Orientador: Walter Belik / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Economia / Made available in DSpace on 2018-08-07T00:27:10Z (GMT). No. of bitstreams: 1 Bolliger_FlavioPinto_D.pdf: 792580 bytes, checksum: 5d29dcc76c9f69b57fc7fa26ab2eaa0c (MD5) Previous issue date: 2006 / Resumo: O objeto da tese é a contribuição das atividades agroindustriais para geração de renda e emprego nas condições da economia brasileira nos anos recentes. São discutidas as concepções usuais de agroindústria, o modo como se operacionalizam esses conceitos para fins de observação estatística, as diferentes avaliações e medidas que dizem respeito à importância de sua inserção, ao perfil diferenciado de seus segmentos e à contribuição da agroindústria para a dinâmica da economia nacional. A partir do princípio da demanda efetiva, é proposta uma abordagem alternativa sobre geração de renda, e sobre a forma de mensurá-la / Abstract: The research¿s subject is the contribution of the agribusiness to the generation of income and occupation within the economic context of Brazil for the last years. The study focuses on the concepts of agro-industry and how they are applied in statistical surveys, the specific measuring of their importance, the differences between sub-sectors and the contribution of the agro-industrial segment to the dynamics of the national economy. Based on the principle of effective demand, it is presented an alternative proposal about income generation and its measurement / Doutorado / Politica Economica / Doutor em Ciências Econômicas

Orientador: David Dequech Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Economia / Made available in DSpace on 2018-08-11T20:11:26Z (GMT). No. of bitstreams: 1 Leite_FabricioPitombo_M.pdf: 1074190 bytes, checksum: cebbb5895912efdcc4bb8a0b6a39d64f (MD5) Previous issue date: 2008 / Resumo: A interpretação sugerida no presente estudo evidencia o caráter mais amplo assumido pela teoria da preferência pela liquidez, qual seja, de uma teoria da escolha e precificação de ativos em geral. Para tal, parte-se da explanação acerca dos motivos para demandar moeda, explicitando-se também as conexões entre esses motivos e a incerteza que permeia o ambiente econômico. Na busca pela especificidade da teoria da preferência pela liquidez, isto é, no que esta se diferencia de uma teoria alternativa para a demanda por moeda, discute-se a determinação da taxa de juros em decorrência destes motivos, com destaque para a expressão da moeda como um ativo e para o fato de rendimentos pecuniários serem auferidos por quem se dispõe a abdicar da posse de moeda e reter títulos, tudo isso com a gama de ativos limitada aos dois supracitados. Finalmente, abandonando-se o mundo dicotômico construído a partir da moeda e de um outro ativo e a partir da extensão de um mesmo princípio definidor básico, chega-se à escolha e precificação de ativos em geral, com o que a teoria da preferência pela liquidez adquire sua representação máxima. / Abstract: The interpretation suggested in the present study emphasizes the broad character of liquidity preference theory, namely, as a theory of asset choice and pricing in general. To this end, the thesis starts with the explanation of the motives to demand money, as well as the connections between these motives and the uncertainty that permeates the economic environment. Looking for the peculiarity of liquidity preference theory, as distinct from an alternative theory of demand for money, the thesis discusses the determination of the interest rate as a result of these motives, highlighting the expression of money as an asset and the fact that monetary yields are earned by whoever is willing to part with money and hold securities, all this with the basket of assets restricted to these two. Lastly, the thesis abandons this dichotomic world of money and only one other asset, and, on the basis of the same defining fundamental principle, arrives at asset choice and pricing in general, with the result that liquidity preference theory assumes its most general form. / Mestrado / Mestre em Ciências Econômicas

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Civil Engineering, 1980 / Bibliography: leaves 441-455. / by Peter Douglas Hall. / Ph. D. / Ph. D. Massachusetts Institute of Technology, Department of Civil Engineering

Theoretically, an equiproportionate change in prices and income should not affect the sales of products. This is known as the homogeneity of demand property on which the economic consumer demand theory is built. Rejection of this assumption is indicative of a state of mind called ‘money illusion’. Evidence from applied economics literature suggests that consumers respond asymmetrically to equal changes in prices and income. Such an asymmetry could be, among other things, due to the exclusion of marketing mix variables in their demand functions or inappropriate grouping of products. The main focus of the dissertation is to provide a theoretically consistent approach to include marketing variables in a sales response function. Specifically, advertising is hypothesized to act as a moderator in eliminating the asymmetry. A related issue investigated in this research is the existence and empirical testing of mental expenditure accounts. Grouping of products into mental expenditure accounts is thought to improve the homogeneity of demand. A system of equations is developed since the model involves prices and advertising of all products. The systems approach offers a consistent means to analyze sales when advertising programs interact; for example, orange juice advertising may affect the demand for milk and vice versa. The expenditure share system of equations is estimated using the Seemingly Unrelated Regression (SUR) estimation procedure to allow for dependence among error terms and cross-equation coefficients. Theoretically, this research tests the validity of the well established consumer demand theory. It provides an approach, consistent with neoclassical economic theory, to include marketing mix variables in sales response modeling. Managerially, this study helps in determining the level of advertising necessary to reduce the asymmetry in consumer response due to price and income changes. Substitution patterns obtained from the proposed analysis will aid managers to decide upon prices of closely related products within a category in the wake of income changes. The proposed model provides a methodology to explore and test market structure. / Ph. D.

