published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

A Research Report presented to the Graduate School of Business Leadership University of South Africa. In partial fulfilment of the requirements for the MASTERS DEGREE IN BUSINESS LEADERSHIP, UNIVERSITY OF SOUTH AFRICA / The purpose of this research is to analyse the changes in housing values in Windhoek, Namibia over the past ten years and explore links in property value variation to macroeconomic changes during that period. The objectives of this research are twofold. Firstly this research compiles and assesses the movement of housing values over the past ten years. Secondly this research assesses if there is a causal relationship between changes in macroeconomic factors and housing values, and to define the nature of this relationship. The timing and magnitude of response by housing values to changes in macroeconomic factors are investigated. The primary data requirements for this study are a monthly relative value index of housing prices for the Windhoek area and macroeconomic factors. Macroeconomic data collected relates to macroeconomic conditions within Namibia that could have an effect on housing prices. This includes information on housing supply, GDP, population levels, inflation and interest rates. The results of this study explore the relationship between these factors and changes in housing prices as reflected by changes in the housing index. The most significant result of this study is the effect of housing availability on housing values. Changes in the total supply of housing as estimated by the number of houses built in a month affect changes in housing values after 5 and 6 months. A total of 20.5% of the change in housing values can be explained by the change in total housing supply. The effect of interest rates found by this study was lower than the theory and literature reviews would have led us to expect. The results of the Pearson correlation test for the relationship between percentage changes in interest rates and percentage changes in future housing values found that a relationship exists 8 months after the change in interest rates occurred. Interest rates were found to explain 5.5% of the change in housing values 8 months later. No significant effects were noted for changes in inflation. For population and income changes there was insufficient data to perform more than a high level look at possible interactions with the level of housing prices. / Graduate School of Business Leadership / MBL

by Vera Hau Tsz Lai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 227-236). / ABSTRACT --- p.i-ii / ACKNOWLEDGEMENTS --- p.iii-iv / TABLE OF CONTENTS --- p.v-ix / LIST OF FIGURES --- p.x / LIST OF PLATES --- p.xi-xiii / LIST OF TABLES --- p.xiv-xvi / Chapter CHAPTER I --- INTRODUCTION --- p.1 / Chapter 1.1 --- Problem Statement --- p.1 / Chapter 1.2 --- Role of GIS in Housing Price Study --- p.3 / Chapter 1.3 --- Research Objectives --- p.4 / Chapter 1.4 --- Significance --- p.5 / Chapter 1.5 --- Methodologies --- p.6 / Chapter 1.6 --- Organization of Thesis --- p.7 / Chapter CHAPTER II --- LITERATURE REVIEW --- p.9 / Chapter 2.1 --- Introduction --- p.9 / Chapter 2.2 --- Geography of Housing --- p.10 / Chapter 2.3 --- Housing as a Research Question --- p.11 / Chapter 2.4 --- Housing Services and Housing Price --- p.12 / Chapter 2.5 --- Property Price Valuation --- p.14 / Chapter 2.6 --- Hedonic Price Function --- p.15 / Chapter 2.6.1 --- Dependent Variable - Property Price --- p.16 / Chapter 2.6.2 --- Independent Variables Affecting Housing Price --- p.17 / Chapter 2.6.2.1 --- Aspatial Factors --- p.17 / Chapter 2.6.2.2 --- Spatial Factors --- p.18 / Chapter 2.6.2.3 --- Evaluation on Importance of Parameters --- p.26 / Chapter 2.7 --- Functional Form of Hedonic Price Models --- p.33 / Chapter 2.7.1 --- Conventional Specifications --- p.34 / Chapter 2.7.2 --- Box-Cox Transformation --- p.34 / Chapter 2.7.3 --- Conventional Specifications versus Box-Cox Transformation --- p.35 / Chapter 2.8 --- Submarket Analysis