O consumo per capita de pescados no Brasil é relativamente baixo quando comparado com as outras proteínas de origem animais. Do lado da oferta, este fenômeno está relacionado com diversos fatores como, por exemplo, a sobre pesca, a baixa produção nacional, a distância entre centros produtores e consumidores etc. Este trabalho aborda os fatores que estão ligados à sua demanda, tais como: a influência dos preços e da renda da população no seu consumo. Inicialmente, caracterizou-se o problema da oferta de pescados no Brasil. Em seguida, foi feita uma revisão sobre a teoria econômica e o método de cálculo da função e de suas elasticidades para a forma funcional conhecida por Almost Ideal Demand System - AIDS. A partir dos microdados da Pesquisa de Orçamento Familiar - POF 2002-2003, fez-se uma análise descritiva da demanda por pescados no Brasil. Finalmente, foram estimadas as funções demanda e calcularam-se as elasticidades para dois tipos de agrupamentos: um que considerou 5 grupos de proteínas animais e o outro com 7 grupos de alimentos. Estas funções foram estimadas para o Brasil e para duas macro-regiões: Norte-Nordeste e Centro-Sul. Os principais resultados são: o consumo per capita de pescados é baixo porque poucos domicílios consomem pescados. O consumo de pescado da Região Norte-Nordeste é significativamente diferente do padrão observado na Região Centro-Sul do país. Os principais produtos substitutos aos pescados no país são as proteínas mais elaboradas e não as carnes mais tradicionais como a de aves e as vermelhas. Os supermercados são os pontos de vendas mais utilizados pelos consumidores de pescados de renda mais elevada, principalmente na Região Centro-Sul, mas os pequenos estabelecimentos comerciais também possuem grande importância na comercialização de pescados para o consumidor final, principalmente, na Região Norte-Nordeste. / Per capita consumption of fish in Brazil is relatively small as compared to other animal proteins. On the supply side, this phenomenon can be explained by several factors such as: low national fish production, the distance between fish supply regions and the main consumptions centers etc. This study analyses the influence of prices and population income on the demand of fish in Brazil. First, the problem of fish supply in Brazil is characterized. It is followed by reviews of the relevant economic theory and the methods of the function and the elasticity calculations for a functional form known by Almost Ideal Demand System - AIDS. A descriptive analysis of fish demand in Brazil using the microdata called the Familiar Budget Research - POF 2002-2003 is presented. Finally, demand functions and their elasticities are calculated for two different cases: one considering 5 groups of animal proteins and other with 7 groups of food categories. These functions are estimated for Brazil as a whole and two macro-regions: Northnortheast and Center-South. The main results are: per capita consumption of fish is low in Brazil because few households consume fish. The pattern of fish consumption in the North-Northeast Region is different as compared to the Center-South. The main substitutes for fish are the processed proteins and not the traditional types of meat as chicken and red meat. For high income households located mainly in Center-South Region, fish are mainly purchased in supermarkets. However, small commercial establishments are still important in the fish retail market, especially in the North-Northeast.

This PhD thesis focuses on using time series models for counts in modelling and forecasting a special type of count series called intermittent series. An intermittent series is a series of non-negative integer values with some zero values. Such series occur in many areas including inventory control of spare parts. Various methods have been developed for intermittent demand forecasting with Croston’s method being the most widely used. Some studies focus on finding a model underlying Croston’s method. With none of these studies being successful in demonstrating an underlying model for which Croston’s method is optimal, the focus should now shift towards stationary models for intermittent demand forecasting. This thesis explores the application of a class of models for count data called the Integer Autoregressive Moving Average (INARMA) models. INARMA models have had applications in different areas such as medical science and economics, but this is the first attempt to use such a model-based method to forecast intermittent demand. In this PhD research, we first fill some gaps in the INARMA literature by finding the unconditional variance and the autocorrelation function of the general INARMA(p,q) model. The conditional expected value of the aggregated process over lead time is also obtained to be used as a lead time forecast. The accuracy of h-step-ahead and lead time INARMA forecasts are then compared to those obtained by benchmark methods of Croston, Syntetos-Boylan Approximation (SBA) and Shale-Boylan-Johnston (SBJ). The results of the simulation suggest that in the presence of a high autocorrelation in data, INARMA yields much more accurate one-step ahead forecasts than benchmark methods. The degree of improvement increases for longer data histories. It has been shown that instead of identification of the autoregressive and moving average order of the INARMA model, the most general model among the possible models can be used for forecasting. This is especially useful for short history and high autocorrelation in data. The findings of the thesis have been tested on two real data sets: (i) Royal Air Force (RAF) demand history of 16,000 SKUs and (ii) 3,000 series of intermittent demand from the automotive industry. The results show that for sparse data with long history, there is a substantial improvement in using INARMA over the benchmarks in terms of Mean Square Error (MSE) and Mean Absolute Scaled Error (MASE) for the one-step ahead forecasts. However, for series with short history the improvement is narrower. The improvement is greater for h-step ahead forecasts. The results also confirm the superiority of INARMA over the benchmark methods for lead time forecasts.