The traditional method for conducting sensitivity analysis is to repeatedly solve a model while varying the parameters. The solution is then obtained as some average of these optimal solutions under those different conditions or states of the world. The present work presents results of conducting sensitivity analysis using a method more firmly ground in mathematical programming theory. The present analysis models the investment decisions in a case with large uncertainty in demand: the steel industry in Argentina. Special emphasis is devoted to the recent history, where a recent shift in economic policy (1976-1981) towards allowing free competition with imported products resulted in a severe crisis for the steel industry and its trading partners. An increase in exports was observed during this period which is not likely to continue if there is a recovery process. In the first sections, the relation of steel production and economic growth is analyzed in the context of the world situation of the industry, setting the background for the analysis of the Argentinian industry as a case study. The results of the present model adequately describe the existence of unutilized capacity observed in the industry, as well as the recent increase in exports. The most important conclusion of the model is that the traditional method of conducting sensitivity analysis results in significant inefficiency of the reached decisions, involving large losses for a case such as the steel industry considered here. / Master of Arts / incomplete_metadata

This dissertation presents innovative demand management techniques for service systems with limited resources. The first study analyzes demand management policies of animal shelters with limited Kennel space as a set of interacting stochastic queueing systems. In practice, there are two main policies being used, which we call "Kill" and "No-Kill" policies. In a "Kill" system, animals may be euthanized if a shelter is full. Many shelters have moved to a "No-Kill" policy, where they avoid killing for space and adopt other approaches to reduce supply and demand mismatch. Our goal is to provide insights on how No-Kill policies, such as coordination, adoption and neutering campaigns, help reduce the animals' killing rate so that the shelter management can choose the way to effectively solve their problems. In the second part, we consider a topic of demand management for the Sports and Entertainment (S&E) industry, called "Scaling the house", i.e., how to divide seats into zones for different prices to maximize revenue across the venue. From the data obtained from several performance venues in the U.S., we find ticket demand is impacted by locations of seats as well as by price. We characterize closed-form solutions for the optimal two-dimensional zoning decision (with row and column cuts) and the one-dimensional decision (with row cuts), and explore when each model should be applied. The third study considers pricing as a tool to manage demand for the S&E tickets. We develop dynamic pricing with demand learning models where demand is also affected by time left until the show dates. Since the show's popularity is usually uncertain to the seller, we propose a method to learn the overall popularity via Bayesian updates. We perform computational experiments to understand properties of the model solutions and identify when demand learning is most beneficial.

Although the airline industry has drastically changed since its deregulation in 1978, publically available sources of data have remained nearly the same. In the U.S., most researchers and decision-makers rely on government data that contains highly aggregated price information (e.g., average quarterly prices). However, aggregate data can hide important market behavior. With the emergence of online distribution channels, there is a new opportunity to model air travel demand using detailed price information. This dissertation uses online prices and seat maps to build a dataset of daily prices and bookings at the flight-level. Several research contributions are made, all related to leveraging online data to better understand airline pricing and product strategies, and how these strategies impact customers, as well as the industry in general. One major contribution is the finding that the recent product debundling trend in the U.S. airline industry has diluted revenues to the U.S. Airport and Airways Trust Fund by at least five percent. Additionally, several new behavioral insights are found for one debundling trend that has been widely adopted by U.S. airlines: seat reservation fees. Customers are found to be between 2 and 3.3 times more likely to purchase premium coach seats (with extra legroom and early boarding privileges) when there are no regular coach window or aisle seats that can be reserved for free, suggesting that the ability of airlines to charge seat fees is strongly tied to load factors. Model results are used to explore optimal seat fees and find that an optimal static fee could increase revenues by 8 percent, whereas optimal dynamic fees could increase revenues by 10.2 percent. Another major contribution is in modeling daily bookings and estimating price elasticities using ordinary least squares (OLS) regression without correcting for price endogeneity and two-stage least squares (2SLS) regression, which corrects for endogeneity. Results highlight the importance of correcting for price endogeneity (which is not often done in air travel applications). In particular, models that do not correct for endogeneity find inelastic demand estimates whereas models that do correct for endogeneity find elastic demand estimates. This is important, as pricing recommendations differ for inelastic and elastic models. A set of instrumental variables are found to pass validity tests and can be used to correct for price endogeneity in future models of daily flight-level demand.

