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Hrochová, Kateřina. "Srovnání vybraných způsobů ocenění rodinných domů v Bludově a okolí." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-232791.
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The aim of my work entitled "Comparison of the valuation of houses in and around Bludov" is to describe the various valuation methods, which apply to selected properties. A great focus is on the issues of valuation porocedures. The practical part deals with the comparison of prices, resulting from the various valuation methods. The following section deals with the comparison methods of valuation which is applied to five houses in the district Šumperk. The essence of this work is to use the comparative (nevyhláškovou) method for obtaining property prices within the period of 2011-2013. I have created a database of properties from the surrounding area. The result is to reveal how did the price of houses vary during those last 3 years.
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Evangelista, Rui Alexandre Alves. "Is energy efficiency reflected in residential property prices in Portugal?: an investigation based on hedonic house price functions and quantile regression analysis." Doctoral thesis, Universidade de Évora, 2019. http://hdl.handle.net/10174/25784.
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This thesis investigates the degree to which energy efficiency, as it is assessed by Energy Performance Certificates (EPCs), is reflected in residential property prices in Portugal. Its results are based on the analysis of a comprehensive dataset containing information of around 256 thousand residential property sales carried out from 2009 to 2013, a period largely characterized by depressed market conditions. This is the first large-scale study for a southern European country in this area of research. For the first time in this context, the impact of energy efficiency is analyzed along the distribution of residential property prices, using the unconditional quantile regression framework. The findings disclose a 13% sales premium for most energy efficient apartments (i.e. those bearing an A or B EPC rate) and a 5 to 6% market price premium for houses. However, quantile regression results show that the value attached to energy efficiency is not always positive across the distribution of prices. In particular, houses located at or below the 0.2th price quantile display clear energy efficiency price discounts. The use of different energy efficiency scales and cross-country comparisons support the view that energy efficiency price premiums are higher in the Portuguese residential market than in northern European markets. These results contribute to a more comprehensive understanding of the impact of energy efficiency on the real estate market and provide important messages to all political decision-makers interested in improving energy efficiency standards in Portugal; É A EFICIÊNCIA ENERGÉTICA REFLETIDA NOS PREÇOS DOS IMÓVEIS RESIDENCIAIS EM PORTUGAL?
Uma investigação baseada em funções de preços hedónicas e na análise de regressão por quantis
Resumo:
Esta tese investiga em que medida a eficiência energética, tal como é avaliada pelos Certificados de Desempenho Energético (CDE), é refletida nos preços dos imóveis residenciais em Portugal. Os resultados obtidos baseiam-se na análise de um conjunto exaustivo de dados com informação sobre cerca de 256 mil vendas de imóveis realizadas entre 2009 e 2013, um período predominantemente caracterizado pela recessão. Este é o primeiro estudo de larga escala realizado para um país do sul da Europa nesta área de investigação. Pela primeira vez neste contexto, o impacto da eficiência energética é analisado ao longo da distribuição dos preços das habitações através do método da regressão por quantis incondicionais. Os resultados revelam um prémio na venda de 13% para os apartamentos mais eficientes em termos energéticos (i.e., aqueles com CDE A ou B), e de 5 a 6% para as moradias. No entanto, a análise de regressão por quantis mostra que o valor associado à eficiência energética nem sempre é positivo ao longo da distribuição dos preços. Em particular, as moradias situadas abaixo do vigésimo percentil mostram claros descontos associados à maior eficiência energética. A utilização de diferentes escalas energéticas e a comparações entre países apoia a ideia de que os prémios associados à eficiência energética são maiores no mercado português do que em mercados do norte da Europa. Estes resultados contribuem para um conhecimento mais amplo do impacto da eficiência energética no mercado imobiliário e fornecem importantes mensagens a todos os decisores políticos interessados em melhorar os padrões de eficiência energética em Portugal.
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Anop, Sviatlana. "Apartment price determinants : A comparison between Sweden and Germany." Licentiate thesis, KTH, Fastigheter och byggande, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-161652.
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Similar development of economic fundamentals in Germany over the last two decades did not lead to the same dramatic house price increases as it is in Sweden. What can explain this house price stability over a long period? This thesis attempts to find the answer this question. The first paper in this thesis contains an extended literature review on the studies focused on the factors affecting house prices in the short and in the long run. Existing literature adopts a broad variation of approaches and reaches different conclusions attempting to answer the question about what are the key drivers of house prices. Conclusions often depend on the model specifications and econometric methods applied. Though there is a considerable agreement in real estate economics theory regarding the main factors that affect house prices (or so called “fundamental determinants”), it is hard to find a consistent definition regarding what factors can be considered as “fundamentals” and what factors belong to “non-fundamentals”. The dominating factors that are presented in the majority of the studies are income, population, interest rate, housing stock and unemployment. Studies done after the recent financial crisis put more attention on such factors as the behavior of the market participants, financing conditions and regulations. The characteristics of the bank lending and valuation policies as well as regulations on the rental market have received attention in the research literature, but the impact of these factors on house price dynamics is not measured and not well described. Therefore the other two papers in this thesis aim to provide a better insight in to the factors that create fluctuations in housing markets. The second paper investigates the effects of macroeconomic indicators such as population, income housing stock, mortgage interest rate on house prices. Estimation is done by applying panel data methodology on regional data for major cities in Germany and Sweden and by using yearly observations from 1995 to 2010. Results suggest that the long-run development of apartment prices in Sweden can be explained by changes in such factors as population, disposable income per capita, mortgage interest rate, housing stock, and prices per square meter in the previous period. The price for the previous period has the highest impact in comparison with other factors in Sweden. At the same time for Germany this is the only factor that is valid for long-term house price development. Estimates for fundamental factors such as population, disposable income, mortgage interest rate and housing stock appeared as not significant in house price development in the long run in Germany. A closer analysis has shown that the fundamental factors developed in a similar way in both countries during the analyzed period, though the house prices dynamic is very different. The conclusion is that fundamental factors cannot provide an explanation for the differences in house price developments in two countries and further analysis of institutional differences