Relevant bibliographies by topics / Comparison of house prices

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Academic literature on the topic 'Comparison of house prices'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Comparison of house prices"

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Hu, Lan, Yongwan Chun, and Daniel A. Griffith. "A Multilevel Eigenvector Spatial Filtering Model of House Prices: A Case Study of House Sales in Fairfax County, Virginia." ISPRS International Journal of Geo-Information 8, no. 11 (November 10, 2019): 508. http://dx.doi.org/10.3390/ijgi8110508.

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House prices tend to be spatially correlated due to similar physical features shared by neighboring houses and commonalities attributable to their neighborhood environment. A multilevel model is one of the methodologies that has been frequently adopted to address spatial effects in modeling house prices. Empirical studies show its capability in accounting for neighborhood specific spatial autocorrelation (SA) and analyzing potential factors related to house prices at both individual and neighborhood levels. However, a standard multilevel model specification only considers within-neighborhood SA, which refers to similar house prices within a given neighborhood, but neglects between-neighborhood SA, which refers to similar house prices for adjacent neighborhoods that can commonly exist in residential areas. This oversight may lead to unreliable inference results for covariates, and subsequently less accurate house price predictions. This study proposes to extend a multilevel model using Moran eigenvector spatial filtering (MESF) methodology. This proposed model can take into account simultaneously between-neighborhood SA with a set of Moran eigenvectors as well as potential within-neighborhood SA with a random effects term. An empirical analysis of 2016 and 2017 house prices in Fairfax County, Virginia, illustrates the capability of a multilevel MESF model specification in accounting for between-neighborhood SA present in data. A comparison of its model performance and house price prediction outcomes with conventional methodologies also indicates that the multilevel MESF model outperforms standard multilevel and hedonic models. With its simple and flexible feature, a multilevel MESF model can furnish an appealing and useful approach for understanding the underlying spatial distribution of house prices.
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Kok, Shiau Hui, Normaz Wana Ismail, and Chin Lee. "The sources of house price changes in Malaysia." International Journal of Housing Markets and Analysis 11, no. 2 (April 3, 2018): 335–55. http://dx.doi.org/10.1108/ijhma-04-2017-0039.

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Purpose The purpose of this paper is to examine the house market in Malaysia from 2002 to 2015. Specifically, the macroeconomic determinants on the house price and house demand are investigated. Design/methodology/approach Structural Vector Autoregressive Regression was adopted to estimate the unexpected changes in both house demand (residential transaction volume) and prices based on economic theoretical reasoning that consider shock from macroeconomic determinants. Findings The transaction volume and real house prices respond to most of the macroeconomic shocks. While the impact of real gross domestic product (GDP) on house prices appears to be stronger and longer in comparison to other macroeconomic shocks, a 60 per cent change in house prices can be explained by real GDP regardless of whether it is in the short run or the long run. The studies also reveal that a positive effective exchange rate plays an important role when demonstrating the transaction volume. Moreover, monetary liquidity plays a major role in justifying the transaction volume. This implies that mortgage lending may have an impact on housing demand. Meanwhile, movements of house prices cannot be explained by the demand in quantity. This signifies that supply has a strong influence in determining the price. Research limitations/implications This study has implications on policymakers of which the interest rate as a cooling measure might not be effective in the short run. The interest rate has very little impact on housing prices. Furthermore, policymakers should address the concerns on speculations, as the results reveal that monetary liquidity and the exchange rate have a strong impact on the housing demand. Originality/value This study seeks to provide answers regarding the recent upsurge of Malaysian housing prices. Besides focusing on the house price changes, this study addresses the role of transaction volume while evaluating the house market, as housing prices are usually downwards rigid. Since the price and transaction volume are both related to the transaction activity, this study is significant and could be a good reflection on the actual demand behaviour in the residential market.
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Cui, Nana, Hengyu Gu, Tiyan Shen, and Changchun Feng. "The Impact of Micro-Level Influencing Factors on Home Value: A Housing Price-Rent Comparison." Sustainability 10, no. 12 (November 22, 2018): 4343. http://dx.doi.org/10.3390/su10124343.

