Energy availability from livestock and agricultural productivity in Europe, 1815–1913: a new comparison

This article explores the proposition that a reason for high agricultural productivity in the early nineteenth century was relatively high energy availability from draught animals. The article is based on the collection of extensive new data indicating different trends in draught power availability and the efficiency of its use in different countries of Europe. This article shows that the proposition does not hold, and demonstrates that, although towards the end of the nineteenth century England had relatively high numbers of draught animals per agricultural worker, it also had low number of workers and animals per hectare, indicating the high efficiency of muscle power, rather than an abundance of such power. The higher efficiency was related to a specialization on less labour-intensive farming and a preference for horses over oxen.     

Mandatory versus voluntary labelling of genetically modified food: evidence from an economic experiment

Opponents of the voluntary labelling scheme for genetically modified (GM) food products often argue that consumers have the “right to know” and therefore advocate mandatory labelling. In this article, we argue against this line of reasoning. Using experimental auctions we show that the quality of the signal generated by a mandatory labelling scheme is affected by the number of labels in the market. If there are two labels, one for GM products and one for non‐GM products, mandatory and voluntary labelling schemes generate a similar degree of uncertainty about the quality of products that do not carry a label.     

INCOME POVERTY AND MULTIDIMENSIONAL DEPRIVATION: LESSONS FROM CROSS‐REGIONAL ANALYSIS

The study of multidimensional deprivation has become one of the most relevant lines of research in the analysis of low‐income households. The search for significant relationships between multidimensional deprivation and income poverty has been a central issue and most empirical studies have found a very weak link. This paper aims at examining the possibility of an aggregation bias in national‐level studies, which could conceal disparities between regions. As regional differences and decentralization processes stand out in Spain as compared to other OECD countries, we focus the analysis on this country. Latent class models are used to define deprivation indices using the Spanish EU‐SILC. The results seem to show that the absence of significant relationships between both phenomena still holds at a regional level. The decomposition methods used in the paper show that it might be due to some regional singularities in some determining factors of income and multidimensional poverty.     

Technology management and collaboration profile: virtual companies and industrial platforms in the high‐tech biotechnology industries

In this paper we discuss collaboration in the area of technology management. We propose the concept of collaboration profile to describe various forms of networks along key differentiating characteristics. The collaboration profile is then applied using two examples to illustrate different forms of collaboration in the biotechnology industries, the ‘virtual company’ and the ‘industrial platform’. Based on interviews with members of a virtual company as well as members of industrial platforms and drawing conclusions from theoretical insights, the advantages and disadvantages of these forms and their suitability for different stages of the technology life cycle will be discussed. Specifically, we address the following questions: What kind of collaboration profile applies to virtual companies and industrial platforms? How does the suitability of collaboration forms vary with the stage of technology development? Furthermore, we demonstrate the usefulness of the collaboration profile for analysing features and potential problems of collaborations by describing two examples. Focusing on the key characteristics of a collaboration helps to check the appropriateness of the collaboration form and to identify and manage respective problems.     

Score-driven copula models for portfolios of two risky assets

ABSTRACT

The precise measurement of the association between asset returns is important for financial investors and risk managers. In this paper, we focus on a recent class of association models: Dynamic Conditional Score (DCS) copula models. Our contributions are the following: (i) We compare the statistical performance of several DCS copulas for several portfolios. We study the Clayton, rotated Clayton, Frank, Gaussian, Gumbel, rotated Gumbel, Plackett and Student's t copulas. We find that the DCS model with the Student's t copula is the most parsimonious model. (ii) We demonstrate that the copula score function discounts extreme observations. (iii) We jointly estimate the marginal distributions and the copula, by using the Maximum Likelihood method. We use DCS models for mean, volatility and association of asset returns. (iv) We estimate robust DCS copula models, for which the probability of a zero return observation is not necessarily zero. (v) We compare different patterns of association in different regions of the distribution for different DCS copulas, by using density contour plots and Monte Carlo (MC) experiments. (vi) We undertake a portfolio performance study with the estimation and backtesting of MC Value-at-Risk for the DCS model with the Student's t copula.