809 resultados para Housing prices
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Esta tese contém dois capítulos, cada um lidando com a teoria e a história dos bancos e arranjos financeiros. No capítulo 1, busca-se extender uma economia Diamond-Dybvig com monitoramento imperfeito dos saques antecipados e realizar uma comparação do bem estar social em cada uma das alocações possíveis, como proposto em Presscott and Weinberg(2003). Esse monitoramento imperfeito é implementado a partir da comunicação indireta ( através de um meio de pagamento) entre os agentes e a máquina de depósitos e saques que é um agregado do setor produtivo e financeiro. A extensão consiste em estudar alocações onde uma fração dos agentes pode explorar o monitoramento imperfeito e fraudar a alocação contratada ao consumirem mais cedo além do limite, usando múltiplos meios de pagamento. Com a punição limitada no período de consumo tardio, essa nova alocação pode ser chamada de uma alocação separadora em contraste com as alocações agregadoras onde o agente com habilidade de fraudar é bloqueado por um meio de pagamento imune a fraude, mas custoso, ou por receber consumo futuro suficiente para tornar a fraude desinteressante. A comparação de bem estar na gama de parâmetros escolhida mostra que as alocações separadoras são ótimas para as economias com menor dotação e as agregadoras para as de nível intermediário e as ricas. O capítulo termina com um possível contexto histórico para o modelo, o qual se conecta com a narrativa histórica encontrada no capítulo 2. No capítulo 2 são exploradas as propriedade quantitativas de um sistema de previsão antecedente para crises financeiras, com as váriaveis sendo escolhidas a partir de um arcabouço de ``boom and bust'' descrito mais detalhadamente no apêndice 1. As principais variáveis são: o crescimento real nos preços de imóveis e ações, o diferencial entre os juros dos títulos governamentais de 10 anos e a taxa de 3 meses no mercado inter-bancário e o crescimento nos ativos totais do setor bancário. Essas variáveis produzem uma taxa mais elevada de sinais corretos para as crises bancárias recentes (1984-2008) do que os sistemas de indicadores antecedentes comparáveis. Levar em conta um risco de base crescente ( devido à tendência de acumulação de distorções no sistema de preços relativos em expansões anteriores) também provê informação e eleva o número de sinais corretos em países que não passaram por uma expansão creditícia e nos preços de ativos tão vigorosa.
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Credit markets in emerging economies can be distinguished from those in advanced economies in many respects, including the collateral required for households to borrow. This work proposes a DSGE framework to analyze one peculiarity that characterizes the credit markets of some emerging markets: payroll-deducted personal loans. We add the possibility for households to contract long-term debt and compare two different types of credit constraints with one another, one based on housing and the other based on future income. We estimate the model for Brazil using a Bayesian technique. The model is able to solve a puzzle of the Brazilian economy: responses to monetary shocks at first appear to be strong but dissipate quickly. This occurs because income – and the amount available for loans – responds more rapidly to monetary shocks than housing prices. To smooth consumption, agents (borrowers) compensate for lower income and for borrowing by working more hours to repay loans and erase debt in a shorter time. Therefore, in addition to the income and substitution effects, workers consider the effects on their credit constraints when deciding how much labor to supply, which becomes an additional channel through which financial frictions affect the economy.
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In 1980, housing prices in the main US cities rose with distance to the city center. By 2010, that relationship had reversed. We propose that this development can be traced to greater labor supply of high-income households through reduced tolerance for commuting. In a tract-level data set covering the 27 largest US cities, years 1980-2010, we employ a city-level Bartik demand shifter for skilled labor and find support for our hypothesis: full-time skilled workers favor proximity to the city center and their increased presence can account for the observed price changes, notably the rising price premium commanded by centrality.
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Amenities value provided by green areas, sea, river and natural landscapes are hardly perceived and incorporated on urban planning and development. In this work, distance and view to protected and non-protected green areas, sea and river were evaluated as to how they increase the housing prices in Natal. Hedonic pricing methods were used with linear models to estimate the marginal implicit value of environmental, residential and neighborhood features. Results on Chapter 1 demonstrate the view to the sea and protected natural areas were largely capitalized on housing prices, while non-protected natural areas didn t display such effect. Housing prices also increase when close to the sea or to parks entrance. However, housing prices fall when houses are near non-protected natural areas. When estates with sea view were excluded, the protected natural areas view and a longer distance to non-protected natural areas increased dwelling prices. Results on Chapter 2 point the sea view as an hedonic variable the contributes strongly to the property selling prices, even though not always as the greatest contributor; furthermore, the property proximity to Dunas Park or City of the Park entrance increases its price, as does closeness to Dunas Park, view to City of the Park or Dunas Park. On the other hand, selling prices diminish if properties are close to City of the Park or Morro do Careca. Results on this study confirm the hedonic pricing methods is an important intrument, capable of revealing to popullation the importance of enviromental amenities and can be used by public managers for creating public policies for conservation and restoration projects
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The nocturnal, terrestrial frog Eleutherodactylus coqui, known as the Coqui, is endemic to Puerto Rico and was accidentally introduced to Hawai‘i via nursery plants in the late 1980s. Over the past two decades E. coqui has spread to the four main Hawaiian Islands, and a major campaign was launched to eliminate and control it. One of the primary reasons this frog has received attention is its loud mating call (85–90 dB at 0.5 m). Many homeowners do not want the frogs on their property, and their presence has influenced housing prices. In addition, E. coqui has indirectly impacted the floriculture industry because customers are reticent to purchase products potentially infested with frogs. Eleutherodactylus coqui attains extremely high densities in Hawai‘i, up to 91,000 frogs ha-1, and can reproduce year-round, once every 1–2 months, and become reproductive around 8–9 months. Although the Coqui has been hypothesized to potentially compete with native insectivores, the most obvious potential ecological impact of the invasion is predation on invertebrate populations and disruption of associated ecosystem processes. Multiple forms of control have been attempted in Hawai‘i with varying success. The most successful control available at this time is citric acid. Currently, the frog is established throughout the island of Hawai‘i but may soon be eliminated on the other Hawaiian Islands via control efforts. Eradication is deemed no longer possible on the island of Hawai‘i.