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The housing sales market in China has flourished and gained considerable interest, while the housing rental market has lagged behind and been ignored over the past two decades. With the acceleration of urbanization, the housing rental demand is rising rapidly. Exploring and comparing the influencing factors on housing sale prices and rental prices has significance for sustainable urban planning and management. Using house purchase transaction and rent transaction data in 2017, as well as the average housing price and rent data in 2016 in Beijing, China, this paper compares the spatial distribution and it employs the hedonic price model and quantile regression model to quantify the average and distributional effects of micro-level influencing factors on housing prices and housing rents. Results show that housing prices and housing rents both have a decentralized distribution with multiple centers, but rents of residential communities with high housing prices may not necessarily be high. Both homeowners and renters prefer properties with good structural, locational, and neighborhood characteristics, as well as a good school attendance zone, whereas they still differ in terms of preferences. Homeowners prefer a higher-quality living environment. Renters are more concerned with proximity to an employment center and public transit convenience. Moreover, the price premium of school quality for homeowners exceeds the premium for renters. Higher-priced homeowners or renters differ in the preferences from lower-priced homeowners or renters. Higher-priced homeowners and higher-priced renters are more willing to live in property with a larger number of bedrooms, proximity to a major employment center, park, or school, as well as a location in a school attendance zone with higher school quality.
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Janet, Xin, and Ka-Chi Lam. "Building a House Prices Forecasting Model in Hong Kong." Construction Economics and Building 2, no. 2 (November 17, 2012): 57–70. http://dx.doi.org/10.5130/ajceb.v2i2.2901.

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This paper builds a house prices forecasting model for private residential houses in HongKong, based on general macroeconomic indicators, housing related data and demographicfactors for the period of 1980 to 2001. A reduce form economic model has been derivedfrom a multiple regression analysis where three sets and eight models were derived foranalysis and comparison. It is found that household income, land supply, population andmovements in the Hang Seng Index play an important role in explaining house pricemovements in Hong Kong. In addition, political events, as identified, cannot be ignored.However, the results of the models are unstable. It is suggested that the OLS may nota best method for house prices model in Hong Kong situation. Alternative methods aresuggested.
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Breton, Magdalena Opazo, John Britton, Yue Huang, and Ilze Bogdanovica. "Comparison between Online and Offline Price of Tobacco Products Using Novel Datasets." International Journal of Environmental Research and Public Health 15, no. 10 (October 17, 2018): 2282. http://dx.doi.org/10.3390/ijerph15102282.

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Price of tobacco products has traditionally been relevant both for the industry, to respond to policy changes, and for governments, as an effective tobacco control measure. However, monitoring prices across a wide range of brands and brand variants requires access to expensive commercial sales databases. This study aims to investigate the comparability of average tobacco prices from two commercial sources and an in-house monitoring database which provides daily data in real time at minimal cost. We used descriptive and regression analysis to compare the monthly average numbers of brands, brand variants, products and prices of cigarettes and hand-rolling tobacco using commercial data from Nielsen Scantrack and Kantar Worldpanel, and an online price database (OPD) created in Nottingham, for the period from May 2013 to February 2017. There were marked differences in the number of products tracked in the three data sources. Nielsen was the most comprehensive and Kantar Worldpanel the least. Though average prices were very similar between the three datasets, Nottingham OPD prices were the highest and Kantar Worldpanel the lowest. However, regression analysis demonstrated that after adjustment for differences in product range, price differences between the datasets were very small. After allowing for differences in product range these data sources offer representative prices for application in price research. Online price tracking offers an inexpensive and near real-time alternative to the commercial datasets.
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Ciarlone, Alessio. "House price cycles in emerging economies." Studies in Economics and Finance 32, no. 1 (March 2, 2015): 17–52. http://dx.doi.org/10.1108/sef-11-2013-0170.

