Thesis (MA (Geography and Environmental Studies))--University of Stellenbosch, 2010. / ENGLISH ABSTRACT: The research problem addressed in this study is how to ascertain the primary determinants of house prices in Hout Bay. This overarching aim encompasses three interwoven aspects. The research attempts first to determine which factors generally affect property prices in Hout Bay; second, to assess the extent to which individual factors affect house prices; and third, to discover the role variables collectively play in determining house prices in Hout Bay. Four objectives emerge from this subdivision of the aim, namely identify potential house priceinfluencing factors in Hout Bay; quantify the selected locational variables; statistically analyse the variables to distinguish the significant and insignificant ones; and use regression analysis to deduce the collective and individual influences of the significant factors on house prices. Structured interviews were conducted with representatives of 12 estate agencies in Hout Bay to uncover factors affecting the local property market. Through insights gleaned from the literature, manipulation of municipal valuation and cadastral data and the structured interviews, 39 structural and site-related variables, 18 distance variables and 11 socioeconomic variables were constructed. Several preliminary and descriptive analyses performed on the variables gave a general impression of the distribution of data and assisted in identifying statistically significant variables for determining house prices. These analyses included measures of central tendency (mean, median and mode); measures of dispersion (minimum and maximum values, range, standard deviation, skewness and kurtosis); the compilation of histograms for each variable; analysis of variance (ANOVA) on nominal data variables; and the creation of 2D scatterplots for ordinal data variables. Spearman rank order correlation was performed on the nominal and ordinal data variables. Statistically weak variables and those exhibiting signs of multicollinearity were eliminated. A best-subsets regression analysis was executed on the remaining variables. The regression model performed adequately, explaining close to 54% of the variation in house prices in Hout Bay. Among the individual factors, the size of the erf was the strongest predictor of the house price dependent variable, house size was the second most important factor, while distance to busy roads and quality of the house shared similar importance. Regression residuals were also mapped to expose spatial patterns. It is recommended that comparable research be conducted on a citywide scale, that variables be quantified differently and that new GIS techniques be incorporated in future studies. / AFRIKAANSE OPSOMMING: Die navorsingsprobleem wat hierdie studie aanspreek, is hoe om vas te stel wat die primêre faktore is wat huispryse in Houtbaai bepaal. Hierdie oorkoepelende doelwit vervat drie onderling verwante aspekte. Eerstens, poog die navorsing om te bepaal watter faktore in die algemeen huispryse in Houtbaai beïnvloed; tweedens, om te assesseer tot watter mate individuele faktore huispryse affekteer; en derdens, om te ontdek watter kollektiewe rol veranderlikes in die bepaling van huispryse in Houtbaai speel. Vanuit hierdie onderverdeling van die navorsingsdoelwit het vier doelstellings ontstaan, naamlik identifiseer die potensiële faktore wat huispryse in Houtbaai beïnvloed; kwantifiseer die geselekteerde liggingsveranderlikes; voer verskeie analises uit op die veranderlikes om die beduidende en onbeduidende veranderlikes te identifiseer; en benut regressie-analise om die kollektiewe en individuele invloed van beduidende faktore op huispryse in die studiegebied vas te stel. Gestruktureerde onderhoude is met verkoopslui van 12 eiendomsagentskappe in Houtbaai gevoer om die faktore te bepaal wat die plaaslike eiendomsmark beïnvloed. Deur middel van insigte verkry uit die akademiese literatuur, manipulasie van munisipale waardasie- en kadastrale data en die gestruktureerde onderhoude is 39 strukturele en liggingsverwante veranderlikes, 18 afstandsveranderlikes en 11 sosio-ekonomiese veranderlikes geskep. Verskeie analises wat op die veranderlikes uitgevoer is, het ‘n algemene indruk van die verspreiding van die data verskaf en het die identifisering van statistiesbeduidende veranderlikes bevorder. Hierdie analises het maatstawwe vir sentrale neiging (rekenkundige gemiddelde, mediaan en modus); maatstawwe vir dispersie (minimum en maksimum, variasiewydte, standaardafwyking, skeefheid en kurtose); die samestelling van histogramme vir elke veranderlike; die analise van variansie (ANOVA) op veranderlikes met nominale data; en die skep van 2D-spreidingstippe vir veranderlikes met ordinale data behels. Spearman se rangorde korrelasie is op beide die nominale en ordinale data uitgevoer. Statistiesonbeduidende veranderlikes, of dié wat tekens van multikollineariteit met ander veranderlikes getoon het, is geëlimineer. ‘n Beste deelversameling regressie-analise is uitgevoer op die oorblywende veranderlikes. Die regressiemodel het gepaste resultate behaal deurdat dit byna 54% van die variasie in Houtbaai se huispryse verklaar het. Van die individuele veranderlikes was die grootte van die erf die sterkste voorspeller van die huisprys afhanklike veranderlike, huisgrootte was die tweede belangrikste faktor, terwyl afstand van besige paaie en die kwaliteit van die huis soortgelyke invloed gedeel het. Die regressiemodel se residu’s is gekarteer om ruimtelike patrone vas te stel. Dit word aanbeveel dat soortgelyke navorsing op ‘n stadswye skaal uitgevoer word, dat die veranderlikes op ander wyses gekwantifiseer word en dat nuwe GIStegnieke in toekomstige studies aangewend word.