Consumption of food away from home (FAFH) is widely believed to be a contributing factor to the current obesity crisis and other diet related problems in North America. At present, in Canada, a number of issues related to FAFH consumption such as the relationship between obesity and fast foods, trans-fats, sugar and sodium content of restaurant foods, and restaurant advertising for children are being widely discussed. In these discussions, it is apparent that the interrelationships between FAFH, nutrition and diet related diseases are complex. Therefore, there are significant gaps in our knowledge. In this study, a number of important research questions related to FAFH consumption were studied in order to provide a detailed understanding of FAFH purchase trends, nutrient demand trends, factors affecting these trends and to provide some idea of the possible effectiveness of proposed policy interventions in the area. In paper one of this study, a sample of Canadian FAFH purchases were analysed using a two stage demand model to examine the impact of industry advertising, households habit forming preferences and socio-demographic and economic variables. Given the unique method of restaurant categorization, results provide new and additional information of the impact of above variables in Canadian context. The second study examined the demand for selected nutrients in FAFH to understand factors affecting nutrient intake in FAFH foods focusing on chain restaurants. An innovative measure of nutrient content (nutrient density) was used in the analysis and study results provides interesting new information about nutrient consumption from chain restaurants in the FAFH market. The third study examined how some specific food industry changes in product formulations aimed at reducing trans-fatty acids (TFAs) could and have affected consumers overall diet quality and their demand for food away from home. This study provides some indications of effectiveness of the current trans-fat recommendations in Canada. In summary, this study is an empirical investigation of a number of questions related to Canadian FAFH consumption: What is the structure of the FAFH market in Canada? What are the households FAFH purchasing patterns? What is the impact of advertising and habit forming preferences and socio-economic and demographic factors on FAFH purchases? What are the nutrition profiles of the most popular menu items of chain restaurants? What are the factors affecting nutrient demand in FAFH foods? Would a specific food industry change in product formulation such as reducing TFAs have affect consumers overall diet quality and their demand for FAFH? In general, results from the three independent studies provide useful information to fill some of the gaps in our knowledge of FAFH consumption, especially on health and nutrition with implications for public policy. / Agricultural and Resource Economics

This dissertation makes contributions in topics related to mechanism design and learn-ing in game theoretic environments through three essays. The rst essay deals withthe question of mechanism design in the principal-agent model. The main contribu-tion of this essay is in extending the work by Piketty (1993). It prescribes a mechanismin incomplete informational settings where the principal is able to implement rst-best contracts while extracting the entire surplus. Importantly, the mechanism issuch that the desired outcome can be uniquely obtained when agents play the actionthat survives iterative elimination of dominated strategies. Furthermore, given themechanism, the desired outcome is shown to be a truth-revealing Nash equilibriumwhich is also Pareto-ecient. It is shown that the proposed mechanism also has thefeature that none of the agents prefer any of the other possible Nash Equilibria tothe status quo. It thus gives insights into possible mechanisms in nite agent settingsthat could improve upon the traditional second-best results.In the second essay, a model of sophisticated learning is developed where itassumes that a fraction of the population is sophisticated while the rest are adaptive learners. Sophisticated learners in the model try to maximize their cumulative payoin the entire length of the repeated game and are aware of the way adaptive learnerslearn. Sophisticated learning contrasts other models of learning which typically tendto maximize the payo for the next period by extrapolating the history of play.The sophisticated learning model is estimated on data of experiments on repeatedcoordination games where it provides evidence of such learning behavior.The third essay deals with the optimal pricing policy for a rm in an oligopolythat is uncertain about the demand it faces. The demand facing the oligopoly, whichcan be learned through their pricing policy, changes over time in a Markovian fashion.It also deduces the conditions in which learning (experimentation) is not achievableand outlines the dierent learning policies that are possible in other settings. Themodel combines the monopoly learning literature with that of the literature on pric-ing behavior of rms over business cycles. The model has interesting insights onthe pricing behavior over business cycles. It predicts that prices jump as the beliefof a possible future boom rises over a certain threshold. The model also predictscompetition to be quite vigorous following a boom while rms are predicted not toexperiment with their (pricing) policies for many periods following a bust.

