On-Demand Mobility (ODM) is a concept to address congestion problems. Using electric aircraft and vertical take-off with limited landing (VTOL) capabilities, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A conditional logit model was developed to estimate mode choice behavior and to estimate ODM demand; presenting automobile and public transportation as the two competing modes to ODM. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. Nine scenarios were run varying the input for a base fare, landing fare, cost per-passenger-mile, auto operational costs, and ingress (waiting) times. The results yielded sensitivity of demand to all these parameters and especially showed a great difference in demand when auto costs were decreased from the standard American Automobile Association (AAA) cost per mile to a likely, future auto operating cost. The challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1. / Master of Science / On-Demand Mobility (ODM) is a concept to address congestion problems. Using an electric propulsion aircraft, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time; an “air taxi” or “air Uber” as coined by media outlets. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A model was developed to estimate mode choice behavior and to estimate ODM demand based on existing travel behavior and patterns in the Northern California region. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. The results from the model yielded sensitivity of demand to these challenges and especially showed a great difference in demand as the cost of operating the car decreases in the future, making it a great competitor to the ODM concept. The major challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1.

我國廠商自1980年代中期以後，由於台幣升值、工資上漲、環保意識抬頭以及土地取得不易等因素導致競爭力下降，紛紛至國外投資設廠生產，此時台商對外投資的區域大都集中於東南亞和美國。1987年政府開放民眾赴大陸探親，使香港亦成為台商投資大陸的中繼站，1991年政府更直接開放廠商前往大陸直接投資；而日本的投資案件也伴隨市場開放逐漸增加。隨著歐洲聯盟的經濟暨貨幣聯盟Economic and Monetary Union（EMU）的醞釀與開始運作，以及中、東歐的共產封閉經濟體系逐漸向外開放，自1990年起台商也逐漸增加對歐洲的投資。因此，瞭解影響台商對外直接投資區位選擇的因素，是值得研究的課題。 本研究以1988-1997年經濟部投審會所核准的對外投資廠商作為實證研究對象，投資區位則依地主國地緣位置及經濟發展程度劃分為北美洲、歐洲、亞洲已開發國家或新興工業化國家以及大陸與東南亞國家等四大區位。並以McFadden（1974）的Conditional Logit Model作為實證模型，探討勞動成本、資金成本、市場大小、基礎建設、及群聚效果在台商對外直接投資區位的選擇決策中所扮演的角色。 本研究結果發現，在勞動成本方面，低廉的工資對赴大陸與東南亞國家以及歐洲投資的台商有吸引力。在資金成本方面，除了租稅競爭的亞洲國家之外，低稅率是吸引台商前往海外投資的一大因素。在市場要素方面，龐大消費市場的潛在商機不容許台商忽視其存在。基礎建設的良窳僅影響台商對北美洲投資的意願；對其他區域而言，中央政府經濟事務性支出愈高或許代表著當地基礎建設的不足而阻礙了台商的投資意願。至於群聚效果則是影響台商對外投資區位選擇的要素之一，但對於至亞洲已開發或新興工業化國家投資的台商而言，群聚負效果是他們望而卻步的。

We analyze empirically the role played by energy inflation as a determinant of downward corrections in house prices. Using a dataset for 18 OECD economies spanning the last four decades, we identify periods of downward house price adjustment and estimate conditional logit models to measure the effect of energy inflation on the probability of these house price corrections after controlling for other relevant macroeconomic variables. Our results give strong evidence that increases in energy price inflation raise the probability of such corrective periods taking place. This phenomenon could be explained by various channels: through the adverse effects of energy prices on economic activity and income reducing the demand for housing; through the particular impact on construction and operation costs and their effects on the supply and demand of housing; through the reaction of monetary policy on inflation withdrawing liquidity and further reducing demand; through improving attractiveness of commodity versus housing investment on asset markets; or through a lagging impact of common factors on both variables, such as economic growth. Our results contribute to the understanding of the pass-through of oil price shocks to financial markets and imply that energy price inflation should serve as a leading indicator for the analysis of macro-financial risks. (authors' abstract)