This thesis examines the effects of monetary policy shocks on the housing market. To this end, TVP-VAR model with dynamic dimension selection and stochastic volatility is estimated using monthly data for the United States over the period 1999-2017. Moreover, the model features estimating the optimal value of the Bayesian shrinkage coefficient in a time-varying manner. Since the sample covers the Zero Lower Bound period, Wu-Xia shadow rate is employed to measure the stance of monetary policy. To assess the link between housing variables and monetary policy, impulse responses and forecast error variance decompositions are provided. However, due to the time-varying nature of the model, they are estimated only for selected time periods that correspond both to the events that most likely influenced the path of macroeconomic and financial variables and to periods of low economic uncertainty. The main results are threefold. First, the model suggests that monetary policy shocks can contribute to developments in house prices. Second, the stimulative monetary policy positively affects residential investment and negatively affects mortgage rates, however, the effects are not significant due to the large confidence bands of the impulse responses. Third, higher values of the shrinkage hyperparameter are crucial for...

Submitted by Guilherme Lisboa Ramirez (guilherme.ramirez@uol.com.br) on 2013-02-27T17:11:14Z No. of bitstreams: 1 Dissertacao_Guilherme_Ramirez_vf.pdf: 937329 bytes, checksum: ad15d191716d7337747bcc3f83b75fa0 (MD5) / Approved for entry into archive by Vera Lúcia Mourão (vera.mourao@fgv.br) on 2013-02-27T17:30:52Z (GMT) No. of bitstreams: 1 Dissertacao_Guilherme_Ramirez_vf.pdf: 937329 bytes, checksum: ad15d191716d7337747bcc3f83b75fa0 (MD5) / Made available in DSpace on 2013-02-27T17:58:58Z (GMT). No. of bitstreams: 1 Dissertacao_Guilherme_Ramirez_vf.pdf: 937329 bytes, checksum: ad15d191716d7337747bcc3f83b75fa0 (MD5) Previous issue date: 2013-01-29 / The analysis of the evolution of housing affordability indexes is important in monitoring variations in the capability of a household to purchase a house. The methodology used in this study allows the analysis of housing affordability indexes for different income classes, once it takes into account the whole distribution of household income and house prices, since they have different skewness. The analysis of the Brazilian market under this methodology has shown a decrease in housing affordability in recent years, due to a steeper rise in house prices when compared to the combined effect of household income variations and the loosening of credit constraints. / A análise da evolução dos indicadores de housing affordability permite acompanhar o comportamento do poder de compra de um imóvel. A metodologia utilizada nesta dissertação, ao considerar toda a distribuição da renda domiciliar e do preço dos imóveis, uma vez que as mesmas possuem assimetrias diferentes, possibilita analisar estes indicadores para diferentes segmentos da população. A aplicação desta metodologia para o mercado brasileiro possibilitou observar que a capacidade de compra se reduziu nos últimos anos devido, principalmente, ao aumento do preço dos imóveis a uma taxa maior do que a variação da renda combinada com a flexibilização das condições de credito imobiliário.