in the housing markets is done in the third paper. Third paper applies a comparative analysis approach and hypothetico-deductive method in order to examine the differences in the banking policies on mortgage financing and approaches to valuation of mortgage properties in Germany and Sweden. The results suggest that the extreme rise in Swedish house prices above the long-term trend was created by expanding bank lending policies that was supported by the general macroeconomic factors and regulation environment on the housing market. The main difference between countries in approaches to valuation for mortgage purposes is that in Germany that mortgage is based not on the market value as it is in Sweden, but on the long-run sustainable value, so called “fundamental” value. Mortgage lending value is determined in such a way that is also develops in the same tempo as fundamentals in the long-run and is not that procyclical as market value. Using a long-term sustainable value has a restrictive effect on the housing prices and in such a way stabilizes the market. One more factor that gives stability to the housing market in Germany is the well-functioning rental market. Third paper contributes to a better understanding of necessary conditions for the house prices to rise in the long run above the fundamentals level and suggests policy solutions that can reduce the risks of housing bubbles and increase financial stability.Ekonomiska fundamenta hur utvecklats på ungefär samma sätt i Tyskland och Sverige, men medan huspriserna i Sverige stigit kraftigt har de varit stabila i Tyskland. Vad kan förklara denna skillnad? Syftet med denna licentiatuppsats är att försöka förklara det. Den första uppsatsen innehåller en omfattande litteraturöversikt rörande vad som styr huspriser på kort och lång sikt. Den existerande litteraturen innehåller många olika angreppssätt och kommer till olika svar om vad som driver huspriserna. Slutsatserna beror ofta på hur modellerna specificerats och vilken ekonometrisk metod som använts. Det finns dock betydande enighet i ekonomisk teori om vad som är de grundläggande faktorerna som styr huspriserna (så kallade fundamenta) så finns delade meningar om hur dessa exakt ska specificeras och vad som räknas som icke-fundamentala faktorer. De vanligaste fundamentala faktorerna i studierna är inkomst, befolkning, räntenivå, bostadsutbudet och arbetslöshet. Studier gjorda efter den senaste finanskrisen betonar med beteendefaktorer, finansieringsförhållande och regleringar. Egenskaperna hos bankernas långivning och värderingsprinciper liksom effekten av hur hyresmarknaden fungerar har då fått lite utrymme vilket motiverar att de behandlas mer ingående i denna studie. Den andra uppsatsen undersöker effekterna av makroekonomiska indikatorer som befolkning, inkomst, bostadsutbud och räntenivåer på huspriser i Tyskland och Sverige. Studien begränsas till ett antal större städer och bygger på data från 1995-2010. Paneldataanalys används. Resultaten pekar på att den långsiktiga prisutvecklingen i Sverige kan förklaras av sådana fundamentala faktorer, men också att priset föregående period påverkar priset perioden efter. För Tyskland är enbart den sista faktorn av betydelse, dvs utvecklingen av de fundamentala faktorerna påverkar inte prisutvecklingen där. Trots att de fundamentala faktorerna utvecklas på liknande sätt så leder de inte till samma utveckling av huspriserna. Detta motiverar djupare studier av institutionella skillnader mellan bostadsmarknaderna i de båda länderna. Den tredje uppsatsen är en jämförande studie som använder hypotetiskt deduktiv metod för att undersöka om skillnader i bankerna lånepolicy och skillnader i värdebegrepp kan förklara skillnader i prisutveckling på bostäder. Resultaten pekar på att de snabbt stigande priserna i Sverige kan förklaras med en expansiv långivning. En viktig skillnad är att medan långivning i Sverige grundas på aktuellt marknadsvärde medan den i Tyskland bygger på ett långsiktigt värde som ska spegla långsiktiga fundamentala faktorer, ett så kallat "mortgage lending value". Detta värde utvecklas mer sakta och ska inte svänga med konjunkturerna på det sätt som ett marknadsvärde normalt gör. Genom att långivning grundas på detta värde stabiliseras marknaden. En annan faktor som bidrar till att stabilisera de tyska bostadspriserna är att det finns en fungerande hyresmarknad som skapar ett alternativ till att köpa. Bidraget i den tredje uppsatsen är att öka vår förståelse av nödvändiga villkor för att huspriserna inte ska stiga snabbt och att den pekar på åtgärder som kan minska risken för prisbubblor på bostadsmarknaden, och minska risken för finansiell instabilitet.
QC 20150316
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Drcmánková, Hana. "Srovnání cen rodinného domu v různých částech města Brna v letech 2015 a 2016." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2016. http://www.nusl.cz/ntk/nusl-261294.
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Diploma thesis deals with price comparison of family house in Brno – Královo Pole between 2015 and 2016. This family house is located near of the town center and then will be as a simulation moved to the outskirts, Brno – Líšeň. House prices are determined by observed price and market value. The task is to find out and evaluate the price differences, dependents to the valuation time and the place. I will make summary of factors that affect these prices.
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Vojíř, Ondřej. "Srovnání cen rodinného domu v různých částech města Havlíčkův Brod v letech 2014 a 2015." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-233178.
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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.
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Křenková, Kristýna. "Analýza vlivu provedených stavebních úprav na obvyklou cenu vybraných rodinných domů v Rožnově pod Radhoštěm." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-232925.
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The target of this theses entitled „Analysis od the impact of construction modifications on the standard price of selected detached houses in Rožnov pod Radhoštěm“ is assess what extent is the standart price of selected detached houses influence by construction modifications made . The next task is to describe the necessary valuation of real estate. The practical part deals ascertainment the loading price of five different types of houses according to the currently valid legislation No. 151/1997 Coll., including outdoors modification and subsidiary buildings approximating to family houses. The findings are also prices of houses made comparative method calculated in accordance with a regulation by direct comparison , which was created database of real estate. Land forming a single functional units with family homes which were valued using valuation regulations and Naegeliho class position. At the end of this thesis the comparison of the identified unit prices depending on your reconstructions.
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Kollár, Filip. "Vliv lokality na výši obvyklé ceny rodinného domu v Ostravě." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-399635.
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The main topic of the master’s thesis is the inluence of the locality on the usual price of a family house in town of Ostrava. This analysis does not only focus on usual criterias (accessibility to the center, etc.), but also addresses the specific problems of the region, eg. air quality. There is also a questionnaire survey aimed at identifying respondents' preferences regarding the choice of the ideal location for housing. For the valuation of the selected family house, two methods are selected, namely the comparative method according to the valid valuation rule and the method of market comparison, specifically the direct comparison method, which are described in more detail in the theoretical introduction. The final part deals with the comparison of the outcomes of these two methods and possible discrepancies that might arise.
