Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks

Although it is commonly accepted that most macroeconomic variables are nonstationary, it is often difficult to identify the source of the non-stationarity. In particular, it is well-known that integrated and short memory models containing trending components that may display sudden changes in their parameters share some statistical properties that make their identification a hard task. The goal of this paper is to extend the classical testing framework for I(1) versus I(0)+ breaks by considering a a more general class of models under the null hypothesis: non-stationary fractionally integrated (FI) processes. A similar identification problem holds in this broader setting which is shown to be a relevant issue from both a statistical and an economic perspective. The proposed test is developed in the time domain and is very simple to compute. The asymptotic properties of the new technique are derived and it is shown by simulation that it is very well-behaved in finite samples. To illustrate the usefulness of the proposed technique, an application using inflation data is also provided.

Revisiting the size-R&D productivity relation: introducing the mediating role of decision-making style on the scale and quality of innovative output

We develop a mediation model in which firm size is proposed to affect the scale and quality of innovative output through the adoption of different decision styles during the R&D process. The aim of this study is to understand how the internal changes that firms undergo as they evolve from small to larger organizations affect R&D productivity. In so doing, we illuminate the underlying theoretical mechanism affecting two different dimensions of R&D productivity, namely the scale and quality of innovative output which have not received much attention in previous literature. Using longitudinal data of Spanish manufacturing firms we explore the validity of this mediation model. Our results show that as firms evolve in size, they increasingly emphasize analytical decision making, and consequently, large-sized firms aim for higher-quality innovations while small firms aim for a larger scale of innovative output.

Quantitative analysis of image factors in a cultural heritage tourist destination

The tourism consumer’s purchase decision process is, to a great extent, conditioned by the image the tourist has of the different destinations that make up his or her choice set. In a highly competitive international tourist market, those responsible for destinations’ promotion and development policies seek differentiation strategies so that they may position the destinations in the most suitable market segments for their product in order to improve their attractiveness to visitors and increase or consolidate the economic benefits that tourism activity generates in their territory. To this end, the main objective we set ourselves in this paper is the empirical analysis of the factors that determine the image formation of Tarragona city as a cultural heritage destination. Without a doubt, UNESCO’s declaration of Tarragona’s artistic and monumental legacies as World Heritage site in the year 2000 meant important international recognition of the quality of the cultural and patrimonial elements offered by the city to the visitors who choose it as a tourist destination. It also represents a strategic opportunity to boost the city’s promotion of tourism and its consolidation as a unique destination given its cultural and patrimonial characteristics. Our work is based on the use of structured and unstructured techniques to identify the factors that determine Tarragona’s tourist destination image and that have a decisive influence on visitors’ process of choice of destination. In addition to being able to ascertain Tarragona’s global tourist image, we consider that the heterogeneity of its visitors requires a more detailed study that enables us to segment visitor typology. We consider that the information provided by these results may prove of great interest to those responsible for local tourism policy, both when designing products and when promoting the destination.

Portfolio delegation under short-selling constraints

In this paper we study delegated portfolio management when themanager's ability to short-sell is restricted. Contrary to previousresults, we show that under moral hazard, linear performance-adjustedcontracts do provide portfolio managers with incentives to gatherinformation. The risk-averse manager's optimal effort is an increasingfunction of her share in the portfolio's return. This result affectsthe risk-averse investor's optimal contract decision. The first best,purely risk-sharing contract is proved to be suboptimal. Usingnumerical methods we show that the manager's share in the portfolioreturn is higher than the rst best share. Additionally, this deviationis shown to be: (i) increasing in the manager's risk aversion and (ii)larger for tighter short-selling restrictions. When the constraint isrelaxed the optimal contract converges towards the first best risksharing contract.

The psychosocial difficulties in brain disorders that explain short term changes in health outcomes.

BACKGROUND: This study identifies a set of psychosocial difficulties that are associated with short term changes in health outcomes across a heterogeneous set of brain disorders, neurological and psychiatric. METHODS: Longitudinal observational study over approximately 12 weeks with three time points of assessment and 741 patients with depression, bipolar disorders, multiple sclerosis, parkinson's disease, migraine, traumatic brain injury and stroke. The data on disability was collected with the checklist of the International Classification of Functioning, Disability and Health. The selected health outcomes were the Short Form 36 and the World Health Organization Disability Assessment Schedule. Multilevel models for change were applied controlling for age, gender and disease severity. RESULTS: The psychosocial difficulties that explain the variability and change over time of the selected health outcomes were energy and drive, sleep, and emotional functions, and a broad range of activities and participation domains, such as solving problems, conversation, areas of mobility and self-care, relationships, community life and recreation and leisure. CONCLUSIONS: Our findings are of interest to researchers and clinicians for interventions and health systems planning as they show that in addition to difficulties that are diagnostic criteria of these disorders, there are other difficulties that explain small changes in health outcomes over short periods of time.

Short communication. Persistence of point crop yield subjective estimates

En este trabajo se investiga la persistencia de las estimaciones puntuales subjetivas de rendimientos en cultivos anua- les realizadas por un amplio grupo de agricultores. La persistencia en el tiempo es una condición necesaria para la co- herencia y la confiabilidad de las estimaciones subjetivas de variables aleatorias. Los sujetos entrevistados estimaron valores puntuales de rendimientos de cultivos anuales (rendimientos medio, mayor, mínimo y más frecuente). Se han encontrado diferencias relativas poco importantes en todas las variables, excepto en los rendimientos mínimos, donde existe una alta dispersión. Los resultados son interesantes para estimar la adecuación de las técnicas de estimación de probabilidades subjetivas para ser utilizadas en los sistemas de ayuda en la toma de decisiones en agricultura.

Regression-based techniques for statistical decision making in single-case designs

The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies.

Searching for consensus in ahp-group decision making. A bayesian perspective

This paper sets out to identify the initial positions of the different decisionmakers who intervene in a group decision making process with a reducednumber of actors, and to establish possible consensus paths between theseactors. As a methodological support, it employs one of the most widely-knownmulticriteria decision techniques, namely, the Analytic Hierarchy Process(AHP). Assuming that the judgements elicited by the decision makers follow theso-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al.,1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknownvariance, a Bayesian approach is used in the estimation of the relative prioritiesof the alternatives being compared. These priorities, estimated by way of themedian of the posterior distribution and normalised in a distributive manner(priorities add up to one), are a clear example of compositional data that will beused in the search for consensus between the actors involved in the resolution ofthe problem through the use of Multidimensional Scaling tools