After the recent world financial crisis, macroprudential policy tools have started to play an important role in maintaining financial stability. In many countries, the tools have been extensively used only in recent years and their effectiveness is often difficult to assess. Using an index as a proxy for policy tools is one of ways to measure their impact. In this thesis, a new index capturing, in contrast with other studies, also an intensity factor, is constructed. Results are mostly in accordance with economic intuition and existing studies and suggest that indices constructed in an equivalent way can help to understand the impact of policies on changes in housing prices and credit volumes. JEL Classification F12, F21, F23, H25, H71, H87 Keywords macroprudential policy, systemic risk, house prices growth, credit growth Author's e-mail Lucie.Wdowyczynova@hotmail.com Supervisor's e-mail Simona.Malovana@gmail.com

The diploma thesis is mainly focused on the housing market and central bank's (supervisory authority's) potential reactions to risks arising from it. The thesis provides a broader perspective of the housing market so that the first part is devoted to the liquidity surplus as it is closely connected with the housing market. The next part of the thesis focuses on housing price bubbles and subsequent bursts as well as the tools of the central bank (supervisory authority) to mitigate such risks. It is discussed whether using monetary policy to affect house prices that do not reflect fundamentals is advisable. Macroprudential policy with its tools is introduced as an alternative. Special attention is paid to the Czech housing market.

In this thesis the heterogeneity of regional real estate prices in United States is investigated. A high dimensional VAR model with additional exogenous predictors, originally introduced by \cite{fan11}, is adopted. In this framework, the common factor in regional house prices dynamics is explained by exogenous predictors and the spatial dependencies are captured by lagged house prices in other regions. For the purpose of estimation and variable selection under high-dimensional setting the concept of Penalized Least Squares (PLS) with different penalty functions (e.g. LASSO penalty) is studied in detail and implemented. Moreover, clustering methods are employed to identify subsets of statistical regions with similar house prices dynamics. It is demonstrated that these clusters are well geographically defined and contribute to a better interpretation of the VAR model. Next, we make use of the LASSO variable selection property in order to construct the impulse response functions and to simulate the prices behavior when a shock occurs. And last but not least, one-period-ahead forecasts from VAR model are compared to those from the Diffusion Index Factor Model by \cite{stock02}, a commonly used model for forecasts.

The thesis deals comparison of house prices in Havlíčkův Brod in 2014 and 2015. The task is to find out and assess influence of lokality for the price of family house. This family house is located in suburb of the town and then for comparison will be moved to the center Havlíčkův Brod. House prices are determined by observed price and market value. The important element of thesis will determine factors, which affect these price.

I den här rapporten undersöks hur geografiskt läge, fastighetens fysiska egenskaper och ägandeform påverkar priset för småhus i Stockholms län. Målet med undersökningen är att ta fram en modell, baserad på de faktorer som påverkar bostadspriset mest, som kan användas för att uppskatta en fastighets värde. Undersökningen är baserad på data för småhus som sålts i Stockholms län 2020. Datasetet som används har erhållits av Booli. Efter att datasetet kontrollerats och vid behov anpassats för att uppfylla antaganden för multipel linjär regression, så tillämpas multipel linjär regression. Framåtselektion används för att ta fram de faktorer som starkast påverkar priset och därmed bör ingå i den slutliga modellen. Resultat från undersökningen visar att levnadsyta är den faktor som starkast påverkar priset på småhus i Stockholms län. Vidare bidrar även faktorer som avstånd till vatten, konstruktionsår och vilken kommun huset är beläget i. Slutligen diskuteras även vilken betydelse undersökningen och modellen som tas fram kan tänkas ha för större fastighetsägare. / This report investigates how geographic position, physical attributes of the property and form of ownership affect the price of houses in Stockholm County. The research goal is to develop a model, based on the factors with the strongest impact on house prices, which can be used to estimate the value of a property. The investigation is based on data of sold houses in Stockholm County in 2020. The dataset was obtained from Booli. After relevant adjustments of the dataset have been made, in order to satisfy the assumptions of multiple linear regression, multiple linear regression was applied. Thereafter, forward selection was used to determine which factors to include in the final model. The results indicate that living area is the factor with the highest impact on property prices. Furthermore, other important factors are distance to water, construction year and which municipality the property is situated in. Finally, the importance of the investigation and the model for larger property owners is discussed.