The objective of Paper [I] is to analyze potential effects on the Swedish forest sector of a continuing rise in the use of forest resources as fuel in energy generation. An increasing use of forest resources as an energy input may have effects outside the energy sector. In this paper we consider this by estimating a system of demand and supply equations for the four main actors on the Swedish roundwood market. In Paper [II], we estimate a dynamic factor demand model for the Swedish pulp industry. We find weak evidence of adjustment costs for capital. The results suggest that the user cost of capital is a significant determinant of pulp industry investments. We also find that pulp industry investments are insensitive to variations in the price of electricity. Paper [III] proposes a flexible form of adjustment cost function. An empirical illustration shows that the flexible form can detect both convex and non-convex adjustment costs. Furthermore, the flexible form permits testing for the experience effect on adjustment cost. The objective of paper [IV] is to analyze the price formation for wood fuel used by the Swedish district heating sector. According to previous research there is a significant potential for increasing the use of wood fuel in Sweden. The question raised in this paper is why this potential is not realized. According to our results we cannot reject the efficient market hypothesis for all years. The objective of Paper [V] is to test for market power on the market for biofuels. To achieve our objective we make use of the idea of Granger causality. If past values of quantity contribute significantly to the determination of price, quantity is said to Granger cause price, which we will treat as a sign of market power. According to our findings this effect is present.

Intelligent IT-based solutions, often called Smart Grids, are considered to be the future balancers of renewable energy sources. One area within the Smart Grid concept is called demand response, which is focused on making customers more consumption flexible by making them more active in their consumption. In this thesis the aim is to analyze a business model by investigating the income potential for a demand response solution as well as its market potential. This has been done through literature studies, interviews and development of a computational model. The use of 5000 households with flexible consumption can provide a cost reduction of 17.2% or 2.4 million SEK for a balance responsible party during an average year. If the solution is used to make strategic bids on the regulation markets the study indicates that the largest potential for revenues lies within this strategy. Potential customers show a genuine interest in the solution, but are worried about implementation costs, product reliability and contract solutions. The business model needs further development to increase its reliability. The impact of using strategic bids optimally needs to be investigated, and a thorough market analysis would be of great help to answer the questions: how should tomorrow’s contracts look like and which actors will be present on tomorrow’s electricity market?

Denna uppsats behandlar de relativa prisökningar som skett för snusprodukter i Sverige och vill undersöka om dessa har lett till minskad efterfrågan som nationalekonomisk teori föreslår. Utifrån teori och tidigare forskning har en efterfrågemodell konstruerats för att möjliggöra en statistik undersökning. Variablerna som ingår i modellen är inhämtade från Statistiska centralbyråns prisenhet och Swedish Match AB och inkluderar prisuppgifter för varor, försäljningsstatistik och disponibel inkomst under tidsperioden 1999-2009. Resultaten från regressionsanalyser för tidsseriedata visar på att de ökade priserna har haft en negativ inverkan på efterfrågan på snus under den gällande tidsperioden, men att denna effekt varit förhållandevis liten.