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Durišová, Nina. "Zdroje cen pro porovnávací způsob ocenění u rodinných domů v severní části okresu Brno-venkov." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-414144.
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The objective of this work, price sources for the comparative valuation method for houses in the northern part of Brno-venkov district, is to create eight databases of houses based on advertised and carried prices. Using the input database the another database for pricing is created, then databases with advertised and carried prices are compared and to obtain results. The valuation of houses is done using sales comparison approach. Based on the results, we can conclude that price is not the only information that may affect the valuation, by mainly the lack of information about specific real estate might affect the results. We propose recommendations for valuation and verification of the information about compared and valuated real estates.
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Varadínková, Jitka. "Analýza vlivu lokality na výši obvyklé ceny rodinných domů v okrese Hodonín." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-390155.
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Locality can affect the price of real property items. This diploma thesis focuses on pricing of family houses in cities, towns and villages and effects which have an impact on the price. Part of the paper deals with the description of the used pricing methods, their procedures, laws and the regulation, description of the real estate property market existing at the time the diploma thesis was written and the description of the priced family houses. The aim is to ascertain the price of land, family houses using the method of costs and comparison and evaluating the unit prices depending on locality.
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Wang, Yuefeng. "Essays on modelling house prices." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/16242.
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Housing prices are of crucial importance in financial stability management. The severe financial crises that originated in the housing market in the US and subsequently spread throughout the world highlighted the crucial role that the housing market plays in preserving financial stability. After the severe housing market crash, many financial institutions in the US suffered from high default rates, severe liquidity shortages, and even bankruptcy. Against this background, researchers have sought to use econometric models to capture and forecast prices of homes. Available empirical research indicates that nonlinear models may be suitable for modelling price cycles. Accordingly, this thesis focuses primarily on using nonlinear models to empirically investigate cyclical patterns in housing prices. More specifically, the content of this thesis can be summarised in three essays which complement the existing literature on price modelling by using nonlinear models. The first essay contributes to the literature by testing the ability of regime switching models to capture and forecast house prices. The second essay examines the impact of banking factors on house price fluctuations. To account for house price characteristics, the regime switching model and generalised autoregressive conditionally heteroscedastic (GARCH) in-mean model have been used. The final essay investigates the effect of structural breaks on the unit root test and shows that a time-varying GARCH in-mean model can be used to estimate the housing price cycle in the UK.
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Kubičková, Veronika. "Srovnání vybraných způsobů ocenění pro nemovitost typu rodinný dům v lokalitě okolí Tišnova." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-232526.
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My diploma paper is focused on description of the ways of assessing, which are used in practice. The diploma paper should also make a comparison between those assessing methods and recognise the difference between them. Next aim of my diploma paper is to shortly mention the questions of International valuation norms (standards), but only those parts, which are related with assessing of real property. Practical part of my diploma paper is especially focused on assessing of family houses by chosen assessing methods, which are: cost approach, comparison method (nenašla jsem), standard price and price at present time. Whose resultant values will be compared. Partial task is recognition how the aspect of job opportunity is influencing the price of family house, which was counted by comparison method.
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Chalupová, Monika. "Srovnání vybraných způsobů ocenění pro bezbariérové rodinné domy v Jihlavě a okolí." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-232822.
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Target for this thesis is to describe the methods of evaluation, and with chosen evaluation methods, by the use of comparison, to highlight their difference. This thesis is focused mostly on the barrier-free houses, that require special construction alterations for the handicaped. Next target for this thesis is to compare the price difference of the regular house and the barrier - free house. Practical part of the thesis is focused mostly on estimating the price of the family houses by the chosen evaluation methods, which are cost method, comparison method and standard price. Their final prices will be compared with each other. Partial task of the thesis is to find out, how big part of the final price of the house is the aspect of the barrier-free construction.
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Sauer, Nick. "Srovnání cen rodinného domu v různých částech Českých Budějovic v letech 2015 a 2016." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2016. http://www.nusl.cz/ntk/nusl-241250.
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Abstract This thesis Compare the price of the family house in various parts of Ceske Budejovice in 2015 and 2016 "deals with the valuation of a family house at the usual price and the price determined in 2015 and 2016. The family house is located on the outskirts of the city and then will be relocated to the city center. The usual price is determined by comparison, the comparison is made with similar family houses offered for sale in the real estate advertising. The price recorded for the year 2015 will be calculated by using valuation Decree no. 441/2013 Coll., as amended by Decree no. 199/2014 Coll. 2016 using valuation Decree no. 441/2013 Coll., as amended by Decree no. 199/2014 Coll., Decree no. 345/2015 Coll., Decree no. 53/2016 Coll. The theoretical part explains the basic important concepts which relate to the thesis. In the practical part are processed individual methods of valuation for 2015 and 2016 and localities - outskirt and center of České Budějovice. The output of the practical part is comparison of the usual price and the price established. Finally, we evaluate the factors that affect the cost of family houses.
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Berglund, Jonas. "Determinants and Forecasting of House Prices." Thesis, Uppsala University, Department of Economics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8050.
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This is an empirical study which goal is to determine what causes changes in housing prices. It is done by using data for Stockholm and Sydney to create a model to forecast the change of house prices in the two cities. The findings suggest that the main determinants are nominal interest, household income, and the supply of new dwellings.
This is in line with previous studies. It is also investigated whether the use of financial indicators such as the development of the stock market has an impact on the house prices.
The findings regarding the implication of the financial indicators are dubious. Lastly, an investigation is made to see whether the so-called “ripple effect” can be applied to an international level. The inclusion of the ripple effect seems to be positive to the forecasting models used in this paper.
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Cardona, Cervantes Gabriel. "Formation of House Prices in Sweden." Thesis, Jönköping University, JIBS, Economics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-11313.
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In this research, Sweden’s municipalities are categorized into five economic regions which put emphasis on location. Furthermore, since house prices reflect and are reflected by the existing cycles in the economy, four time periods are considered. By using extensive data collected by Sweden Statistics (SCB), this study tests eight variables factors to be used in a cross-section analysis which will help researchers understand which factors are consistent in explaining the formation of house prices in terms of location and time. The conclusion that can be drawn is that no factor can fully explain house prices at a national level and that the Population variable was consistent in regional changes and Employment was consistent in time changes. This has lead to a greater understanding of the field of regional house prices in order for it to contribute to real estate investments or purchases.
