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.

<p>In the first chapter of this dissertation, I outline a hedonic equilibrium model that explicitly controls for moving costs and forward-looking behavior. Hedonic equilibrium models allow researchers to recover willingness to pay for spatially delineated amenities by using the notion that individuals "vote with their feet." However, the hedonic literature and, more recently, the estimable Tiebout sorting model literature, has largely ignored both the costs associated with migration (financial and psychological), as well as the forward-looking behavior that individuals exercise in making location decisions. Each of these omissions could lead to biased estimates of willingness to pay. Building upon dynamic migration models from the labor literature, I estimate a fully dynamic model of individual migration at the national level. By employing a two-step estimation routine, I avoid the computational burden associated with the full recursive solution and can then include a richly-specified, realistic state space. With this model, I am able to perform non-market valuation exercises and learn about the spatial determinants of labor market outcomes in a dynamic setting. Including dynamics has a significant positive impact on the estimates of willingness to pay for air quality. In addition, I find that location-specific amenity values can explain important trends in observed migration patterns in the United States.</p><p>The second chapter of this dissertation describes a model which estimates willingness to pay for air quality using property value hedonics techniques. Since Rosen's seminal 1974 paper, property value hedonics has become commonplace in the non-market valuation of environmental amenities, despite a number of well-known methodological problems. In particular, recovery of the marginal willingness to pay function suffers from important endogeneity biases that are difficult to correct with instrumental variables procedures [Epple (1987)]. Bajari and Benkard (2005) propose a "preference inversion" procedure for recovering heterogeneous measures of marginal willingness to pay that avoids these problems. However, using cross-sectional data, their approach imposes unrealistic constraints on the elasticity of marginal willingness to pay. Following Bajari and Benkard's suggestion, I show how data describing repeat purchase decisions by individual home buyers can be used to relax these constraints. Using data on ozone pollution in the Bay Area of California, I find that endogeneity bias and flexibility in the shape of the marginal willingness to pay function are both important.</p><p>Finally, in the third chapter of this dissertation, I combine the insights of the Bajari-Benkard inversion approach employed in second chapter with more standard estimation techniques (i.e., Rosen (1974)) to arrive at a new hedonic methodology that allows for flexible and heterogeneous preferences while avoiding the endogeneity problems that plague the traditional Rosen two-stage model. Implementing this estimator using the Bay Area ozone data, I again find evidence of considerable heterogeneity and of endogeneity bias. In particular, I find that a one unit deterioration in air quality (measured in days in which ozone levels exceed the state standards) raises marginal willingness to pay by $145.18 per year. The canonical two-stage Rosen model finds, counter-intuitively, that this same change would reduce marginal willingness to pay by $94.24.</p> / Dissertation

<p>In this dissertation, I discuss two important factors in individuals' decision-making processes: subjective expectation bias and time-inconsistent preferences. In Chapter I, I look at how individuals' own subjective expectations about certain future events are different from what actually happens in the future, even after controlling for individuals' private information. This difference, which is defined as the expectation bias in this paper, is found to have important influence on individuals' choices. Specifically, I look into the relationship between US elderly's subjective longevity expectation biases and their smoking choices. I find that US elderly tend to over-emphasize the importance of their genetic makeup but underestimate the influence of their health-related choices, such as smoking, on their longevity. This finding can partially explain why even though US elderly are found to be more concerned with their health and more forward-looking than we would have concluded using a model which does not allow for subjective expectation bias, we still observe many smokers. The policy simulation further confirms that if certain public policies can be designed to correct individuals' expectation biases about the effects of their genes and health-related choices on their longevity, then the average smoking rate for the age group analyzed in this paper will go down by about 4%.</p><p>In Chapter II, my co-author, Hanming Fang, and I look at one possible explanation to the under-utilization of preventive health care in the United States: procrastination. Procrastination, the phenomenon that individuals postpone certain decisions which incur instantaneous costs but bring long-term benefits, is captured in economics by hyperbolic discount factors and the corresponding time-inconsistent preferences. This chapter extends the semi-parametric identification and estimation method for dynamic discrete choice models using Hotz and Miller's (1993) conditional choice probability approach to the setting where individuals may have hyperbolic discounting time preferences and may be naive about their time inconsistency. We implement the proposed estimation method to US adult women's decisions of undertaking mammography tests to evaluate the importance of present bias and naivety in the under-utilization of mammography, controlling for other potentially important explanatory factors such as age, race, household income, and marital status. Preliminary results show evidence for both present bias and naivety in adult women's decisions of undertaking mammography tests. Using the parameters estimated, we further conduct some policy simulations to quantify the effects of the present bias and naivety on the utilization of preventive health care in the US.</p> / Dissertation

