Measuring Value‐at‐Risk in Project Finance Transactions

Despite the remarkable importance of project finance in international financial markets, no quantitative models to measure and quantify the risk associated with a deal for the project's lenders have been developed yet. The topic has recently become crucial, since the New Basle Capital Accord gives banks a choice of whether to adopt simpler (but possibly higher) standard capital requirements or to develop internal rating models for project finance transactions. The paper proposes how Monte Carlo simulations may be used to derive a Value‐at‐Risk estimate for project finance deals and discusses the critical issues that must be considered when developing such a model.     

Foreign players,team production,and technical efficiency: Evidence from European soccer

As on-field success is nowadays the main objective of European soccer clubs, good management needs to extract the highest sport success from the squad talent at hand. Because teams differ in their quality, performance needs to be compared with the best practice of comparable units. One remarkable source of heterogeneity across teams is the squad composition, which can produce gains from diversity together with communication costs. The paper studies the efficiency in sporting performance of soccer teams, paying attention to how the number of foreign players relates to productive inefficiency. Using data for 146 teams in the top 5 European leagues during 10 seasons, we estimate a double heteroskedastic True Random Effects Stochastic Frontier team production function. We find that (i) the number of passes, ball recoveries, and shots from the penalty area improve team efficiency, and (ii) a higher number of foreign players increase inefficiency. Our findings suggest that gains from squad diversity might be offset by communication costs.     

Value versus Volume in the Catch of the Spanish South‐Atlantic Trawl Fishery

An understanding of the link between the level of inputs and resultant level of outputs is of considerable importance when trying to manage fisheries through input controls. To this end, studies of several fisheries have been undertaken to examine this relationship through the estimation of production functions and frontiers, using either catch weight or revenue as the dependent variable. The choice of the appropriate output variable to use in the analysis will depend on the objectives of the fishermen. Maximisation of catch weight is often proposed as an objective of fishermen rather than maximisation of profits. In this paper, the technical efficiency scores of vessels operating in the Spanish south‐Atlantic trawl fishery are estimated using the stochastic production frontier approach. The production frontiers are estimated with both the weight and the value of the catch as the dependent variable. The results of the analysis suggest that fishermen adopt a range of strategies but relatively few aim to maximise catch weight only. The differences in strategies may reflect heterogeneous attitudes towards risk, with more risk averse fishermen aiming to trade‐off some potential catch value for a more certain quantity of catch.     

Knowledge spillovers in US patents: A dynamic patent intensity model with secret common innovation factors

During the past two decades, innovations protected by patents have played a key role in business strategies. This fact enhanced studies of the determinants of patents and the impact of patents on innovation and competitive advantage. Sustaining competitive advantages is as important as creating them. Patents help sustaining competitive advantages by increasing the production cost of competitors, by signaling a better quality of products and by serving as barriers to entry. If patents are rewards for innovation, more R&D should be reflected in more patent applications but this is not the end of the story. There is empirical evidence showing that patents through time are becoming easier to get and more valuable to the firm due to increasing damage awards from infringers. These facts question the constant and static nature of the relationship between R&D and patents. Furthermore, innovation creates important knowledge spillovers due to its imperfect appropriability. Our paper investigates these dynamic effects using US patent data from 1979 to 2000 with alternative model specifications for patent counts. We introduce a general dynamic count panel data model with dynamic observable and unobservable spillovers, which encompasses previous models, is able to control for the endogeneity of R&D and therefore can be consistently estimated by maximum likelihood. Apart from allowing for firm specific fixed and random effects, we introduce a common unobserved component, or secret stock of knowledge, that affects differently the propensity to patent of each firm across sectors due to their different absorptive capacity.     

Modelling the volatility of commodities prices using a stochastic volatility model with random level shifts

We use the approach of Qu and Perron (Econom J 16(3):309–339, 2013) for the modeling and inference of volatility of a set of commodity prices in the presence of random level shifts of unknown timing, magnitude and frequency. Our approach contributes to the study of commodities in several aspects. First, we test for the presence of a genuine long-memory process in the volatility of commodities. Second, we determine that the random level shifts are certainly the main source of variation in the commodity price volatility. Finally, we estimate the volatility and its components as latent variables, thereby making it possible to evaluate their level of correlation with macroeconomic variables in small open economies such as Latin-American countries where the dependence on commodity price volatility is high. We use six commodity series: agriculture, livestock, gold, oil, industrial metals and a general commodity index. All series cover the period from January 1983 until December 2013 in daily frequency. The results show that although the occurrence of a level shift is rare, (about once every 1.5 or 1.8 years), this component clearly contributes most to the variation in the volatility. Furthermore, isolating the level shift component from the overall volatility indicates a strong relationship of this component with a set of business cycle indicators of several Latin American countries.     

Characterization of bidding behavior in multi-unit auctions

This paper considers a very general class of single or multi-unit auctions of indivisible objects. The model allows for interdependent values, multidiminensional types and any attitude towards risk. Assuming only optimal behavior, we prove that each bid is chosen in order to equalize the marginal benefit to the marginal cost of bidding. This generalizes many existing results in the literature. We use this characterization to obtain sufficient conditions for truthful bidding, monotonic best reply strategies and identification results for multi-unit auctions.     

The influence of perceived risk on Internet shopping behavior: a multidimensional perspective

The present study analyzes the influence that perceived risk in online shopping has on the process of e‐commerce adoption by end consumers. With this aim, the Technology Acceptance Model is taken as a reference framework, proposing an Extended E‐Commerce Acceptance Model that includes the diverse constructs of perceived risk: financial, performance, social, time, psychological and privacy. Empirical evidence is obtained from two samples, one is composed by Internet users with no experience in web shopping and the other is formed by online buyers. The results obtained confirm that the intention to shop through the Internet is positively influenced by general attitude toward the system and negatively influenced by the risk associated with the Web. Regarding the importance of the risk dimensions considered in the study, the economic and performance facets are the ones that have a greater influence on e‐commerce adoption, while social and time dimensions are the less relevant.