Doctor of Philosophy / Department of Economics / Philip G. Gayle / This dissertation is composed of two essays in the field of Industrial Organization. Specifically, the empirical studies are conducted by focusing on the market structure and competition issues in the airline industry. The first essay investigates entry deterrence through incumbents’ pricing strategies in the airline industry. Recent research finds evidence that incumbent airlines tend to cut fares in response to the “threat” of entry by Southwest Airlines. Instead of focusing on the entry threat by a single carrier, this essay re-examines this issue by looking at incumbent airlines’ price response when entry is threatened by a wider variety of potential entrant airlines. Results show that incumbents’ response vary by the identity of the firm making the threat. As expected, incumbents cut fares in response to the threat of entry by some potential entrants; however, a new result is also found that incumbents may respond by raising their fare depending on who is making the threat. The second essay looks into an antitrust-relevant issue in the airline industry. Proper antitrust analysis often focuses on whether the concerned differentiated products are truly competing with each other. This essay uses a structural econometric model to investigate whether nonstop and connecting air travel products effectively compete with each other. Estimate results suggest that connecting products may be an attractive alternative to nonstop products for leisure travelers but less so for business travelers. If connecting products are counterfactually eliminated, the empirical model predicts small price changes for nonstop products. This suggests that the two product types only weakly compete with each other and can be treated as being in separate product markets for antitrust purposes.

Thesis advisor: Frank Gollop / My doctoral dissertation consists of three essays in the field of Industrial Organization. The first two consider exclusive dealing contracts between upstream and downstream firms theoretically, while the third measures consumer substitution among geographically differentiated air travel products empirically. In the first chapter I study the ability of an incumbent seller to use exclusive dealing contracts to foreclose efficient entry when there are n downstream buyers, where n can be viewed as a measure of the degree of downstream competition. The effect of downstream competition on the ability of the upstream incumbent to use exclusive contracts anticompetitively depends on whether upstream firms compete over linear or two-part prices. The model also highlights an interesting effect of the sunk cost of upstream entry that is ignored in models with exactly two buyers. In the second chapter I investigate the ability of an incumbent monopolist to exclude a potential entrant via exclusive dealing contracts when these contracts include an agreement over price. I find that a simple entry game yields both exclusionary and entry equilibria. The exclusionary equilibrium is unique, however, under most reasonable assumptions; for example if buyers are downstream competitors, if entry or the marginal cost of the potential entrant are uncertain, or if the incumbent can commit not to compete for unsigned buyers. When buyers compete with one another downstream, the optimal guaranteed price is above (below) the marginal cost of the incumbent when downstream buyers compete over strategic complements (substitutes). In the third and final chapter (co-authored with Kyle Buika) I study the question of geographic market definition in the US airline industry. Though an accurate definition of an economic market is important for any study of industry, there is no rule governing what exactly constitutes a market. To define a market we must ask the question "between which products do consumers substitute,'' knowing that the answer to this question will depend on how "close'' products are to one another in product space, as well as how close they are to one another, and to consumers, in geographic space. We estimate a discrete choice model of air travel demand that uses known information about the locations of products and consumers, which allows us to study substitution patterns among air travel products at different airports. We evaluate the commonly used city-pair and airport-pair definitions of a market for air travel, and conclude that a city-pair is the appropriate definition. We also employ the Hypothetical Monopolist test for antitrust market definition, as defined by the Department of Justice and Federal Trade Commission, and conclude that the relevant geographic market for antitrust analysis is, according to this test, frequently more narrowly defined as an airport-pair. Finally we conduct merger simulations under different market definitions and compare the results to those obtained using our own results, and conclude that accounting for geography is important when studying mergers. / Thesis (PhD) — Boston College, 2011. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

Thesis advisor: Andrew Beauchamp / Thesis advisor: Peter Gottschalk / This dissertation examines how caregiving for an elderly parent affects an adult child's labor supply and wages. In the first chapter (co-authored with Courtney H. Van Houtven and Norma B. Coe) we identify the relationship between informal care and labor force participation in the United States, both on the intensive and extensive margins, and examine wage effects. We control for time-invariant individual heterogeneity; rule out or control for endogeneity; examine effects for men and women separately; and analyze heterogeneous effects by task and intensity. We find modest decreases--1.4-2.4 percentage points--in the likelihood of working for caregivers providing personal care. Male and female chore caregivers, meanwhile, are more likely to retire. For female care providers who remain working, we find evidence that they decrease work by 3-10 hours per week and face a 2.3-2.6 percent wage penalty. We find little effect of caregiving on working men's hours or wages except for a wage premium for male intensive caregivers. In the second chapter I formulate and estimate a dynamic discrete choice model of elder parent care and work to analyze how caregiving affects a woman's current and future labor force participation and wages. Intertemporal tradeoffs, such as decreased future earning capacity due to a current reduction in labor market work, are central to the decision to provide care. The existing literature, however, overlooks such long-term considerations. I depart from the previous literature by modeling caregiving and work decisions in an explicitly intertemporal framework. The model incorporates dynamic elements such as the health of the elderly parent, human capital accumulation and job offer availability. I estimate the model on a sample of women from the Health and Retirement Study by efficient method of moments. The estimates indicate that intertemporal tradeoffs matter considerably. In particular, women face low probabilities of returning to work or increasing work hours after a caregiving spell. Using the estimates, I simulate several government sponsored elder care policy experiments: a longer unpaid leave than currently available under the Family and Medical Leave Act of 1993; a paid work leave; and a caregiver allowance. The leaves encourage more work among intensive care providers since they guarantee a woman can return to her job, while the caregiver allowance discourages work. A comparison of the welfare gains generated by the policies shows that half the value of the paid leave can be achieved with the unpaid leave, and the caregiver allowance generates gains comparable to the unpaid leave. / Thesis (PhD) — Boston College, 2012. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

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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.