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Esta dissertação visa avaliar o padrão comportamental dos pedestres nos deslocamentos na cidade de Porto Alegre. É abordado a partir da base de dados provenientes da pesquisa de entrevistas domiciliares realizadas em 2003 em Porto Alegre. Para isto, caracterizaram-se os deslocamentos a pé na cidade e identificaram-se as regiões de maior e menor concentração de viagens a pé. A fim de determinar os fatores que influenciam a decisão de caminhar foram estimados modelos logit binomiais para as viagens menores que 2 km em cada uma das regiões identificadas anteriormente. As variáveis explicativas para os modelos analisados incluem características do domicílio (disponibilidade de automóvel e renda por domicílio), dos residentes (idade), das viagens (distância e motivo da viagem), da forma urbana (densidade de domicílios, densidade populacional, comprimento médio das quadras, padrão do sistema viário, tipo de uso do solo e estacionamento tarifado em área pública) e da disponibilidade de transporte coletivo na origem da viagem. Foram consideradas duas categorias de viagens: viagens por motivo trabalho/estudo e viagens por motivo não trabalho/estudo (motivos recreacionais, compras, saúde, assuntos pessoais e outros). Os resultados do estudo mostram que características sócio-econômicas dos residentes, características das viagens e da forma urbana influenciam a escolha do modo a pé. Analisando os valores de elasticidade obtidos para as duas categorias de viagens originadas em Petrópolis e no Centro pode-se inferir que as variáveis que exercem maior influência estão relacionadas principalmente a características da viagem (distância) e à configuração física da rede viária. A análise de sensibilidade evidenciou a sensibilidade do modelo frente a alterações das variáveis estudadas. Os resultados obtidos servem de apoio para um planejamento mais adequado da mobilidade e acessibilidade dos pedestres. / This thesis aims to evaluate the pedestrians’ behavior in Porto Alegre. The study was based on a Porto Alegre household survey of 2003. During the analysis, the pedestrian trips were characterized and the traffic zones with the larger and the smaller number of pedestrian trips were identified. In order to determine the influencing factors related to the walk choice, binomial logit models were developed for trips with less than 2km in each traffic zone previously identified. The explanatory variable used in the models included the characteristics of the household (auto availability and household income), of the household members (age), of the trip (distance and purpose of the trip), of the built environment (housing units density, population density, mean block size, street patterns, land use and public parking), and transit availability in the origin of the trip. Two types of pedestrian travel were considered: work and non-work trips (shopping, health, personal purposes and others). The study results showed that socio-economic characteristics, trip characteristics and local measures of the built environment influence walk modechoice. Elasticity results for the two types of trips, with origin in “Petrópolis” and Downtown, indicate that the most influence variables are connected with trip characteristics (distance) and street design. The sensibility analysis showed the model sensibility strength under the changes introduced in the variables studied. These analysis results may provide support for a better planning for pedestrians’ mobility and accessibility.

