Measuring the Economic Significance of Structural Exchange Rate Models

This paper examines both the in-sample and out-of-sample performance of three monetary fundamental models of exchange rates and compares their out-of-sample performance to that of a simple Random Walk model. Using a data-set consisting of five currencies at monthly frequency over the period January 1980 to December 2009 and a battery of newly developed performance measures, the paper shows that monetary models do better (in-sample and out-of-sample forecasting) than a simple Random Walk model.

Domestic Violence and Football in Glasgow: Are Reference Points Relevant?

Much research suggests that sporting events can trigger domestic violence with recent evidence suggesting that pre-match expectations (which can be interpreted as reference points) play an especially important role in this relationship. In particular, unexpectedly disappointing results have been associated with large increases in domestic violence. This paper contributes to this literature using a new data set containing every domestic violence incident in Glasgow over a period of more than eight years. We find that Old Firm matches, where Glasgow rivals Celtic and Rangers play, are associated with large increases in domestic violence (regardless of the timing or the outcome of the match). Non-Old Firm matches tend to have little impact on domestic violence. Furthermore, we fi nd little evidence for the importance of reference points. Matches with disappointing outcomes, relative to pre-match expectations, are found to be associated with unusual increases in domestic violence only in a very limited set of matches.

Domestic Violence and Football in Glasgow: Are Reference Points Relevant?

Much research suggests that sporting events can trigger domestic violence with recent evidence suggesting that pre-match expectations (which can be interpreted as reference points) play an especially important role in this relationship. In particular, unexpectedly disappointing results have been associated with large increases in domestic violence. This paper contributes to this literature using a new data set containing every domestic violence incident in Glasgow over a period of more than eight years. We find that Old Firm matches, where Glasgow rivals Celtic and Rangers play, are associated with large increases in domestic violence (regardless of the timing or the outcome of the match). Non-Old Firm matches tend to have little impact on domestic violence. Furthermore, we find little evidence for the importance of reference points. Matches with disappointing outcomes, relative to pre-match expectations, are found to be associated with unusual increases in domestic violence only in a very limited set of matches.

Using VARs and TVP-VARs with Many Macroeconomic Variables

This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.

The added value from a general equilibrium analyses of increased efficiency in household energy use

The aim of the paper is to identify the added value from using general equilibrium techniques to consider the economy-wide impacts of increased efficiency in household energy use. We take as an illustrative case study the effect of a 5% improvement in household energy efficiency on the UK economy. This impact is measured through simulations that use models that have increasing degrees of endogeneity but are calibrated on a common data set. That is to say, we calculate rebound effects for models that progress from the most basic partial equilibrium approach to a fully specified general equilibrium treatment. The size of the rebound effect on total energy use depends upon: the elasticity of substitution of energy in household consumption; the energy intensity of the different elements of household consumption demand; and the impact of changes in income, economic activity and relative prices. A general equilibrium model is required to capture these final three impacts.

An Empirical Examination of the R&D Boundaries of the Firm - A Problem-Solving Perspective

We consider, both theoretically and empirically, how different organization modes are aligned to govern the efficient solving of technological problems. The data set is a sample from the Chinese consumer electronics industry. Following mainly the problem solving perspective (PSP) within the knowledge based view (KBV), we develop and test several PSP and KBV hypotheses, in conjunction with competing transaction cost economics (TCE) alternatives, in an examination of the determinants of the R&D organization mode. The results show that a firm’s existing knowledge base is the single most important explanatory variable. Problem complexity and decomposability are also found to be important, consistent with the theoretical predictions of the PSP, but it is suggested that these two dimensions need to be treated as separate variables. TCE hypotheses also receive some support, but the estimation results seem more supportive of the PSP and the KBV than the TCE.

