Innovation sources and productivity: 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 Catalan 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 services industries.

Factors explaining local privatization: A meta-regression analysis

Privatization of local public services has been implemented worldwide in the last decades. Why local governments privatize has been the subject of much discussion, and many empirical works have been devoted to analyzing the factors that explain local privatization. Such works have found a great diversity of motivations, and the variation among reported empirical results is large. To investigate this diversity we undertake a meta-regression analysis of the factors explaining the decision to privatize local services. Overall, our results indicate that significant relationships are very dependent upon the characteristics of the studies. Indeed, fiscal stress and political considerations have been found to contribute to local privatization specially in the studies of US cases published in the eighties that consider a broad range of services. Studies that focus on one service capture more accurately the influence of scale economies on privatization. Finally, governments of small towns are more affected by fiscal stress, political considerations and economic efficiency, while ideology seems to play a major role for large cities.

A potential vector of Schistosoma mansoni in Uruguay

Susceptibily experiments were carried out with a Biomphalaria straminea-like planorbid snail (Biomphalaria aff. straminea, species inquirenda) from Espinillar, near Salto (Uruguay), in the area of the Salto Grande reservoir, exposed individually to 5 miracidia of Schistosoma mansoni (SJ2 and BH2 strains). Of 130 snails exposed to the SJ2 strain, originally infective to Biomphalaria tenagophila, 30 became infected (23%). The prepatent (precercaria) period ranged from 35 to 65 days. The cercarial output was irregular, following no definite pattern, varying from 138 to 76,075 per snail (daily average 4.3 to 447.5 and ending up with death. Three specimens that died, without having shed cercarie, on days 69 (2) and 80 after exposure to miracidia, had developing secondary sporocysts in their tissues, justifying the prospect of a longer precercarial period in these cases. In a control group of 120 B. teangophila, exposed to the SJ2 strain, 40 became infected, showing an infection rate (33.3%) not significantly different from that of the Espinillar snail (X [raised to the power of] 2 = 3.26). No cercarie were produced by any of the Espinilar snails exposed to miracidia of the BH2 strain, originally infective to Biomphalaria glabrata. Four specimens showed each a primary sporocyst in one tentacle, which disappeared between 15 and 25 days post-exposure, and two others died with immature, very slender sporocysts in their tissues on days 36 and 54. In a control group of 100 B. glabrata exposed to BH2 miracidia, 94 shed cercariae (94%) and 6 remained negative. Calculation of Frandsen's (1979a, b) TCP/100 index shows that "Espinillar Biomphalaria-SJ2 S. mansoni" is a vector-parasite "compatible" combination. Seeing that tenagophila-borne schistosomiasis is prevalent in Rio de Janeiro and São Paulo states and has recently spread sothwards to Santa Catarina state, and the range of B. tenagophila overlaps taht of the Espinillar Biomphalaria, the possibility of schistosomiais establishing itself in Uruguay, although not imminent, is not to be disregarded.

Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

Bayesian Model Averaging in the Instrumental Variable Regression Model

This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

Biological control of Biomphalaria tenagophila (Mollusca, Planorbidae), a schistosomiasis vector, using the fish Geophagus brasiliensis (Pisces, Cichlidae) in the laboratory or in a seminatural environment

In order to investigate a possible method of biological control of schistosomiasis, we used the fish Geophagus brasiliensis (Quoy & Gaimard, 1824) which is widely distributed throughout Brazil, to interrupt the life cycle of the snail Biomphalaria tenagophila (Orbigny, 1835), an intermediate host of Schistosoma mansoni. In the laboratory, predation eliminated 97.6% of the smaller snails (3-8 mm shell diameter) and 9.2% of the larger ones (12-14 mm shell diameter). Very promising results were also obtained in a seminatural environment. Studies of this fish in natural snail habitats should be further encouraged.

Reversible behavioural autistic-like regression: A manifestation of a special (new?) epileptic syndrome in a 28-month-old child. A 2-year longitudinal study .

A 28-month-old boy was referred for acute onset of abnormal head movements. History revealed an insidious progressive regression in behaviour and communication over several months. Head and shoulder 'spasms' with alteration of consciousness and on one occasion ictal laughter were seen. The electroencephalograph (EEG) showed repeated bursts of brief generalized polyspikes and spike-wave during the 'spasms', followed by flattening, a special pattern which never recurred after treatment. Review of family videos showed a single 'minor' identical seizure 6 months previously. Magnetic resonance imaging was normal. Clonazepam brought immediate cessation of seizures, normalization of the EEG and a parallel spectacular improvement in communication, mood and language. Follow-up over the next 10 months showed a new regression unaccompained by recognized seizures, although numerous seizures were discovered during the videotaped neuropsychological examination, when stereotyped subtle brief paroxysmal changes in posture and behaviour could be studied in slow motion and compared with the 'prototypical' initial ones. The EEG showed predominant rare left-sided fronto-temporal discharges. Clonazepam was changed to carbamazepin with marked improvement in behaviour, language and cognition which has been sustained up to the last control at 51 months. Videotaped home observations allowed the documentation of striking qualitative and quantitative variations in social interaction and play of autistic type in relation to the epileptic activity. We conclude that this child has a special characteristic epileptic syndrome with subtle motor and vegetative symptomatology associated with an insidious catastrophic 'autistic-like' regression which could be overlooked. The methods used to document such fluctuating epileptic behavioural manifestations are discussed.

Strong exceptional sequences of vector bundles on certain Fano varieties

"Vegeu el resum a l'inici del document del fitxer adjunt."

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.