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Purpose – This paper aims to investigate the characteristics of house price dynamics for a sample of 16 emerging economies from Asia and Central and Eastern Europe over the period of 1995-2011. Design/methodology/approach – Linking housing valuations to a set of conventional fundamental determinants – relative to both the supply and the demand side of the market, institutional factors and other asset prices – and modelling short-term price dynamics – which reflect gradual adjustment to underlying fundamentals –conclusions about the existence and the basic nature of house price overvaluation (undervaluation) are drawn. Findings – Overall, it was found that actual house prices in the sample of emerging economies are not overly disconnected from fundamentals. Rather, they tend to reflect a somewhat slow adjustment to shocks to the latter. Moreover, the evidence that housing valuations may be driven by overly optimistic (or pessimistic) expectations is, in general, weak. Research limitations/implications – Residential property prices used in the empirical analysis have many limitations: while some series are derived using a hedonic pricing method, others are based on floor area prices collected by national authorities; while some countries publish house prices in national currency per-square metre (or per apartment or per dwelling), others calculate an index number scaled to some base year; while some countries publish statistics for the whole national territory, others produce data only for the capital city or for the largest cities in the country; data from national sources refer to different types of residential property; finally, available time series are relatively short, which may adversely affect the robustness of estimation results. Practical implications – The decomposition suggested in the paper has important implications: it would be paramount, in fact, for policymakers to implement market-specific diagnoses, and to find the right policy instruments that can ideally distinguish between the two underlying components driving house price short-run dynamics. Originality/value – There is a very small body of empirical literature on housing market developments in emerging economies, especially if focussed on the comparisons between the actual dynamics of housing valuations and the equilibrium ones.
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Banai, Ádám, Nikolett Vágó, and Sándor Winkler. "Measuring heterogeneity of house price developments in Hungary, 1990–2016." Acta Oeconomica 68, no. 3 (September 2018): 377–414. http://dx.doi.org/10.1556/032.2018.68.3.4.

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This study presents the detailed methodology of generating house price indices for the Hungarian market. The index family is an expansion of the Hungarian housing market statistics in several regards. The nationwide index is derived from a database starting from 1990, and thus the national index is regarded as the longest in comparison to the house price indices available so far. The long time series allow us to observe and compare the real levels of house prices across economic cycles. Another important innovation of this index family is its ability to capture house developments by regions and settlement types, which sheds light on the strong regional heterogeneity underlying the Hungarian housing market.
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Blaseio, Benedikt, and Colin Jones. "Regional economic divergence and house prices: a comparison of Germany and the UK." International Journal of Housing Markets and Analysis 12, no. 4 (August 5, 2019): 722–35. http://dx.doi.org/10.1108/ijhma-08-2018-0055.

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Purpose Increasing regional wealth disparities have been explained by the role of agglomeration economies and the concentration of skilled mobile human capital. This paper aims to draw out the role of the housing market by considering the differential experience of Germany and the UK. Design/methodology/approach The empirical analysis is based on the comparison of regional house price trends in Germany and UK-based annual data from 1991 to 2015. Findings Regional house price inequality is found to have increased in both countries with the spatial concentration of skilled human capital. However, the main conclusion is that there are differential paths to regional house price inequality explained by the parameters of each country’s housing market. Originality/value The research is the first to compare and explain differential regional house price trends across countries.
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HANSEN, JAMES. "Australian House Prices: A Comparison of Hedonic and Repeat-Sales Measures." Economic Record 85, no. 269 (June 2009): 132–45. http://dx.doi.org/10.1111/j.1475-4932.2009.00544.x.

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Bourassa, Steven, Eva Cantoni, and Martin Hoesli. "Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods." Journal of Real Estate Research 32, no. 2 (January 1, 2010): 139–60. http://dx.doi.org/10.1080/10835547.2010.12091276.