Still in the Era of Area Studies? Political-Scientific Perspectives on European Competition Policy in the 2000s

This note reviews the political-scientific literature on European competition policy (ECP) in the 2000s. Based on a data set extracted from four well-known journals, and using an upfront methodology and explicit criteria, it analyzes the literature both quantitatively and qualitatively. On the quantitative side, it shows that, although a few sub-policy areas are still neglected, ECP is not the under-researched policy it used to be. On the qualitative side, the literature has greatly improved since the 1990s: Almost all articles now present a clear research question, and most advance specific theoretical claims/hypotheses. Yet, improvements can be made on research design, statistical testing, and, above all, state-of-the-art theorizing (e.g. in the game-theoretical treatment of delegation problems). Indeed, it is paradoxical that ECP specialists do not pay more attention to theoretical questions which are so central to the actual policy area they study.

Análisis y sintonización de aplicaciones paralelas/distribuidas de bioinformática: caso de estudio mpiBLAST

En termes de temps d'execució i ús de dades, les aplicacions paral·leles/distribuïdes poden tenir execucions variables, fins i tot quan s'empra el mateix conjunt de dades d'entrada. Existeixen certs aspectes de rendiment relacionats amb l'entorn que poden afectar dinàmicament el comportament de l'aplicació, tals com: la capacitat de la memòria, latència de la xarxa, el nombre de nodes, l'heterogeneïtat dels nodes, entre d'altres. És important considerar que l'aplicació pot executar-se en diferents configuracions de maquinari i el desenvolupador d'aplicacions no port garantir que els ajustaments de rendiment per a un sistema en particular continuïn essent vàlids per a d'altres configuracions. L'anàlisi dinàmica de les aplicacions ha demostrat ser el millor enfocament per a l'anàlisi del rendiment per dues raons principals. En primer lloc, ofereix una solució molt còmoda des del punt de vista dels desenvolupadors mentre que aquests dissenyen i evaluen les seves aplicacions paral·leles. En segon lloc, perquè s'adapta millor a l'aplicació durant l'execució. Aquest enfocament no requereix la intervenció de desenvolupadors o fins i tot l'accés al codi font de l'aplicació. S'analitza l'aplicació en temps real d'execució i es considra i analitza la recerca dels possibles colls d'ampolla i optimitzacions. Per a optimitzar l'execució de l'aplicació bioinformàtica mpiBLAST, vam analitzar el seu comportament per a identificar els paràmetres que intervenen en el rendiment d'ella, com ara: l'ús de la memòria, l'ús de la xarxa, patrons d'E/S, el sistema de fitxers emprat, l'arquitectura del processador, la grandària de la base de dades biològica, la grandària de la seqüència de consulta, la distribució de les seqüències dintre d'elles, el nombre de fragments de la base de dades i/o la granularitat dels treballs assignats a cada procés. El nostre objectiu és determinar quins d'aquests paràmetres tenen major impacte en el rendiment de les aplicacions i com ajustar-los dinàmicament per a millorar el rendiment de l'aplicació. Analitzant el rendiment de l'aplicació mpiBLAST hem trobat un conjunt de dades que identifiquen cert nivell de serial·lització dintre l'execució. Reconeixent l'impacte de la caracterització de les seqüències dintre de les diferents bases de dades i una relació entre la capacitat dels workers i la granularitat de la càrrega de treball actual, aquestes podrien ser sintonitzades dinàmicament. Altres millores també inclouen optimitzacions relacionades amb el sistema de fitxers paral·lel i la possibilitat d'execució en múltiples multinucli. La grandària de gra de treball està influenciat per factors com el tipus de base de dades, la grandària de la base de dades, i la relació entre grandària de la càrrega de treball i la capacitat dels treballadors.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation - intramural and external R&D— on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140 Keywords: Innovation sources, R&D, Productivity, Quantile Regression

The Global Diffusion of Regulatory Agencies: Channels of Transfer and Stages of Diffusion

The autonomous regulatory agency has recently become the ‘appropriate model’ of governance across countries and sectors. The dynamics of this process is captured in our data set, which covers the creation of agencies in 48 countries and 16 sectors since the 1920s. Adopting a diffusion approach to explain this broad process of institutional change, we explore the role of countries and sectors as sources of institutional transfer at different stages of the diffusion process. We demonstrate how the restructuring of national bureaucracies unfolds via four different channels of institutional transfer. Our results challenge theoretical approaches that overemphasize the national dimension in global diffusion and are insensitive to the stages of the diffusion process. Further advance in study of diffusion depends, we assert, on the ability to apply both cross-sectoral and cross-national analysis to the same research design and to incorporate channels of transfer with different causal mechanisms for different stages of the diffusion process.

An Introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions

We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

A critical analysis of dimensions and curve fitting practice in economics

When dealing with sustainability we are concerned with the biophysical as well as the monetary aspects of economic and ecological interactions. This multidimensional approach requires that special attention is given to dimensional issues in relation to curve fitting practice in economics. Unfortunately, many empirical and theoretical studies in economics, as well as in ecological economics, apply dimensional numbers in exponential or logarithmic functions. We show that it is an analytical error to put a dimensional unit x into exponential functions ( a x ) and logarithmic functions ( x a log ). Secondly, we investigate the conditions of data sets under which a particular logarithmic specification is superior to the usual regression specification. This analysis shows that logarithmic specification superiority in terms of least square norm is heavily dependent on the available data set. The last section deals with economists’ “curve fitting fetishism”. We propose that a distinction be made between curve fitting over past observations and the development of a theoretical or empirical law capable of maintaining its fitting power for any future observations. Finally we conclude this paper with several epistemological issues in relation to dimensions and curve fitting practice in economics

Employment effects of service offshoring: evidence from matched firms

This paper studies the effects of service offshoring on the level and skill composition of domestic employment, using a rich data set of Italian firms and propensity score matching techniques. The results show that service offshoring has no effect on the level of employment but changes its composition in favor of high skilled workers.

Diagnostic accuracy of G-CSF, IL-8, and IL-1ra in critically ill children with suspected infection.

OBJECTIVE: To elucidate the diagnostic accuracy of granulocyte colony-stimulating factor (G-CSF), interleukin-8 (IL-8), and interleukin-1 receptor antagonist (IL-1ra) in identifying patients with sepsis among critically ill pediatric patients with suspected infection. DESIGN AND SETTING: Nested case-control study in a multidisciplinary neonatal and pediatric intensive care unit (PICU) PATIENTS: PICU patients during a 12-month period with suspected infection, and plasma available from the time of clinical suspicion (254 episodes, 190 patients). MEASUREMENTS AND RESULTS: Plasma levels of G-CSF, IL-8, and IL-1ra. Episodes classified on the basis of clinical and bacteriological findings into: culture-confirmed sepsis, probable sepsis, localized infection, viral infection, and no infection. Plasma levels were significantly higher in episodes of culture-confirmed sepsis than in episodes with ruled-out infection. The area under the receiver operating characteristic curve was higher for IL-8 and G-CSF than for IL-1ra. Combining IL-8 and G-CSF improved the diagnostic performance, particularly as to the detection of Gram-negative sepsis. Sensitivity was low (<50%) in detecting Staphylococcus epidermidis bacteremia or localized infections. CONCLUSIONS: In this heterogeneous population of critically ill children with suspected infection, a model combining plasma levels of IL-8 and G-CSF identified patients with sepsis. Negative results do not rule out S. epidermidis bacteremia or locally confined infectious processes. The model requires validation in an independent data-set.

The multipoint Morisita index for the analysis of spatial patterns

In many fields, the spatial clustering of sampled data points has many consequences. Therefore, several indices have been proposed to assess the level of clustering affecting datasets (e.g. the Morisita index, Ripley's Kfunction and Rényi's generalized entropy). The classical Morisita index measures how many times it is more likely to select two measurement points from the same quadrats (the data set is covered by a regular grid of changing size) than it would be in the case of a random distribution generated from a Poisson process. The multipoint version (k-Morisita) takes into account k points with k >= 2. The present research deals with a new development of the k-Morisita index for (1) monitoring network characterization and for (2) detection of patterns in monitored phenomena. From a theoretical perspective, a connection between the k-Morisita index and multifractality has also been found and highlighted on a mathematical multifractal set.