<p>This dissertation consists of three chapters relating to</p> <p>identification and inference in dynamic microeconometric models</p> <p>including dynamic discrete games with many players, dynamic games with</p> <p>discrete and continuous choices, and semiparametric binary choice and</p> <p>duration panel data models.</p> <p>The first chapter provides a framework for estimating large-scale</p> <p>dynamic discrete choice models (both single- and multi-agent models)</p> <p>in continuous time. The advantage of working in continuous time is</p> <p>that state changes occur sequentially, rather than simultaneously,</p> <p>avoiding a substantial curse of dimensionality that arises in</p> <p>multi-agent settings. Eliminating this computational bottleneck is</p> <p>the key to providing a seamless link between estimating the model and</p> <p>performing post-estimation counterfactuals. While recently developed</p> <p>two-step estimation techniques have made it possible to estimate</p> <p>large-scale problems, solving for equilibria remains computationally</p> <p>challenging. In many cases, the models that applied researchers</p> <p>estimate do not match the models that are then used to perform</p> <p>counterfactuals. By modeling decisions in continuous time, we are able</p> <p>to take advantage of the recent advances in estimation while</p> <p>preserving a tight link between estimation and policy experiments. We</p> <p>also consider estimation in situations with imperfectly sampled data,</p> <p>such as when we do not observe the decision not to move, or when data</p> <p>is aggregated over time, such as when only discrete-time data are</p> <p>available at regularly spaced intervals. We illustrate the power of</p> <p>our framework using several large-scale Monte Carlo experiments.</p> <p>The second chapter considers semiparametric panel data binary choice</p> <p>and duration models with fixed effects. Such models are point</p> <p>identified when at least one regressor has full support on the real</p> <p>line. It is common in practice, however, to have only discrete or</p> <p>continuous, but possibly bounded, regressors. We focus on</p> <p>identification, estimation, and inference for the identified set in</p> <p>such cases, when the parameters of interest may only be partially</p> <p>identified. We develop a set of general results for</p> <p>criterion-function-based estimation and inference in partially</p> <p>identified models which can be applied to both regular and irregular</p> <p>models. We apply our general results first to a fixed effects binary</p> <p>choice panel data model where we obtain a sharp characterization of</p> <p>the identified set and propose a consistent set estimator,</p> <p>establishing its rate of convergence under different conditions.</p> <p>Rates arbitrarily close to <italic>n<super>-1/3</super></italic> are</p> <p>possible when a continuous, but possibly bounded, regressor is</p> <p>present. When all regressors are discrete the estimates converge</p> <p>arbitrarily fast to the identified set. We also propose a</p> <p>subsampling-based procedure for constructing confidence regions in the</p> <p>models we consider. Finally, we carry out a series of Monte Carlo</p> <p>experiments to illustrate and evaluate the proposed procedures. We</p> <p>also consider extensions to other fixed effects panel data models such</p> <p>as binary choice models with lagged dependent variables and duration</p> <p>models.</p> <p>The third chapter considers nonparametric identification of dynamic</p> <p>games of incomplete information in which players make both discrete</p> <p>and continuous choices. Such models are commonly used in applied work</p> <p>in industrial organization where, for example, firms make discrete</p> <p>entry and exit decisions followed by continuous investment decisions.</p> <p>We first review existing identification results for single agent</p> <p>dynamic discrete choice models before turning to single-agent models</p> <p>with an additional continuous choice variable and finally to</p> <p>multi-agent models with both discrete and continuous choices. We</p> <p>provide conditions for nonparametric identification of the utility</p> <p>function in both cases.</p> / Dissertation

American households spend over $30 billion on tourism and take over 177 million long-distance leisure trips each year. These trips, and the subsequent vehicle miles traveled, have a significant impact on the transportation systems at major destinations across the country, especially those destinations that are still improving their transportation systems. Surprisingly, not much is known related to this type of travel. This dissertation expands the current knowledge of tourism travel behavior, in terms of how people make decisions regarding long-distance leisure activities and time use. Specifically, this dissertation develops and comprehensively examines a behavioral framework for household tourism time use and activity patterns. This framework combines (and builds upon) theory and methods from both transportation and tourism research fields such that it can be used to improve tourism demand modeling. This framework takes an interdisciplinary approach to describe how long distance leisure travelers allocate and maximize their time use across various types of activities. It also considers the many levels of tourism time use and activity patterns, including the structuring the broad annual leisure activity and time budget, forming individual tourism trips within the defined budget, and selecting specific activities and timing during each distinct tourism trip. Subsequently, this dissertation will additionally apply the time use and activity participation behavioral framework to four critical tourism research topics to demonstrate how the tourism behavioral framework can effectively be used to provide behavioral insights into some of the most commonly studied critical tourism issues. These application topics include household participation in broad tourism travel activities, travel parties’ tourism destination and travel mode selection, individuals’ loyalty towards daily and tourism activities, and travel parties’ participation in combinations of specific tourism trip activities. These application studies incorporate a variety of data sources, decision makers, study scales, situation-appropriate modeling techniques, and economic/individual/environmental factors to capture all aspects of the decision and travel activity-making process. / text