Master thesis in Economics
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Frostad, Astrid Øksendal. "Immigration and House Prices in Norway." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for samfunnsøkonomi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-26906.
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During the past decades, many developed countries including Norway have experienced a remarkable rise in both house prices and immigration inflows. Extant studies have aimed to shed light on how immigration inflows affect housing prices. Given the large weight that housing consumption has on the household budget, the immigration’s impact on housing prices could be an important matter (Sá, 2011). This thesis studies the short term and long term effect of immigration on house prices in Norway’s largest cities from 1986 to 2012. I find that immigration has had a significantly positive effect on house prices. An immigration inflow equal to 1% of a city’s total population is coincident with an increase in housing prices of about 2,9%. These results are consistent with the findings of previous studies. My findings indicate that on average, immigration contributes to nearly one fifth of the total increase of housing prices in Norway. I did not find evidence that the short term effect of immigration on house prices has been greater than the long term effect, although economic theory suggests that the short term effect should be greater than the long term effect since in the long run the supply of housing will adapt to the demand.
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Song, In Ho. "Essays on House Prices and Consumption." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306848116.
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Van, der Walt Stephan. "Determinants of house prices in Hout Bay." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4250.
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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.
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Mendicino, Caterina, and Maria Teresa Punzi. "House Prices, Capital Inflows and Macroprudential Policy." WU Vienna University of Economics and Business, 2014. http://epub.wu.ac.at/4281/1/wp180.pdf.
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This paper evaluates the monetary and macroprudential policies that mitigate the procyclicality arising from
the interlinkages between current account deficits and financial vulnerabilities. We develop a two-country
dynamic stochastic general equilibrium (DSGE) model with heterogeneous households and collateralised debt. The model predicts that external shocks are important in driving current account deficits that are coupled with run-ups in house prices and household debt. In this context, optimal policy features an interest-rate response to credit and a LTV ratio that countercyclically responds to house price dynamics. By allowing an interest-rate response to changes in financial variables, the monetary policy authority improves social welfare, because of the large welfare gains accrued to the savers. The additional use of a countercyclical LTV ratio that responds to house prices, increases the ability of borrowers to smooth consumption over the cycle and is Pareto improving. Domestic and foreign shocks account for a similar fraction of the welfare gains delivered by such a policy. (authors' abstract)Series: Department of Economics Working Paper Series
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Liebersohn, Carl J. "Housing demand, regional house prices and consumption." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118008.
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Thesis: S.M. in Management Science Research, Massachusetts Institute of Technology, Sloan School of Management, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 24-25).
This paper provides a new explanation for regional variation in the 2000-2012 housing and consumption boom and bust. Cities with a greater share of growing industries experienced larger housing demand shocks, larger house price increases from 2001-2006 and greater price declines from 2006-2011. Consistent with theory, price effects were stronger in housing-supply inelastic cities. City-level differences in housing demand are also correlated with supply elasticity. Controlling for industry, I estimate a durables consumption-house price elasticity of 0.08 from 2001-2006, 60% smaller than estimates without the controls. Post- 2006, the estimated elasticity is 0.19 and housing prices rather than local conditions explain consumption changes.
by Carl J. Liebersohn.
S.M. in Management Science Research
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Engström, Isak, and Alan Ihre. "Predicting house prices with machine learning methods." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260140.
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In this study, the machine learning algorithms k-Nearest-Neighbours regression (k-NN) and Random Forest (RF) regression were used to predict house prices from a set of features in the Ames housing data set. The algorithms were selected from an assessment of previous research and the intent was to compare their relative performance at this task. Software implementations for the experiment were selected from the scikit-learn Python library and executed to calculate the error between the actual and predicted sales price using four different metrics. Hyperparameters for the algorithms used were optimally selected and the cleaned data set was split using five-fold cross-validation to reduce the risk of bias. An optimal subset of hyperparameters for the two algorithms was selected through the grid search algorithm for the best prediction. The Random Forest was found to consistently perform better than the kNN algorithm in terms of smaller errors and be better suited as a prediction model for the house price problem. With a mean absolute error of about 9 % from the mean price in the best case, the practical usefulness of the prediction is rather limited to making basic valuations.I den här studien användes maskininlärningsalgoritmerna k-Nearest-Neighbours regression och Random Forest regression för att förutsäga huspriserna från en uppsättning variabler i Ames Housing datasetet. Algoritmerna valdes utifrån en bedömning av tidigare forskning och avsikten var att jämföra deras relativa prestanda i lösandet av denna uppgift. För experimentet valdes programvaruimplementeringar från Pythonbiblioteket scikit-learn och kördes för att beräkna felet mellan det faktiska och förutsedda försäljningspriset med fyra olika mätsätt. Hyperparametrar för de använda algoritmerna valdes optimalt och den rengjorda datamängden delades med femfaldig korsvalidering för att minska risken för partiskhet med hänsyn till datat. En optimal delmängd av hyperparametrar valdes även ut med algoritmen grid search för bästa möjliga förutsägelse. Random Forest-algoritmen visade sig konsekvent prestera bättre än k-NN-algoritmen i bemärkelsen minimalt fel och är en mer lämplig modell för problemet. Med ett genomsnittligt absolutfel på ca 9 % från det genomsnittliga priset i bästafallet är den praktiska användbarheten av förutsägelsen tämligen begränsad till att göra grundläggande värderingar.
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Ångman, Josefin. "What is driving house prices in Stockholm?" Thesis, Stockholms universitet, Nationalekonomiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-130692.
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An increased mortgage cap was introduced in 2010, and as of May 1st 2016 an amortization requirement was introduced in an attempt to slow down house price development in Sweden. Fluctuations in the house prices can significantly influence macroeconomic stability, and with house prices in Stockholm rising even more rapidly than Sweden as a whole makes the understanding of Stockholm’s dynamics very important, especially for policy implications. Stockholm house prices between the first quarter of 1996 and the fourth quarter of 2015 is therefore investigated using a Vector Error Correction framework. This approach allows a separation between the long run equilibrium price and short run dynamics. Decreases in the real mortgage rate and increased real financial wealth seem to be most important in explaining rising house prices. Increased real construction costs and increased real disposable income also seem to have an effect. The estimated models suggest that around 40-50 percent, on average, of a short-term deviation from the long-run equilibrium price is closed within a year. As of the last quarter 2015, real house prices are significantly higher compared to the long run equilibrium price modeled. The deviation is found to be around 6-7 percent.
