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.

Interaction and marginal effects are often an important concern, especially when variables are allowed to interact in a nonlinear model. In a linear model, the interaction term, representing the interaction effect, is the impact of a variable on the marginal effect of another variable. In a nonlinear model, however, the marginal effect of the interaction term is different from the interaction effect. This report provides a general derivation of both effects in a nonlinear model and a linear model to clearly illustrate the difference. These differences are then demonstrated with empirical data. The empirical study shows that the corrected interaction effect in an ordered logit or probit model is substantially different from the incorrect interaction effect produced by the margins command in Stata. Based on the correct formulas, this report verifies that the interaction effect is not the same as the marginal effect of the interaction term. Moreover, we must be careful when interpreting the nonlinear models with interaction terms in Stata or any other statistical software package. / text

Paired comparison models in loglinear form are generalised linear models and can be fitted using the IWLS algorithm. Unfortunately, the design matrices can become very large and thus a method is needed to reduce computational load (relating to both space and time). This paper discusses an algorithm for fitting loglinear paired comparison models in the presence of many nuisance parameters which is based on partition rules for symmetric matrices and takes advantage of the special structure of the design matrix in Poisson loglinear models. The algorithm is implemented as an R function. Some simple examples illustrate its use for fitting both paired comparison models and (multinomial) logit models. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Σκοπός της παρούσας διατριβής είναι η ανάδειξη των χαρακτηριστικών των επιχειρήσεων – στόχων του βιομηχανικού τομέα και η δυνατότητα πρόβλεψης αυτών αποκαλύπτοντας έτσι τα κίνητρα των αγοραστών. Ο σκοπός αυτός επιτυγχάνεται μέσα από ένα διαφοροποιημένο τρόπο ανάπτυξης του θεωρητικού πλαισίου (σε σχέση με τους υφιστάμενους) και κατ’ επέκταση των θεωρητικών υποθέσεων. Σε αντιστοιχία με τις θεωρητικές υποθέσεις αναπτύσσεται η δειγματοληψία και ορίζονται οι μεταβλητές. Συνέπεια τούτου, οι μεταβλητές διακρίνονται σε χρηματοοικονομικές και μη χρηματοοικονομικές. Το κύριο βάρος της εργασίας εστιάζεται στην εφαρμογή εναλλακτικών οικονομετρικών υποδειγμάτων αναφορικά με τους στόχους – εξαγοράς. Η κύρια συνεισφορά της διατριβής εντοπίζεται στη θεωρητική ανάπτυξη και εφαρμογή ενός νέου ουσιαστικά οικονομετρικού υποδείγματος του Bootstrap Mixed Logit (BMXL) που δίνει μια νέα διάσταση τόσο στον εντοπισμό των χαρακτηριστικών των επιχειρήσεων – στόχων όσο και στη δυνατότητα βελτίωσης της πρόβλεψης αυτών. Τέλος η εργασία ολοκληρώνεται εξάγοντας τα κύρια συμπεράσματα και κάνοντας προτάσεις για μελλοντική έρευνα και συνεισφορά. / The purpose of this dissertation is the identification of the characteristics of takeover targets of industrial sector and its predictive ability revealing the motives of buyers. This purpose is achieved using a different theoretical context and manner of sampling. We distinct the variables into financial and non financial. We focus on the application of alternative econometric model relatively to the takeover targets. The contribution of this dissertation is located to the theoretical development and application of a new econometric model the Bootstrap Mixed Logit (BMXL)that provide a new dimension not only on the identification of takeover targets but also on the ability of their prediction. Finally, the dissertation concludes making suggestion for future research.