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Dissertations / Theses on the topic "Comparison of house prices"

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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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Books on the topic "Comparison of house prices"

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Lusht, Kenneth M. A comparison of house prices brought by English auctions and private negotiations in Melbourne. Canberra, ACT: Urban Research Program, Research School of Social Sciences, Australian National University, 1993.

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Duncan, S. Do house prices rise that much?: A comparison of Britain and Europe. Brighton: University of Sussex, 1989.

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Crone, Theodore M. Estimating house price appreciation: A comparison of methods. Philadelphia: Federal Reserve Bank of Philadelphia, Economic Research Division, 1992.

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Haefele, John. The Arkham House supplement: Bibliographical additions, comments, marginalia, and a revised, expanded collectors' price guide comparison to Arkham House/Mycroft & Moran. [United States]: J. Haefele, 1997.

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Pain, Nigel. Modelling structural change in the UK housing market: A comparison of alternative house price models. London: National Institute of Economic and Social Research, 1996.

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Shad, Parviz. London house prices. London: Bartlett School of Architecture and Planning, 1988.

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Bajari, Patrick. House prices and consumer welfare. Cambridge, Mass: National Bureau of Economic Research, 2003.

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Mississippi. Legislature. PEER Committee. Comparison of state contract prices with retail prices for commodity items. [Jackson, Miss.]: PEER Committee, Mississippi Legislature, 1995.

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Green, Richard K. Demographic factors and real house prices. Cambridge, Mass: National Bureau of Economic Research, 1993.

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Giussani, Bruno. Econometric model of regional house prices. Kingston-upon-Thames: Apex Centre, 1990.

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Book chapters on the topic "Comparison of house prices"

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Diewert, W. Erwin, Kiyohiko G. Nishimura, Chihiro Shimizu, and Tsutomu Watanabe. "A Comparison of Alternative Approaches to Measuring House Price Inflation." In Property Price Index, 81–125. Tokyo: Springer Japan, 2020. http://dx.doi.org/10.1007/978-4-431-55942-9_3.

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Nie, Huihua. "Collusion and House Prices." In Collusion, Local Governments and Development in China, 77–105. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5059-6_4.

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White, Allen L. "House Prices and House Buyers: Does Energy Matter?" In The GeoJournal Library, 325–52. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5416-8_18.

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Iparraguirre, José Luis. "Ageing, House Prices, and Economic Crises." In Economics and Ageing, 301–33. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29013-9_7.

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Richmond, Peter. "Will house prices rise in 2007? A comparative assessment of house prices in London and Dublin." In Coping with the Complexity of Economics, 131–45. Milano: Springer Milan, 2009. http://dx.doi.org/10.1007/978-88-470-1083-3_8.

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Ncube, Mthuli, and Eliphas Ndou. "Monetary Policy Transmission, House Prices and Consumption." In Monetary Policy and the Economy in South Africa, 43–64. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137334152_4.

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Zhou, Xiaobo, Yufei Wang, and Jie Wei. "Global Urban Sustainable Competitiveness Report 2017–2018." In House Prices: Changing the City World, 529–603. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9111-9_10.

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Ni, Pengfei, Marco Kamiya, Li Shen, Weijin Gong, and Haidong Xu. "Reviews of Global Urban Competitiveness 2017–2018 Driving Force, Agglomeration, Connectivity and the New Global City." In House Prices: Changing the City World, 49–131. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9111-9_2.

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Ni, Pengfei, and Yangzi Zhang. "Research Background and Literature Review." In House Prices: Changing the City World, 135–45. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9111-9_3.

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Cao, Qingfeng. "The Relationship Between Housing Prices and Urban Competitiveness: A Theoretical Framework." In House Prices: Changing the City World, 147–55. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9111-9_4.

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Conference papers on the topic "Comparison of house prices"

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Ecer, Fatih. "Comparision of Hedonic Regression Method and Artificial Neural Networks to Predict Housing Prices in Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.01150.