This thesis investigates the relationship between conflict, economic growth, state capacity and natural resources in Sub-Saharan Africa. It contributes to the limited research in this area and empirically examines these relationships using different econometric models. The first empirical chapter uses a panel dataset that covers the period 1997 - 2013 to analyse the effects of economic growth on conflict in Nigeria using the negative binomial model. The findings support the direct relationship between economic growth and conflict in Nigeria. Controlling for other factors, the results indicate that increase in growth rate - measured by annual growth rate of GDP per capita - decreases the expected number of conflicts. The study finds no evidence of a relationship between levels of wealth in a state and the incidence of conflicts. The analysis controls for factors such as spill-over effects from other states and year and state effects. Finally, to address potential concerns that economic growth could be a cause of conflict or that other unobserved factors could confound the relationship between economic growth and conflict, the chapter employs instrumental variable (IV) estimation using percentage change in rainfall as an instrument. The results with the IV estimation are similar to the results without IV in terms of both sign and significance, indicating that the negative effect of economic growth on conflicts is not due to reverse causality or omitted variables. For robustness checks, a Panel Autoregressive model (PVAR) is also employed. The second empirical chapter analyses the effect of conflict on state capacity in Sub-Saharan Africa. State capacity is measured in terms of fiscal and legal capacity. It also looks at the effects of internal and external conflicts on state capacity. The chapter adopts the Ordinary least squared (OLS) and the system generalised methods of moments (GMM) estimation methods to analyse the panel data consisting of 49 Sub-Saharan countries over the period 2000 - 2015. The results suggest that conflicts have a negative and significant effect on state capacity. However, when military expenditure is used as a proxy for state capacity it is found that conflict strengthens state capacity. The results are consistent with theoretical argument that internal conflicts polarise societies and make it more difficult for governments to reach a consensus in investing in state capacity, while external conflicts mobilise domestic population against a common enemy thereby helping in state capacity building. Finally, the third empirical chapter examines the effect of natural resources on conflict onset and duration using discrete choice models with a dataset covering the period 1980 -2016. The results on the duration analysis show that natural resources prolong duration of conflicts. However, it is found that not all natural resources prolong duration of conflicts. Oil production does not seem to affect duration, whereas oil reserves and gas production lengthens the duration. The findings from the onset analysis show that both production and reserves of natural resources increase the risk of conflict onset.

Travel to outdoor recreational spaces belongs to a general class of research questions for understanding destination and travel mode choices. In travel demand modelling, discrete choice models (DCMs) have been applied to understand and predict a wide range of choices, such as how people choose among alternative destinations for jobs, homes, shopping, personal services etc. Surprisingly, DCMs have rarely been used to understand and model travel to outdoor recreational spaces. In the current literature for modelling travel to outdoor recreational spaces, the established models are Negative Binomial Regression (NBR) models, such as what was used in the UK NEA studies. However, these NBR models were developed to assess the effects of travel to outdoor recreational spaces at a national level, and they are not intended for assessing choices of individual sites. One reason for this is, as identified by previous studies, is that compared with the DCMs, the NBR models have certain limits on estimating people's choice behaviours. There is, therefore, no existing model that can represent and predict how people choose to travel to outdoor recreational spaces. Given the importance of outdoor recreational activities to urban land use planning and public health, this is a clear gap in the field. The aim of this study is to develop a new travel demand model capable of representing and predicting travel to individual outdoor recreational sites. This is achieved by answering four main research questions: First, how to build the new model for outdoor recreational travel? Secondly, is the estimation accurate enough? Thirdly, to what extent can the new model be transferred to destinations outside the case study area? And, finally, how can city planners and designers use this new method? The new model draws upon ideas from random utility theory that underlies the conventional travel demand models to represent trip generation, trip distribution and mode choice. This research follows the standard modelling procedure: data collection and preliminary analysis, model calibration, model validation and model application. The data are collated from a wide range of sources that, importantly for model transferability, cover all areas in England. The new model has been calibrated for a case study area which spanned 14 selected districts in the North-West region. Validation of the new model is based on estimating the numbers of trips to two outdoor recreational sites (Wigg Island and Wigan Flashes) and to nine English National Parks where data on visitor trips exist. In the final stage of the research, the new model is applied to estimate the changes that would arise from planning and design interventions in existing (Wigg Island and Moore Nature Reserve) and proposed (Arpley Country Park) sites. At the end of this process, it is possible to show that the new model can predict the number of trips to individual destinations and that the model can be transferred to other outdoor recreation sites. Furthermore, the new model presented here is capable of predicting the changes in the volume and catchment of visits to an existing green space after land use planning or urban ecological interventions. This is a completely new theoretical model that is focused on understanding and quantifying the travel choices to outdoor recreation sites, which can inform decision makers by forecasting changes in outdoor recreational travel demand, according to different planning scenarios.