Climate change is being observed through increased average temperatures world-wide, as well as through increased frequency of extreme events, such as floods and droughts. As climate is an uncontrollable yet essential input in the agriculture industry, the impact of climate change may have on crop production in Saskatchewan is of importance. The main objective of this study is to investigate how farmers adapt to climate change by switching their crop mix, and how this crop mix may change under future climate change scenarios. A fractional multinomial logit (FMNL) model was used to assess how total area of cropland has changed over a thirty year time period. The panel data included variables to represent the land characteristics of Saskatchewan (i.e. the three major soil zones - Black, Dark Brown and Brown), climatic variables to represent average monthly temperature and precipitation, and price and policy variables in order to assess how average seeded area of each crop group changed. With these results, a simple simulation model was developed to evaluate how the area of each crop group in a base year comparison (2000) would change under future climate scenarios for each soil zone. The results from the FMNL model indicate that crop allocation depends largely on the price of other crop groups and temperatures in the spring (April) and summer (July). Climate plays and important role in the major crop groups, such as wheat, canola and pulses. Cool, dry springs are the ideal conditions when choosing nearly all crops, while hot, wet summers increase the choice to leave land to summerfallow. Policy and the different soil zones also play a significant role in area allocation decisions. Changes in policies such as the removal of the Crow’s Nest Pass Agreement, and the removal of oats from the Canadian Wheat Board (CWB) marketing, had a negative impact on the choice to grow wheat, as expected. The different soil zones in Saskatchewan played an important role in area allocation for a majority of the crops, having a negative effect on the choice of wheat over every other crop group except pulses and summerfallow. Three climate change scenarios were simulated for each soil zone and compared to a base area (year 2000 area seeded) of crop groups. The findings from the projected changes in climate indicate that the area allocated to wheat will continue to decrease into the future, following current trends. The average projected decline in wheat area from the base years by 2099 ranges between 3.5% to 4.6% in the Black soil zone, between 2.7% and 2.9% in the Dark Brown and 2.7% to 4% in the brown soil zone, depending on climate change scenario. Interestingly, the area left to summerfallow is projected to increase over the future climate change scenarios. The choice of wheat is preferred over pulses, feed and forages, while the choice of specialty oilseeds (flaxseed, mustard seed and canary seed) are projected to become preferred over wheat in the future. The major conclusion from this research are: (i) following current trends, the area devoted to spring wheat and durum wheat would continue to decline into the future; (ii) Area devoted to wheat remains a preferred choice over pulses, feed and forages while specialty oilseeds represent a viable alternative choice to wheat and (iii) most significantly, summerfallow area would increase. This is in contrast to the current trend of declining summerfallow area as a result of tighter crop rotations. This finding was observed throughout all three soil zones as well as for all three climate change projection periods. This will have major implications on individual farmers as well as the economy in Saskatchewan, as summerfallow does not produce a crop in the year it is chosen. It is therefore important to determine a possible new crop mix that would benefit from the projected change in climate. This study could be improved by including a measure of profitability for each crop group and introducing a new crop group that is better suited to the projected change in climate in Saskatchewan.

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The thesis comprises five papers and an introductory overview of applied models and methods. The papers concern interdependences and interrelations in models applied to empirical analyses of various problems related to production, consumption, location and trade. Among different definitions of 'structural analysis' one refers to the study of the properties of economic models on the assumption of invariant structural relations, this definition is close to what is aimed at in lire present case. Although the subjects cover widely differing aspects of the economic system, applied models and methods, i.e. entropy maximizing (information minimizing) models and random utility maximizing models, are in many cases closely connected. Tlic first paper reports on a regional input-ouput study applied to Norrbotten, Sweden. The paper is mainly concentrated on developing and estimating an econometric model, describing the structural interdependences in the Norrbotten economy. The chapter is composed of three parts. The first part concerns the theoretical basis of the model, the main fields of application and principal problems in connection with the estimation. The core of the estimated model is defined by the intersectoral dependences in the Norrbotten economy. This model can be viewed as a part of a more general model of the regional economy, and such a general model is briefly outlined. The second part reports on the collection and arranging of data, and the methods used for the estimation of the model. In the third part the results are presented. A special interest concerns the effects of production changes in the basic industries in the county, as to the expected impact on different industries and occupational groups. The second paper concerns some aspects of the problem of predicting trade flows in the forest sector. The model, based on information theory, is predicting current trade flows by adjusting the historical, a priori, trade flows to satisfy current export and import totals. In the third paper an entropy model is employed to decompose the interregional and intraregional employment change in Sweden and Stockholm, during the period 1960 - 1980, into effects attributed to regions (zones), industries, occupations and interaction effects. The fourth paper presents an empirical analysis of housing choice, based on individual data of households in Stockholm. The consumer choice is regarded as a complex choice from a finite set of discrete alternatives and a probabilistic choice mode! (multinomial logit) is employed, where secondary dwelling is included in the housing choice decision. In the final paper spectral analysis is used for identifying the significant components of cycle behaviour in time series of Swedish exports of forest products over a twenty year time period. / digitalisering@umu