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Owner-occupied housing is both a place to live and also the most important asset in many households’ portfolio. Accurately predicting of house prices is therefore of great interest to the general public. This paper aims to compare the housing price prediction accuracies of Hedonic Model (HM) and Artificial Neural Networks (ANNs). In order to achieve this aim, two techniques’ prediction results were compared by using four performance criteria: RMSE, MAE, MAD, and Theil’s U statistic. This study uses the HM and ANNs to empirically determine the house prices in Turkey. HM is the standard technique for modeling the behavior of house prices over the past three decades and is based on micro economic theory. The non-linear relationship between house price and its determinants can be modeled by an ANN, so it is employed in this paper as an alternative method. Empirical results revealed that ANNs performed better than HM in house price predictions, indicating that ANNs could be useful for prediction of house prices. More clearly, the performance criteria from the ANNs are smaller than those from the HM by roughly 60-90%. For instance, the ANN model has about 77 percent lower RMSE, 91 percent lower MAE, 64 percent lower MAD, and 77 percent lower Theil’s U statistic than those of the HM.
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Liebenberg, B. J., J. Erasmus, E. Erasmus, and Douw Boshoff. "The Use of Economic Modeling for Interprovincial Comparisons of House Prices." In The 3rd Human and Social Sciences at the Common Conference. Publishing Society, 2015. http://dx.doi.org/10.18638/hassacc.2015.3.1.185.

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de La Paz, Paloma, and Francisco Juarez. "Long Term House Price Series for Spain: Construction and International Comparison." In 22nd Annual European Real Estate Society Conference. European Real Estate Society, 2015. http://dx.doi.org/10.15396/eres2015_239.

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Huang, Chyouhwu Brian, and Hung-Shyong Chen. "Heat Insulating Materials Thermal Conductivity Determination by Means of Comparison With a Standard Plate of Known Conductivity." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-89382.

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Due to the soaring energy prices, the cost to maintain a basic living standard has increased, therefore choosing right insulated materials when building a new house/appliance is important. The heat transfer coefficient plays a vital role; therefore, developing an effective, accurate, and low cost testing machine is an important issue. This is also the goal of this research. The testing apparatus developed can be used to measure the thermal conductivity as a basis for the choice of the materials. The heat conduction testing equipment was designed using “the thermal conductivity comparison with a known conductivity” method in addition to the basic heat conduction theory. For the best results, several parameters were used to fine-tune the operating conductions, such as cooling flow rate, heat source temperature, etc. Three types of materials were used as the sample for verifying the accuracy of the developed apparatus: gypsum board, silicon cement and PE polyethylene foam. Four heat sources temperatures were tested: 30°C, 35°C, 40°C, and 45°C. Two cooling flow rates were used: 108 liter/hour and 90 liter/hour. In the end, ANSYS was used to validate the testing results. The testing results show that the measured thermal conductivity is accurate. Equilibrium can be reached faster when testing with high cooling flow rates. The best hot plate temperature is 30°C.
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"Measuring House Prices." In 6th European Real Estate Society Conference: ERES Conference 1999. ERES, 1999. http://dx.doi.org/10.15396/eres1999_202.

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"Future House Prices." In 4th European Real Estate Society Conference: ERES Conference 1997. ERES, 1997. http://dx.doi.org/10.15396/eres1997_121.

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Twomey, Kelly M., and Michael E. Webber. "Evaluating the Cost of Food in a Carbon Constrained Economy." In ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90185.

