Determining the season of death from the family composition of insects infesting carrion

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comportamento dos níveis plasmáticos do Peptídeo Natriurético tipo-B em idosos com função sistólica do ventrículo esquerdo preservada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Patterns of regional differentiation in post-Soviet Russia

This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

Analisi delle preferenze per le diverse categorie di pomodoro trasformato nel food service

Il pomodoro è una delle colture principali del panorama agro-alimentare italiano e rappresenta un ingrediente base della tradizione culinaria nazionale. Il pomodoro lavorato dall’industria conserviera può essere trasformato in diverse tipologie merceologiche, che si differenziano in base alla tecniche di lavorazione impiegate ed alle caratteristiche del prodotto finito. la percentuale di spesa totale destinata all’acquisto di cibo fuori casa è in aumento a livello globale e l’interesse dell’industria alimentare nei confronti di questo canale di vendita è quindi crescente. Mentre sono numerose le indagine in letteratura che studiano i processi di acquisto dei consumatori finali, non ci sono evidenze di studi simili condotti sugli operatori del Food Service. Obiettivo principale della ricerca è quello di valutare le preferenze dei responsabili acquisti del settore Food Service per diverse tipologie di pomodoro trasformato, in relazione ad una gamma di attributi rilevanti del prodotto e di caratteristiche del cliente. La raccolta dei dati è avvenuta attraverso un esperimento di scelta ipotetico realizzato in Italia e alcuni mercati esteri. Dai risultati ottenuti dall’indagine emerge che i Pelati sono la categoria di pomodoro trasformato preferita dai responsabili degli acquisti del settore Food Service intervistati, con il 35% delle preferenze dichiarate nell'insieme dei contesti di scelta proposti, seguita dalla Polpa (25%), dalla Passata (20%) e dal Concentrato (15%). Dai risultati ottenuti dalla stima del modello econometrico Logit a parametri randomizzati è emerso che alcuni attributi qualitativi di fiducia (credence), spesso impiegati nelle strategie di differenziazione e posizionamento da parte dell’industria alimentare nel mercato Retail, possono rivestire un ruolo importante anche nell’influenzare le preferenze degli operatori del Food Service. Questo potrebbe quindi essere un interessante filone di ricerca da sviluppare nel futuro, possibilmente con l'impiego congiunto di metodologie di analisi basate su esperimenti di scelta ipotetici e non ipotetici.

America's Shifting Color Line? Reexamining Determinants of Latino Racial Self-Identification

Objectives. Latinos are the nation's largest minority group and will double in size by 2050. Their size coupled with the fact that Latinos do not constitute a separate race raises questions about Latinos' incorporation into the U. S. racial hierarchy. This article explores patterns of Latino racial identity formation, examining the determinants of racial identity. Methods. Using the 2006 Latino National Survey, I estimate multinomial logit and ordered probit models of identification choices. Results. Latino racial identity is strongly associated with several factors, including socioeconomic status, measures of perceived discrimination and commonality, and measures of acculturation/assimilation. Most Latinos have a broader, more complex understanding of race. Furthermore, some Latinos do believe that they occupy a unique position in the racial hierarchy. Conclusions. The results suggest that the color line W. E. DuBois argued has long divided our nation may eventually shift.

Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

Renal Cryoablation: Investigation of Periprocedural Visualization Tools and Treatment Response Quantification

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in the procedure. This study sought to mitigate uncertainty in these visual comparisons by quantifying tissue response to cryoablation and providing visualization of the response during the procedure. Based on retrospective analysis of MR-guided cryoablation patient data, registration and segmentation algorithms were investigated and implemented for periprocedural visualization to deliver iceball position/size with respect to planning images registered within 3.3mm with at least 70% overlap and a quantitative logit model was developed to relate perfusion deficit in renal parenchyma visualized in verification images as a result of iceball size visualized in monitoring images. Through retrospective study of 20 patient cases, the relationship between likelihood of perfusion loss in renal parenchyma and distance within iceball was quantified and iteratively fit to a logit curve. Using the parameters from the logit fit, the margin for 95% perfusion loss likelihood was found to be 4.28 mm within the iceball. The observed margin corresponds well with the clinically accepted margin of 3-5mm within the iceball. In order to display the iceball position and perfusion loss likelihood to the radiologist, algorithms were implemented to create a fast segmentation and registration module which executed in under 2 minutes, within the clinically-relevant 3 minute monitoring period. Using 16 patient cases, the average Hausdorff distance was reduced from 10.1mm to 3.21 mm with average DSC increased from 46.6% to 82.6% before and after registration.

