Not all shadow banking is bad! Evidence from credit intermediation of non-financial Chinese firms

Review of Quantitative Finance and Accounting - Using data from 2009 to 2016 data, we investigate the relation between leverage and investment in listed firms in China against the backdrop of...     

Lasting impacts and perceived inequities: community reappraisal of the siting of a regional biosolids processing facility in rural Ontario

This paper presents a comparative study of the shift in community perceptions pre- and post-siting of a biosolids processing facility – the Organic Material Recovery Centre – in the rural Township of Southgate, Ontario. The study responds to the need for comparative studies examining residents’ perceptions of contested noxious facilities during acrimonious siting processes and later during facility operations. Interviews were conducted before and after the techno-industrial facility was sited to compare community perceptions of the proposed and operational facility, and further examine residents’ experiences with residual impacts and reflections on the siting process. Results reveal that once the facility began operations and residents had the opportunity to understand its operational mandate and directions, many residents seem to accept the facility as less threatening to well-being, quality of life and core values. Nonetheless, sustained community concerns shifted to invisible impacts and long-term uncertainty. Findings highlight lingering intra-community conflict between those supporting and those who remained concerned about negative impacts. As a result of the hostile community conflict, the local politics seems to have morphed into a ‘one-issue’ political scene, whereby all issues are divided along the lines of municipal councillors opinions of the facility These findings make methodological contributions with pre- and post-siting comparative qualitative research and contribute theoretically to our understanding of residents’ reappraisal of contested noxious techno-industrial facilities, show sustained divisive social impacts within the community, and call for meaningful consultation and increased participatory siting processes that accounts for the diversity of values and expectations during facility siting.     

Understanding Dutch visitors’ motivations to concentration camp memorials

This study examined the motivations to visit concentration camp memorial sites in the Netherlands. Nine hundred and seventy-five Dutch respondents participated in a panel survey. The data were analysed by means of an exploratory factor analysis, to yield underlying motivational factors. The findings revealed that potential visitors were motivated to visit Holocaust concentration camp memorial sites for “memory”, “gaining knowledge and awareness”, and “exclusivity”. We generalize the motivations from Dutch concentration camp memorial sites to a universal level and discuss the future stages to achieve a universally valid motivation scale for visits to concentration camp memorial sites.     

Extracting a common stochastic trend: Theory with some applications

This paper investigates the statistical properties of estimators of the parameters and unobserved series for state space models with integrated time series. In particular, we derive the full asymptotic results for maximum likelihood estimation using the Kalman filter for a prototypical class of such models—those with a single latent common stochastic trend. Indeed, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator and show that the conventional method of inference is valid for this class of models. The models we explicitly consider comprise a special–yet useful–class of models that may be employed to extract the common stochastic trend from multiple integrated time series. Such models can be very useful to obtain indices that represent fluctuations of various markets or common latent factors that affect a set of economic and financial variables simultaneously. Moreover, our derivation of the asymptotics of this class makes it clear that the asymptotic Gaussianity and the validity of the conventional inference for the maximum likelihood procedure extends to a larger class of more general state space models involving integrated time series. Finally, we demonstrate the utility of this class of models extracting a common stochastic trend from three sets of time series involving short- and long-term interest rates, stock return volatility and trading volume, and Dow Jones stock prices.     

The problem of the uninsured

The problem of the uninsured cannot be fully understood without considering the role of non-market alternatives to ‘market insurance’ called ‘self-insurance’ and ‘self-protection’ (SISP), including the public ‘health care safety-net’ system. We tackle the problem by formulating a ‘full-insurance’ paradigm that accounts for all four interacting insurance measures. We apply two versions of the full-insurance model to estimate, via calibrated simulations, the impacts of SISP on the fraction of uninsured, health spending, and health levels, and to assess how the mandated Affordable Care Act might affect these outcomes in comparison with the CBO projections in 2010. The results indicate that policy analyses which overlook the role of the real price of market insurance relative to the shadow prices of SISP in determining the decision to insure can grossly distort the capacity of mandated reforms like the ACA to insure the uninsured, contain overall health care costs, and improve health and welfare outcomes.     

Utopian community football? Sport,hope and belongingness in the lives of refugees and asylum seekers

Refugees and asylum seekers have become increasingly demonised as part of anti-migrant sentiment leading to social exclusion. Sport has been utilised as a tool for social cohesion though evidence as to its efficacy in such a task is limited. Based on a three-year research programme exploring the role of football in the lives of refugees and asylum seekers in the U.K., this paper examines the concept of belonging, provides evidence for the role of community-based sport in social development and concludes with a call for practitioners to maximise their belief in concrete utopian ideals without losing the inherent critical approach needed to positively develop the industry in which they work.     

Time-varying forecasts by variational approximation of sequential Bayesian inference

Methods developed for making time-varying forecasts in economic and financial analysis include (a) equal-weighted moving-window (or rolling) regression, (b) time-weighted (e.g. exponentially weighted) regression, (c) the Kalman filter (KF) and (d) adaptive Kalman filters. This paper developed a new method based on variational approximation of sequential Bayesian inference (VASB). Concepts and notions of the sequential Bayesian analysis and the variational approximation of an intractable posterior are simple and straightforward. Our VASB algorithm is not complicated and is easy to code. For a regression on multiple time-series, the regression coefficients, standard errors, prediction and residual error are time-varying and are estimated jointly at every time step. For a single time-series (e.g. price returns of an asset), its mean and variance are time-varying and are predicted jointly at every time step. The VASB algorithm performs better than the rolling and time-weighted statistics or regressions and the KF in terms of higher predictive power and stronger robustness. Derivations of the VASB algorithm are presented in the appendices.     

Using Aggregate Time Series Variables to Forecast Notices of Default

This paper emphasizes the economic variables and data used to model notices of default in California. Forecast models are notoriously complicated and require sophisticated software to run. Few businesses, particularly small enterprises, have the necessary resources to engage in large-scale model building. Datasets can be difficult and expensive to obtain and usually require significant analysis. The paper focuses on methodology to give the model a general appeal.     

Specialized Careers

An agent has different abilities in two types of tasks. These tasks are revealed over time through his performance. The agent initially decides whether to engage in only one task (specialize) or to take on any task that arises (be a generalist). This decision trades off the cost of being idle against staying available for relatively lucrative tasks. We compare specializing with acting as a generalist in an infinite‐horizon model and provide complete characterizations of efforts. We show how specializing acts as a means of committing to exert more effort. In a two‐period version of the model, this implies that positive costs for switching strategies, through license fees, for example, may be socially desirable.