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Researchers have long recognized that the non-random sorting of individuals into groups generates correlation between individual and group attributes that is likely to bias naive estimates of both individual and group effects. This paper proposes a non-parametric strategy for identifying these effects in a model that allows for both individual and group unobservables, applying this strategy to the estimation of neighborhood effects on labor market outcomes. The first part of this strategy is guided by a robust feature of the equilibrium in the canonical vertical sorting model of Epple and Platt (1998), that there is a monotonic relationship between neighborhood housing prices and neighborhood quality. This implies that under certain conditions a non- parametric function of neighborhood housing prices serves as a suitable control function for the neighborhood unobservable in the labor market outcome regression. The second part of the proposed strategy uses aggregation to develop suitable instruments for both exogenous and endogenous group attributes. Instrumenting for each individual's observed neighborhood attributes with the average neighborhood attributes of a set of observationally identical individuals eliminates the portion of the variation in neighborhood attributes due to sorting on unobserved individual attributes. The neighborhood effects application is based on confidential microdata from the 1990 Decennial Census for the Boston MSA. The results imply that the direct effects of geographic proximity to jobs, neighborhood poverty rates, and average neighborhood education are substantially larger than the conditional correlations identified using OLS, although the net effect of neighborhood quality on labor market outcomes remains small. These findings are robust across a wide variety of specifications and robustness checks.
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The correlation between wage premia and concentrations of firm activity may arise due to agglomeration economies or workers sorting by unobserved productivity. A worker's residential location is used as a proxy for their unobservable productivity attributes in order to test whether estimated work location wage premia are robust to the inclusion of these controls. Further, in a locational equilibrium, identical workers must receive equivalent compensation so that after controlling for residential location (housing prices) and commutes workers must be paid the same wages and only wage premia arising from unobserved productivity differences should remain unexplained. The models in this paper are estimated using a sample of male workers residing in 33 large metropolitan areas drawn from the 5% Public Use Microdata Sample (PUMS) from the 2000 U.S. Decennial Census. We find that wages are higher when an individual works in a location that has more workers or a greater density of workers. These agglomeration effects are robust to the inclusion of residential location controls and disappear with the inclusion of commute time suggesting that the effects are not caused by unobserved differences in worker productivity. Extended model specifications suggest that wages increase with the education level of nearby workers and the concentration of workers in an individual's own industry or occupation.
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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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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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With an increasing demand for rural resources and land, new challenges are approaching affecting and restructuring the European countryside. While creating opportunities for rural living, it has also opened a discussion on rural gentrification risks. The concept of rural gentrification encircles the influx of new residents leading to an economic upgrade of an area making it unaffordable for local inhabitants to stay in. Rural gentrification occurs in areas perceived as attractive. Paradoxically, in-migrants re-shape their surrounding landscape. Rural gentrification may not only cause displacement of people but also landscape values. Thus, this research aims to understand the twofold role of landscape in rural gentrification theory: as a possible driver to attract residents and as a product shaped by its residents. To understand the potential gentrifiers’ decision process, this research has provided a collection of drivers behind in-migration. Moreover, essential indicators of rural gentrification have been collected from previous studies. Yet, the available indicators do not contain measures to understand related landscape changes. To fill this gap, after analysing established landscape assessment methodologies, evaluating the relevance for assessing gentrification, a new Landscape Assessment approach is proposed. This method introduces a novel approach to capture landscape change caused by gentrification through a historical depth. The measures to study gentrification was applied on Gotland, Sweden. The study showed a population stagnating while the number of properties increased, and housing prices raised. These factors are not indicating positive growth but risks of gentrification. Then, the research applied the proposed Landscape Assessment method for areas exposed to gentrification. Results suggest that landscape change takes place on a local scale and could over time endanger key characteristics. The methodology contributes to a discussion on grasping nuances within the rural context. It has also proven useful for indicating accumulative changes, which is necessary in managing landscape values.
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Mode of access: Internet.
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Mode of access: Internet.
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We estimate empirically the effect of immigration on house prices and residentialconstruction activity in Spain over the period 1998-2008. This decade is characterized by both aspectacular housing market boom and a stunning immigration wave. We exploit the variation inimmigration across Spanish provinces and construct an instrument based on the historicallocation patterns of immigrants by country of origin. The evidence points to a sizeable causaleffect of immigration on both prices and quantities in the housing market. Between 1998 and2008, the average Spanish province received an immigrant inflow equal to 17% of the initialworking-age population. We estimate that this inflow increased house prices by about 52% andis responsible for 37% of the total construction of new housing units during the period. Thesefigures imply that immigration can account for roughly one third of the housing boom, both interms of prices and new construction.