Migration and Wellbeing at the Lower Echelons of the Economy: A Study of Delhi Slums

This paper based on a primary survey of households (2004-05) in the slum clusters of Delhi examines whether migrants are likely to experience upward mobility in their place of destination or alternatively, if they merely transfer their poverty from rural areas to large cities. First, a simple bifurcation of population in terms of poor and non-poor sub-groups is examined along with the incidence of poverty across different categories of occupations and non-workers. Then, an explanation of the variations in per capita expenditure across households is provided, and a binomial logit model (poor/non-poor) is developed identifying the variables which raise (or reduce) the probability of being non-poor (or poor). Next, an estimate of the wellbeing (deprivation) index is derived from factor analysis of a large number of variables including demographic and economic aspects of households. Empirical findings suggest that while duration of migration and the wellbeing index do not have a definite relationship, migrant households who have been in the city for a very long time have a higher wellbeing index on average than those who migrated in the last ten years. This tends to support the view that migrants do not merely transfer rural poverty to urban areas, and further that population mobility yields improvement in the living standard, if only in the very long term. Implementation of "employment-cum-shelter" support schemes in the urban areas may contribute to their wellbeing.

Chapter 8 Location Choice of Japanese Multinationals: Country Characteristics or Region Characteristics?

In the present global era in which firms choose the location of their plants beyond national borders, location characteristics are important for attracting multinational enterprises (MNEs). The better access to countries with large market is clearly attractive for MNEs. For example, special treatments on tariffs such as the Generalized System of Preferences (GSP) are beneficial for MNEs whose home country does not have such treatments. Not only such country characteristics but also region characteristics (i.e. province-level or city-level ones) matter, particularly in the case that location characteristics differ widely between a nation's regions. The existence of industrial concentration, that is, agglomeration, is a typical regional characteristic. It is with consideration of these country-level and region-level characteristics that MNEs decide their location abroad. A large number of academic studies have investigated in what kinds of countries MNEs locate, i.e. location choice analysis. Employing the usual new economic geography model (i.e. constant elasticity of substitution (CES) utility function, Dixit-Stiglitz monopolistic competition, and ice-berg trade costs), the literature derives the profit function, of which coefficients are estimated using maximum likelihood procedures. Recent studies are as follows: Head, Rise, and Swenson (1999) for Japanese MNEs in the US; Belderbos and Carree (2002) for Japanese MNEs in China; Head and Mayer (2004) for Japanese MNEs in Europe; Disdier and Mayer (2004) for French MNEs in Europe; Castellani and Zanfei (2004) for large MNEs worldwide; Mayer, Mejean, and Nefussi (2007) for French MNEs worldwide; Crozet, Mayer, and Mucchielli (2004) for MNEs in France; and Basile, Castellani, and Zanfei (2008) for MNEs in Europe. At the present time, three main topics can be found in this literature. The first introduces various location elements as independent variables. The above-mentioned new economic geography model usually yields the profit function, which is a function of market size, productive factor prices, price of intermediate goods, and trade costs. As a proxy for the price of intermediate goods, the measure of agglomeration is often used, particularly the number of manufacturing firms. Some studies employ more disaggregated numbers of manufacturing firms, such as the number of manufacturing firms with the same nationality as the firms choosing the location (e.g., Head et al., 1999; Crozet et al., 2004) or the number of firms belonging to the same firm group (e.g., Belderbos and Carree, 2002). As part of trade costs, some investment climate measures have been examined: free trade zones in the US (Head et al., 1999), special economic zones and opening coastal cities in China (Belderbos and Carree, 2002), and Objective 1 structural funds and cohesion funds in Europe (Basile et al., 2008). Second, the validity of proxy variables for location elements is further examined. Head and Mayer (2004) examine the validity of market potential on location choice. They propose the use of two measures: the Harris market potential index (Harris, 1954) and the Krugman-type index used in Redding and Venables (2004). The Harris-type index is simply the sum of distance-weighted real GDP. They employ the Krugman-type market potential index, which is directly derived from the new economic geography model, as it takes into account the extent of competition (i.e. price index) and is constructed using estimators of importing country dummy variables in the well-known gravity equation, as in Redding and Venables (2004). They find that "theory does not pay", in the sense that the Harris market potential outperforms Krugman's market potential in both the magnitude of its coefficient and the fit of the model to be estimated. The third topic explores the substitution of location by examining inclusive values in the nested-logit model. For example, using firm-level data on French investments both in France and abroad over the 1992-2002 period, Mayer et al. (2007) investigate the determinants of location choice and assess empirically whether the domestic economy has been losing attractiveness over the recent period or not. The estimated coefficient