<p>This dissertation consists of three separate essays that use dynamic models to better understand the human capital accumulation process. First, I analyze the role of migration in human capital accumulation and how migration varies over the business cycle. An interesting trend in the data is that, over the period of the Great Recession, overall migration rates in the US remained close to their respective long-term trends. However, migration evolved differently by employment status: unemployed workers were more likely to migrate during the recession and employed workers less likely. To isolate mechanisms explaining this divergence, I estimate a dynamic, non-stationary search model of migration using a national longitudinal survey from 2004-2013. I focus on the role of employment frictions on migration decisions in addition to other explanations in the literature. My results show that a divergence in job offer and job destruction rates caused differing migration incentives by employment status. I also find that migration rates were muted because of the national scope of the Great Recession. Model simulations show that spatial unemployment insurance in the form of a moving subsidy can help workers move to more favorable markets.</p><p>In the second essay, my coauthors and I explore the role of information frictions in the acquisition of human capital. Specifically, we investigate the determinants of college attrition in a setting where individuals have imperfect information about their schooling ability and labor market productivity. We estimate a dynamic structural model of schooling and work decisions, where high school graduates choose a bundle of education and work combinations. We take into account the heterogeneity in schooling investments by distinguishing between two- and four-year colleges and graduate school, as well as science and non-science majors for four-year colleges. Individuals may also choose whether to work full-time, part-time, or not at all. A key feature of our approach is to account for correlated learning through college grades and wages, thus implying that individuals may leave or re-enter college as a result of the arrival of new information on their ability and/or productivity. We use our results to quantify the importance of informational frictions in explaining the observed school-to-work transitions and to examine sorting patterns.</p><p>In the third essay, my coauthors and I investigate the evolution over the last two decades in the wage returns to schooling and early work experience. </p><p>Using data from the 1979 and 1997 panels of the National Longitudinal Survey of Youth, we isolate changes in skill prices from changes in composition by estimating a dynamic model of schooling and work decisions. Importantly, this allows us to account for the endogenous nature of the changes in educational and accumulated work experience over this time period. We find an increase over this period in the returns to working in high school, but a decrease in the returns to working while in college. We also find an increase in the incidence of working in college, but that any detrimental impact of in-college work experience is offset by changes in other observable characteristics. Overall, our decomposition of the evolution in skill premia suggests that both price and composition effects play an important role. The role of unobserved ability is also important.</p> / Dissertation

Hawaii’s pristine ocean and tropical environment is a keystone of Hawaii tourism and the state economy. Water pollution from stormwater and development threatens the beach quality to both residents and tourists. In order to understand the lost nonmarket value, we assess changes in quality of beach characteristics including water and sand quality, swimming safety conditions, and congestion using a Discrete Choice Experiment of recreational beach users. Further, we study willingness to pay (WTP) for water management strategies in Hawaii using another discrete choice experiment, including structural and nonstructural Best Management Practices, testing, monitoring, and educational efforts. Using a mixed logit model, beach quality results suggest similar preferences among resident and tourists. Both groups consistently have higher WTP to avoid poor quality levels versus obtaining excellent levels. Additionally, water quality is the single most important attribute. For the policy discrete choice experiment, both parties exhibit similar ranking of WTP to initiate water quality management strategies, with improved testing methods followed by education having the highest WTP. Lastly, we use Benefit-Cost analysis to find that all significant management strategies may be viable, since WTP is greater than the predicted cost of implementation based on expert opinion of Hawaiian policy leaders.

THE AUSTRALIAN HEALTH CARE SYSTEM has an overarching objective to improve the well-being of all Australians in an equitable and efficient manner. But like most developed economy health care systems, it has experienced a continual increase in demand for health care services along with increased pressure to improve efficiency, quality, and sustainability. To assist in health sector management, policy formulation, investment decisions and reform, the Australian government developed the National Health Performance Framework (NHPF). The NHPF employs performance indicators across nine dimensions of health care, including Effectiveness, Appropriateness, Efficiency, Responsiveness, Accessibility, Safety, Continuity, Capability, and Sustainability. While the National Health Performance Committee has recognised that performance indicators used within the NHPF are inadequate, this thesis argues that the solution is not a simple matter of collecting additional data and constructing new and ???improved??? indicators. Due to resource constraints within the health care system there is an implicit performance trade-off across dimensions. The NHPF must take into consideration the value individuals place on the health care dimensions to enable a shift of limited resources to those areas that are most valued. The starting point for the NHPF should be to determine what society wants out of a health system. The purpose of this thesis is to determine Australian society???s preferences for performance across the nine NHPF dimensions of health care. This is achieved using a choice modelling experiment, which describes the performance of the current health care system and alternative health care systems the government could work towards, and asks respondents to compare and choose which system they prefer. A mixed multinomial logit model is used to analyse respondent choices in order to incorporate alternative tastes across attributes, and correlation of tastes across alternatives and scenarios. Relative values attached to the nine NHPF dimensions of health care are calculated and preferences for the dimensions are ranked. The thesis concludes by exploring individual preferences derived form the choice modelling experiment in the context of social welfare theory. It also outlines the strengths and weaknesses of the methodology, provides suggestions for further research, and offers a use for social preferences in the development of performance frameworks within the Australian health care system.

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.