Thesis (Ph. D.)--Ohio State University, 2007. / Full text release at OhioLINK's ETD Center delayed at author's request

D. Comm. / The South African vehicle industry is currently struggling to narrow the gap between the demand and supply for new vehicles. Customers are confronted with long waiting lists for some models, while producers are carrying high stock levels on other models. A possible explanation for this is the complex nature of the demand for vehicles, resulting in difficulty to analyze and forecast vehicle sales. The demand for large and luxury passenger vehicles is to a. large extent status-driven, while the demand for commercial vehicles and tractors can be seen as derived demand because they are being used in the production process. Motorcycles, on the other hand, can be seen as "inferior goods" due to their discomfort. Demand management suggests that managers must react proactively to changes in the market with the aid of strategic information systems. A key ingredient of information systems is econometric models. These models transform data into decision-relevant information. The availability and knowledge of these models are, however, very limited. Studies performed on the vehicle industry produced only a few broadly defined models. They analyze only the main categories and do not, for example, distinguish between small and large vehicles, while this mix of sales is important for the majority of stakeholders in the vehicle industry. If forecasts are made with these models, decisions will be based on inaccurate forecasts and scarce resources will be wasted. This study is executed against this background. It is an attempt to narrow this gap between demand and supply and to address the shortcomings of previous econometric models. The primary objective of the study is to compile and test an econometric model for each vehicle category in South Africa. The secondary objective is to investigate the use of econometric models in the strategic planning processes in the vehicle industry to gain a competitive advantage. In order to make conclusions and recommendations to the industry, the following steps were followed: All vehicle categories in South Africa were identified (small passenger cars, medium passenger cars, large passenger cars, light commercial vehicles, medium commercial vehicles, heavy commercial vehicles, tractors and motorcycles). A unique data base was compiled for each category of vehicle (prices of new vehicles, prices of second-hand vehicles and numbers sold). Economic and graphic analyses were performed on every category, investigating the determinants of the demand for that category of vehicle. An econometric model was estimated for each category of vehicle. These models were tested economically, statistically and econometrically to verify the soundness thereof. The uses of these models were illustrated ("what if" analyses and forecasting). The role of managers in the vehicle industry in the application of these models were investigated. It can be concluded from the results of the econometric models that consumer behaviour in the vehicle industry can be analysed and forecast quite accurately. It was proven from the results that the factors influencing the demand for the different categories of vehicles, and especially the extent to which these determinants influence demand, differ considerably among the categories. This emphasizes the importance of analyses of this nature where the determinants of demand are analyzed for each and every type of vehicle. This also emphasizes the risk managers take when decisions are based on models where all these categories are combined and only total vehicle demand is analyzed. The responsiveness of management depends to a large extent on the quality of the information systems in the company. The new approach, 'identified in this study, concentrates on the direct use of information systems, and more specifically econometric models, to establish a competitive advantage.

The price elasticity of demand coefficient for a good or service is a measure of the sensitivity, or responsiveness, of the quantity demanded of a product to changes in the price of that product. The price elasticity of demand coefficients were generated for goods and services in nine different industries for the years 1972 to 1984. A simple linear demand function was employed, using the changes in the Consumer Price Index as a proxy for changes in price and Personal Consumption Expenditures, taken from the National Income and Product Accounts, as a proxy for quantity. Beta measures the sensitivity, or responsiveness, of a stock to the market. An industry average beta coefficient was generated for each of the nine industries over the time period, using the beta coefficients published by Value Line for firms which met certain criteria. In order to test the relationship between the price elasticity of demand and an industry average beta coefficient, a simple regression was performed using the beta coefficient as the dependent variable and the price elasticity of demand coefficient as the independent variable. The results broke down into 3 basic categories: those industries for which there seemed to be no relationship, those industries where there was a fairly strong probability that a relationship exists and the price elasticity of demand explains at least part of the variation in beta coefficients, and those industries where there was a very high probability that a relationship does exist and the variation in the price elasticity of demand coefficients substantially explained the variation in the industry average beta coefficients. The first category includes the food at home, tobacco, and shoe industries. The second category includes the men's clothing, the women's clothing, and the alcoholic beverages industries, and the third includes the automobile, airline, and fast-food restaurant industries.