This thesis compares different approaches to estimating budgets for Kuhn-Tucker (KT) demand systems, more specifically for the multiple discrete-continuous extreme value (MDCEV) model. The approaches tested include: (1) The log-linear regression approach (2) The stochastic frontier regression approach, and (3) arbitrarily assumed budgets that are not necessarily modeled as a function of decision maker characteristics and choice-environment characteristics. The log-linear regression approach has been used in the literature to model the observed total expenditure as way of estimating budgets for the MDCEV models. This approach allows the total expenditure to depend on the characteristics of the choice-maker and the choice environment. However, this approach does not offer an easy way to allow the total expenditure to change due to changes in choice alternative-specific attributes, but only allows a reallocation of the observed total expenditure among the different choice alternatives. To address this issue, we propose the stochastic frontier regression approach. The approach is useful when the underlying budgets driving a choice situation are unobserved, but only the expenditures on the choice alternatives of interest are observed. The approach is based on the notion that consumers operate under latent budgets that can be conceived (and modeled using stochastic frontier regression) as the maximum possible expenditure they are willing to incur. To compare the efficacy of the above-mentioned approaches, we performed two empirical assessments: (1) The analysis of out-of-home activity participation and time-use (with a budget on the total time available for out-of-home activities) for a sample of non-working adults in Florida, and (2) The analysis of household vehicle type/vintage holdings and usage (with a budget on the total annual mileage) for a sample of households in Florida. A comparison of the MDCEV model predictions (based on budgets from the above mentioned approaches) demonstrates that the log-linear regression approach and the stochastic frontier approach performed better than arbitrarily assumed budgets approaches. This is because both approaches consider heterogeneity in budgets due to socio-demographics and other explanatory factors rather than arbitrarily imposing uniform budgets on all consumers. Between the log-linear regression and the stochastic frontier regression approaches, the log-linear regression approach resulted in better predictions (vis-à-vis the observed distributions of the discrete-continuous choices) from the MDCEV model. However, policy simulations suggest that the stochastic frontier approach allows the total expenditures to either increase or decrease as a result of changes in alternative-specific attributes. While the log-linear regression approach allows the total expenditures to change as a result of changes in relevant socio-demographic and choice-environment characteristics, it does not allow the total expenditures to change as a result of changes in alternative-specific attributes.

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。

The aim of this thesis is to study the effect of smoking and drinking on wages in Sweden. The data used in this study is the Swedish Level-of-living survey (LNU) from 1991. A multinomial logit model and the marginal effects from the estimated model are used to study the effect of smoking and drinking on wages in Sweden. The empirical results conclude that medium drinking increases the probability of having a high income, i.e. there is a positive significant relationship between medium drinking and wages in Sweden. Also concluded from the empirical results is that there is not a significant relationship between smoking and wages in Sweden.

This thesis investigates the associations between crash outcomes, the existence and type of driver distraction as well as driver’s age. The crash outcomes considered in this thesis consist of the type of crash as well as the injury severity sustained by occupants involved in the crash. An ordered logit model was built to predict the likelihood of severe injuries and a multinomial model was developed to predict the likelihood that a driver will be involved in one of three common crash types: singular, angular, and rearend. In these models, various factors (e.g., weather, driver’s gender, and speeding) have been statistically controlled for, but the main focus was on the interaction of driver’s age and distraction type. The findings of this thesis have implications for policy making and prioritizing capabilities of distraction-related safety systems.

This thesis investigates the associations between crash outcomes, the existence and type of driver distraction as well as driver’s age. The crash outcomes considered in this thesis consist of the type of crash as well as the injury severity sustained by occupants involved in the crash. An ordered logit model was built to predict the likelihood of severe injuries and a multinomial model was developed to predict the likelihood that a driver will be involved in one of three common crash types: singular, angular, and rearend. In these models, various factors (e.g., weather, driver’s gender, and speeding) have been statistically controlled for, but the main focus was on the interaction of driver’s age and distraction type. The findings of this thesis have implications for policy making and prioritizing capabilities of distraction-related safety systems.