<p>Wildlife species generate value through their consumptive and non-consumptive uses. Consumptive uses of these species include hunting and trapping, while wildlife watching is an example of a non-consumptive use. Understanding the value of various wildlife is imperative for public agencies’ management decisions regarding different wildlife areas (e.g., nature preserves, state forests/parks, reservoirs, county/city parks). Individuals’ values for wildlife interactions on public lands can depend on the context in which these interactions occur as well as the probability of an interaction occurring. We utilize a stated preference choice experiment to estimate Indiana residents’ willingness to pay (WTP) for a marginal increase in the chance of seeing white-tailed deer and five furbearing species (bobcat, coyote, river otter, raccoon, red fox) while engaging in their favorite activities at Indiana recreational areas. Our WTP estimates are analogous to value of statistical life (VSL) calculations, and hence we refer to them as the “value of a statistical species” (VSS). We find that the VSS of a bobcat ranges from $22.73 to $41.30, the VSS of a coyote ranges from -$1.94 to $9.74, the VSS of a raccoon ranges from $5.25 to $21.69, the VSS of a red fox ranges from $43.31 to $62.52, the VSS of a white-tailed deer ranges from $22.70 to $27.00, and the VSS of a river otter ranges from $23.18 to $45.98. Our analysis suggests that individuals’ values for wildlife depend on the activity they are undertaking when they see the wildlife.  </p>

台商製造業在中國大陸的投資區位選擇行為，依個體選擇理論來說，是受到廠商本身的特性與區域條件兩者的影響，本研究的重點放在區位條件的影響上。但由於台商也是中國大陸FDI的一環，因此在參考過去其他地區的FDI區位選擇實證後，本研究將針對台商研究中較為欠缺的區位選擇行為，架構出台商投資中國大陸的個體選擇模型，並以更細化的產業別分類探討各區域條件的影響效果。最後再透過訪談的過程，針對實證的結果加以再驗證，得到完整以區位條件為觀點所架構出的台商製造業區位選擇模式。 由本研究的研究成果中可以發現，台商還是延續了過去在台灣的生產模式，凸顯了台商對於中國大陸的投資重視聚集的特性。但在勞力因素、商業服務的集中度、國家高新政策上，則因產業別的不同而產生出較大的歧異。訪談的結果也顯示出勞力條件的影響將會在未來日漸弱化，這種趨勢是和生產要素的移動性息息相關。但台商在中國大陸的投資已注意到市場潛力的需求，也成為近來台商投資中國大陸區位選擇時的重要轉變。另一方面，在基礎建設的投資與國家產業政策的投入對各產業別的影響上，顯示不見得政府的投資與廠商的投入有絕對的正向關係，這可能和投資的效率性有關，必須更進一步探討；但就整體台商而言，則驗證了人為扶植的產業政策的確可以為地方帶來廠商的聚集，且訪談結果更認為產品性質的差異，會影響到廠商在區位選擇時，考量基礎運輸設施種類的需求，這一部份也因為投審會資料的限制而無法得到量化模型證實。而稅的負擔經過模型校估後得到顯著的負相關，在訪談的結果中，發現跟台商在會計上的習慣可能也有關。台商通常會以作帳的方式產生負債經營的狀況以隱藏實際獲利情形，使實際的所得稅負擔遠低於應負擔金額。 總之，本研究雖然是以各省市所能提供的區域條件來看待台商的區位選擇。但如勞力等生產要素在在流動性逐漸增強的趨勢下，的確可能削弱了地區條件的優勢，可是由政策與聚集所創造出來的地域條件，卻是不容易被替代的。本研究的結果證實的這樣的觀點，至少在目前台商投資大陸的情形中，還是深受這種創造出來的地域條件所影響，一旦聚集形成，就傾向於自我延續下去，強化了由地域觀點的角度來看廠商區位選擇的理由。但政策的介入卻要注意效率性的問題，這也是未來的研究可以發展的方向。