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Kollárová, Lucie. "Srovnání cen rodinného domu ve vybraných lokalitách v okrese Karviná v letech 2016 a 2017." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-317081.
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The thesis "Comparison of Family House Prices in Selected Locations in the District of Karviná in 2016 and 2017" deals with the awarding of the selected family house at the usual price established in 2016 and 2017 and the determination of the price difference in these years. The family house is fictitious at the beginning in one of the selected locations of the district of Karviná and is then placed in 3 other selected localities. The usual price is determined by comparison. Comparison is made with similar family homes offered for sale in real estate ads. The price determined for 2016 for the year 2017 is determined according to the valuation regulations. In the theoretical part of the thesis are defined and explained the basic important concepts related to valuation and methods of valuation are approximated. In the practical part of the thesis are elaborated various methods of valuation for the years 2016 and 2017 for chosen RD located in selected locations of Karviná district, namely the town of Orlová, the statutory city of Havířov, the town of Bohumín and the village of Petrovice near Karviná. The output of the practical part of the thesis is a comparison of the prices of the usual and discovered ones and they are evaluated by the factors that make the individual prices change.
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Mikesková, Dana. "Vliv lokality na výši obvyklé ceny rodinného domu." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-433231.
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The subject of this diploma thesis is mainly to find out what is the impact on the location on the usual price of a selected house in the Vyškov district. Part of the award is the creation of a database of family houses, including the following criteria, which will be subsequently evaluated. The necessary part of the work is also a description of administrative districts in the Vyškov district, which are Slavkov u Brna, Bučovice and Vyškov. Furthermore, the work will deal with the description of the real estate market and errors in advertising.
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Macko, Peter. "Vliv nemateriálových faktorů na cenu rezidenčních staveb ve vybrané lokalitě Brno-venkov." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-414101.
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The subject of the diploma thesis Influence of non-material factors on the price of residential buildings in a selected Brno-venkov location is the valuation of a specific family house in three different localities in the district of Brno-venkov. The valuation of the chosen family house is performed by a comparative approach using the method of a direct comparison. The selected localities include the district of the municipality with extended powers of Rosice, district of the municipality with extended powers of Šlapanice and the district of the municipality with extended powers of Židlochovice. The aim of the work is also to compare an influence of non-material factors on the price of family houses in the selected locality. The individual effects of material and non-material factors on the price of the family house are contained in selected multiplication coefficients, which adjust the price of the compared properties from their own databases considering to the valued object.
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Grandner, Thomas, and Dieter Gstach. "Joint adjustment of house prices, stock prices and output towards short run equilibrium." Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/158/1/document.pdf.
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A dynamic IS-LM model including stocks and houses as additional assets will be analyzed in this paper. Providing also housing services, a major consumption item for most households, houses create an additional link between the monetary and the real sector of the economy. The adjustment path of output, house prices and stock prices after exogenous policy shocks will be derived within a rational expectation setup. This will show how different reaction patterns of asset prices are related to different elasticities of housing services demand. These general analytical results are contrasted with relevant empirical work, particularly Lastrapes [2002], leading to the identification of plausible elasticity ranges. The particular results for those shed new light upon the ongoing discussion about demand effects from real estate wealth and about determinants of house price fluctuations. (author's abstract)Series: Department of Economics Working Paper Series
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Brasington, David Martin. "The relationship between house prices and school quality." Connect to resource, 1997. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1271853632.
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Ryhage, Marcus. "Dynamics of U.S. House Prices : A VECM Approach." Thesis, Umeå universitet, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172358.
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This paper aims to analyze the U.S. house price dynamics to estimate a long-term equilibrium price level for the U.S. housing market, using fundamental underlying macroeconomic factors. For this, in line with the empirical literature, a vector error-correction model is employed. The results find a cointegrating relationship between the housing prices and its long-run driving factors: Residential Investment Ratio (RIR), Personal Disposable Income (PDI), and Construction Cost (CC), implying that these factors have a decisive role in determining equilibrium level of U.S. house prices. The estimated long-run equilibrium level suggests that the U.S. housing market is currently underpriced, which can bring some skepticism to our model. However, our model does manage to predict future house prices about one year in advance of the actual house price movement. Further, the slow rate of adjustment towards equilibrium testifies of a rigid housing market in the U.S.
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Navrátilová, Martina. "Analýza rozhodujících vlivů na hodnotu vybraných rodinných domů v Brně." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2016. http://www.nusl.cz/ntk/nusl-241124.
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The objective of diploma thesis is to determine the price of five selected houses in Brno and consecutively to define the factors governing their price. The theoretical part is devoted to methods of real estate valuation and fundamental concepts involved. Family houses are valued according to valid Czech regulations and the price is determined. Above that the sales comparison approach is used comparing valuated properties with comparable properties that have recently been offered. A database of such properties has been created and the market value of five selected houses was determined.
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Ratcliffe, Anita. "House prices and consumption, subjective well-being and retirement." Thesis, University of Bristol, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544333.
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Andersson, Erik. "The Relationship Between House Prices and the Stock Market." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Economics, Finance and Statistics, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-24094.
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Stocks and houses are the two major assets on the balance sheet of American households. Changes in the two markets have a large influence on wealth and the general economy. This thesis investigates the relationship between the stock market and the house market in the U.S from 1987 to 2013. The sample period is unique since it includes two structural breaks, the dot-com bubble and the most recent financial crisis. A bivariate correlation analysis is applied to investigate the correlation and the Granger causality test, based on a vector autoregressive model (VAR), investigates the causality between the two variables. The causality test is performed with and without GDP and interest rates as control variables. In order to investigate a potential dynamic causality, the full sample period is divided into two periods. The bivariate correlation analysis concludes that a large and positive correlation exists between the two markets. All causality tests indicate a unidirectional causality running from the stock market to the house market. An impulse response function (IRF) is estimated in order to investigate the size and timing of the causality. The IRF concludes that a one percentage change in the stock market affects the house market by 0.032581 percent three years later, corresponding to a change in the value of real estates possessed by American households of 7.04 billion of dollars. The same number amounts to 47.00 billion of dollars five years later. It is concluded that the relationship has a significant influence on the wealth of American households hence a need for developing a hedging instrument which reduces the ramifications from changes in the stock market is large.
