Key Determinants of the Stage of Internationalisation of Australian Wineries

A four stage measure capturing, awareness, interest, trial and adoption is employed to identify the key determinants of the stage of internationalisation of Australian wineries. Drawing from data from 292 wineries and using structural equation modelling techniques, this paper analyses the effects of a multitude of factors previously hypothesised to influence the stage of internationalisation. The results indicate that while these wineries exhibit characteristics described in the extant literature, significant differences remain. The paper concludes by discussing the limitations and areas for further research.     

Recycling and extending product-life: an evolutionary modelling

This paper presents a model-based analysis of firms’ economic incentives to extend product life and market recyclable products. We address this problem by developing an evolutionary simulation model to describe the behavior of business firms as interacting with consumers and recyclers. Market structure, business firms’ R&D strategies and consumers’ preferences are found to have an important influence here. The simulation results show that improvement in recycling is necessary but not sufficient to solve the issue of increase in waste. Recycling will need to be backed up with an extension in product-life to face such an unwanted increase. Adopting such a strategy could be positive for firms and for the environment because it could lead to high economic performance, both in terms of profits and market share, and to high environmental performance, both in terms of product recyclability and product lifetime. Our results suggest introducing regulation policies aimed at encouraging firms to invest in developing green products, i.e. those which are easily recyclable and which have a long lifetime, and getting consumers to buy them. It would also seem crucial to lend support to innovation outlay for such firms and to favor their seeking to improve product performance.

Promoting cost efficiency and uniformity in parcel delivery centre locations and service areas: a GIS-based analysis

This paper provides a systematic framework to determine local delivery centre (LDC) locations and service areas to reduce delivery costs and balance the allocation of parcel delivery loads to promote sustainable LDC development. Based on a case study of a parcel distribution company in Korea, this study proposes two strategies for LDC service area delineation within each terminal service boundary that either minimises the total delivery time or balances the allocation of delivery loads. This research contributes to improving cost efficiency and balancing delivery load allocations in planning LDC locations and service areas that can potentially promote the long-term mutual sustainable development of parcel distribution companies and their local delivery counterparts.     

A bivariate Poisson count data model using conditional probabilities

The applied econometrics of bivariate count data predominantly focus on a bivariate Poisson density with a correlation structure that is very restrictive. The main limitation is that this bivariate distribution excludes zero and negative correlation. This paper introduces a new model which allows for a more flexible correlation structure. To this end the joint density is decomposed by means of the multiplication rule in marginal and conditional densities. Simulation experiments and an application of the model to recreational data are presented.     

Non-parametric estimation of historical volatility

Evolving volatility is a dominant feature observed in most financial time series and a key parameter used in option pricing and many other financial risk analyses. A number of methods for non-parametric scale estimation are reviewed and assessed with regard to the stylized features of financial time series. A new non-parametric procedure for estimating historical volatility is proposed based on local maximum likelihood estimation for the t-distribution. The performance of this procedure is assessed using simulated and real price data and is found to be the best among estimators we consider. We propose that it replaces the moving variance historical volatility estimator.     

Dependence calibration and portfolio fit with factor-based subordinators

The paper explores the properties of a class of multivariate Lévy processes used for asset returns. We focus on describing both linear and non-linear dependence in an economic sensible and empirically appropriate way. The processes are subordinated Brownian motions. The subordinator has a common and an idiosyncratic component, to reflect the properties of trade, which it represents. A calibration to a portfolio of 10 US stock indices returns over the period 2009–2013 shows that the hyperbolic specification has a very good fit to marginal distributions, to the overall correlation matrix and to the return distribution of both long-only and long-short random portfolios, which also incorporate non-linear dependence. Their tail behaviour is also well captured by the variance gamma specification. The main message is not only the goodness of fit, but also the flexibility in capturing dependence and the ease of calibration on large sets of returns.     

Correlation smile matching for collateralized debt obligation tranches with α-stable distributions and fitted Archimedean copula models

As an extension of the standard Gaussian copula model to price collateralized debt obligation (CDO) tranche swaps we present a generalization of a one-factor copula model based on stable distributions. For special parameter values these distributions coincide with Gaussian or Cauchy distributions, but changing the parameters allows a continuous deformation away from the Gaussian copula. All these factor copulas are embedded in a framework of stochastic correlations. We furthermore generalize the linear dependence in the usual factor approach to a more general Archimedean copula dependence between the individual trigger variable and the common latent factor. Our analysis is carried out on a non-homogeneous correlation structure of the underlying portfolio. CDO tranche market premia, even throughout the correlation crisis in May 2005, can be reproduced by certain models. From a numerical perspective, all these models are simple, since calculations can be reduced to one-dimensional numerical integrals.     

Crossing spatial analyses and livestock economics to understand deforestation processes in the Brazilian Amazon: the case of São Félix do Xingú in South Pará

The Amazon is the largest tropical forest area on Earth, and has been undergoing rapid deforestation for the last four decades. In the Brazilian Amazon, large‐scale pasture for cattle ranching and soybean production are the main land uses, leading to a yearly deforestation rate of 0.5%. These conversions are mostly located in frontier areas distributed along the so‐called “arc of deforestation”. Within this large zone, various land use change processes are interacting through several modes of land valuation and organisation. From several case studies in the State of Pará (Brazil), the current project aims at analysing how landscape dynamics are related to infrastructure development, ecological conditions, zoning policies and to the evolution and the organisation of the production, consumption and marketing chains of livestock products. This paper presents the results for one test site, the region of São Félix do Xingú, South of Pará This region is the focus of land speculation, cattle expansion, and deforestation. Road construction, investments in electrical energy, financial credit for cattle, and the land reform policies have all fuelled this process. All these factors make this region one of the most dynamic agricultural frontiers in the Brazilian Amazon. The main objective of the paper is to improve our understanding of deforestation processes by crossing spatial analyses and 1ivestock economics.studies, and to characterise the role and impact of various natural and anthropic factors in the location and development of the main types of farmers, and their policy implications.     

Quadratic Hawkes processes for financial prices

We introduce and establish the main properties of QHawkes (‘Quadratic’ Hawkes) models. QHawkes models generalize the Hawkes price models introduced in Bacry and Muzy [Quant. Finance, 2014, 14(7), 1147–1166], by allowing feedback effects in the jump intensity that are linear and quadratic in past returns. Our model exhibits two main properties that we believe are crucial in the modelling and the understanding of the volatility process: first, the model is time-reversal asymmetric, similar to financial markets whose time evolution has a preferred direction. Second, it generates a multiplicative, fat-tailed volatility process, that we characterize in detail in the case of exponentially decaying kernels, and which is linked to Pearson diffusions in the continuous limit. Several other interesting properties of QHawkes processes are discussed, in particular the fact that they can generate long memory without necessarily being at the critical point. A non-parametric fit of the QHawkes model on NYSE stock data shows that the off-diagonal component of the quadratic kernel indeed has a structure that standard Hawkes models fail to reproduce. We provide numerical simulations of our calibrated QHawkes model which is indeed seen to reproduce, with only a small amount of quadratic non-linearity, the correct magnitude of fat-tails and time reversal asymmetry seen in empirical time series.