for inclusive value is strongly significant and near unity, indicating that the national economy is not different from the rest of the world in terms of substitution patterns. Similarly, Disdier and Mayer (2004) investigate whether French MNEs consider Western and Eastern Europe as two distinct groups of potential host countries by examining the coefficient for the inclusive value in nested-logit estimation. They confirm the relevance of an East-West structure in the country location decision and furthermore show that this relevance decreases over time. The purpose of this paper is to investigate the location choice of Japanese MNEs in Thailand, Cambodia, Laos, Myanmar, and Vietnam, and is closely related to the third topic mentioned above. By examining region-level location choice with the nested-logit model, I investigate the relative importance of not only country characteristics but also region characteristics. Such investigation is invaluable particularly in the case of location choice in those five countries: industrialization remains immature in those countries which have not yet succeeded in attracting enough MNEs, and as a result, it is expected that there are not yet crucial regional variations for MNEs within such a nation, meaning the country characteristics are still relatively important to attract MNEs. To illustrate, in the case of Cambodia and Laos, one of the crucial elements for Japanese MNEs would be that LDC preferential tariff schemes are available for exports from Cambodia and Laos. On the other hand, in the case of Thailand and Vietnam, which have accepted a relatively large number of MNEs and thus raised the extent of regional inequality, regional characteristics such as the existence of agglomeration would become important elements in location choice. Our sample countries seem, therefore, to offer rich variations for analyzing the relative importance between country characteristics and region characteristics. Our empirical strategy has a further advantage. As in the third topic in the location choice literature, the use of the nested-logit model enables us to examine substitution patterns between country-based and region-based location decisions by MNEs in the concerned countries. For example, it is possible to investigate empirically whether Japanese multinational firms consider Thailand/Vietnam and the other three countries as two distinct groups of potential host countries, by examining the inclusive value parameters in nested-logit estimation. In particular, our sample countries all experienced dramatic changes in, for example, economic growth or trade costs reduction during the sample period. Thus, we will find the dramatic dynamics of such substitution patterns. Our rigorous analysis of the relative importance between country characteristics and region characteristics is invaluable from the viewpoint of policy implications. First, while the former characteristics should be improved mainly by central government in each country, there is sometimes room for the improvement of the latter characteristics by even local governments or smaller institutions such as private agencies. Consequently, it becomes important for these smaller institutions to know just how crucial the improvement of region characteristics is for attracting foreign companies. Second, as economies grow, country characteristics become similar among countries. For example, the LCD preferential tariff schemes are available only when a country is less developed. Therefore, it is important particularly for the least developed countries to know what kinds of regional characteristics become important following economic growth; in other words, after their country characteristics become similar to those of the more developed countries. I also incorporate one important characteristic of MNEs, namely, productivity. The well-known Helpman-Melitz-Yeaple model indicates that only firms with higher productivity can afford overseas entry (Helpman et al., 2004). Beyond this argument, there may be some differences in MNEs' productivity among our sample countries and regions. Such differences are important from the viewpoint of "spillover effects" from MNEs, which are one of the most important results for host countries in accepting their entry. The spillover effects are that the presence of inward foreign direct investment (FDI) aises domestic firms' productivity through various channels such as imitation. Such positive effects might be larger in areas with more productive MNEs. Therefore, it becomes important for host countries to know how much productive firms are likely to invest in them. The rest of this paper is organized as follows. Section 2 takes a brief look at the worldwide distribution of Japanese overseas affiliates. Section 3 provides an empirical model to examine their location choice, and lastly, we discuss future works to estimate our model.

Location choice in low-income countries : evidence from Japanese investments in East Asia

Unlike most existing studies, this paper examines the location choices of MNEs in developing countries. Specifically, we investigate the location choices of Japanese MNEs among East Asian developing countries by estimating a four-stage nested logit model at the province level. Noteworthy results of location elements are as follows. As is consistent with the mechanics of cheap labor-seeking FDI, Japanese MNEs are more likely to invest in locations with low income and low tariff rates on products from Japan. Also, accessibility to other locations and/or ports matters in attracting Japanese MNEs because it is crucial in importing materials and exporting their products. In addition, WTO membership and bilateral investment treaties are important because these contribute to the settlement of trade and investment disputes, which is more likely to be necessary in developing countries.

