Changing threat perceptions and the efficient provisioning of international security

This paper proposes a mechanism for structuring international institutions to efficiently provision global security against the threat of a rogue nation, by an alliance of nations. This paper investigates how the evolution of public opinion, in the respective countries facing the rogue nation's threat, affects the mechanism. It also analyzes the impact of “fair‐weather friends” within the alliance, i.e., allies that increase support for security effort when the threat becomes less dangerous but withdraw support in more dangerous circumstances. Additionally, it explores how the possibility of sequential action by the allies, rather than simultaneous action, might affect joint security efforts.     

An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa

This paper tests whether housing prices in the five segments of the South African housing market, namely large-middle, medium-middle, small-middle, luxury and affordable, exhibit non-linearity based on smooth transition autoregressive (STAR) models estimated using quarterly data from 1970:Q2 to 2009:Q3. Findings point to an overwhelming evidence of non-linearity in these five segments based on in-sample evaluation of the linear and non-linear models. We next provide further support for non-linearity by comparing one- to four-quarters-ahead out-of-sample forecasts of the non-linear time series model with those of the classical and Bayesian versions of the linear autoregressive (AR) models for each of these segments, for the out-of-sample horizon 2001:Q1 to 2009:Q3, using the in-sample period 1970:Q2 to 2000:Q4. Our results indicate that barring the one-, two and four-step(s)-ahead forecasts of the small segment, the non-linear model always outperforms the linear models. In addition, given the existence of strong causal relationship amongst the house prices of the five segments, the multivariate versions of the linear (classical and Bayesian) and STAR (MSTAR) models were also estimated. The MSTAR always outperformed the best performing univariate and multivariate linear models. Thus, our results highlight the importance of accounting for non-linearity, as well as the possible interrelationship amongst the variables under consideration, especially for forecasting.     

Accountability and legitimacy in earth system governance: A research framework

Along with concerns over the effectiveness of earth system governance, ways of enhancing its accountability and legitimacy are increasingly coming to the fore in both scholarly debate and political practice. Concerns over accountability and legitimacy pertain to all levels of governance, from the local to the global, and cover the spectrum of public and private governance arrangements. This conceptual article elaborates on the sources, mechanisms and reform options relating to more accountable, legitimate and democratic earth system governance. We proceed in four steps. First, we conceptualize accountability and legitimacy in earth system governance. Second, we place questions of accountability and legitimacy within the larger context of earth system transformation, which, we argue, poses special challenges to the pursuit of accountability and legitimacy. Third, drawing on the contributions to this special section, we analyze different sources and mechanisms of accountability and legitimacy and their effects on the democratic potential and effectiveness of governance. Fourth, in concluding, we outline reform options that may help alleviate persisting deficits in the democratic potential of earth system governance.     

Researches in Corporate Social Responsibility: A Review of Shifting Focus,Paradigms, and Methodologies

Owing to the growing academic and practitioner’s interest in the field of Corporate Social Responsibility, there is a need to do a comprehensive assessment and synthesis of research activities. This article addresses this need and examines the academic literature on Corporate Social Responsibility and Performance using a paradigmatic and methodological lens. The objective of this article is fourfold. First, it examines the status of CSR research from its beginning especially after 1970 to year 2008 in leading academic journals and reports to assess the focus areas of research on CSR so far. Second, it analyzes the research paradigms adopted in these research articles using the Operations Research Paradigm framework. Third, it compares and contrasts various kinds of research articles, methodologies, and research designs used in various researches in literature. Finally, it uncovers the implications of this study and directions for future research.     

Supply-side investments: An international analysis of the return and risk relationship in the Travel & Leisure sector

This study investigates supply-side investments in the tourism sector, analysing the return and risk relationship of investments in tourism across several countries. The performance of tourism sector companies listed on the stock exchange, for the top one dozen countries according to the World Economic Forum (WEF) tourism rankings, is investigated by region, across these countries and within each country by comparison to other sectors. Several metrics are used to compare the risk-adjusted returns, over a 15-year period ending March 2007 and sub-periods to check the persistence of performance over time. The results present a strikingly different ranking than those of the WEF. The implications for the flow of investment funds are of importance in a global capital market. Money will flow to those investments with the highest expected returns for a given risk level and this has consequential impacts for economic growth and employment in the tourism sector.     

Time-varying persistence in US inflation

The persistence property of inflation is an important issue not only for economists, but especially for central banks, given that the degree of inflation persistence determines the extent to which central banks can control inflation. Further, not only is it the level of inflation persistence that is important in economic analyses, but also the question of whether the persistence varies over time, for instance, across business cycle phases, is equally pertinent, since assuming constant persistence across states of the economy is sure to lead to misguided policy decisions. Against this backdrop, we extend the literature on long-memory models of inflation persistence for the US economy over the monthly period of 1920:1–2014:5, by developing an autoregressive fractionally integrated moving-average-generalized autoregressive conditional heteroskedastic model with a time-varying memory coefficient which varies across expansions and recessions. In sum, we find that inflation persistence does vary across recessions and expansions, with it being significantly higher in the former than in the latter. As an aside, we also show that persistence of inflation volatility is higher during expansions than in recessions. Understandably, our results have important policy implications.     

