862 resultados para Hedonic Property Value Model
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The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.
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The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.
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Thesis (Master's)--University of Washington, 2016-06
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We re-examine the dynamics of returns and dividend growth within the present-value framework of stock prices. We find that the finite sample order of integration of returns is approximately equal to the order of integration of the first-differenced price-dividend ratio. As such, the traditional return forecasting regressions based on the price-dividend ratio are invalid. Moreover, the nonstationary long memory behaviour of the price-dividend ratio induces antipersistence in returns. This suggests that expected returns should be modelled as an AFIRMA process and we show this improves the forecast ability of the present-value model in-sample and out-of-sample.
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It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.
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This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.
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Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.
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After reviewing the Present Value Model (PVM), in its basic form and with its major extensions, the authors carried out a literature review on the instrumental uses of farm land prices; namely what land prices may reveal in the framework of the PVM. Urban influence, non-market goods and climate change are topics where the PVM used with applied data may reveal farmers’ or landowners’ beliefs or subjective values, which are discussed in this paper. There is also extensive discussion of the topic of public regulations, and how they may affect land price directly, or through its present value.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregressive process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The Öltered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidenced for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.
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This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregression process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The filtered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidence for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.
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Increasing levels of segregation in American schools raises the question: do home buyers pay for test scores or demographic composition? This paper uses Connecticut panel data spanning eleven years from 1994 to 2004 to ascertain the relationship between property values and explanatory variables that include school district performance and demographic attributes, such as racial and ethnic composition of the student body. Town and census tract fixed effects are included to control for neighborhood unobservables. The effect of changes in school district attributes is also examined over a decade long time frame in order to focus on the effect of long run changes, which are more likely to be capitalized into prices. The study finds strong evidence that increases in percent Hispanic has a negative effect on housing prices in Connecticut, but mixed evidence concerning the impact of test scores on property values. Evidence is also found to suggest that student test scores have increased in importance for explaining housing prices in recent years while the importance of percent Hispanic has declined. Finally, the study finds that estimates of property tax capitalization increase substantially when the analysis focuses on long run changes.
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Una de las principales líneas de investigación de la economía urbana es el comportamiento del mercado inmobiliario y sus relaciones con la estructura territorial. Dentro de este contexto, la reflexión sobre el significado del valor urbano, y abordar su variabilidad, constituye un tema de especial importancia, dada la relevancia que ha supuesto y supone la actividad inmobiliaria en España. El presente estudio ha planteado como principal objetivo la identificación de aquellos factores, ligados a la localización que explican la formación del valor inmobiliario y justifican su variabilidad. Definir este proceso precisa de una evaluación a escala territorial estableciendo aquellos factores de carácter socioeconómico, medioambiental y urbanístico que estructuran el desarrollo urbano, condicionan la demanda de inmuebles y, por tanto, los procesos de formación de su valor. El análisis se centra en valores inmobiliarios residenciales localizados en áreas litorales donde la presión del sector turístico ha impulsado un amplio. Para ello, el ámbito territorial seleccionado como objeto de estudio se sitúa en la costa mediterránea española, al sur de la provincia de Alicante, la comarca de la Vega Baja del Segura. La zona, con una amplia diversidad ecológica y paisajística, ha mantenido históricamente una clara distinción entre espacio urbano y espacio rural. Esta dicotomía ha cambiado drásticamente en las últimas décadas, experimentándose un fuerte crecimiento demográfico y económico ligado a los sectores turístico e inmobiliario, aspectos que han tenido un claro reflejo en los valores inmobiliarios. Este desarrollo de la comarca es un claro ejemplo de la política expansionista de los mercados de suelo que ha tenido lugar en la costa española en las dos últimas décadas y que derivado en la regeneración de un amplio tejido suburbano. El conocimiento del marco territorial ha posibilitado realizar un análisis de variabilidad espacial mediante un tratamiento masivo de datos, así como un análisis econométrico que determina los factores que se valoran positivamente y negativamente por el potencial comprador. Estas relaciones permiten establecer diferentes estructuras matemáticas basadas en los modelos de precios hedónicos, que permiten identificar rasgos diferenciales en los ámbitos económico, social y espacial y su incidencia en el valor inmobiliario. También se ha sistematizado un proceso de valoración territorial a través del análisis del concepto de vulnerabilidad estructural, entendido como una situación de fragilidad debida a circunstancias tanto sociales como económicas, tanto actual como de tendencia en el futuro. Actualmente, esta estructura de demanda de segunda residencia y servicios ha mostrado su fragilidad y ha bloqueado el desarrollo económico de la zona al caer drásticamente la inversión en el sector inmobiliario por la crisis global de la deuda. El proceso se ha agravado al existir un tejido industrial marginal al que no se ha derivado inversiones importantes y un abandono progresivo de las explotaciones agropecuarias. El modelo turístico no sería en sí mismo la causa del bloqueo del desarrollo económico comarcal, sino la forma en que se ha implantado en la Costa Blanca, con un consumo del territorio basado en el corto plazo, poco respetuoso con aspectos paisajísticos y medioambientales, y sin una organización territorial global. Se observa cómo la vinculación entre índices de vulnerabilidad y valor inmobiliario no es especialmente significativa, lo que denota que las tendencias futuras de fragilidad no han sido incorporadas a la hora de establecer los precios de venta del producto inmobiliario analizado. El valor muestra una clara dependencia del sistema de asentamiento y conservación de las áreas medioambientales y un claro reconocimiento de tipologías propias del medio rural aunque vinculadas al sector turístico. En la actualidad, el continuo descenso de la demanda turística ha provocado una clara modificación en la estructura poblacional y económica. Al