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

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.

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.

Fethiye-G&ouml / cek area is one of the nine coastal Specially Protected Area (SPA) in Turkey. Since mid-80&rsquo / s G&ouml / cek town has developed to be a yachting center, and the bays of G&ouml / cek have acquired a well-earned international fame as a paradise for boating vacations. However, the uncontrolled yachting in this bay area presents a growing pressure on the environment, and the coastal and marine ecosystem. In this thesis a computer model for simulating the movements of yachts in G&ouml / cek Bays is developed. The computer model uses the Multinomial Logit Model (MNL) to find the probabilities for the boaters to select the next bay to visit. The model predicts the number of boats in each bay at the end of a day, the number of boats visited each bay during the day and the distribution of boater categories among the bays throughout the simulation time. In order to get the data needed for the inputs, a questionnaire was formed, and a detailed survey was carried out in G&ouml / cek Bays. In addition to the questionnaires, the number of the boats anchored were also observed in the field studies. The model is applied to the G&ouml / cek Bays and the results obtained are compared with the data obtained in the field. In the following years, the yacht movements and distributions at various anchor locations can be predicted with this model. These predictions will be useful in a future management plan that aims to control of yacht movement and anchoring.

In this paper we study data on discrete labor market transitions from Austria. In particular, we follow the careers of workers who experience a job displacement due to plant closure and observe - over a period of 40 quarters - whether these workers manage to return to a steady career path. To analyse these discrete-valued panel data, we apply a new method of Bayesian Markov chain clustering analysis based on inhomogeneous first order Markov transition processes with time-varying transition matrices. In addition, a mixtureof- experts approach allows us to model the probability of belonging to a certain cluster as depending on a set of covariates via a multinomial logit model. Our cluster analysis identifies five career patterns after plant closure and reveals that some workers cope quite easily with a job loss whereas others suffer large losses over extended periods of time.

Made available in DSpace on 2014-06-11T19:27:19Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-09-28Bitstream added on 2014-06-13T18:55:56Z : No. of bitstreams: 1 oliveira_mjg_me_arafcl.pdf: 295933 bytes, checksum: 2c3c89bc1ef42e80153321a65c5d111b (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A Educação Superior pode ser considerada uma ferramenta que possibilita ao indivíduo, através do investimento em seu Capital humano, ampliação de sua capacidade produtiva, maiores salários, proporcionando menor iniqüidade na distribuição de renda entre os indivíduos. O objetivo deste trabalho é traçar um perfil sócio-econômico do recém formado no ensino superior brasileiro com base em dados do Exame Nacional do Desempenho dos Estudantes (ENADE). Como se sabe, a escolha do curso superior no Brasil tem forte influência de fatores sociais e econômicos. Para estimar probabilidades com que um graduado seja de determinado curso, dado seu perfil, um modelo logit multinomial foi estimado. Conclui-se que quando a expectativa em relação ao curso é de ganhos futuros, homens brancos, negros e mulatos tendem a escolher cursos de exatas e engenharias. Em contrapartida, os cursos de humanas, em sua maioria, são demandados por mulheres brancas, negras e mulatas. Mesmo assim, há mulheres brancas, em certas regiões como Sudeste e Sul, que tem preferência por curso de engenharias e exatas / Higher education can be considered a tool that enables an individual, through investment in human capital, expanding his or her production abilities, higher wages, providing less unequal distribution of income among individuals.This work aims to build a profile of the Brazilian college graduated based on data from ENADE (Student Performance National Exam). As fairly known, college career choice in Brazil is strongly affected by social and economic factors. In order to estimate the probability of choosing a career, given the student profile, a multinomial logit model will be estimated. It is possible to conclude that when the expectation is over the course of future earnings, white males, blacks and mulattoes tend choose the exact and engineering courses. In contrast, the humanities courses, mostly, are demanded by white, black and mulatto. Still, there are white women in certain regions such as Southeast and South, which has a preference for engineering courses and exact

Orientador: Alexandre Sartoris Neto / Banca: Luciana Togeiro / Banca: Marislei Nishijima / Resumo: A Educação Superior pode ser considerada uma ferramenta que possibilita ao indivíduo, através do investimento em seu Capital humano, ampliação de sua capacidade produtiva, maiores salários, proporcionando menor iniqüidade na distribuição de renda entre os indivíduos. O objetivo deste trabalho é traçar um perfil sócio-econômico do recém formado no ensino superior brasileiro com base em dados do Exame Nacional do Desempenho dos Estudantes (ENADE). Como se sabe, a escolha do curso superior no Brasil tem forte influência de fatores sociais e econômicos. Para estimar probabilidades com que um graduado seja de determinado curso, dado seu perfil, um modelo logit multinomial foi estimado. Conclui-se que quando a expectativa em relação ao curso é de ganhos futuros, homens brancos, negros e mulatos tendem a escolher cursos de exatas e engenharias. Em contrapartida, os cursos de humanas, em sua maioria, são demandados por mulheres brancas, negras e mulatas. Mesmo assim, há mulheres brancas, em certas regiões como Sudeste e Sul, que tem preferência por curso de engenharias e exatas / Abstract: Higher education can be considered a tool that enables an individual, through investment in human capital, expanding his or her production abilities, higher wages, providing less unequal distribution of income among individuals.This work aims to build a profile of the Brazilian college graduated based on data from ENADE (Student Performance National Exam). As fairly known, college career choice in Brazil is strongly affected by social and economic factors. In order to estimate the probability of choosing a career, given the student profile, a multinomial logit model will be estimated. It is possible to conclude that when the expectation is over the course of future earnings, white males, blacks and mulattoes tend choose the exact and engineering courses. In contrast, the humanities courses, mostly, are demanded by white, black and mulatto. Still, there are white women in certain regions such as Southeast and South, which has a preference for engineering courses and exact / Mestre

Reflecting the growing interest from both consumers and policymakers, and building on recent developments in Willingness to Pay (WTP) methodologies, we evaluate consumer preferences for an archetypal traditional food product. Specifically we draw on stated preference data from a discrete choice experiment, considering the traditional Hungarian mangalitza salami. A WTP space specification of the generalized multinomial logit model is employed, which accounts for not only heterogeneity in preferences but also differences in the scale of the idiosyncratic error term. Results indicate that traditional food products can command a substantial premium, albeit contingent on effective quality certification, authentic product composition and effective choice of retail outlet. Promising consumer segments and policy implications are identified. (authors' abstract)

E-Commerce research shows that existing studies on online consumer choice behavior has focused on comparative studies of channel or store choice (online or offline), or online store choice (different e-tailers). Relatively less effort has been devoted to consumers’ online brand choice behavior within a single e-tailer. The goal of this research is to model online brand choice, including generating loyalty variables, setting up base model, and exploring the effects of Internet-specific attributes, i.e., order delivery, webpage display and order confirmation, on online brand choice at the SKU level. Specifically, this research adopts the Multinomial Logit Model (MNL) as the estimation methods. To minimize the model bias, the refined smoothing constants for loyalty variables (brand loyalty, size loyalty, and SKU loyalty) are generated using the Nonlinear Estimation Algorithm (NEA). The findings suggest that SKU loyalty is a better predictor of online brand choice than brand loyalty and size loyalty. While webpage display has little effect on the brand choice, order delivery has positive effect on the choice. Online order confirmation turns out to be helpful in choice estimation. Moreover, online consumers are not sensitive to net price of the alternatives, but quite sensitive to price promotion. These results have meaningful implications for marketing promotions in the online environment and suggestions for future research.