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京都大学 / 新制・課程博士 / 博士(経済学) / 甲第23669号 / 経博第652号 / 新制||経||300(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 山田 憲, 教授 西山 慶彦, 准教授 高野 久紀 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

This thesis examines the existence of a dominant route between a hub pair and factors that influence bike share cyclists route choices. This research collects 132,396 hub to-hub global positioning system (GPS) trajectories over a 12-month period between April 1, 2015 and March 31, 2016 from 750 bicycles provided by a bike share program (BSP) called SoBi (Social Bicycles) Hamilton. Then, a GIS-based map-matching toolkit is used to convert GPS points to map-matched trips and generate a series of route attributes. In order to create choice sets, unique routes between the same hub pair are extracted from all corresponding repeated trips using a link signature tool. The results from t statistics and Path-size logit models indicate that bike share cyclists are willing to detour for some positive features, such as bicycle facilities and low traffic volumes, but they also try to avoid too circuitous routes, turns, and steep slopes over 4% though detouring may come with a slight increase in turns. This research not only helps us understand BSP cyclist route preferences but also presents a GIS-based approach to determine potential road segments for additional bike facilities on the basis of such preferences. / Thesis / Master of Science (MSc)

Modern bike share systems (BSSs) allow users to rent from a fleet of bicycles at hubs across the designated service area. With clear evidence of cycling being a health-positive form of active transport, furthering our understanding of the underlying processes that affect BSS ridership is essential to continue further adoption. Using 286,587 global positioning system (GPS) trajectories over a 12-month period between January 1st, 2018 and December 31st, 2018 from a BSS called SoBi (Social Bicycles) Hamilton, the number of trips on every traveled link in the service area are predicted. A GIS-based map-matching toolkit is used to generate cyclists’ routes along the cycling network of Hamilton, Ontario to determine the number of observed unique trips on every road segment (link) in the study area. To predict trips, several variables were created at the individual link level including accessibility measures, distances to important locations in the city, proximity to active travel infrastructure (SoBi hubs, bus stops), and bike infrastructure. Linear regression models were used to estimate trips. Eigenvector spatial filtering (ESF) was used to explicitly model spatial autocorrelation. The results suggest the largest positive predictors of cycling traffic in terms of cycling infrastructure are those that are physically separated from the automobile network (e.g., designated bike lanes). Additionally, hub-trip distance accessibility, a novel measure, was found to be the most significant variable in predicting trips. A demonstration of how the model can be used for strategic planning of road network upgrades is also presented. / Thesis / Master of Science (MSc)

Public bike share systems have been recognized as an effective way to promote active and sustainable public transportation. With the health benefits of bike share becoming better understood, North American cities have continued to invest in cycling infrastructure and impose new policies to not only encourage the usage of bike share systems but also expand their operations to new cities. The city of Hamilton, Ontario, implemented its own bike share system in March 2015. Using the system’s global positioning system (GPS) data for annually aggregated trip departures, arrivals, and totals in 2017, this research explores various environment factors that have an impact on users’ bike share usage at hub level. Nine predictive linear regression models were developed for three different scenarios depending on the type of hubs and members for trip departures, arrivals, and totals. In terms of variance explained across the core service area, the models suggested the main factors that attract users were distance to McMaster University and the number of racks available at hubs. Furthermore, the working population and distance to the Central Business District and the closest bike lane in the immediate vicinity (200 m buffer) also played important roles as contributing factors. Based on the primary predictors, this research takes one step further and estimates potential trips at candidate sites to inform future expansion of public bike share system. The candidate locations were created on appropriate land uses by applying a continuous surface of regularly shaped cells, a hexagonal tessellation, on the area of interest. The estimated potential usage at candidate sites demonstrated that the east part of the city should be targeted for future bike share expansion. / Dissertation / Master of Science (MSc)

