Using a dataset from TAIFEX, Taiwan Futures Exchange, we conduct an account-level analysis of the relation between prior loss consequences and subsequent trading behaviors. We apply two proxy variables of trading activities into our analysis, which are trade size and number of trades. We find that the degree of prior losses has a great effect upon trade size and trading number on the next trading day. This finding proves to the evidence that hedonic editing hypothesis sometimes fails and there are some limitations for it. We further examine for different trader types and the empirical results show that individual investors exhibit the strongest bias while other trader types do uncertainly. We also find the behavioral bias is a persistent phenomenon for individual investors. Overall, our study suggests that prior loss degree has a significant influence on investors’ following trading behaviors.

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Esta dissertação destina-se a realizar um estudo sobre o mercado imobiliário de lançamentos residenciais, mais especificamente apartamentos, no Município de São Paulo, tendo como base a utilização de preços hedônicos. Este trabalho baseia-se, principalmente, na abordagem da Teoria do Consumidor, de Lancaster, bem como em estudos relativos à precificação hedônica, de Court e Griliches, e em aplicações relativas ao mercado imobiliário, como a de Aryeetey-Attoh. Por meio de uma pesquisa qualitativa com especialistas, para a definição das variáveis hedônicas explicativas, e de uma pesquisa quantitativa, para a coleta de 480 dados amostrais relativos a preços de lançamento compreendidos entre os meses de abril de 2002 e março de 2003 e atributos para cada faixa de renda distrital de São Paulo, aplicam-se as técnicas de regressão conhecidas como cross-section, onde algumas especificações semilogarítmicas são propostas, escolhendo-se, para cada faixa de renda, a que apresenta o melhor ajuste estatístico. O método proposto permite a verificação do “pacote" de atributos que é mais representativo para a valorização dos imóveis residenciais em lançamento no Município de São Paulo, possibilitando a comparação da importância relativa de cada um para cada faixa de renda distrital. Portanto, permite-se o estudo de estratégias e de gerenciamento de projetos, designados para cada tipo específico de empreendimento imobiliário, de acordo com as preferências dos consumidores e das características das localidades. / This study intends to make a research about the real estate market, more specifically new apartments, in the Municipality of Sao Paulo, using hedonic prices theory. This work is based on the approach to Consumer Theory, by Lancaster, on some hedonic price studies, by Court and Griliches, and on real estate market applications, like Aryeetey-Attoh´s. Using a qualitative research with specialists, to define the independent hedonic variables, and a quantitative research, to provide 480 sample data related to launching prices occurred between April 2002 and March 2003 and attributes for each segment of low, middle and high income in the Municipality of Sao Paulo, it is used the regression techniques known as cross-section, in which some semilogarithmic specifications are suggested, choosing, for each income, the one that offers the best statistic adjust. The proposed method allows the verification about which attributes interfere the most in the price of real estates in Sao Paulo and it compares the relative importance of each one of these attributes whenever there are changes in social classes. Thus, it allows the study of strategies and project management, designated to each kind of real estate, according to the consumers’ preferences and locality characteristics.

The U.S. wool industry has long received lower prices for comparable wool types than those of Australia. In order to better understand such price differences, economic evaluations of both the U.S. and Australian wool markets were conducted. This research focused on two primary objectives. The first objective was to determine what price differences existed between the Australian and U.S. wool markets and measure that difference. The second objective was to calculate price differences attributable to wool characteristics, as well as those resulting from regional, seasonal, and yearly differences. In order to accomplish the objectives, the study was set up into three different hedonic pricing models: U.S., Australian, and combined. In the U.S. model, there were significant price differences in season, year, region, level of preparation, and wool description. In addition, average fiber diameter (AFD) had a negative nonlinear relationship with price and lot weight had a positive linear relationship with price. The Australian model was notably different than the U.S. model in that there were only three variables. The yearly variable follows the same general pattern as the U.S. data but with a smaller span of difference. The seasonal price differences were distinctly different than the U.S. because of the difference in seasonal patterns. In addition, the AFD had a similar negative nonlinear relationship with price. The final model combines both the U.S. data and the Australian data. The combined model had only three variables: season, year, AFD and country. As in the case of the previous two models, AFD had the same negative nonlinear relationship and similar price elasticity. Overall, there was a -30.5 percent discount for U.S. wool when compared to Australian wool. This can be attributed to several different factors. One of which is that the Australian wool industry has a more extensive marketing scheme when compared to the U.S wool market as a whole. However, this is only a beginning to future research that needs to be conducted. Continuing this study for future years, having more descriptive categories, and additional countries would further add explanation to wool prices.