Abstract The topic of an overheated housing market, in Sweden, has been extensively discussed, not least by the media. This thesis will contribute to the debate by answering the question whether a potential price bubble exists in the Swedish housing market. Years between 1984 and 2004 are analysed using conventional metrics, which include house price-to- rent and income ratios respectively, changes in the dynamics of real house prices, as well as demographic variations. The analyse continues with the use of the imputed rent, also known as the yearly cost of ownership. Moreover the fundamental factors; interest rates, indebtedness and turnover of houses are discussed. It will be concluded that the conventional measures can be misleading. The imputed rent is a superior measure since it is the true cost of ownership and it accounts for changes in important determinants of house demand, mainly the interest rate. The answer to the title of this paper is; no, house prices (in 2004) in Sweden did not appear to be particularly overvalued, neither when compared to yearly rents in the tenancy market, disposable incomes, nor when low levels of interest rates are taken into account. However, this does not rule out that house prices cannot fall in the near future. / Sammanfattning Denna kandidatuppsats behandlar ämnet om en möjlig husprisbubbla i Sverige. Sedvanliga tekniker som används vid analysering av prisbubblor innefattar användandet av proportionen mellan huspriser och hyror samt disponibla inkomster. Även dynamiken i reella huspriser och demografiska förändringar utvärderas. I denna analys jämförs åren mellan 1984 och 2004 genom att använda “imputed rent”, vilken representerar den årliga kostnaden av ägande. Även fundamentala faktorer som räntan, skuldsättningen samt omsättningen av hus undersöks. Den slutsats som uppsatsen resulterar i understryker att de sedvanliga bruken kan vara vilseledande och att ”imputed rent” är en bättre teknik. Detta eftersom ”imputed rent” representerar den verkliga kostnaden av ägande samt inbegriper viktiga avgörande faktorer, som räntan. Därför är svaret på titeln; nej, huspriserna (år 2004) i Sverige förefaller sig inte vara särskilt övervärderade, när de jämförs med årliga hyror av likvärdiga hyresrättslägenheter och disponibla inkomster, samt när hänsyn tas till den låga räntan. Detta utesluter dock inte en framtida nedgång av huspriserna.

<p>Abstract</p><p>The topic of an overheated housing market, in Sweden, has been extensively discussed, not least by the media. This thesis will contribute to the debate by answering the question whether a potential price bubble exists in the Swedish housing market. Years between 1984 and 2004 are analysed using conventional metrics, which include house price-to- rent and income ratios respectively, changes in the dynamics of real house prices, as well as demographic variations. The analyse continues with the use of the imputed rent, also known as the yearly cost of ownership. Moreover the fundamental factors; interest rates, indebtedness and turnover of houses are discussed.</p><p>It will be concluded that the conventional measures can be misleading. The imputed rent is a superior measure since it is the true cost of ownership and it accounts for changes in important determinants of house demand, mainly the interest rate. The answer to the title of this paper is; no, house prices (in 2004) in Sweden did not appear to be particularly overvalued, neither when compared to yearly rents in the tenancy market, disposable incomes, nor when low levels of interest rates are taken into account. However, this does not rule out that house prices cannot fall in the near future.</p> / <p>Sammanfattning</p><p>Denna kandidatuppsats behandlar ämnet om en möjlig husprisbubbla i Sverige. Sedvanliga tekniker som används vid analysering av prisbubblor innefattar användandet av proportionen mellan huspriser och hyror samt disponibla inkomster. Även dynamiken i reella huspriser och demografiska förändringar utvärderas.</p><p>I denna analys jämförs åren mellan 1984 och 2004 genom att använda “imputed rent”, vilken representerar den årliga kostnaden av ägande. Även fundamentala faktorer som räntan, skuldsättningen samt omsättningen av hus undersöks. Den slutsats som uppsatsen resulterar i understryker att de sedvanliga bruken kan vara vilseledande och att ”imputed rent” är en bättre teknik. Detta eftersom ”imputed rent” representerar den verkliga kostnaden av ägande samt inbegriper viktiga avgörande faktorer, som räntan. Därför är svaret på titeln; nej, huspriserna (år 2004) i Sverige förefaller sig inte vara särskilt övervärderade, när de jämförs med årliga hyror av likvärdiga hyresrättslägenheter och disponibla inkomster, samt när hänsyn tas till den låga räntan. Detta utesluter dock inte en framtida nedgång av huspriserna.</p>