This dissertation consists of two essays. In the first essay, I examine the source of momentum in stock returns. The reversal of momentum returns has been interpreted as evidence that momentum results from delayed overreaction to information. I examine momentum and reversals conditional on firms’ share issuance (net of repurchases) during the momentum holding period and show that (1) among losers, the momentum returns are statistically significant, but the reversals are non-existent, for both issuers and non-issuers; (2) among winners, momentum and reversals are restricted to issuers, but are non-existent among non-issuers. After further conditioning on firm size, I find that winner reversals are restricted to small, equity issuing firms. After excluding these small issuers from the sample, the remaining firms have strong momentum profits with no accompanying reversals. The evidence suggests that the return reversals are a manifestation of the poor performance of equity issuing firms. Further, while investor overreaction potentially contributes to the momentum among winners, a large fraction of firms do not earn any significant abnormal returns following initial price continuation, suggesting that underreaction, and not delayed overreaction to information, is the dominant source of momentum in stock returns. In the second essay, I examine alternative explanations of reversals in stock returns. George and Hwang (2007) find that long-term reversals in stock returns are driven by investors’ incentive to defer payment of taxes on locked-in capital gains rather than by overreaction to information. I show that return reversals are instead attributable to the negative relationship between firms’ composite share issuance and future stock returns documented in Daniel and Titman (2006). The ability of locked-in capital gains measures to forecast stock returns is largely subsumed by the composite share issuance measure. My results do not support the hypothesis that capital gains taxes drive long-term return reversals. / Ph. D.

This dissertation looks at the relationship between airport size (e.g. small, medium, large) and air service continuity and operational performance. It consists of three studies, each written in journal format. The first study analyzes the markets served pre- and post-recession while focusing on the operational strategies adopted by the top Major Carriers and Low-Cost Carriers (LCCs) in the United States. Findings show that LCCs have outpaced major carriers in terms of expanding their network and the number of markets served. During the same time, major carriers have gained a greater flight share in the markets they already serve. Post-recession, LCCs have shown preference to competing with major carriers over other LCCs. The second study investigates the declining service levels at small airports compared to large-hub airports, which continue to benefit from higher levels of service and increased airline presence. Using a fixed-effects conditional logistic regression, this study looked at factors contributing to service loss in region-to-region markets serving small communities between 2007 and 2013. Results show that 1) markets affected by a merger are indeed at a higher risk of losing service; 2) markets that are operated by a fuel-intensive, small-aircraft fleet have a higher chance to be discontinued and 3) an increased number of competitors greatly reduces potential market service loss. The third and final study proposes a new methodology to calculate original delay and propagated delays using combined aviation operational datasets that provide detailed flight information and causal factors behind delays. In addition to calculating original and propagated delay for the month of July of 2018, this study differentiated between original delays that occur during the turnaround phase, taxiing phase and en-route and incorporates causal factor information to identify the true source behind propagated delay. Two fixed-effects linear regression models were introduced that predict Total Propagated Delay and the share of propagated delay given an airport's ability to absorb upstream delay during the turnaround phase. Results show that most delay propagation chains originate at large-hub airports and are mostly concentrated at airports within the same geographical area. However, delays originating at large-hub airports were found to be the quickest to recover (i.e. least number of downstream flight legs affected) and large-hub airports have a higher ability to absorb delay at the turnaround phase compared to smaller airports given the significantly higher schedule buffer time airlines plan at large-hub airports. / Doctor of Philosophy / The changing nature of the air service industry is dependent on several key factors, including but not limited to the major and low-cost airlines, the frequency of service at different sized-airports and the operational performance of the airports in the system. Each airport can be classified by size based on the annual number of enplanements. This dissertation looks at the relationship between airport size (e.g. small, medium, large), service continuity and operational performance. It consists of three studies, each written in journal format. Over the past two decades, the U.S. air transportation network witnessed several economic downturns forcing airlines to shift their operational strategies, cease service or merge with an airline counterpart. The first study analyzes routes served before and after the recession by exploring the presence of major and low-cost carriers in these markets to understand how several economic downturns have influenced the operating strategy of airlines in the US. While Low-cost carriers focused on expanding their network and offering service in an increased number of new routes, major carriers increased their presence in the markets in which they already serve. Furthermore, after the recession, low-cost carriers chose to increasingly compete with major carriers over their low-cost counterparts. The second study explored the factors that can potentially contribute to the loss of service in routes serving small communities. While airlines continue to compete on the most profitable routes, small airports recently suffered from reduced service levels and in some instance service discontinuity. Results show that 1) routes that were once served by two airlines that merged are at a higher risk of losing service; 2) routes that are operated by a fuel-intensive small aircraft fleet have a higher chance to be discontinued and 3) an increased presence of airlines competing in a route greatly reduces potential service loss. In addition to evaluating service continuity, the third and final study looks at flight delays across the US and dives into the effect of airport size on propagated delay. Delays on a flight can be caused by inefficiencies and capacity restrictions at airports and may also be the result of delay that happen earlier in the day and that propagates to multiple flights downstream that share the same resources. That is, a delay can affect multiple flights whenever these flights are all operated by the same aircraft equipment. Costing the air transportation network billions of dollars annually, the third study examines the original and propagated delays at US airports by collecting data from multiple sources to incorporate the original source and cause of delay. Results show that most delay originates at large-hub airports and are mostly concentrated at airports within the same geographical area. However, delays originating at large-hub airports were found to be the quickest to recover and large-hub airports have a higher ability to absorb delay at the turn compared to smaller airports as airlines allocate additional minutes of schedule padding at large-hub airports.

