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This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance process and define both a random effects and a fixed effects spatial generalized two-stage least squares estimator for the regression parameters of the model. We prove consistency of the proposed estimators and derive their joint asymptotic distribution, which is robust to heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random against the spatial fixed effects model. (authors' abstract) / Series: Department of Economics Working Paper Series

Many databases involve ordered discrete responses in a temporal and spatial context, including, for example, land development intensity levels, vehicle ownership, and pavement conditions. An appreciation of such behaviors requires rigorous statistical methods, recognizing spatial effects and dynamic processes. This dissertation develops a dynamic spatial ordered probit (DSOP) model in order to capture patterns of spatial and temporal autocorrelation in ordered categorical response data. This model is estimated in a Bayesian framework using Gibbs sampling and data augmentation, in order to generate all autocorrelated latent variables. The specifications, methodologies, and applications undertaken here advance the field of spatial econometrics while enhancing our understanding of land use and air quality changes. The proposed DSOP model incorporates spatial effects in an ordered probit model by allowing for inter-regional spatial interactions and heteroskedasticity, along with random effects across regions (where "region" describes any cluster of observational units). The model assumes an autoregressive, AR(1), process across latent response values, thereby recognizing time-series dynamics in panel data sets. The model code and estimation approach is first tested on simulated data sets, in order to reproduce known parameter values and provide insights into estimation performance. Root mean squared errors (RMSE) are used to evaluate the accuracy of estimates, and the deviance information criterion (DIC) is used for model comparisons. It is found that the DSOP model yields much more accurate estimates than standard, non-spatial techniques. As for model selection, even considering the penalty for using more parameters, the DSOP model is clearly preferred to standard OP, dynamic OP and spatial OP models. The model and methods are then used to analyze both land use and air quality (ozone) dynamics in Austin, Texas. In analyzing Austin's land use intensity patterns over a 4-point panel, the observational units are 300 m × 300 m grid cells derived from satellite images (at 30 m resolution). The sample contains 2,771 such grid cells, spread among 57 clusters (zip code regions), covering about 10% of the overall study area. In this analysis, temporal and spatial autocorrelation effects are found to be significantly positive. In addition, increases in travel times to the region's central business district (CBD) are estimated to substantially reduce land development intensity. The observational units for the ozone variation analysis are 4 km × 4 km grid cells, and all 132 observations falling in the study area are used. While variations in ozone concentration levels are found to exhibit strong patterns of temporal autocorrelation, they appear strikingly random in a spatial context (after controlling for local land cover, transportation, and temperature conditions). While transportation and land cover conditions appear to influence ozone levels, their effects are not as instantaneous, nor as practically significant as the impact of temperature. The proposed and tested DSOP model is felt to be a significant contribution to the field of spatial econometrics, where binary applications (for discrete response data) have been seen as the cutting edge. The Bayesian framework and Gibbs sampling techniques used here permit such complexity, in world of two-dimensional autocorrelation. / text

Submitted by Vitor Bovo (vitorbovo@hotmail.com) on 2011-08-26T00:07:04Z No. of bitstreams: 1 Dissertação Vitor Bovo - Final Protocolada.pdf: 2961673 bytes, checksum: 2da3f793ce6283d4140f390c02baee53 (MD5) / Approved for entry into archive by Gisele Isaura Hannickel (gisele.hannickel@fgv.br) on 2011-08-26T15:37:19Z (GMT) No. of bitstreams: 1 Dissertação Vitor Bovo - Final Protocolada.pdf: 2961673 bytes, checksum: 2da3f793ce6283d4140f390c02baee53 (MD5) / Approved for entry into archive by Gisele Isaura Hannickel (gisele.hannickel@fgv.br) on 2011-08-26T15:37:32Z (GMT) No. of bitstreams: 1 Dissertação Vitor Bovo - Final Protocolada.pdf: 2961673 bytes, checksum: 2da3f793ce6283d4140f390c02baee53 (MD5) / Made available in DSpace on 2011-08-26T15:39:05Z (GMT). No. of bitstreams: 1 Dissertação Vitor Bovo - Final Protocolada.pdf: 2961673 bytes, checksum: 2da3f793ce6283d4140f390c02baee53 (MD5) Previous issue date: 2011-08-05 / Este trabalho propõe um instrumento capaz de absorver choques no par BRL/USD, garantindo ao seu detentor a possibilidade de realizar a conversão entre essas moedas a uma taxa observada recentemente. O Volatility Triggered Range Forward assemelha-se a um instrumento forward comum, cujo preço de entrega não é conhecido inicialmente, mas definido no momento em que um nível de volatilidade pré-determinado for atingido na cotação das moedas ao longo da vida do instrumento. Seu cronograma de ajustes pode ser definido para um número qualquer de períodos. Seu apreçamento e controle de riscos é baseado em uma árvore trinomial ponderada entre dois possíveis regimes de volatilidade. Esses regimes são determinados após um estudo na série BRL/USD no período entre 2003 e 2009, baseado em um modelo Switching Autoregressive Conditional Heteroskedasticity (SWARCH). / This work proposes an instrument able to absorb shocks in the BRL/USD rate, ensuring its holder the capability of doing foreign currency exchange at some immediate prevailing rate. The Volatility Triggered Range Forward resembles a plain-vanilla forward whose delivery price is unknown initially and will be set once a pre-determined level of volatility threshold is reached in the exchange rate along the instrument’s life. Its payoff schedule can be set for any number of periods. Pricing and risk management is based on a trinomial lattice weighted between two possible regimes of volatility. These regimes are determined after a study of the BRL/USD series for the period between 2003 and 2009, based on a Switching Autoregressive Conditional Heteroskedasticity (SWARCH) model.