The purpose of this thesis is to investigate further whether oil price has an effect on house price inflation and additionally if it has a link to house price turning points. The methodology is grounded on the previous research paper made by Breitenfellner et al. (2015). The results are based on quarterly data from the countries; Finland, Denmark, Norway and Sweden through the time span of 1990-2018. A linear fixed regression model was performed including the explanatory variables of monetary policy and credit developments, macroeconomic fundamentals, housing market variable and demographic variables. Secondly, a logit model was used to identify a relationship between oil price and house price turning points. The model used misalignment made from GDP per capita and real interest rate. The empirical analysis confirms that there is a positive relationship between oil prices and house price inflation. This evidence contradicts a major share of previous research papers (see Bernanke, 2010; Kaufmann et al., 2011). However, there are also some previous papers (see Yiqi, (2017); Antonakakis et al., 2016) and theoretical linkages in line with a positive correlation. Concerning, the oil price and house price inflation no empirical significance was found regarding their relationship. For future research, one could include regional aspects for the purpose of controlling for geographical differences.

The Water Framework Directive requires reduced environmental impacts from human activities and for the assessment of the non-market benefits of pollution remediation schemes. This policy shift has exacerbated the research problems surrounding the physical, social and economic consequences of the relationship between land use and water quality. This research seeks to quantify the major socio-economic and environmental benefits for people which may arise as riverine pollution is reduced. To achieve these aims this research integrates primary data analyses combining choice experiment techniques with geographical information system based analyses of secondary data concerning the spatial distributions of riverine pollution. Current knowledge on the microbial quality of river water, measured by faecal indicator organism (FIO) concentrations and assessed at catchment scale, is inadequate. This research develops generic regression models to predict base- and high-flow faecal coliform (FC) and enterococci (EN) concentrations, using land cover and population (human and livestock) variables. The resulting models are then used both to predict FIO concentrations in unmonitored watercourses and to evaluate the likely impacts of different land use scenarios, enabling insights into the optimal locations and cost-effective mix of implementation strategies. Valuation experiments frequently conflate respondents’ preferences for different aspects of water quality. This analysis uses stated preference techniques to disaggregate the values of recreation and ecological attributes of water quality, thereby allowing decision makers to better understand the consequences of adopting alternative investment strategies which favour either ecological, recreational or a mix of benefits. The results reveal heterogeneous preferences across society; specifically, latent class analysis identifies three distinct groups, holding significantly different preferences for water quality. From a methodological perspective this research greatly enhances the ongoing synthesis of geographic and economic social sciences and addresses important policy questions which are of interest to a variety of stakeholders, including government departments and the water industry.

As an alternative renewable source for bioenergy, forest biomass has recently drawn more attention from the U.S. government and the general public. Woody biomass policies have been adopted to encourage the new bioenergy industry. A variety of state policy incentives attempt to create a desirable legal climate and lure new firms, imposing two important questions regarding state government policies and the sustainable use of forest resources. This dissertation sheds some light on these questions. The first paper constructs a woody biomass policy index through scoring each statute and weighting different categories of policies from the vantage point of renewable energy investment. It analyzes the disparity in the strength of state government incentives in the woody biomass utilization. The second paper employs a conditional logit model (CLM) to explore the effects of woody biomass policies on the siting decisions of new bioenergy projects. In addition, significant state attributes influencing the births of new bioenergy firms are identified such as resource availability, business tax climate, delivered pulpwood price, and the average wage rate. The third paper uses the Sub-Regional Timber Supply (SRTS) model to examine the regional aggregate forest biomass feedstock potential in Tennessee and to predict the impacts of additional pulpwood demand on the regional roundwood market through 2030. The fourth paper includes the benefits of thinning and logging residues in a dynamic optimization model to analyze how bioenergy policies will impact forest stock, harvest levels, optimal rotation, and silvicultural effort. The results may have substantial implications regarding woody biomass policies, the creation of a new bioenergy industry, and sustainable forest resource management. A lucrative state woody biomass policy support and tax climate can attract new bioenergy businesses. States endowed with abundant forest resources may choose to provide strong tax incentives to spur the birth of new plants. However, overuse of forest biomass can impact roundwood markets and traditional wood processing industries. How government incentives will affect the sustainability of natural resources can be diverse. These findings offer constructive insights in the enactment and implementation of new woody biomass legislation.