This dissertation aims to address issues related to supply and demand of organic wheat either as a commodity or contained in the final consumer products. Objectives for the first essay are to evaluate organic wheat price and premium risk, how it affects the profitability of organic wheat production, and examine whether hedging and forecasting can be used to manage the organic wheat price risk. A side objective is to apply and evaluate several data imputation methods to recover missing organic wheat price observations. Objectives for the second essay are to identify “very likely,” “likely,” and “unlikely” consumers of organic wheat products, examine the differences across the consumer groups to understand which sociodemographic characteristics and other factors drive demand for organic wheat products, and which product characteristics and labels are important to consumers. Objectives for the third essay are to obtain willingness to pay values for organic label alone, examine whether combining organic label with other labels (non-GMO, gluten-free, sugar-free or low-carb) is beneficial for consumers, and evaluate whether knowledge and familiarity with organic, wheat or gluten intolerance or avoidance, and other sociodemographic characteristics affect how consumers value the organic label alone and in combination with other labels. The analyses in the second and third essay are performed using two wheat product categories (bread and cookies) to examine how findings differ across different product categories. This dissertation provides several societal benefits. The findings provide insights that may play an important role in supporting growth of the organic wheat production through reduction of uncertainty associated with wheat commodity prices and final consumer demand. Understanding the dynamics of organic wheat prices, how they can affect profitability of organic wheat production and what can be done to reduce the uncertainty is critical to organic wheat growers and food manufacturers when they make production decisions. The findings in the second and third essay will assist food manufacturers and marketers as they develop new products and marketing strategies and make labelling decisions. The findings in this dissertation may allow them to match consumers’ needs better, and thus use the limited organic wheat supply more efficiently.

The individuals with disabilities are disproportionately vulnerable to hazards. However, there is very little research inquiry focused on evacuation environments and the behavior of individuals with disabilities. The most widely applied computational method used to study how effective the built environment facilities emergency evacuations in individuals-based modeling. Current pedestrian evacuation models rarely include individuals with disabilities in their simulated populations due to there being very few empirical studies of the evacuation behavior of individuals with disabilities. As a result, the models do not replicate accurate patterns of pedestrian or evacuation behavior of a heterogeneous population, which results in the evacuation needs of individuals with disabilities being generally overlooked. To begin addressing this limitation, our research group at Utah State University (USU) has performed empirical research to observe the microscopic evacuation behavior of individuals with disabilities in heterogeneous population contexts. The purpose of this research was to: (1) develop and analyze evacuation curves to understand and assess evacuation strategies for heterogeneous populations, and (2) analyze the microscopic behavior of evacuees at exit doors necessary for developing credible and valid pedestrian and evacuation models. Doing so will contribute to evacuation models which replicate accurate patterns of pedestrian and evacuation behavior of heterogeneous populations, leading to the consideration of the evacuation needs of individuals with disabilities.

This thesis evaluates truck route choice set generation algorithms and derives guidance on using the algorithms for effective generation of choice sets for modeling truck route choice. Specifically, route choice sets generated from a breadth first search link elimination (BFS-LE) algorithm are evaluated against observed truck routes derived from large streams of GPS traces of a sizeable truck fleet in the Tampa Bay region of Florida. A systematic evaluation approach is presented to arrive at an appropriate combination of spatial aggregation and minimum number of trips to be observed between each origin-destination (OD) location for evaluating algorithm-generated choice sets. The evaluation is based on both the ability to generate relevant routes that are typically considered by the travelers and the generation of irrelevant (or extraneous) routes that are seldom chosen. Based on this evaluation, the thesis offers guidance on effectively using the BFS-LE approach to maximize the generation of relevant routes. It is found that carefully chosen spatial aggregation can reduce the need to generate large number of routes for each trip. Further, estimation of route choice models and their subsequent application on validation datasets revealed that the benefits of spatial aggregation might be harnessed better if irrelevant routes are eliminated from the choice sets. Lastly, a comparison of route attributes of the relevant and irrelevant routes shed light on presence of systematic differences in route characteristics of the relevant and irrelevant routes.