Made available in DSpace on 2014-06-11T19:28:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-02-24Bitstream added on 2014-06-13T18:57:29Z : No. of bitstreams: 1 souza_fa_me_jabo.pdf: 1931388 bytes, checksum: 4c66f4cd56386572eb7ad4b52f5d1472 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho avaliou a influência da heterocedasticidade e dos níveis nutricionais (número e posição) utilizados em ensaios dose-resposta, na estimativa do nível-ótimo e no ajuste dos modelos, além de verificar o quão informativas são as estatísticas utilizadas para avaliar a precisão do ajuste (R², R² ajustado, CV e SQD). Utilizaram-se dados dos experimentos realizados por Nascimento et al. (2007) e Siqueira (2009) e dados simulados. Constatou-se que, quando os níveis estiveram distribuídos próximos do verdadeiro requerimento, os modelos com platô proporcionaram resultados mais confiáveis. Já os modelos quadrático e exponencial se mostraram mais adequados para situações no qual os níveis estão mais dispersos em relação ao verdadeiro requerimento. A heterocedasticidade não interferiu na estimativa do nível-ótimo, porém influenciou no ajuste dos modelos e proporcionou pequenas mudanças nos parâmetros das equações obtidas. O coeficiente de determinação (ajustado e não ajustado) foi diretamente influenciado pela definição do nível mais próximo do ótimo e dos níveis extremos, enquanto que, o coeficiente de variação e a soma dos quadrados dos desvios, pelos níveis iniciais e pelo nível próximo do ótimo. A soma dos quadrados dos desvios demonstrou ser mais sensível, pois seu valor apresentou pequenas variações entre os modelos nas diferentes situações, que as outras estatísticas não detectaram. Ressalta-se a importância de se estabelecer corretamente o intervalo dos níveis estudados para que a dispersão dos valores do nível-ótimo estimado seja minimizada e que o ajuste seja satisfatório, independente do modelo utilizado / This work evaluated the influence of heteroskedasticity and the nutritional levels (number and position) used in dose-response trials to estimating the optimal-level and the adjustment of the models, also check how informative are the statistics used to evaluate the accuracy of fit (R ², R ² adjusted, CV and SQD). The data used in this experiment are from Nascimento et al. (2007) and’ Siqueira (2009) trials and simulated data. It was found that when levels were distributed close to the real requirement, the models with plateau have provided more reliable results. Since the quadratic and exponential models were more suitable for situations in which the levels are more dispersed about the real requirement. The heteroskedasticity did not affect the estimate of the level-optimal, but influenced the adjustment of the models and provided small changes in the parameters of the equations obtained. The coefficient of determination (adjusted and unadjusted) was directly influenced by the definition of the level closest to the optimum and extreme levels, while the coefficient of variation and the sum of squares of deviations were influenced by the initial levels and the level close to the optimum. The sum of squares of deviations was more sensitive, because its value showed small variations between models in different situations that the other statistics did not detect. Emphasized the importance to precisely define the range of levels studied to the dispersion of the obtained optimal-level is minimized and the fit is satisfactory regardless of the model

The empirical paper studies the relationship between property value and hedonic attributes. To indentify the determinant characteristics the influent the private real estate price, their degrees of significance and help with the valuation procedure, 8870 private residential property transactions with caveats lodged across country are selected from Urban Redevelopment Authority of Singapore. 40 models are tested and RMSE, R-Square, Adjusted R-Square, F-Value tests are performed to discover the overall fitness of the models. Breusch-Pagan F-Test is performed to test the existence of heteroskedasticity and VIF test to check multicolinearity. Z score is performed to check the spatial autocorrelation. Three founding are discovered. Firstly, size, age, floor level, population density level, latitude and construction status are core attributes resulting from the regression. Secondly, new district zones classified by functions are detected instead of 28 administrative districts. Thirdly, government policies and local customs (Feng Shui) are proven to be determinant variables as well. Two suggestions are given to regulate the market in the end of this article.