The U.S. wool industry has long received lower prices for comparable wool types than those of Australia. In order to better understand such price differences, economic evaluations of both the U.S. and Australian wool markets were conducted. This research focused on two primary objectives. The first objective was to determine what price differences existed between the Australian and U.S. wool markets and measure that difference. The second objective was to calculate price differences attributable to wool characteristics, as well as those resulting from regional, seasonal, and yearly differences. In order to accomplish the objectives, the study was set up into three different hedonic pricing models: U.S., Australian, and combined. In the U.S. model, there were significant price differences in season, year, region, level of preparation, and wool description. In addition, average fiber diameter (AFD) had a negative nonlinear relationship with price and lot weight had a positive linear relationship with price. The Australian model was notably different than the U.S. model in that there were only three variables. The yearly variable follows the same general pattern as the U.S. data but with a smaller span of difference. The seasonal price differences were distinctly different than the U.S. because of the difference in seasonal patterns. In addition, the AFD had a similar negative nonlinear relationship with price. The final model combines both the U.S. data and the Australian data. The combined model had only three variables: season, year, AFD and country. As in the case of the previous two models, AFD had the same negative nonlinear relationship and similar price elasticity. Overall, there was a -30.5 percent discount for U.S. wool when compared to Australian wool. This can be attributed to several different factors. One of which is that the Australian wool industry has a more extensive marketing scheme when compared to the U.S wool market as a whole. However, this is only a beginning to future research that needs to be conducted. Continuing this study for future years, having more descriptive categories, and additional countries would further add explanation to wool prices.

High productivity rates, usage of nonproductive land, renewability and recovery of waste nutrients and potential for CO2 emission reduction represent some of the advantages that selected algae species might have over competing products. Many research studies have investigated potential usage of algae for different purposes, such as cosmetics or aquaculture; however most of the research studies have focused on the feasibility of algae as a source of second generation biodiesel and feed meal. Because of its high costs of production, using algae only for the purpose of biodiesel production might not be profitable. Thus, for global scale algae commercialization it is important that it be used as a feed meal along with being marketed to the biodiesel industry. One of the major problems faced by economists when attempting to analyze the feasibility of algae is the absence of a market for algae-based fuel and meal. Given that no market exists, prices for algae cannot be observed and realistic investment analysis becomes difficult to perform in this sector. The objective of this study is to estimate a potential price of algae meal using hedonic pricing techniques. For that purpose, twenty two different feed meals commonly having the same usage as Post Extracted Algae Residue (PEAR) are decomposed into their chemical constituents in order to calculate the market value of each characteristic. Calculated prices of these characteristics are then used to estimate the price of algae meal and compare it to different feed meals. Results suggest that algae prices are strictly variable to its chemical components across different algae types. Besides, PEAR represents a sustainable source of financial value and might be considered one of the cornerstones in making algae commercialization a feasible and profitable option.

Esta dissertação destina-se a realizar um estudo sobre o mercado imobiliário de lançamentos residenciais, mais especificamente apartamentos, no Município de São Paulo, tendo como base a utilização de preços hedônicos. Este trabalho baseia-se, principalmente, na abordagem da Teoria do Consumidor, de Lancaster, bem como em estudos relativos à precificação hedônica, de Court e Griliches, e em aplicações relativas ao mercado imobiliário, como a de Aryeetey-Attoh. Por meio de uma pesquisa qualitativa com especialistas, para a definição das variáveis hedônicas explicativas, e de uma pesquisa quantitativa, para a coleta de 480 dados amostrais relativos a preços de lançamento compreendidos entre os meses de abril de 2002 e março de 2003 e atributos para cada faixa de renda distrital de São Paulo, aplicam-se as técnicas de regressão conhecidas como cross-section, onde algumas especificações semilogarítmicas são propostas, escolhendo-se, para cada faixa de renda, a que apresenta o melhor ajuste estatístico. O método proposto permite a verificação do “pacote” de atributos que é mais representativo para a valorização dos imóveis residenciais em lançamento no Município de São Paulo, possibilitando a comparação da importância relativa de cada um para cada faixa de renda distrital. Portanto, permite-se o estudo de estratégias e de gerenciamento de projetos, designados para cada tipo específico de empreendimento imobiliário, de acordo com as preferências dos consumidores e das características das localidades. / This study intends to make a research about the real estate market, more specifically new apartments, in the Municipality of Sao Paulo, using hedonic prices theory. This work is based on the approach to Consumer Theory, by Lancaster, on some hedonic price studies, by Court and Griliches, and on real estate market applications, like Aryeetey-Attoh´s. Using a qualitative research with specialists, to define the independent hedonic variables, and a quantitative research, to provide 480 sample data related to launching prices occurred between April 2002 and March 2003 and attributes for each segment of low, middle and high income in the Municipality of Sao Paulo, it is used the regression techniques known as cross-section, in which some semilogarithmic specifications are suggested, choosing, for each income, the one that offers the best statistic adjust. The proposed method allows the verification about which attributes interfere the most in the price of real estates in Sao Paulo and it compares the relative importance of each one of these attributes whenever there are changes in social classes. Thus, it allows the study of strategies and project management, designated to each kind of real estate, according to the consumers’ preferences and locality characteristics.