incorporar estas modificaciones a los modelos especificados podemos comprobar un verdadero desmoronamiento de los valores. Es posible que el remanente de vivienda construida actualmente vaya dirigido a un potencial comprador que se encuentra en retroceso y que se vincula a unos rasgos territoriales ya no existentes. Encontrar soluciones adaptables a la oferta existente, implica la viabilidad de renovación del sistema poblacional o modificaciones a nivel económico. La búsqueda de respuestas a estas cuestiones señala la necesidad de recanalizar el desarrollo, sin obviar la potencialidad del ámbito. SUMMARY One of the main lines of research regarding the urban economy focuses on the behavior of the real estate market and its relationship to territorial structure. Within this context, one of the most important themes involves considering the significance of urban property value and dealing with its variability, particularly given the significant role of the real estate market in Spain, both in the past and present. The main objective of this study is to identify those factors linked to location, which explain the formation of property values and justify their variability. Defining this process requires carrying out an evaluation on a territorial scale, establishing the socioeconomic, environmental and urban planning factors that constitute urban development and influence the demand for housing, thereby defining the processes by which their value is established. The analysis targets residential real estate values in coastal areas where pressure from the tourism industry has prompted large-scale transformations. Therefore, the focal point of this study is an area known as Vega Baja del Segura, which is located on the Spanish Mediterranean coast in southern Alicante (province). Characterized by its scenic and ecological diversity, this area has historically maintained a clear distinction between urban and rural spaces. This dichotomy has drastically changed in past decades due to the large increase in population attributed to the tourism and real estate markets – factors which have had a direct effect on property values. The development of this area provides a clear example of the expansionary policies which have affected the housing market on the coast of Spain during the past two decades, resulting in a large increase in suburban development. Understanding the territorial framework has made it possible to carry out a spatial variability analysis through massive data processing, as well as an econometric analysis that determines the factors that are evaluated positively and negatively by potential buyers. These relationships enable us to establish different mathematical systems based on hedonic pricing models that facilitate the identification of differential features in the economic, social and spatial spheres, and their impact on property values. Additionally, a process for land valuation was established through an analysis of the concept of structural vulnerability, which is understood to be a fragile situation resulting from either social or economic circumstances. Currently, this demand structure for second homes and services has demonstrated its fragility and has inhibited the area’s economic development as a result of the drastic fall in investment in the real estate market, due to the global debt crisis. This process has been worsened by the existence of a marginal industrial base into which no important investments have been channeled, combined with the progressive abandonment of agricultural and fishing operations. In and of itself, the tourism model did not inhibit the area’s economic development, rather it is the result of the manner in which it was implemented on the Costa Brava, with a land consumption based on the short-term, lacking respect for landscape and environmental aspects and without a comprehensive organization of the territory. It is clear that the link between vulnerability indexes and property values is not particularly significant, thereby indicating that future fragility trends have not been incorporated into the problem in terms of establishing the sale prices of the analyzed real estate product in question. Urban property values are clearly dependent on the system of development and environmental conservation, as well as on a clear recognition of the typologies that characterize rural areas, even those linked to the tourism industry. Today, the continued drop in tourism demand has provoked an obvious modification in the populational and economic structures. By incorporating these changes into the specified models, we can confirm a real collapse in values. It’s possible that the surplus of already-built homes is currently being marketed to a potential buyer who is in recession and linked to certain territorial characteristics that no longer exist. Finding solutions that can be adapted to the existing offer implies the viability of renewing the population system or carrying out modifications on an economic level. The search for answers to these questions suggests the need to reform the development model, without leaving out an area’s potentiality.
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Use of nonlinear parameter estimation techniques is now commonplace in ground water model calibration. However, there is still ample room for further development of these techniques in order to enable them to extract more information from calibration datasets, to more thoroughly explore the uncertainty associated with model predictions, and to make them easier to implement in various modeling contexts. This paper describes the use of pilot points as a methodology for spatial hydraulic property characterization. When used in conjunction with nonlinear parameter estimation software that incorporates advanced regularization functionality (such as PEST), use of pilot points can add a great deal of flexibility to the calibration process at the same time as it makes this process easier to implement. Pilot points can be used either as a substitute for zones of piecewise parameter uniformity, or in conjunction with such zones. In either case, they allow the disposition of areas of high and low hydraulic property value to be inferred through the calibration process, without the need for the modeler to guess the geometry of such areas prior to estimating the parameters that pertain to them. Pilot points and regularization can also be used as an adjunct to geostatistically based stochastic parameterization methods. Using the techniques described herein, a series of hydraulic property fields can be generated, all of which recognize the stochastic characterization of an area at the same time that they satisfy the constraints imposed on hydraulic property values by the need to ensure that model outputs match field measurements. Model predictions can then be made using all of these fields as a mechanism for exploring predictive uncertainty.
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I show that intellectual property rights yield static efficiency gains, irrespective oftheir dynamic role in fostering innovation. I develop a property-rights model of firmorganization with two dimensions of non-contractible investment. In equilibrium, thefirst best is attained if and only if ownership of tangible and intangible assets is equallyprotected. If IP rights are weaker, firm structure is distorted and efficiency declines:the entrepreneur must either integrate her suppliers, which prompts a decline in theirinvestment; or else risk their defection, which entails a waste of her human capital. Mymodel predicts greater prevalence of vertical integration where IP rights are weaker,and a switch from integration to outsourcing over the product cycle. Both empiricalpredictions are consistent with evidence on multinational companies. As a normativeimplication, I find that IP rights should be strong but narrowly defined, to protect abusiness without holding up its potential spin-offs.