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This thesis focuses on analysis and comparison of volatility on selected European stock markets. At first paper briefly introduces the reader to the specific features of financial econometrics and the importance of asset returns volatility analysis. Further chapters precisely cover the construction of linear and nonlinear conditional heteroscedasticity models as an appropriate tool for describing the volatility in financial data. The empirical part of the thesis analyze four stock exchange indices from various European regions and seek appropriate models to express volatility behavior in period before the financial crisis in 2008 and also during the crisis phase. Based on selected models, the paper tries to compare the volatility in both periods within the specific stock market index and moreover between different regions. The last section examines asymmetric effects in volatility of stock indices using their graphical representation.

[pt] A partir do método de Rigobon (2001) para identificação de um sistema de equações simultâneas na presença de heterocedasticidade, aprofundamos a discussão sobre a relação entre os preços internacionais de commodities e o câmbio real para países com determinadas características. Ao contrário da abordagem tradicional da literatura de commodity currency nesta dissertação admitimos a possibilidade dos preços de commodities serem endógenos em relação à taxa de câmbio, trabalhamos com séries que incorporam mais de um regime cambial e, através de diversas simulações, encontramos evidências de que hipóteses sobre a estacionariedade das séries, em torno da raiz unitária, não afetam significativamente os resultados do exercício empírico. Salvo algumas restrições, os resultados derivados sugerem que o câmbio real do Brasil deve apreciar em resposta a elevações nos preços internacionais das principais commodities que exporta, mas a elasticidade dos preços de commodities em relação ao câmbio não pode ser considerada estatisticamente diferente de zero. Para a Nova Zelândia, as evidências indicam que os efeitos contemporâneos dos movimentos da taxa de câmbio sobre os preços das suas principais commodities exportadas é significativo, embora o efeito dos preços das commodities sobre o câmbio deva ser considerado estatisticamente igual a zero. / [en] Using Rigobons (2001) identification method for simultaneous equations models, based on the heteroskedasticity of the structural shocks, we analyze the relationship between the exchange rate and commodity prices for specific countries. Instead of the traditional approach of the commodity currency literature, we allow for endogenous effects of the exchange rates on the commodity prices, and we work with series that span two exchange rate regimes. From the results of some simulations, we also find out that the lack of assumptions about the stationarity of the series, close to the unity root, do not harm the conclusions of the empirical exercise. In spite of some caveats, the results of the empirical investigation suggest that the real exchange rate of Brazil should appreciate in response to a rise in the prices of its most important export commodities. However, the elasticity of the commodity prices to the exchange rate can not be considered different from zero, implicating that the country does not have much market power in the trade of these commodities. For New Zealand, the evidence indicates that exchange rate variations are important for the determination of the commodity prices, although the impact of commodity prices on the exchange rate is statistically equal to zero.

The thesis "Four Essays on the Econometric Modelling of Volatility and Durations" consists of four research papers in the area of financial econometrics on topics of the modelling of financial market volatility and the econometrics of ultra-high-frequency data. The aim of the thesis is to develop new econometric methods for modelling and hypothesis testing in these areas. The second chapter introduces a new model, the time-varying GARCH (TV-GARCH) model, in which volatility has a smooth time-varying structure of either additive or multiplicative type. To characterize smooth changes in the (un)conditional variance we assume that the parameters vary smoothly over time according to the logistic transition function. A data-based modelling technique is used for specifying the parametric structure of the TV-GARCH models. This is done by testing a sequence of hypotheses by Lagrange multiplier tests presented in the chapter. Misspecification tests are also provided for evaluating the adequacy of the estimated model. The third chapter addresses the issue of modelling deterministic changes in the unconditional variance over a long return series. The modelling strategy is illustrated with an application to the daily returns of the Dow Jones Industrial Average (DJIA) index from 1920 until 2003. The empirical results sustain the hypothesis that the assumption of constancy of the unconditional variance is not adequate over long return series and indicate that deterministic changes in the unconditional variance may be associated with macroeconomic factors. In the fourth chapter we propose an extension of the univariate multiplicative TV-GARCH model to the multivariate Conditional Correlation GARCH (CC-GARCH) framework. The variance equations are parameterized such that they combine the long-run and the short-run dynamic behaviour of the volatilities. In this framework, the long-run behaviour is described by the individual unconditional variances, and it is allowed to vary smoothly over time according to the logistic transition function. The effects of modelling the nonstationary variance component are examined empirically in several CC-GARCH models using pairs of seven daily stock return series from the S&P 500 index. The results show that the magnitude of such effect varies across different stock series and depends on the structure of the conditional correlation matrix. An important feature of financial durations is the evidence of a strong diurnal variation over the trading day. In the fifth chapter we propose a new parameterization for describing the diurnal pattern of trading activity. The parametric structure of the diurnal component allows the duration process to change smoothly over the time-of-day according to the logistic transition function. The empirical results suggest that the diurnal variation may not always have the inverted U-shaped pattern for the trade durations as documented in earlier studies.