Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

State inspection program evaluation and data analysis: data base E SPSS frequencies tabulations for brake components and explanatory variables. Volume III. Final report.

National Highway Traffic Safety Administration, Office of Vehicle Safety Research, Washington, D.C.

The detection of interaction effects ; a report on a computer program for the selection of optimal combinations of explanatory variables /

Errata sheet inserted.

Dimension Reduction of the Explanatory Variables in Multiple Linear Regression

2002 Mathematics Subject Classification: 62J05, 62G35.

QUESTIONNAIRES IN THE SCREENING FOR Schistosoma mansoni INFECTION: A STUDY OF SOCIO DEMOGRAPHIC AND WATER CONTACT VARIABLES IN FOUR COMMUNITIES IN BRAZIL

The use of questionnaires has been recommended for identifying, at a lower cost, individuals at risk for schistosomiasis. In this study, validity of information obtained by questionnaire in the screening for Schistosoma mansoni infection was assessed in four communities in the State of Minas Gerais, Brazil. Explanatory variables were water contact activities, sociodemographic characteristics and previous treatment for schistosomiasis. From 677, 1474, 766 and 3290 individuals eligible for stool examination in the communities, 89 to 97% participated in the study. The estimated probability of individuals to be infected, if they have all characteristics identified as independently associated with S.mansoni infection, varied from 15% in Canabrava, to 42% in Belo Horizonte, 48% in Comercinho and 80% in São José do Acácio. Our results do not support the hypothesis that a same questionnaire on risk factors could be used in screening for S.mansoni infection in different communities.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Exploring the role of social capital influence variables on travel behaviour

This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.

A Bayesian approach to study the risk variables for tuberculosis occurrence in domestic and wild ungulates in South Central Spain

BACKGROUND Bovine tuberculosis (bTB) is a chronic infectious disease mainly caused by Mycobacterium bovis. Although eradication is a priority for the European authorities, bTB remains active or even increasing in many countries, causing significant economic losses. The integral consideration of epidemiological factors is crucial to more cost-effectively allocate control measures. The aim of this study was to identify the nature and extent of the association between TB distribution and a list of potential risk factors regarding cattle, wild ungulates and environmental aspects in Ciudad Real, a Spanish province with one of the highest TB herd prevalences. RESULTS We used a Bayesian mixed effects multivariable logistic regression model to predict TB occurrence in either domestic or wild mammals per municipality in 2007 by using information from the previous year. The municipal TB distribution and endemicity was clustered in the western part of the region and clearly overlapped with the explanatory variables identified in the final model: (1) incident cattle farms, (2) number of years of veterinary inspection of big game hunting events, (3) prevalence in wild boar, (4) number of sampled cattle, (5) persistent bTB-infected cattle farms, (6) prevalence in red deer, (7) proportion of beef farms, and (8) farms devoted to bullfighting cattle. CONCLUSIONS The combination of these eight variables in the final model highlights the importance of the persistence of the infection in the hosts, surveillance efforts and some cattle management choices in the circulation of M. bovis in the region. The spatial distribution of these variables, together with particular Mediterranean features that favour the wildlife-livestock interface may explain the M. bovis persistence in this region. Sanitary authorities should allocate efforts towards specific areas and epidemiological situations where the wildlife-livestock interface seems to critically hamper the definitive bTB eradication success.

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south-east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non-lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.

Aleitamento materno, alimentação complementar, sobrepeso e obesidade em pré-escolares

OBJETIVO: Analisar a associação do sobrepeso e da obesidade com o aleitamento materno e a alimentação complementar em pré-escolares. MÉTODOS: Estudo transversal envolvendo 566 crianças matriculadas em escolas particulares no município de São Paulo, SP, 2004-2005. A variável dependente foi sobrepeso e obesidade. Para a classificação do estado nutricional das crianças foram utilizadas as curvas de percentis do Índice de Massa Corporal para idade, classificando como sobrepeso valores e"P85 e

Introdução de alimentos complementares nos primeiros dois anos de vida de crianças de escolas particulares no município de São Paulo