The objective of this study is to determine Virginia dairy producers’ competitiveness in an industry that is experiencing changing policy and marketing conditions. The competitiveness of Virginia dairy producers is examined in a National Dairy Model that compares both producers’ cost of production across market areas and spatial relationships among producers and consumers. The National Dairy Model (NDM) is a mathematical programming model that minimizes the total costs of producing milk and the assembly costs of shipping dairy products to the final consumer. A state's cost of production in the NDM is determined with a translog cost function. The cost functions are estimated with data collected in the 1989 and 1993 dairy versions of the Farm Costs and Returns Survey (FCRS). The supply and demand information in the NDM is annual data for 1994. Transportation costs are determined with current hauling rates and actual mileage between supply and demand points. Once the costs of production and spatial components of the NDM are formulated, the NDM is solved using the General Algebraic Modeling System (GAMS). The NDM is evaluated under the guidelines of several different scenarios. For example, some alternative marketing scenarios that provide important information about the future of the dairy industry are (1) simulations where the hauling rates are varied, (2) scenarios in which the U.S. becomes a major participant in the export market, and (3) situations where the marketing environment leads to increasing costs of production. Another alternative scenario involves only the spatial dimension of the NDM. Given the current marketing conditions in the dairy industry, the results of the NDM indicate that Virginia dairy producers are competitive in a marketing environment where the location of milk production is determined by a producer's costs of production and location advantages. Using Virginia's translog cost function, the cost per cwt. at the mean of the FCRS production data is $10.60. The cost estimate applies to Virginia's representative dairy farm where the average herd size is 91 cows and annual production per cow is 14,160 pounds. With these estimates and the fact that Virginia producers are near large population centers, the results of the NDM show that Virginia dairy farms are competitive in a deregulated market. / Ph. D.

<p dir="ltr">This study explores the net return and risk associated with different farmland leases, focusing on the tenant’s perspectives. The types of leases investigated include cash rent, crop-share, and eight flex leases. Utilizing data from a case farm in west-central Indiana and employing the @Risk simulation software, the study assesses the financial performance and risk exposure of each lease type. The study's objectives include evaluating net return and risk through simulation models. Hypotheses suggest crop-share leases exhibit lower tenant risk, cash rent leases present higher tenant risk, and flex leases more effectively distribute risk between tenants and landlords. Results indicate that, for risk-averse operators, crop-share leases prove advantageous, while cash rent leases offer higher net returns at the expense of increased risk. Flex leases provide a balanced alternative, mitigating risk while achieving higher net returns than a crop share lease. Stochastic dominance analysis supports the suitability of crop-share and specific flex leases for various risk preferences. Downside risk analysis emphasizes the importance of considering the lower tails of net return distributions. The crop-share lease consistently demonstrates more favorable downside risk characteristics, making it an appealing choice for risk-averse tenants.</p><p dir="ltr">In conclusion, the study contributes valuable insights into the complexities of farmland leasing, offering a nuanced understanding of the trade-offs between net return and risk for different lease types. The results provide practical guidance for tenants seeking leases aligned with their risk preferences and financial goals.</p>