Travelers' value of travel time savings (VTTS) are often used to estimate the benefits of transportation facilities, including managed lanes (MLs). With various eligibility criteria and time of day pricing on the MLs, the VTTS estimation is complicated. This is evident by the underestimation of VTTS on MLs in many of the previous studies. This study investigates stated preference (SP) survey design strategies and differentiating the VTTS for ordinary and some common urgent situations faced by the travelers in an attempt to improve on VTTS estimation on MLs. This study used three different survey design strategies (including a D-efficient design) in an internet based survey of Katy Freeway travelers. It was found that a random attribute level generation strategy, where the VTTS presented in the alternative was adjusted based on the answer to a previous SP question, performs better than the other two designs with respect to VTTS estimation and other survey design efficiency criteria. The analysis to differentiate the VTTS for ordinary and urgent trips was carried out using the state of art in the mixed logit model estimation. It was found that travelers value their travel time savings much more when facing most of these urgent situations rather than ordinary situations. Both peak and off-peak period travelers' VTTS were also found to be significantly greater when on urgent trips. Survey design attribute level ranges were found to significantly affect the VTTS estimation. Further, in order to understand the policy implications of these findings it was demonstrated that classifying all trips as ordinary can significantly underestimate the VTTS benefits offered by the MLs. Additionally, the VTTS of any urgent trips would be greatly underestimated. The study also demonstrated that many of the low and medium income group travelers on urgent trips can have VTTS greater than that of the highest VTTS traveler from the high income group on an ordinary trip. These findings have significant policy implications since the benefits of MLs (and of most transportation investments) are primarily derived from travel time savings. Underestimating the VTTS and hence the benefits for MLs can result in reducing the likelihood of funding such facilities. This study provides an important first step in the proper estimation of these benefits by suggesting modifications to SP surveys to better capture the influence of urgent trips on the value of a ML facility.

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<p>The aim of this thesis is to study the effect of smoking and drinking on wages in Sweden. The data used in this study is the Swedish Level-of-living survey (LNU) from 1991. A multinomial logit model and the marginal effects from the estimated model are used to study the effect of smoking and drinking on wages in Sweden. The empirical results conclude that medium drinking increases the probability of having a high income, i.e. there is a positive significant relationship between medium drinking and wages in Sweden. Also concluded from the empirical results is that there is not a significant relationship between smoking and wages in Sweden.</p>

This study investigates how hate crimes in general and anti-Arab hate crimes in particular were distributed across different regions of the United States during the 2001-2002 period. The study explores how a historical event the terrorist attacks against the U.S. on September 11, 2001 and county population demographics affect the rates of hate crime against Arabs, Muslims or Middle Easterners. It was hypothesized that anti-Arab or anti-Muslim hate crimes displaced other forms of hate crime and were characterized by open acts of violence. According to the contact hypothesis, anti-Arab and anti-Muslim hate crimes would be more likely to occur in counties with relatively high levels of poverty and economic inequality. The research materials were obtained from publicly available data. The hate crime data were obtained from the national hate crime incidents reported to the FBI Uniform Crime Reports (UCR) program.

It has become more important for operators to be able to predict the future number of public transport passengers when consider to place a tender for operating public transport in a city or region, this is due to the new types of operator contracts was introduced quite recently. There are models in use today that can predict this, but they are often time consuming and complex and therefore it can be expensive to perform a forecast. Aside from this, most models in use for Sweden today are adapted for larger cities. Thus, the aim of this thesis is to propose a model that requires minimal input data with a short set up and execution time that can be used to predict a forecast for the public transport system in smaller cities without notably affecting the quality of the result. The developed model is based on a forecast model called LuTrans, which in turn is based on a common method, the four step model. The aim of the model lies within public transportation but it also consider other modes. The input data used by the model mainly consists of socio-economic data, the travel time and distance between all the zones in the network. The model also considers the cost for traveling by car or public transport. The developed model was applied to the Swedish city, Örebro, where a forecast was conducted for a future scenario. It is easily to apply the model to different cities to estimate a forecast for the public transport system. The developed model for the base scenario predicts trips for individual bus lines with an accuracy of 85 % for the city of Örebro. The developed model gave the result that the trips made by public transport in the future scenario of Örebro 2025 will increase annually by 0.94 %. The conclusion is that it is possible to develop a simple model that can be easily applied for a desired city. Although the developed model produced a plausible result for Örebro, further work such as implementation on other cities are required in order to fully evaluate the developed model.