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.     

Brand heritage as a temporal perception: conceptualisation,measure and consequences

ABSTRACT

This research looks at the concept of brand heritage as a branded representation of the past and its influence on cognitive and affective responses. Although numerous items of research mention brand heritage, the subject still lacks conceptual clarity. This paper aims to address this gap and to build a scale measuring its perception by consumers. The literature review leads to a conceptualisation of brand heritage as the perception of a brand’s temporal management. Then, one qualitative and three quantitative studies facilitate the emergence and validate a three-dimensional scale of perceived brand heritage. A model demonstrates how brand heritage enhances brand credibility and personal nostalgia. This paper contributes to the apprehension of change and continuity in brand management, with potential extensions to other disciplines.     

Consumers’ Appreciation of Regional Certification Labels: A Pan‐European Study

Successful regional products, such as Florida oranges, Idaho potatoes and Parma ham, often have to compete against products passing themselves off as the authentic product using the exact same name. This unfair competition misleads consumers, discourages small‐ and medium‐sized enterprises (SMEs) from marketing products based on their region of origin, and may end up hurting rural economies. To protect consumers, and support SMEs and rural economies, many countries around the world have introduced regulations enabling SMEs to legally protect the names of their regional products. The success of these regulations largely depends on consumers’ appreciation of regional certification labels that inform consumers that the name of the regional product is protected and that it denotes the authentic product. To gain an understanding about consumers’ appreciation of regional certification labels, this paper investigates consumers’ image of these labels and proposes a model that relates this image to consumers’ willingness to buy and pay for protected regional products. The model is tested based on Regulation No. 2081/92 that was introduced by the EEC allowing European SMEs to protect their regional products and market their products with a protected‐designation‐of‐origin (PDO) label. Structural equation modelling results suggest that consumers’ image of regional certification labels consists of a quality warranty dimension and an economic support dimension, which positively relate to consumers’ willingness to buy and pay for the protected regional product. Protecting regional products and marketing them with regional certification labels may be beneficial for SMEs producing and marketing regional products. Policy and managerial implications are discussed.     

Disruption management in distributed enterprises: A multi-agent modelling and simulation of cooperative recovery behaviours

Disruption management in industrial areas consists in dealing with unanticipated events that get the plans deviate from their intended course. The solution results from the design and the maintenance of an operating mode ensuring a relevant deployment of individual recovery behaviours.The paper proposes an approach to minimize the impact of disrupting events on the whole system. It is based on an analysis of disrupting events and the characterization of the recovery process, and on a cooperative repair method for distributed industrial systems. This method is based on a cooperative distributed problem solving approach supported by a multi-agent system framework.     

Process System Modelling of Production Technology Alternatives using Input– Output Tables with Sector Specific Units

Input–output analysis is usually based on tables of accounts expressed in uniform monetary or physical units. However, from a process system modelling perspective, tables of accounts in sector specific units may be more useful for evaluating the effectiveness of new production technologies on reducing pollutant emissions. Using the sector specific unit conceptualization of an IO table, one can consider the effect of changes in direct input coefficients for a particular sector on the complete set of total input coefficients independently from the other direct input coefficients. A process system modelling based method for calculating the total industrial outputs from a new technology matrix together with the new relative prices for each sector output is presented. The method is then used to study the effect of technology changes in the steel making industry in Liaoning Province, China on prices and pollutant emissions.     

EMPIRICAL ESTIMATION OF NON-LINEAR INPUT–OUTPUT MODELS: AN ENTROPY ECONOMETRICS APPROACH

Despite theoretical advances, non-linear input–output models have been empirically applied only to a limited extent. This is mainly due to the fact that the number of parameters to be estimated is much higher than the number of available data points. Taking advantage of the recent proliferation of input–output databases and by applying an estimation strategy that relies on entropy econometrics, this paper suggests a way to estimate the parameters that characterize non-linear relationships between inputs and output. This non-linear modelling allows for considering time-specific input coefficients, instead of fixed ones. Several types of multipliers can be derived from this non-linear model, and the proposed generalized maximum entropy (GME) estimator allows estimating them from time series or cross-sectional datasets of input–output tables. The proposed GME technique is illustrated by means of an empirical application that estimates the parameters that characterize a non-linear input–output model for the Spanish economy over the period 1995–2011.     

Recent topics in Applied Financial Economics

This note discusses topics concerning recent evolutions in financial economics research. It focuses in particular on the progress of quantitative finance and applied economics in the context of the global financial crisis. To this end, I examine various important topics in Economics and Finance and discuss several empirical studies on the statistical properties of macroeconomic and financial data through the application of different econometric methodologies. I analyse their empirical findings and discuss their conclusions.     

中国妇女人工流产影响因素的多水平分析

使用多水平模型对1992—1997年中国妇女人工流产行为进行了分析,目的是考察和检验宏观（省级水平）和微观（个人水平）因素对中国妇女分孕次人工流产概率的独立影响及其显著性。多水平模型在模拟具有层次结构性的数据上要优于传统的回归模型,在社会科学领域正在被越来越广泛地应用。多水平模型结果显示:无论是宏观因素还是微观因素,都对妇女人工流产有独立而显著的影响,微观影响在所有孕次都是显著的,而宏观影响则取决于孕次。同时宏观因素对微观上的人工流产社会经济差异也具有显著影响,并与孕次有很大关系。本文的多水平模型有助于全面认识我国妇女人工流产的影响因素。     

From fork to farm: Impacts of more sustainable diets in the EU-27 on the agricultural sector

The implications of dietary changes for the environment and for human health are well documented, but the impacts on the agricultural sector are less well researched. We fill this gap by specifying scenarios in which European consumers' diets approximate the EAT-Lancet dietary recommendations to varying degrees and estimate the effects on agricultural production, incomes and emissions using an agro-economic modelling framework. The combination of different models allows for a detailed assessment of consequences for the agricultural sector from the global through European NUTS2 level to the farm level at different time scales. Shifting European consumption towards the EAT-Lancet recommendations leads to decreasing production of animal-based products, while production of fruits and vegetables increases sharply. The results indicate that the agricultural sector could benefit from a dietary shift, though the results are mixed at country, regional and farm levels. In particular, countries and regions that are highly specialised in animal farming are likely to lose income—at least in the short run—while regions with higher shares of vegetable and fruit farms can expect income gains. In Germany, pig and poultry farms may experience losses of up to 34% of their income, whereas farms with a high share of vegetables could gain more than 30% in income. Our results have implications for the policies to assist these extensive structural adjustments in response to widespread dietary changes.     

Modelling the housing market in OECD countries

Recent episodes of housing bubbles, which occurred in several economies after the burst of the United States housing market, suggest studying the evolution of housing prices from a global perspective. We utilise a theoretical model for the purposes of this contribution, which identifies the main drivers of housing price appreciation, such as, for example, income, residential investment, financial elements, fiscal policy and demographics. In a second stage of our analysis, we test our theoretical hypothesis by means of a sample of 18 OECD countries from 1970 to 2011. We employ the vector error correction econometric technique in terms of our empirical analysis, which permits us to model the long-run equilibrium relationship and the short-run dynamics, which also helps to account for endogeneity and reverse causality problems.