In this study, we apply "the equilibrium price" to investigate the efficiency and the elasticity of Taiwan securities trading market. The "the equilibrium price" of each transaction are used to represent the true price of the security. The intra-daily tick-by-tick data of the Taiwan security market is used to obtain the equilibrium prices. Empirical transaction of the two companies Uni-President Enterprises Corporation and Formosa Plastics Corporation are studied. Time-series models of the equilibrium price and the transaction price are established. The time lengths returning to the equilibrium status are also studied, called the efficiency time. Based on the results, we discuss the efficiency of the two stocks. In order to understand the impact of the efficiency time, linear regression models of the efficiency time are built. Furthermore, the variance ratios of the two stocks are also investigated to study their market efficiency. Finally, the elasticity of demand and the elasticity of supply are studied and their Markov chain models are established. The results show that the two companies stay more time in the inelastic states.

This dissertation makes contributions in topics related to mechanism design and learn-ing in game theoretic environments through three essays. The rst essay deals withthe question of mechanism design in the principal-agent model. The main contribu-tion of this essay is in extending the work by Piketty (1993). It prescribes a mechanismin incomplete informational settings where the principal is able to implement rst-best contracts while extracting the entire surplus. Importantly, the mechanism issuch that the desired outcome can be uniquely obtained when agents play the actionthat survives iterative elimination of dominated strategies. Furthermore, given themechanism, the desired outcome is shown to be a truth-revealing Nash equilibriumwhich is also Pareto-ecient. It is shown that the proposed mechanism also has thefeature that none of the agents prefer any of the other possible Nash Equilibria tothe status quo. It thus gives insights into possible mechanisms in nite agent settingsthat could improve upon the traditional second-best results.In the second essay, a model of sophisticated learning is developed where itassumes that a fraction of the population is sophisticated while the rest are adaptive learners. Sophisticated learners in the model try to maximize their cumulative payoin the entire length of the repeated game and are aware of the way adaptive learnerslearn. Sophisticated learning contrasts other models of learning which typically tendto maximize the payo for the next period by extrapolating the history of play.The sophisticated learning model is estimated on data of experiments on repeatedcoordination games where it provides evidence of such learning behavior.The third essay deals with the optimal pricing policy for a rm in an oligopolythat is uncertain about the demand it faces. The demand facing the oligopoly, whichcan be learned through their pricing policy, changes over time in a Markovian fashion.It also deduces the conditions in which learning (experimentation) is not achievableand outlines the dierent learning policies that are possible in other settings. Themodel combines the monopoly learning literature with that of the literature on pric-ing behavior of rms over business cycles. The model has interesting insights onthe pricing behavior over business cycles. It predicts that prices jump as the beliefof a possible future boom rises over a certain threshold. The model also predictscompetition to be quite vigorous following a boom while rms are predicted not toexperiment with their (pricing) policies for many periods following a bust.

The general public considers Fixed-Route Transit (FRT) to be inconvenient while Demand-Responsive Transit (DRT) provides much of the desired flexibility with a door-to-door type of service. However, FRT is typically more cost efficient than DRT to deploy. Therefore, there is an increased interest in flexible transit services including all types of hybrid services that combine FRT and pure DRT. The demand-responsive feeder transit, also known as Demand-Responsive Connector (DRC), is a flexible transit service because it operates in a demand-responsive fashion within a service area and moves customers to/from a transfer point that connects to a FRT network. In this research we develop analytical models, validated by simulation, to design the DRC system. Feeder transit services are generally operated with a DRC policy which might be converted to a traditional FRT policy for higher demand. By using continuous approximations, we provide an analytical modeling framework to help planners and operators in their choice of the two policies. We compare utility functions of the two policies to derive rigorous analytical and approximate closed-form expressions of critical demand densities. They represent the switching conditions, that are functions of the parameters of each considered scenario, such as the geometry of the service area, the vehicle speed and also the weights assigned to each term contributing to the utility function: walking time, waiting time and riding time. We address the problem faced by planners in determining the optimal number of zones for dividing a service area. We develop analytical models representing the total cost functions balancing customer service quality and vehicle operating cost. We obtain close-form expressions for the FRT and approximation formulas for the DRC to determine the optimal number of zones. Finally we develop a real-case application with collected customer demand data and road network data of El Cenizo, Texas. With our analytical formulas, we obtain the optimal number of zones, and the times for switching FRT and DRC policies during a day. Simulation results considering the road network of El Cenizo demonstrate that our analytical formulas provide good estimates for practical use.