OBJETIVOS: Verificar a idade de introdução de alimentos complementares nos primeiros dois anos de vida e sua relação com variáveis demográficas e socioeconômicas de crianças matriculadas em pré-escolas particulares do município de São Paulo. MÉTODOS: Estudo transversal com informações demográficas e socioeconômicas de 566 crianças, sendo verificada a idade em meses de introdução dos alimentos complementares. Foi considerada como variável dependente a idade em meses da introdução dos alimentos complementares e, como variáveis independentes ou explanatórias, a idade e escolaridade maternas, a condição de trabalho materno e a renda familiar. Para análise da relação entre as variáveis, utilizou-se a técnica de regressão múltipla de Cox. RESULTADOS: 50% das crianças eram do sexo masculino e 61% maiores de 4 anos. A maior proporção das mães tinha nível superior de escolaridade e trabalhava fora. A renda familiar mostrou uma população de alto nível socioeconômico. A água e/ou chá, frutas e leite não-materno foram introduzidos antes do sexto mês de vida. A variável 'idade da mãe' mostrou associação com introdução de três grupos de alimentos: cereais, carne e guloseimas. CONCLUSÃO: Alimentos complementares foram introduzidos precocemente nessa população de nível socioeconômico elevado e a única variável que se associou à introdução desses alimentos foi a idade materna.

Determinantes do consumo de frutas e hortaliças em adolescentes por regressão quantílica

OBJETIVO: Analisar o consumo de frutas, legumes e verduras (FLV) de adolescentes e identificar fatores associados. MÉTODOS: Estudo transversal de base populacional com amostra representativa de 812 adolescentes de ambos os sexos de São Paulo, SP, em 2003. O consumo alimentar foi medido pelo recordatório alimentar de 24 horas. O consumo de FLV foi descrito em percentis e para investigar a associação entre a ingestão de FLV e variáveis explanatórias; foram utilizados modelos de regressão quantílica. RESULTADOS: Dos adolescentes entrevistados, 6,4% consumiram a recomendação mínima de 400 g/dia de FLV e 22% não consumiram nenhum tipo de FLV. Nos modelos de regressão quantílica, ajustados pelo consumo energético, faixa etária e sexo, a renda domiciliar per capita e a escolaridade do chefe de família associaram-se positivamente ao consumo de FLV, enquanto o hábito de fumar associou-se negativamente. Renda associou-se significativamente aos menores percentis de ingestão (p20 ao p55); tabagismo aos percentis intermediários (p45 ao p75) e escolaridade do chefe de família aos percentis finais de consumo de FLV (p70 ao p95). CONCLUSÕES: O consumo de FLV por adolescentes paulistanos mostrou-se abaixo das recomendações do Ministério da Saúde e é influenciado pela renda domiciliar per capita, pela escolaridade do chefe de família e pelo hábito de fumar.

Development of Ramulosis Disease of Cotton Under Controlled Environment and Field Conditions

Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis disease of cotton, is widespread in Brazil and can cause severe yield loss. Because weather conditions greatly affect disease development, the objective of this work was to develop weather-based models to assess disease favorability. Latent period, incidence, and severity of ramulosis symptoms were evaluated in controlled environment experiments using factorial combinations of temperature (15, 20, 25, 30, and 35 degrees C) and leaf wetness duration (0, 4, 8, 16, 32, and 64 h after inoculation). Severity was modeled as an exponential function of leaf wetness duration and temperature. At the optimum temperature of disease development, 27 degrees C, average latent period was 10 days. Maximum ramulosis severity occurred from 20 to 30 degrees C, with sharp decreases at lower and higher temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. In field experiments at Piracicaba, Sao Paulo State, Brazil, cotton plots were inoculated (10(5) conidia ml(-1)) and ramulosis severity was evaluated weekly. The model obtained from the controlled environment study was used to generate a disease favorability index for comparison with disease progress rate in the field. Hourly measurements of solar radiation, temperature, relative humidity, leaf wetness duration, rainfall, and wind speed were also evaluated as possible explanatory variables. Both the disease favorability model and a model based on rainfall explained ramulosis growth rate well, with R(2) of 0.89 and 0.91, respectively. They are proposed as models of ramulosis development rate on cotton in Brazil, and weather-disease relationships revealed by this work can form the basis of a warning system for ramulosis development.

Incorporating demand-side aspects into regional policy: variations in the importance of private investment decision factors across regions

Most regional programs focus on the supply side of regions, emphasizing the attraction conditions offered, such as infrastructure, labor skills, tax incentives, etc. This study analyzes one aspect of the demand side, that is, how investment decisions of private firms are made by asking the question: ""Do corporations decide the same way on investments in different parts of the territory?"" The paper analyzes the investments of 373 large Brazilian firms during 1996-2004. Based on the investment decisions of these firms, the role of sales, cash-flow, external financing, and working capital is investigated through regression analysis. The regional influence is captured by explanatory variables representing regional and firm characteristics, and by interaction dummies between the region and the main investment determinants. The results indicate significant differences across regions in the importance of investment determinants. This information is important for regional development policy, because different mechanisms should be used in different regions to foster private investments.