Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

Out-of-sample forecast tests robust to the choice of window size

This paper proposes new methodologies for evaluating out-of-sample forecastingperformance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide rangeof window sizes. We show that the tests proposed in the literature may lack the powerto detect predictive ability and might be subject to data snooping across differentwindow sizes if used repeatedly. An empirical application shows the usefulness of themethodologies for evaluating exchange rate models' forecasting ability.

The changing relationship between commodity prices and equity prices in commodity exporting

We explore the linkage between equity and commodity markets, focusing in particular on its evolution over time. We document that a country's equity market valuehas significant out-of-sample predictive ability for the future global commodity priceindex for several primary commodity-exporting countries. The out-of-sample predictive ability of the equity market appears around 2000s. The results are robust to usingseveral control variables as well as firm-level equity data. Finally, our results indicatethat exchange rates are a better predictor of commodity prices than equity markets,especially at very short horizons.

Saving lives: Evidence from a conditional food supplementation program

Many governments in developing countries implement programs that aim to address nutrionalfailures in early childhood, yet evidence on the effectiveness of these interventions is scant. Thispaper evaluates the impact of a conditional food supplementation program on child mortality inEcuador. The Programa de Alimentaci?n y Nutrici?n Nacional (PANN) 2000 was implementedby regular staff at local public health posts and consisted of offering a free micronutrient-fortifiedfood, Mi Papilla, for children aged 6 to 24 months in exchange for routine health check-ups forthe children. Our regression discontinuity design exploits the fact that at its inception, the PANN2000 was running for about 8 months only in the poorest communities (parroquias) of certainprovinces. Our main result is that the presence of the program reduced child mortality in cohortswith 8 months of differential exposure from a level of about 2.5 percent by 1 to 1.5 percentagepoints.

A general theory of rank testing

This paper develops an approach to rank testing that nests all existing rank tests andsimplifies their asymptotics. The approach is based on the fact that implicit in every ranktest there are estimators of the null spaces of the matrix in question. The approach yieldsmany new insights about the behavior of rank testing statistics under the null as well as localand global alternatives in both the standard and the cointegration setting. The approach alsosuggests many new rank tests based on alternative estimates of the null spaces as well as thenew fixed-b theory. A brief Monte Carlo study illustrates the results.

Who is afraid of the big bad ban? An evaluation of the effects of the Spanish clean air law on expenditure at hospitality venues

Background:In January 2011 Spain modified clean air legislation in force since 2006, removing all existing exceptions applicable to hospitality venues. Although this legal reform was backed by all political parties with parliamentary representation, the government's initiative was contested by the tobacco industry and its allies in the hospitality industry. One of the most voiced arguments against the reform was its potentially disruptive effect on the revenue of hospitality venues. This paper evaluates the impact of this reform on household expenditure at restaurants and bars and cafeterias. Methods and empirical strategy:We use micro-data from the Encuesta de Presupuestos Familiares (EPF) for years 2006 to 2012 to estimate "two part" models where the probability of observing a positive expenditure and, for those who spend, the expected level of expenditure are functions of an array of explanatory variables. We apply a before-after analysis with a wide range of controls for confounding factors and a flexible modeling of time effects.Results:In line with the majority of studies that analyze the effects of smoking bans using objective data, our results suggest that the reform did not cause reductions in households' expenditures on restaurant services or on bars and cafeteria services.

Univariate versus multivariate modeling of panel data

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.

Alternative tests for correct specification of conditional predictive densities

We propose new methods for evaluating predictive densities that focus on the models' actual predictive ability in finite samples. The tests offer a simple way of evaluatingthe correct specification of predictive densities, either parametric or non-parametric.The results indicate that our tests are well sized and have good power in detecting mis-specification in predictive densities. An empirical application to the Survey ofProfessional Forecasters and a baseline Dynamic Stochastic General Equilibrium modelshows the usefulness of our methodology.

Looking beneath Dalí's paint: non-destructive canvas analysis

A new analytical method was developed to non-destructively determine pH and degree of polymerisation (DP) of cellulose in fibres in 19th 20th century painting canvases, and to identify the fibre type: cotton, linen, hemp, ramie or jute. The method is based on NIR spectroscopy and multivariate data analysis, while for calibration and validation a reference collection of 199 historical canvas samples was used. The reference collection was analysed destructively using microscopy and chemical analytical methods. Partial least squares regression was used to build quantitative methods to determine pH and DP, and linear discriminant analysis was used to determine the fibre type. To interpret the obtained chemical information, an expert assessment panel developed a categorisation system to discriminate between canvases that may not be fit to withstand excessive mechanical stress, e.g. transportation. The limiting DP for this category was found to be 600. With the new method and categorisation system, canvases of 12 Dalí paintings from the Fundació Gala-Salvador Dalí (Figueres, Spain) were non-destructively analysed for pH, DP and fibre type, and their fitness determined, which informs conservation recommendations. The study demonstrates that collection-wide canvas condition surveys can be performed efficiently and non-destructively, which could significantly improve collection management.

New methods for the concentration of viruses from urban sewage using quantitative PCR.