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Darmenov, Askar. "The effect of house prices on home owners savings." CONNECT TO ELECTRONIC THESIS, 2008. http://dspace.wrlc.org/handle/1961/4559.
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Pronin, Mathias. "The Response of the Riksbankto House Prices in Sweden." Licentiate thesis, Stockholms universitet, Nationalekonomiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-118791.
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In the aftermath of the recent financial crisis, an environment of historically low interest rates and extensive household indebtedness in the OECD countries have triggered a vivid debate on whether central banks should react to house price fluctuations in their pursuit of monetary policy. In Sweden, a period of low policy rates and house price inflation was halted when the central bank increased the interest rates in 2010. This paper studies whether the Riksbank reacted to house prices in 1993-2013. Using Bayesian methods and quarterly data, I estimate a DSGE model with patient and impatient households, where the central bank reacts to house price inflation. The results suggest that the Riksbank did respond to house prices during the sample period. The findings are robust and plausible from an economic point of view.
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Johnson, Graham Mathieu. "The Impact of Colleges on House Prices in Ohio." Oberlin College Honors Theses / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1212551133.
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Zhang, Jing. "Three Essays on House Prices: Stationarity, Dynamics, and Expectations." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397436206.
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Oxenstierna, Johan. "Predicting house prices using Ensemble Learning with Cluster Aggregations." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-345157.
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The purpose of this investigation, as prescribed by Valueguard AB, was to evaluate the utility of Machine Learning (ML) models to estimate prices on samples of their housing dataset. Specifically,the aim was to minimize the Median Absolute Percent Error (MDAPE) of the predictions. Valueguard were particularly interested in models where the dataset is clustered by coordinates and/or attributes in various ways to see if this can improve results. Ensemble Learning models with cluster aggregations were built and compared against similar model counterparts which do not partition the data. The weak learners were either lazy kNN learners (k nearest neighbors), or eager ANN learners (artificial neural networks) and the test set objects were either classified to single weak learners or tuned to multiple weak learners. The best results were achieved by the cluster aggregation model where test objects were tuned to multiple weak learners and it also showed the most potential for improvement.
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Aydogan, Helin, and Sofia Gatjetjiladze. "The Relationship Between House Prices and Stock Prices : An Empirical Analysis of the Swedish Market." Thesis, Linköpings universitet, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159791.
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It is of continual topicality to understand the interaction between the stock market and the house market as they are central parts of the economy and important resources and investment alternatives for both households and firms. Hence, these two markets can be crucial for consumers and investors and consequently economic growth. With a focus on Sweden and Sweden's three largest cities, we examine the relationship between house prices and stock prices by including GDP, inflation and the repo rate over the period 1994-2018. We examine this by using time series analysis and investigating both the short and long run relationship by mainly focusing how the causal link looks like based on the theories of wealth effect and credit-price effect. Our results show a negative long run relationship in Sweden indicating that an increase in house prices decreases stock prices, and for the short run there is evidence of the credit-price effect. For Stockholm, we found a positive bidirectional long run relationship and a bidirectional causality was also confirmed for the short run. For Gothenburg, we find a negative long run relationship where an increase in stock prices decreases house prices, however there is no evidence of a causal relationship in the short run. For Malmö we find a positive long run relationship that goes from stock prices to house prices and the reverse causation is found for the short run demonstrating the credit-price effect. Although we find that these markets have a relationship, we still argue that they are relatively separated and that investors can diversify over these assets because of the low values our results show. Keywords: house prices, stock prices, Sweden, wealth effect, credit-price effectDet är av ständig aktualitet att förstå samspelet mellan aktiemarknaden och husmarknaden eftersom de är centrala delar av ekonomin och viktiga resurser och investeringsalternativ för både hushåll och företag. Följaktligen kan dessa två marknader vara avgörande för konsumenter, investerare och därmed ekonomisk tillväxt. Med fokus på Sveriges och Sveriges tre största städer undersöker vi relationen mellan huspriser och aktiepriser genom att inkludera BNP, inflation och reporäntan över perioden 1994–2018. Vi utvärderar detta genom att använda tidsserieanalys och undersöker både den kortsiktiga och långsiktiga relationen, genom att i huvudsak fokusera på hur orsakssambandet ser ut baserat på teorierna inkomsteffekten och kredit-pris effekten. Våra resultat visar en negativ långsiktig relation i Sverige som indikerar att en ökning i huspriser orsakar en minskning aktiepriser och på kort sikt finner vi bevis för kredit-pris effekten. För Stockholm finner vi en positiv långsiktig relation som är dubbelriktat och en dubbelriktad kausalitet bekräftades även för kort sikt. För Göteborg finner vi en negativ långsiktig relation där en ökning av aktiepriserna minskar huspriserna, dock fann vi inga bevis för ett orsakssamband på kort sikt. För Malmö finner vi ett positivt långsiktigt relation som går från aktiepriser till huspriser och det omvända orsakssambandet hittar vi på kort sikt som tyder på kredit-pris effekten. Trots att vi kommer fram till att dessa marknader har en relation så argumenterar vi ändå för att de är relativt separerade och att investerare kan diversifiera över dessa tillgångar på grund av de låga värden våra resultat visar. Nyckelord: huspriser, aktiepriser, Sverige, inkomsteffekten, kredit-pris effekten
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Kim, Sang-Hyuck. "The relationship between accessibility and house price." Thesis, Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/21790.
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Ott, Hervé. "Three Empirical Essays on House Prices in the Euro Area." Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-68009.
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Revend, War. "Predicting House Prices on the Countryside using Boosted Decision Trees." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279849.