Transport modal choice by multinational firms : firm-level evidence from Southeast Asia

We examine transport modal decision by multinational firms to shed light on the role of freight logistics in multinational activity. Using a firm-level survey in Southeast Asia, we show that foreign ownership has a significantly positive and quantitatively large impact on the likelihood that air/sea transportation is chosen relative to truck shipping. This result is robust to the shipping distance, cross-border freight, and transport infrastructure. Both foreign-owned exporters and importers also tend to use air/sea transportation. Thus, our analysis presents a new distinction between multinational and domestic firms in their decision over transport modes.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

Employment rate impacts of charging the Heavy Good Vehicle corridor (Madrid-Sevilla) across Spanish regions: a Random Utility Based Multiregional Input-Output approach

The implementation of a charging policy for heavy goods vehicles in European Union (EU) member countries has been imposed to reflect costs of construction and maintenance of infrastructure as well as externalities such as congestion, accidents and environmental impact. In this context, EU countries approved the Eurovignette directive (1999/62/EC) and its amending directive (2006 /38/EC) which established a legal framework to regulate the system of tolls. Even if that regulation seek s to increase the efficien cy of freight, it will trigger direct and indirect effects on Spain’s regional economies by increasing transport costs. This paper presents the development of a multiregional Input-Output methodology (MRIO) with elastic trade coefficients to predict in terregional trade, using transport attributes integrated in multinomial logit models. This method is highly useful to carry out an ex-ante evaluation of transport policies because it involves road freight transport cost sensitivity, and determine regional distributive and substitution economic effect s of countries like Spain, characterized by socio-demographic and economic attributes, differentiated region by region. It will thus be possible to determine cost-effective strategies, given different policy scenarios. MRIO mode l would then be used to determine the impact on the employment rate of imposing a charge in the Madrid-Sevilla corridor in Spain. This methodology is important for measuring the impact on the employment rate since it is one of the main macroeconomic indicators of Spain’s regional and national economic situation. A previous research developed (DESTINO) using a MRIO method estimated employment impacts of road pricing policy across Spanish regions considering a fuel tax charge (€/liter) in the entire shortest cost path network for freight transport. Actually, it found that the variation in employment is expected to be substantial for some regions, and negligible for others. For example, in this Spanish case study of regional employment has showed reductions between 16.1% (Rioja) and 1.4% (Madrid region). This variation range seems to be related to either the intensity of freight transport in each region or dependency of regions to transport intensive economic sect ors. In fact, regions with freight transport intensive sectors will lose more jobs while regions with a predominantly service economy undergo a fairly insignificant loss of employment. This paper is focused on evaluating a freight transport vehicle-kilometer charge (€/km) in a non-tolled motorway corridor (A-4) between Madrid-Sevilla (517 Km.). The consequences of the road pricing policy implementation show s that the employment reductions are not as high as the diminution stated in the previous research because this corridor does not affect the whole freight transport system of Spain.

Cycling habits and other psychological variables affecting commuting by bicycle in Madrid, Spain

To develop effective cycling policies, decision makers and administrators should know the factors influencing the use of the bicycle for daily mobility. Traditional discrete choice models tend to be based on variables such as time and cost, which do not sufficiently explain the choice of the bicycle as a mode of transportation. Because psychological factors have been identified as particularly influential in the decision to commute by bicycle, this paper examines the perceptions of cycling factors and their influence on commuting by bicycle. Perceptions are measured by attitudes, other psychological variables, and habits. Statistical differences in the variables are established in relation to the choice of commuting mode and bicycle experience (commuter, sport-leisure, no use). Doing so enables the authors to identify the main barriers to commuting by bicycle and to make recommendations for cycling policies. Two underlying structures (factors) of the attitudinal variables are identified: direct benefits and long-term benefits. Three other factors are related to variables of difficulty: physical conditions, external facilities, and individual capacities. The effect of attitudes and other psychological variables on people's decision to cycle to work-place of study is tested by using a logit model. In the case study of Madrid, Spain, the decision to cycle to work-place of study is heavily influenced by cycling habits (for noncommuting trips). Because bicycle commuting is not common, attitudes and other psychological variables play a less important role in the use of bikes.