Viruses are among the most important pathogens present in water contaminated with feces or urine and represent a serious risk to human health. Four procedures for concentrating viruses from sewage have been compared in this work, three of which were developed in the present study. Viruses were quantified using PCR techniques. According to statistical analysis and the sensitivity to detect human adenoviruses (HAdV), JC polyomaviruses (JCPyV) and noroviruses genogroup II (NoV GGII): (i) a new procedure (elution and skimmed-milk flocculation procedure (ESMP)) based on the elution of the viruses with glycine-alkaline buffer followed by organic flocculation with skimmed-milk was found to be the most efficient method when compared to (ii) ultrafiltration and glycine-alkaline elution, (iii) a lyophilization-based method and (iv) ultracentrifugation and glycine-alkaline elution. Through the analysis of replicate sewage samples, ESMP showed reproducible results with a coefficient of variation (CV) of 16% for HAdV, 12% for JCPyV and 17% for NoV GGII. Using spiked samples, the viral recoveries were estimated at 30-95% for HAdV, 55-90% for JCPyV and 45-50% for NoV GGII. ESMP was validated in a field study using twelve 24-h composite sewage samples collected in an urban sewage treatment plant in the North of Spain that reported 100% positive samples with mean values of HAdV, JCPyV and NoV GGII similar to those observed in other studies. Although all of the methods compared in this work yield consistently high values of virus detection and recovery in urban sewage, some require expensive laboratory equipment. ESMP is an effective low-cost procedure which allows a large number of samples to be processed simultaneously and is easily standardizable for its performance in a routine laboratory working in water monitoring. Moreover, in the present study, a CV was applied and proposed as a parameter to evaluate and compare the methods for detecting viruses in sewage samples.

New methods for the concentration of viruses from urban sewage using quantitative PCR.

Viruses are among the most important pathogens present in water contaminated with feces or urine and represent a serious risk to human health. Four procedures for concentrating viruses from sewage have been compared in this work, three of which were developed in the present study. Viruses were quantified using PCR techniques. According to statistical analysis and the sensitivity to detect human adenoviruses (HAdV), JC polyomaviruses (JCPyV) and noroviruses genogroup II (NoV GGII): (i) a new procedure (elution and skimmed-milk flocculation procedure (ESMP)) based on the elution of the viruses with glycine-alkaline buffer followed by organic flocculation with skimmed-milk was found to be the most efficient method when compared to (ii) ultrafiltration and glycine-alkaline elution, (iii) a lyophilization-based method and (iv) ultracentrifugation and glycine-alkaline elution. Through the analysis of replicate sewage samples, ESMP showed reproducible results with a coefficient of variation (CV) of 16% for HAdV, 12% for JCPyV and 17% for NoV GGII. Using spiked samples, the viral recoveries were estimated at 30-95% for HAdV, 55-90% for JCPyV and 45-50% for NoV GGII. ESMP was validated in a field study using twelve 24-h composite sewage samples collected in an urban sewage treatment plant in the North of Spain that reported 100% positive samples with mean values of HAdV, JCPyV and NoV GGII similar to those observed in other studies. Although all of the methods compared in this work yield consistently high values of virus detection and recovery in urban sewage, some require expensive laboratory equipment. ESMP is an effective low-cost procedure which allows a large number of samples to be processed simultaneously and is easily standardizable for its performance in a routine laboratory working in water monitoring. Moreover, in the present study, a CV was applied and proposed as a parameter to evaluate and compare the methods for detecting viruses in sewage samples.

Simple and fast methods based on solid-phase extraction coupled to liquid chromatography with UV detection for the monitoring of caffeine in natural and waste waters as marker of anthropogenic impact

Two concentration methods for fast and routine determination of caffeine (using HPLC-UV detection) in surface, and wastewater are evaluated. Both methods are based on solid-phase extraction (SPE) concentration with octadecyl silica sorbents. A common “offline” SPE procedure shows that quantitative recovery of caffeine is obtained with 2 mL of an elution mixture solvent methanol-water containing at least 60% methanol. The method detection limit is 0.1 μg L−1 when percolating 1 L samples through the cartridge. The development of an “online” SPE method based on a mini-SPE column, containing 100 mg of the same sorbent, directly connected to the HPLC system allows the method detection limit to be decreased to 10 ng L−1 with a sample volume of 100 mL. The “offline” SPE method is applied to the analysis of caffeine in wastewater samples, whereas the “on-line” method is used for analysis in natural waters from streams receiving significant water intakes from local wastewater treatment plants

A limited area model intercomparison on the "Montserrat-2000" flash-flood event using statistical and deterministic methods

In the scope of the European project Hydroptimet, INTERREG IIIB-MEDOCC programme, limited area model (LAM) intercomparison of intense events that produced many damages to people and territory is performed. As the comparison is limited to single case studies, the work is not meant to provide a measure of the different models' skill, but to identify the key model factors useful to give a good forecast on such a kind of meteorological phenomena. This work focuses on the Spanish flash-flood event, also known as "Montserrat-2000" event. The study is performed using forecast data from seven operational LAMs, placed at partners' disposal via the Hydroptimet ftp site, and observed data from Catalonia rain gauge network. To improve the event analysis, satellite rainfall estimates have been also considered. For statistical evaluation of quantitative precipitation forecasts (QPFs), several non-parametric skill scores based on contingency tables have been used. Furthermore, for each model run it has been possible to identify Catalonia regions affected by misses and false alarms using contingency table elements. Moreover, the standard "eyeball" analysis of forecast and observed precipitation fields has been supported by the use of a state-of-the-art diagnostic method, the contiguous rain area (CRA) analysis. This method allows to quantify the spatial shift forecast error and to identify the error sources that affected each model forecasts. High-resolution modelling and domain size seem to have a key role for providing a skillful forecast. Further work is needed to support this statement, including verification using a wider observational data set.