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This thesis intends to evaluate the feasibility of supervised learning models for predicting house prices on the countryside of South Sweden. It is essential for mortgage lenders to have accurate housing valuation algorithms and the current model offered by Booli is not accurate enough when evaluating residence prices on the countryside. Different types of boosted decision trees were implemented to address this issue and their performances were compared to traditional machine learning methods. These different types of supervised learning models were implemented in order to find the best model with regards to relevant evaluation metrics such as root-mean-squared error (RMSE) and mean absolute percentage error (MAPE). The implemented models were ridge regression, lasso regression, random forest, AdaBoost, gradient boosting, CatBoost, XGBoost, and LightGBM. All these models were benchmarked against Booli's current housing valuation algorithms which are based on a k-NN model. The results from this thesis indicated that the LightGBM model is the optimal one as it had the best overall performance with respect to the chosen evaluation metrics. When comparing the LightGBM model to the benchmark, the performance was overall better, the LightGBM model had an RMSE score of 0.330 compared to 0.358 for the Booli model, indicating that there is a potential of using boosted decision trees to improve the predictive accuracy of residence prices on the countryside.Denna uppsats ämnar utvärdera genomförbarheten hos olika övervakade inlärningsmodeller för att förutse huspriser på landsbygden i Södra Sverige. Det är viktigt för bostadslånsgivare att ha noggranna algoritmer när de värderar bostäder, den nuvarande modellen som Booli erbjuder har dålig precision när det gäller värderingar av bostäder på landsbygden. Olika typer av boostade beslutsträd implementerades för att ta itu med denna fråga och deras prestanda jämfördes med traditionella maskininlärningsmetoder. Dessa olika typer av övervakad inlärningsmodeller implementerades för att hitta den bästa modellen med avseende på relevanta prestationsmått som t.ex. root-mean-squared error (RMSE) och mean absolute percentage error (MAPE). De övervakade inlärningsmodellerna var ridge regression, lasso regression, random forest, AdaBoost, gradient boosting, CatBoost, XGBoost, and LightGBM. Samtliga algoritmers prestanda jämförs med Boolis nuvarande bostadsvärderingsalgoritm, som är baserade på en k-NN modell. Resultatet från denna uppsats visar att LightGBM modellen är den optimala modellen för att värdera husen på landsbygden eftersom den hade den bästa totala prestandan med avseende på de utvalda utvärderingsmetoderna. LightGBM modellen jämfördes med Booli modellen där prestandan av LightGBM modellen var i överlag bättre, där LightGBM modellen hade ett RMSE värde på 0.330 jämfört med Booli modellen som hade ett RMSE värde på 0.358. Vilket indikerar att det finns en potential att använda boostade beslutsträd för att förbättra noggrannheten i förutsägelserna av huspriser på landsbygden.
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Gottvald, Aleš. "Analýza vlivu lokality a na výši obvyklé ceny rodinných domů v Brně a okolí." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-234453.
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This Thesis examines the valuation of five family houses in Brno and neighbouring areas. The theoretical part of the paper defines a number of approaches to real estate valuation as well as some key terms and concepts linked to it. The applied part focuses on valuation of the aforementioned family houses by using a range of methods; Cost, comparative and direct comparison. Based on these results a usual price is then set. Based on the estimates of respective prices an analysis of the effect of area on the usual price of a property was conducted.
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Orford, Scott. "Valuing the built environment : a GIS approach to the hedonic modelling of housing markets." Thesis, University of Bristol, 1997. http://hdl.handle.net/1983/e619939f-13f9-4c94-b897-50dc231b1059.
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The valuation of the built environment has been a traditional concern of geographers. A particular interest has been the way in which the value of locational externalities are incorporated into house prices through housing market dynamics. However, much of the previous research into this process has been of North American origin, despite the fact that house prices, and property valuations in general, have become a major part of British life. This research aims to begin to rectify this shortfall by studying the spatial dynamics of the Cardiff Housing Market. Implicit in this research is an attempt to move towards a valuation of locational externalities at the micro-scale. The research employs two distinct method of analysis. Firstly, ARC / INFO GIS is used to construct a context-sensitive GIS of the Cardiff housing market. An important aspect of this GIS is the use of Ordnance Survey's ADDRESS-POINT product to geo-reference individual properties to a resolution of 0.1 metre. Several large and complex socio-economic and property related datasets were then attached to this coverage, including house price survey data, local taxation data, and data from a Housing Condition Survey of one in five dwellings in the central area of Cardiff. This GIS is one of the most comprehensive constructed for any city, and is relatively unique in this kind of research. The second method of analysis employs the hedonic pricing technique to impute monetary values for the implicit attributes of housing. An important part of the research is an investigation into the specification of the hedonic house price function. The traditional specification is essentially aspatial, and does not take into account the spatial nature the data, and thus the spatial dynamics of the housing market that generates it. To rectify this, three different specifications of the hedonic house price function are investigated: the traditional specification, the spatial parameter drift specification and the multi-level specification. The research concludes that the multi-level specification is best at modelling the spatial heterogeneity and spatial dependence inherent in housing market data. The results from this modelling show that the valuation of locational externalities are intimately bound up with the attributes of the housing stock and the characteristics of the resident households, resulting in a complex juxtaposition of positive and negative valuations of location at the local level.
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Sollander, Robin. "Prediktion av huspriser i Falun / Prediction of House Prices in Falun." Thesis, KTH, Matematik (Avd.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105808.
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I denna uppsats tillämpas multipel regressionsanalys med syfte att predikera huspriser i Falun. Data som består av dels priset vid ett antal husförsäljningar och dels ett antal eventuellt samvarierande förklarande variabler analyseras. Två lämpliga, modeller som på ett så precist och enkelt sätt som möjligt förutsäger en kommande försäljning av ett hus tas fram. I den första finns en mäklarfirmas utropspris med som förklarande variabel i den andra inte. Prediktionsförmågan för de båda modellerna blir inte användbar i praktiken men bättre då utropspris finns med. De förklarande variablerna blir för modellen med utropspris också boarea, om huset har garage och om huset ligger i stadsdelen Slätta. För modellen utan utropspris är de förklarande variablerna taxerat markvärde, taxerat byggnadsvärde och tomtarea.This paper applies multiple regression analysis to predict house prices in Falun. Data consisting of sales price and a number of possible explanatory variables is analyzed. Two appropriate, models that are as precise in predicting and simple as possible are developed. In the first model a home sales office’s starting price is included as an explanatory variable in the other not. The predictive ability of the two models is not useful in practice, but better when starting price is included. The explanatory variables are for the model with the starting price included also living area, if the house has a garage or not and if the house is located in the district Slätta. For model without starting price the explanatory variables are taxed land value, taxed building value and land area. 3
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Wei, Xiangjing. "House Prices and Mortgage Defaults: Econometric Models and Risk Management Applications." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/rmi_diss/24.