Traditionnellement, les migrants internes chinois migrent seuls et laissent derrière eux leurs époux et enfants. Depuis vingt ans, ils sont toutefois plus nombreux à migrer avec les membres de leur famille. Peu d’études ont été consacrées à ce type de migrants. Selon la théorie de la migration de Mincer, les migrants familiaux ne choisissent pas un lieu de destination de la même façon que les migrants individuels. Ils ne sont pas attirés par les mêmes facteurs que les migrants individuels. En nous basant sur la littérature sur le sujet, qui met en relief le rôle des facteurs économiques dans la décision de migrer, nous nous posons alors la question de recherche suivante : les facteurs économiques ont-ils plus d’incidence sur le choix de destination pour les individus que les familles. En contrepartie, ces derniers seraient, plus que ceux qui migrent seuls, motivés par des facteurs environnementaux ou socio-sanitaires? Nos analyses sont effectuées avec les données de l’Enquête chinoise dynamique sur les migrants de 2014, qui contient des informations sur 200 937 migrants résidant dans 346 villes, et de l’Annuaire statistique des villes chinoises. Les analyses statistiques sont réalisées avec un modèle logit conditionnel, qui permet de déduire, sachant qu’une migration a eu lieu, l’attractivité des villes liée à leurs caractéristiques géographiques, économiques, sociales ou encore environnementales. Nos résultats suggèrent que les migrants familiaux sont en effet moins motivés que les migrants individuels par des facteurs économiques favorables dans les villes de destination, tels que des revenus moyens élevés, une quantité élevée de dépenses dans l’immobilier, une proportion élevée d’entreprises privées et de travailleurs autonomes, un taux de chômage bas et une proportion élevée d’emplois dans le secteur secondaire. Nos résultats indiquent aussi que les migrants familiaux sont motivés par certaines caractéristiques socio-sanitaires telles que la quantité de dépenses dans l’éducation, les sciences et la technologie et de lits d’hôpitaux. Nous remarquons que ces effets sont plus forts chez les migrants ayant eu des enfants avant de migrer et vivant avec ceux-ci au moment de l’enquête. Nous notons par ailleurs que certains de ces résultats sont affectés par un effet d’âge, qui peut être confondu avec le cycle de vie familiale, les migrants familiaux étant en général plus âgés que ceux ou celles qui migrent seuls. / Traditionally, Chinese internal migrants migrate alone and leave behind their spouse and children. Over the past twenty years, more migrants have migrated with members of their nuclear family (Fan et al., 2011, Fan et Li, 2019, Duan et al., 2008). Few studies have been devoted to this type of migrants. According to Mincer’s migration theory (1977), family migrants do not choose a place of destination in the same way as individual migrants. They also are not attracted by the same pull factors as individual migrants. The purpose of our research is to address the following question: Do the economic factors have a greater impact on the destination choice of families when compared to individuals, the former being more motivated by environmental, social and health factors? Our analyzes are performed with data from the 2014 China Migrants Dynamic Survey, which contains information on 200,937 migrants residing in 346 cities, and the Statistical Yearbook of Chinese Cities. The statistical analyses are performed with a conditional logit model. The results indicate that family migrants are less motivated than individual migrants by favourable economic factors such as high average incomes, high proportion of private businesses and self-employed workers, high amount of spending on real estate, high proportion of high employment in the secondary sector and low unemployment rate. Our results also allow us to conclude that family migrants are motivated by certain social and health characteristics such as the quantity of hospital beds and the amount of expenditure on education, science, and technology. We note that these effects are more important among migrants who had children before migrating and living with them at the time of the survey. However, we observe that some of these results are due to an age effect.