In this thesis, I investigate economic and policy implications of individual choice decisions, including consumers’ choices among differentiated products and households’ decisions on intra-household resource allocations. In the first chapter, I develop a consumer demand model for US retail banking services in which consumers have preference over the geographical convenience of their banks’ networks. The purpose of the study is to identify consumers’ taste for branch network convenience in the US banking industry and to assess the effect of this demand motive on bank revenues, consumer surplus, and market structure. I show that consumers value the geographical convenience of their bank branch network to a large extent. Specifically, a branch that is one mile closer is equivalent to a branch with a 0.4 percent higher annual interest rate. Furthermore, consumers value proximity of the branch network to both their residence and workplace. The counterfactual experiment shows that banks with a larger number of branches enjoy greater network benefits in terms of revenue. Meanwhile, consumers benefit from the reduction in their expected travel distance by choosing depository institutions with large-scale networks. The second chapter examines how parents adjust bride-prices and land divisions to compensate their sons for differences in their schooling expenditures in rural China. The model is tested using data from a unique household interview survey carried out in Hebei Province. The main estimate implies that when a son receives one yuan less in schooling investment than his brother, he will obtain 0.7 yuan more in observable marital and post-marital transfers as partial compensation. This marginal compensation estimate is quantitatively larger than any comparable estimate using North American data, suggesting that the unitary model is a useful model of resource allocation for sons in traditional agricultural families. As a supplement to Chapter 2, Chapter 3 investigates matchmakers’ negotiation role in rural Chinese marriages and its impact on marital transfer from the parents to the children at the time of marriage. Using a unique household-level dataset collected in Hebei province, I find that a negotiator’s involvement can raise the total marital transfer by 20 percent, which supports my public goods story.

The growing interest among consumers in the link between diet and health makes functional food one of the fastest growing sectors in the global food industry, especially functional dairy products. Understanding consumer choices with respect to functional food is an important and relatively new research area. Given the credence nature of functional food attributes, labelling plays a key role in allowing consumers to make informed choices about foods with enhanced health attributes. In 2007, Canada launched a review of the regulatory system for health claims on functional foods, which included rules concerning the approval, labelling and verification of health claims. In 2010 two new health claims related to oat products and plant sterols were approved by Health Canada. An analysis of how consumers respond to health claim information is therefore timely. This thesis focuses on examining the effects of different types of labelling and verification of health claims on consumers stated preferences for a specific functional food product, Omega-3 milk. The analysis incorporates reference-dependent effects. This study improves the knowledge of Canadian consumer understanding of health claims and the impact of health claims on consumer choice. This research is one of the first studies to simultaneously examine the effects of different types of health claims (e.g. function claims, risk reduction claims and disease prevention claims) and other ways of signalling or implying health benefits (e.g. symbols) on Canadian consumers' functional food choices. This study contributes to the knowledge in this domain by providing a comparative analysis of different types of labelling strategies. The extant knowledge of labelling effects in the formats of risk reduction claims, disease prevention claims and symbols or imagery on functional foods is limited. One of the primary contributions of this study is addressing this gap in the literature. The theoretical framework of this thesis is based on random utility theory. A stated preference choice experiment is designed to examine consumers' response to Omega-3 milk under different labelling scenarios. Using data from an online survey of 740 Canadians conducted in summer 2009, discrete choice models, including Conditional Logit, Random Parameter Logit and Latent Class models, and Willingness-To-Pay (WTP) values are estimated. The results suggest that full labelling (function claims, risk reduction claims and disease prevention claims) is preferred over partial labelling (e.g. the use of a heart symbol to imply a health claim), but primarily for risk reduction claims. There is no significant difference between a function claim, such as "good for your heart" and partial labelling in the form of a red heart symbol. The results also suggest that consumers on average respond positively to verification of health claims by government and the third party agencies, however, the Latent Class models reveal considerable heterogeneity in consumer attitudes toward the source of verification. The influences of key-socio-demographic (e.g. income, education and health status) and attitudinal factors (e.g. attitude, trust and knowledge) provide further insights into consumer responses in the choice experiment to identify different consumer segments. Moreover, the results reveal reference-dependent effects where perceived losses of ingredient or price attributes have a greater influence on consumer choice than perceived gains. In terms of industry and public policy implications, this study suggests that food manufacturers in Canada would benefit from the ability to make more precise health claims. The implications derived from the Latent Class Models could help the Canadian functional food industry to identify target consumer segments with different characteristics for the purpose of developing marketing strategies. Furthermore, the results of this study suggest that Canadian consumers are receptive to both full labelling and partial labelling. It indicates that public policy makers need to pay attention to effectively regulating health claims for functional foods so as to balance the need for credible health claims to facilitate the development of the functional food sector with the imperative of protecting consumers from misleading health claims. Public policy makers should also be aware that the verification of health claims plays an important role in reducing consumers' uncertainty and making health claims more credible.

