in order to improve the institutional capabilities to facilitate commercialization projects. Secondly, programs providing support to specific commercialization projects. This paper explores how these types of programs are operated at government level. An example of implementation at university level is also given. The lessons to be learned from the Canadian case are related to how the government initiatives encourage a bottom-up approach. This is accomplished by providing resources for direct use in commercialization projects or to develop professional expertise in technology transfer in the university sector, by experimenting with new initiatives, and finally by facilitating cooperation between commercializing organizations.     

Analytically comparing disaster resilience across multiple dimensions

It is important to compare the resilience of complex human systems to different types of disasters, in order to assess their inherent vulnerabilities and take appropriate actions to strengthen them. Resilient behavior can be complicated and multi-dimensional, however, and one must be able to characterize the different ways in which that resilience actually exhibits itself in practice. With this in mind, this paper discusses creating a multi-dimensional indicator for the resilience of a complex human system, and it explores an approach for visualizing and analyzing the relationships between each of the individual resilience dimensions. Because decision makers may differ on the relative contribution of the different dimensions to overall resilience, the paper further discusses the issue of weighting the different dimension values and the impacts that such a weighting scheme can have on the relative ranking of different scenarios. We illustrate the ability to characterize the complexity of multi-dimensional resilience by analyzing an empirical data set that measures the relative resilience of the New York metropolitan area to seven different natural disasters between 2010 and 2012.     

Some statistical and DEA evaluations of relative efficiencies of public and private institutions of higher learning

This paper uses the Charnes, Cooper and Rhodes (CCR) ratio form of Data Envelopment Analysis (DEA) (1) to examine how DEA can be utilized in analyzing different aspects of production behavior of institutions of higher learning (IHLs) as an alternative to more traditional approaches such as econometric-regression models, and (2) to compare “specifically” relative efficiencies of public and private doctoral-granting universities in the U.S. and to analyze technical and scale efficiencies of those universities. The separation of doctoral-granting universities into universities with and without medical colleges represents a departure from preceding studies. This division proved very important in uncovering substantial differences in behavior between the two groups even when using the “statistical averaging” approaches that were customary in previous studies. For both groups, public universities proved more efficient than private universities when managerial and program inefficiencies are present in the data. When managerial inefficiencies are disentangled from the data and medical schools are not present, private universities have more efficient programs. However, their managers are less efficient users of program opportunities than are managers in public universities. Another portion of the current study dealt with returns-to-scale possibilities. These differed markedly (even on average) between IHLs with and without medical schools. Moreover, analyses by DEA showed marked ranges of variation for returns-to-scale possibilities for individual IHLs within each group. These possibilities have generally been concealed by the statistical averaging utilized in previous econometric studies. Further, their identification is beyond the ability of the usual types of one-at-a-time ratio and trend analyses.     

Planning the production of electrical energy

In the paper, an effort is made to answer many of the perplexing questions concerning pricing and investment decisions that must be faced if the development of the electrical energy industry in the United States is to be carried on within a fully integrated or at least partially integrated framework.By using an intertemporal-spatial equilibrium model, solutions are suggested to such problems as the efficient pricing, allocation, and additions to generating capacity facing the electrical energy industry when peak demands occur at different times in different regions, when regions have different kinds and sizes of generating plants and are endowed with resources of different costs and availabilities, when prices do not reflect marginal costs, and when there are restrictions on transmission capacity.