Major bleeding risk and healthcare economic outcomes of non-valvular atrial fibrillation patients newly-initiated with oral anticoagulant therapy in the real-world setting

Aims: This study compared the risk for major bleeding (MB) and healthcare economic outcomes of patients with non-valvular atrial fibrillation (NVAF) after initiating treatment with apixaban vs rivaroxaban, dabigatran, or warfarin.

Methods: NVAF patients who initiated apixaban, rivaroxaban, dabigatran, or warfarin were identified from the IMS Pharmetrics Plus database (January 1, 2013–September 30, 2015). Propensity score matching (PSM) was used to balance differences in patient characteristics between study cohorts: patients treated with apixaban vs rivaroxaban, apixaban vs dabigatran, and apixaban vs warfarin. Risk of hospitalization and healthcare costs (all-cause and MB-related) were compared between matched cohorts during the follow-up.

Results: During the follow-up, risks for all-cause (hazard ratio [HR]?=?1.44, 95% confidence interval [CI]?=?1.2–1.7) and MB-related (HR?=?1.57, 95% CI?=?1.0–2.4) hospitalizations were significantly greater for patients treated with rivaroxaban vs apixaban. Adjusted total all-cause healthcare costs were significantly lower for patients treated with apixaban vs rivaroxaban ($3,950 vs $4,333 per patient per month [PPPM], p?=?.002) and MB-related medical costs were not statistically significantly different ($100 vs $233 PPPM, p?=?.096). Risk for all-cause hospitalization (HR?=?1.98, 95% CI?=?1.6–2.4) was significantly greater for patients treated with dabigatran vs apixaban, although total all-cause healthcare costs were not statistically different. Risks for all-cause (HR?=?2.22, 95% CI?=?1.9–2.5) and MB-related (HR?=?2.05, 95% CI?=?1.4–3.0) hospitalizations were significantly greater for patients treated with warfarin vs apixaban. Total all-cause healthcare costs ($3,919 vs $4,177 PPPM, p?=?.025) and MB-related medical costs ($96 vs $212 PPPM, p?=?.026) were significantly lower for patients treated with apixaban vs warfarin.

Limitations: This retrospective database analysis does not establish causation.

Conclusions: In the real-world setting, compared with rivaroxaban and warfarin, apixaban is associated with reduced risk of hospitalization and lower healthcare costs. Compared with dabigatran, apixaban is associated with lower risk of hospitalizations.     

Was the recent downturn in US real GDP predictable?

This article uses a small set of variables – real GDP, the inflation rate and the short-term interest rate – and a rich set of models – atheoretical (time series) and theoretical (structural), linear and nonlinear, as well as classical and Bayesian models – to consider whether we could have predicted the recent downturn of the US real GDP. Comparing the performance of the models to the benchmark random-walk model by root mean-square errors, the two structural (theoretical) models, especially the nonlinear model, perform well on average across all forecast horizons in our ex post, out-of-sample forecasts, although at specific forecast horizons certain nonlinear atheoretical models perform the best. The nonlinear theoretical model also dominates in our ex ante, out-of-sample forecast of the Great Recession, suggesting that developing forward-looking, microfounded, nonlinear, dynamic stochastic general equilibrium models of the economy may prove crucial in forecasting turning points.     

Forecasting US real house price returns over 1831–2013: evidence from copula models

Given the existence of nonnormality and nonlinearity in the data generating process of real house price returns over the period of 1831–2013, this article compares the ability of various univariate copula models, relative to standard benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1874–2013, based on an in-sample of 1831–1873. Overall, our results provide overwhelming evidence in favour of the copula models (Normal, Student’s t, Clayton, Frank, Gumbel, Joe and Ali-Mikhail-Huq) relative to linear benchmarks, and especially for the Student’s t-copula, which outperforms all other models both in terms of in-sample and out-of-sample predictability results. Our results highlight the importance of accounting for nonnormality and nonlinearity in the data generating process of real house price returns for the US economy for nearly two centuries of data.     

Stock market interdependence between Australia and its trading partners: does trade intensity matter?

We investigate the extent and manner of stock market interdependence between Australia and its trading partners and examine whether this is affected by trade intensity. Based on trade intensity, we classify Australia’s trading partners into major, medium and minor partners. We hypothesize that markets with greater (lower) trade intensity will be more (less) interdependent with Australia. We perform correlation (unconditional and conditional) analyses between Australia and its trading partners. Our results indicate that most of the markets that are highly correlated with Australia are its major trading partners. We conduct panel regression analysis to investigate whether trade intensity has any impact on the stock market correlations between Australia and its trading partners. The results show that trade intensity significantly and positively affect the correlations of Australia with its major trading partners. Thus, the results confirm our hypothesis that trade intensity drives stock market interdependence between Australia and its trading partners.