The growing interest among consumers in the link between diet and health makes functional food one of the fastest growing sectors in the global food industry, especially functional dairy products. Understanding consumer choices with respect to functional food is an important and relatively new research area. Given the credence nature of functional food attributes, labelling plays a key role in allowing consumers to make informed choices about foods with enhanced health attributes. In 2007, Canada launched a review of the regulatory system for health claims on functional foods, which included rules concerning the approval, labelling and verification of health claims. In 2010 two new health claims related to oat products and plant sterols were approved by Health Canada. An analysis of how consumers respond to health claim information is therefore timely. This thesis focuses on examining the effects of different types of labelling and verification of health claims on consumers stated preferences for a specific functional food product, Omega-3 milk. The analysis incorporates reference-dependent effects. This study improves the knowledge of Canadian consumer understanding of health claims and the impact of health claims on consumer choice. This research is one of the first studies to simultaneously examine the effects of different types of health claims (e.g. function claims, risk reduction claims and disease prevention claims) and other ways of signalling or implying health benefits (e.g. symbols) on Canadian consumers' functional food choices. This study contributes to the knowledge in this domain by providing a comparative analysis of different types of labelling strategies. The extant knowledge of labelling effects in the formats of risk reduction claims, disease prevention claims and symbols or imagery on functional foods is limited. One of the primary contributions of this study is addressing this gap in the literature. The theoretical framework of this thesis is based on random utility theory. A stated preference choice experiment is designed to examine consumers' response to Omega-3 milk under different labelling scenarios. Using data from an online survey of 740 Canadians conducted in summer 2009, discrete choice models, including Conditional Logit, Random Parameter Logit and Latent Class models, and Willingness-To-Pay (WTP) values are estimated. The results suggest that full labelling (function claims, risk reduction claims and disease prevention claims) is preferred over partial labelling (e.g. the use of a heart symbol to imply a health claim), but primarily for risk reduction claims. There is no significant difference between a function claim, such as "good for your heart" and partial labelling in the form of a red heart symbol. The results also suggest that consumers on average respond positively to verification of health claims by government and the third party agencies, however, the Latent Class models reveal considerable heterogeneity in consumer attitudes toward the source of verification. The influences of key-socio-demographic (e.g. income, education and health status) and attitudinal factors (e.g. attitude, trust and knowledge) provide further insights into consumer responses in the choice experiment to identify different consumer segments. Moreover, the results reveal reference-dependent effects where perceived losses of ingredient or price attributes have a greater influence on consumer choice than perceived gains. In terms of industry and public policy implications, this study suggests that food manufacturers in Canada would benefit from the ability to make more precise health claims. The implications derived from the Latent Class Models could help the Canadian functional food industry to identify target consumer segments with different characteristics for the purpose of developing marketing strategies. Furthermore, the results of this study suggest that Canadian consumers are receptive to both full labelling and partial labelling. It indicates that public policy makers need to pay attention to effectively regulating health claims for functional foods so as to balance the need for credible health claims to facilitate the development of the functional food sector with the imperative of protecting consumers from misleading health claims. Public policy makers should also be aware that the verification of health claims plays an important role in reducing consumers' uncertainty and making health claims more credible.