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This dissertation first investigates the possible house price trend and the relationship with the mortgage market, from the perspective of risk management; then it chooses the angle from bond insurers and figures out possible methods to avoid capital procyclicality. In Chapter I, we apply vector auto regression models (VAR) and simultaneous equations models (SEM) to estimate the dynamic relations among house price returns, mortgage rates and mortgage default rates, using historical data during the time period of 1979 through second quarter 2008. We find that house prices would be better estimated and predicted with the consideration of the mortgage market. In Chapter II, following the methodology of co-integration, we first construct several succinct measures to display the possible intrinsic values of house prices. In the short run, house price return dynamics are investigated by dynamic adjustments following Capozza et al (2002) and error correction models. We examine the possible overshooting problem of house price returns. By analytical derivations and simulations, we demonstrate the effects of the coefficients on overshooting. In Chapter III, we adopt a structural model with time-varying correlations for bond insurers. We consider losses due to bond insurers’ downgrading and losses from both insurance contracts and investment portfolio. On that basis, we propose forward-looking smoothing rules of capital over a full business cycle, instead of only based on a short-term horizon, to avoid the procyclicality. With the smoothed capital, a bond insurer can actually establish some capital buffer in good times to support the potential losses in crisis.
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Magnusson, Amanda, and Lina Makdessi. "Is there a relationship between oil prices and house price inflation?" Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44471.
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The purpose of this thesis is to investigate further whether oil price has an effect on house price inflation and additionally if it has a link to house price turning points. The methodology is grounded on the previous research paper made by Breitenfellner et al. (2015). The results are based on quarterly data from the countries; Finland, Denmark, Norway and Sweden through the time span of 1990-2018. A linear fixed regression model was performed including the explanatory variables of monetary policy and credit developments, macroeconomic fundamentals, housing market variable and demographic variables. Secondly, a logit model was used to identify a relationship between oil price and house price turning points. The model used misalignment made from GDP per capita and real interest rate. The empirical analysis confirms that there is a positive relationship between oil prices and house price inflation. This evidence contradicts a major share of previous research papers (see Bernanke, 2010; Kaufmann et al., 2011). However, there are also some previous papers (see Yiqi, (2017); Antonakakis et al., 2016) and theoretical linkages in line with a positive correlation. Concerning, the oil price and house price inflation no empirical significance was found regarding their relationship. For future research, one could include regional aspects for the purpose of controlling for geographical differences.
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Yi, Yimin. "Understanding Changes in the Distribution of House Prices in Beijing, China." Thesis, North Dakota State University, 2016. https://hdl.handle.net/10365/27974.
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This thesis provides some evidences in understanding house price in Beijing. The rst
part examines appreciation rate of house price across the distribution from 2013 to 2015.
Similar temporal patterns of appreciation for different parts of price distribution are shown,
while the rates of appreciation of low-priced homes are found to be higher than higher-priced
homes over almost the full research period.
The second part analyzes changes in the distribution of house price between 2012
and 2015. We disentangle temporal changes into a composition effect attributed to altered
house characteristics and a coefficient effect driven by varying regression coefficients. Mean
decomposition suggests that only 13% of average price gaps are attributed to the composition
effect. Quantile decomposition results indicate that the contribution of the composition effect
rises monotonously from the left tail of distribution to the right tail while the contribution
of the coefficient effect only shows slight variation.
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Avramis, Nicholas. "Investigating the macroeconomic determinants of RDP house prices in South Africa." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/25094.
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The main purpose of this study is to investigate the relationship between macroeconomic variables and South Africa's affordable housing market using basic multivariate regression analysis. This paper empirically examines whether increases in RDP house prices can be explained by or attributed to the movements in gross domestic product (GDP), prime lending rate (RATE), the stock market (JSE) and inflation (CPI). As an exploratory paper in nature, data of RDP resales prices from eight major metropolitan cities in South Africa was collected from the Centre of Affordable Housing Finance (CAHF) for the period 2007 to 2015. The findings from the regression analysis show that only JSE is a key determinant of RDP housing prices in South Africa. Since there was no a statistically significant relationship that could be found between affordable housing price movements and GDP, RATE and CPI, this study suggests that hedonic variables should be used in future studies, as well as accounting for regional differences. Notwithstanding, since the resale of RDP homes is a new dimension in the real estate market and whose introduction is also still at its infancy in South Africa, an examination of the RDP home prices is important to the financiers (financial institutions), investors, housing authorities, the government and other interested stakeholders who might want to have an understanding of the factors that drive the prices of these homes in South Africa. The results from this study, therefore, play a role in informing these parties as they allow them to make better decisions in terms of whether to make financing available (financial institutions), policy formulation or direction (government) and whether to invest or sale (other stakeholders).
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Krčál, Adam. "High-dimensional VAR analysis of regional house prices in United States." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-202128.
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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.
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Abelson, Peter. "House and land prices in Australia with special reference to Sydney." Thesis, London School of Economics and Political Science (University of London), 1992. http://etheses.lse.ac.uk/2587/.
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The thesis describes and explains average house prices and the distribution of house prices in Sydney, Melbourne and Adelaide in the 1970s and 1980s, and average house and land prices and their distribution in Sydney from 1925 to 1970. Part I starts with a brief discussion of the special nature of housing. The rest of Part I describes the house and land prices that the study aims to explain. The Sydney data are described at greater length because these were developed mainly by the writer. Part II reviews economic theories of the price of housing services in the long and short run, the distribution of house prices, and the relationship between house and land prices. The models of average house prices allow, inter alia, for the dual role of housing as a consumption good and asset, the interaction between the demand for and supply of housing, and the disequilibrium nature of the housing market. The models of the distribution of house prices draw on economic theories of urban structure and hedonic house prices. Part III applies these models to explain short and long-run changes in house prices in Sydney, Melbourne and Adelaide since about 1970; the distribution of house prices within each city; and intercity differences in house prices. Part IV models average house and land prices, and explains their spatial distribution, in Sydney from 1925 to 1970. Part V summarises the main results of the research. The thesis provides plausible explanations for most of the observed major house price phenomena. The Appendices contain a note on the requirements for a Ph.D., a review of relevant literature by other writers, and a summary of related work on property prices by the author.
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Kong, Siu-chung. "Housing prices in Hong Kong, 1984-1997." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21027845.
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