Determining and predicting the exact prices of apartments is a complex task. It requires the data on the factors that directly influence the price of the apartment, such as the number of rooms or location of the apartment, and the information about the factors that indirectly affect the price, such as the availability of public transport and public goods near the apartment. One of the limitations of our work is the lack of data on the availability of indirect factors, and so in this paper we purely focus, and determine to what extent direct factors influence the formation of the final price. We find the influence of each of these factors with the help of the hedonic pricing, and the method of linear regression. After the first regression we identified which variable is least significant for our work and removed it. In our case it happened to be the variable Floor that identifies the level of the apartment. Further, we also test other types of regressions, such as semi – log regression, double – log regression, and quadratic regression. This is done to identify which of the regressions demonstrates the clearest picture on the effects of the variables. In other words, in which of the regressions the variables have the most significant parameter values. We found the Regression Five, a quadratic regression, to be an equation with the most significant parameter values. We also identified that the variables Rooms (indicating the number of rooms in the apartments) and Share (indicating the corporate share in the building) to have the biggest impact on the formation of the final price. Thus, we conclude that the variables Rooms and Share have the most significant influence on the price, whereas a quadratic regression (in this paper Regression Five) presents an equation with the most significant values of parameters and the highest degree of explanation.

Valuation of leases based on the contingent valuation may be biased because hypothetical data has limitations. This study used the hedonic method to evaluate factors affecting the value of hunting leases on Sixteenth Section Lands in Mississippi that are auctioned to the public. Due to the competitive nature of the issuance of these leases, this study provides a comprehensive and unbiased estimate of the impact that cover type, game quality, distance to urban areas, and location have on hunting lease prices. The implicit prices of these characteristics indicate that land managers should adopt shorter lease lengths, smaller lease sizes and improve habitat to increase lease revenue.

The effects of severely contaminated properties (e.g. NPL sites) on residential property values are well documented. However, most contaminated sites are not so severe to warrant placement on the NPL, and little is known about the impacts to commercial and industrial property markets. Furthermore, perceptions may be developed about different types of land-uses as a result of information made public about sites placed on lists. If perceptions matter, then properties with no known contamination may be viewed as undesirable neighbors in a way similar to listed sites. Therefore, property value impacts could be even more substantial as compared to only the impacts of known contaminated sites. The economic impacts of known and perceived environmental contamination are quantified by estimating two sets of hedonic property value models using data on commercial and industrial property sales for Fulton County, Georgia. Sites listed on the EPA’s CERCLIS and NFRAP reports and the Georgia EPD’s HSI and NonHSI reports are utilized to estimate the impacts of known environmental contamination. The impacts from perceived contamination are estimated utilizing a set of properties that are identified by an ordered probit model that computes the probability commercial and industrial properties may be contaminated. The probability of contamination model is built on factors that are assumed to be key signals to investors in forming their perceptions about the likelihood commercial and industrial properties may be contaminated. Property value losses due to known contamination were estimated at slightly over $1 billion and potential losses from perceived contamination were near $663 million. Although estimated property value impacts are not equivalent to expected gains that may result from the remediation of all contaminated sites, the magnitude of the estimated losses suggests that significant gains can be achieved if property values recover by only a fraction. Policies could be implemented that prioritize site remediation to target minority and/or economically depressed areas to help spur economic development. Potential increases in the tax base would result in greater property tax revenues for the provision of public services for the community and new economic development could help provide access to new jobs for local residents.