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Although consensus has not been reached regarding the most efficient mechanism to curb anthropogenic greenhouse gas emissions, rising concern over the consequences of global climate change and consequent shifts in public and political sentiment suggest that carbon legislation will be instituted in the US in the near future. The recent climate change bill passed in the House of Representatives titled The American Clean Energy and Security Act of 2009 (HR 2454) includes provisions for a cap-and-trade system intended to reduce the nation’s greenhouse gas emissions 83% by 2050. Consequently, it is likely that some means of carbon pricing will take effect that will make it more expensive to emit greenhouse gases. In a carbon constrained economy, it will become increasingly important to consider every stage of food production and consumption in order to evaluate the potential opportunities for emission reductions. This analysis uses Life-Cycle Assessment to estimate the social cost of food production by quantifying the associated negative externalities under a range of potential carbon prices, using meat and grain as examples. It concludes that 0.42 and 16.0 kg of lifecycle CO2e are embedded in 1 kg of grain and beef production, respectively. Consequently, the marginal cost associated with the emissions caused by grain production under a carbon price range of $10 and $85 per t CO2e is estimated to be between $.004 and $0.036 per kg of grain. By comparison, the estimated marginal cost associated with beef production over the same range of carbon pricing is $0.16 and $1.36 per kg of beef. Considering that the US produces 12 billion kg of beef per year, this range indicates that the carbon cost of beef production alone might fall anywhere between $1.9 and $16.3 billion per year, depending on whether and how a carbon price is applied. This uncertainty and potential carbon price could significantly impact the cost of carbon-intensive foods.
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"House Prices Down Under." In Third Conference of the European Real Estate Society: ERES Conference 1996. ERES, 1996. http://dx.doi.org/10.15396/eres1996_118.

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"Taxes and House Prices." In Third Conference of the European Real Estate Society: ERES Conference 1996. ERES, 1996. http://dx.doi.org/10.15396/eres1996_154.

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Brackin, Patricia, and Jonathan Colton. "Estimating Target Values in Preliminary Design: An Automotive Case Study." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/dtm-8772.

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Abstract Estimation modules have been developed for use with the House of Quality. These estimation modules are used to predict the performance of a proposed design based on the values of the Engineering Characteristics. This, paper describes the development of modules for an automotive case study. Specifically, modules for weight, price, acceleration time, and fuel economy are given. Comparison of estimated values to actual values show an average percent difference of less than 10%.
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Reports on the topic "Comparison of house prices"

1

Disney, Richard, and Daniel Chandler. Measuring house prices: a comparison of different indices. Institute for Fiscal Studies, May 2014. http://dx.doi.org/10.1920/bn.ifs.2014.00146.

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Stroebel, Johannes, and Joseph Vavra. House Prices, Local Demand, and Retail Prices. Cambridge, MA: National Bureau of Economic Research, November 2014. http://dx.doi.org/10.3386/w20710.

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Bajari, Patrick, C. Lanier Benkard, and John Krainer. House Prices and Consumer Welfare. Cambridge, MA: National Bureau of Economic Research, June 2003. http://dx.doi.org/10.3386/w9783.

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Berger, David, Veronica Guerrieri, Guido Lorenzoni, and Joseph Vavra. House Prices and Consumer Spending. Cambridge, MA: National Bureau of Economic Research, October 2015. http://dx.doi.org/10.3386/w21667.

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Campbell, John, Stefano Giglio, and Parag Pathak. Forced Sales and House Prices. Cambridge, MA: National Bureau of Economic Research, April 2009. http://dx.doi.org/10.3386/w14866.

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Etheridge, Ben. House prices and consumption inequality. The IFS, September 2019. http://dx.doi.org/10.1920/wp.ifs.2019.1924.

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Adelino, Manuel, Antoinette Schoar, and Felipe Severino. House Prices, Collateral and Self-Employment. Cambridge, MA: National Bureau of Economic Research, March 2013. http://dx.doi.org/10.3386/w18868.

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Green, Richard, and Patric Hendershott. Demographic Factors and Real House Prices. Cambridge, MA: National Bureau of Economic Research, April 1993. http://dx.doi.org/10.3386/w4332.

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Engelhardt, Gary. House Prices and Home Owner Saving Behavior. Cambridge, MA: National Bureau of Economic Research, July 1995. http://dx.doi.org/10.3386/w5183.

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Mian, Atif, Amir Sufi, and Francesco Trebbi. Foreclosures, House Prices, and the Real Economy. Cambridge, MA: National Bureau of Economic Research, January 2011. http://dx.doi.org/10.3386/w16685.

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