There has been a noticeable swing towards school pupils being driven to and from school, and away from active modes like walking and cycling, in recent decades. This has had a number of side effects. Less reliance on active modes of transport has been a contributing factor in the reducing levels of physical activity for school children. Traffic volumes associated with school trips have also increased. This increased has tended to contribute to an increase in traffic congestion, adverse environmental effects and reductions in levels of sustainability. School trip traffic contributes specifically to congestion at school gates. Schools have been identified as having significant effects on the transportation system adjacent to them. Schools which seek Resource Consents for new or changed activities are often being required to take measures to mitigate their adverse effects The purpose of this study is to explore the factors contributing to primary school pupils' travel choices. This will help to identify travel choice patterns which may, in turn, be useful in developing policies and planning initiatives which contribute to achieving an efficient and sustainable transport system. A range of literature relevant to school and general commuting travel demand was reviewed. A case study involving the pupils of twenty two Christchurch primary schools was carried out. Pupils and their parents were surveyed to establish mode choices and the factors influencing those choices. The study found that between 55% and 60% of pupils surveyed travel to and from school by car. 30% to 35% walk or scooter, and 5% to 7% cycle. This compares with 34% travelling by car in the late 1980s. In addition, a greater proportion of those pupils who walk, scooter or cycle to school are accompanied by an adult than in the past. The results of the study also suggested that School Travel Plans, when combined with the energy and commitment to implement them can have a significant effect on school travel choices. As part of the case study, parents were asked to rank the importance of a number of factors which could influence choices regarding their children's school travel. The responses from parents identified safety concerns, regarding both road and personal safety, as the major factor behind decisions regarding their children's travel choices. Time constraints coupled with the complexity of travel requirements of many families were identified as significant factors. Multinomial Logit Models for both mode choice and pupils travel independence were then produced for both the journey to and from school. These models were based on the results of the case study. The models produced indicate that, at a school level, there is a correlation between increasing school roll and an increasing proportion of pupils travelling by car. A slight negative correlation between school decile and car usage was also indicated. This is contrary to the normally accepted understanding that in most transport situations there is a positive correlation between increasing affluence and car usage. Superior model results were obtained at a disaggregated individual level, using nine variables relating to the school, the neighbourhood, and the home, than the results obtained using the school based variables of. However, it is not considered that the effort required to obtain information on the additional variables is justified when estimating mode choices of pupils at an individual school. It is therefore recommended that a model using Decile, Average Age, and School Roll variables be used to estimate mode choices at an individual school. At a family level, there was a strong positive correlation between distance from school, age of the pupils, and the number of major roads between school and home, and car usage. It became apparent that the decisions made regarding children's school travel are very complex. Families juggle a number of factors, many of which are in conflict with one another. For example a desire to care for the environment may be in conflict with the demand to get the children to school, and get to work on time. This complex interrelationship between factors has resulted in some instances where normally accepted "Rules of Thumb", such as the understanding that increased car usage is generally associated with increasing wealth, do not appear to be applicable to school travel. The complexity of interrelationships has further meant that it has not been possible to quantify the impact of any one factor on its own.

Parasite control is important to horse health and horse owners should feel highly concerned about the proper treatment of parasites. In the past 30 years, veterinary science has made important advances in treating parasites and provided new products and strategies to optimize treatment and prevention. However, horse owners and managers have been slow to adopt these new recommendations. This study investigates why the transition has not occurred as expected. It examines issues related to the decision-making process of horse owners and managers as they relate to deworming strategies. In addition, it investigates current deworming approaches as well as attitudes towards alternative parasite control strategies, and tries to describe the financial considerations corresponding to each strategy. To this end, a questionnaire was distributed to Thoroughbred farms in Kentucky. The first part of the questionnaire examined the actual approaches of farm managers and characterized the Kentucky Thoroughbred farms. Most farm managers appear to be concerned about drug resistance in parasites and incorporated veterinarian advice in defining their deworming program; however, almost three-quarters of them were still following the traditional rotational deworming program. Based on a conjoint experiment, we were able to evaluate the willingness-to-pay of farm managers for different attributes of a deworming strategy – time and effort spent, decrease in health risks, drug resistance in parasites, and price. The study showed that farm managers were willing to pay a premium for a strategy that is guaranteed “non-resistant” and that decreased health risk by 5%, while they expected a discount for a strategy that requires much time and effort.