and its Delineation --- p.36 / Chapter 2.9 --- Geographic Information Systems --- p.39 / Chapter 2.10 --- GIS in Real Estate --- p.39 / Chapter 2.11 --- Present Adoption of GIS in Real Estate --- p.42 / Chapter 2.11.1 --- Commercial Applications --- p.42 / Chapter 2.11.2 --- Research-wise Applications --- p.43 / Chapter 2.12 --- Hedonic Price Study with GIS --- p.43 / Chapter 2.13 --- Conclusion --- p.45 / Chapter CHAPTER III --- THE STUDY AREA AND RESEARCH METHODOLOGY --- p.47 / Chapter 3.1 --- Introduction --- p.47 / Chapter 3.2 --- Real Estate Sector in Hong Kong --- p.47 / Chapter 3.2.1 --- Importance to Local Economy --- p.48 / Chapter 3.2.2 --- Importance to Housing Production --- p.48 / Chapter 3.3 --- Urban Development and Housing in Hong Kong --- p.51 / Chapter 3.3.1 --- Land Availability and Landuses --- p.51 / Chapter 3.3.2 --- Housing and Urban Development --- p.54 / Chapter 3.3.2.1 --- Early Period of Industrialization --- p.54 / Chapter 3.3.2.2 --- Phase of Economic Restructuring --- p.55 / Chapter 3.3.3 --- Urban Renewal --- p.55 / Chapter 3.3.4 --- Comprehensive Housing Projects --- p.56 / Chapter 3.4 --- New Town Housing - Public or Private-Led --- p.57 / Chapter 3.5 --- Hedonic Price of Private Dormitory in Hong Kong --- p.61 / Chapter 3.5.1 --- Temporal Change in Property Price --- p.62 / Chapter 3.5.2 --- Spatial Variation of Property Price --- p.66 / Chapter 3.6 --- The Research --- p.68 / Chapter 3.6.1 --- Cartographic Analysis --- p.68 / Chapter 3.6.2 --- Hedonic Price Model --- p.69 / Chapter 3.6.3 --- Dependent Variable --- p.69 / Chapter 3.6.4 --- Independent Variables --- p.70 / Chapter 3.6.5 --- Chosen Functional Form in this Research --- p.72 / Chapter 3.6.6 --- Submarket Analysis in Hong Kong --- p.72 / Chapter 3.7 --- Conclusion --- p.72 / Chapter CHAPTER IV --- DATABASE CONSTRUCTIONS --- p.74 / Chapter 4.1 --- Introduction --- p.74 / Chapter 4.2 --- Data Collection --- p.74 / Chapter 4.2.1 --- Base Maps --- p.75 / Chapter 4.2.2 --- Housing Stock and its Attributes --- p.76 / Chapter 4.2.3 --- Official Statistics --- p.76 / Chapter 4.2.4 --- School Quality --- p.77 / Chapter 4.3 --- Data Input --- p.78 / Chapter 4.3.1 --- Graphical Input --- p.78 / Chapter 4.3.1.1 --- Base Maps --- p.78 / Chapter 4.3.1.2 --- Line Data --- p.78 / Chapter 4.3.1.3 --- Point/Polygon Data --- p.79 / Chapter 4.3.2 --- Attribute Data Input --- p.82 / Chapter 4.4 --- Data Editing and Conversions --- p.82 / Chapter 4.4.1 --- Graphical Input --- p.82 / Chapter 4.4.1.1 --- Standard Coverage Editing Procedures --- p.82 / Chapter 4.4.1.2 --- Specific Coverage Editing Procedures --- p.83 / Chapter 4.4.2 --- Attribute Data --- p.84 / Chapter 4.4.2.1 --- Housing Attributes --- p.84 / Chapter 4.4.2.2 --- Landuse Mix --- p.88 / Chapter 4.4.2.3 --- Socioeconomic Status --- p.91 / Chapter 4.4.2.4 --- Employment Figures --- p.91 / Chapter 4.5 --- Data Pre-processing and Manipulation --- p.93 / Chapter 4.5.1 --- Employment Potentials --- p.93 / Chapter 4.5.2 --- Socioeconomic Variables --- p.96 / Chapter 4.5.2.1 --- Interpretation --- p.97 / Chapter 4.5.3 --- School Quality --- p.107 / Chapter 4.5.4 --- Proximity Measurements --- p.110 / Chapter 4.5.5 --- Final Step of Association : Overlay Operations --- p.110 / Chapter 4.6 --- Conclusion --- p.112 / Chapter CHAPTER V --- CARTOGRAPHIC ANALYSIS --- p.114 / Chapter 5.1 --- Introduction --- p.114 / Chapter 5.2 --- Representation of Data --- p.114 / Chapter 5.2.1 --- Location of Premises --- p.114 / Chapter 5.2.2 --- Proximity --- p.118 / Chapter 5.2.3 --- School Quality --- p.118 / Chapter 5.2.4 --- Landuse Mix --- p.129 / Chapter 5.2.5 --- Employment --- p.132 / Chapter 5.2.6 --- Property Price --- p.137 / Chapter 5.3 --- Results and Discussions --- p.137 / Chapter 5.3.1 --- Temporal Variation on Housing Supply --- p.143 / Chapter 5.3.2 --- Temporal Variation on Floor Size --- p.145 / Chapter 5.3.3 --- Temporal Variation on Property Price --- p.148 / Chapter 5.4 --- Locational Variations --- p.150 / Chapter 5.4.1 --- Shift towards the New Towns --- p.150 / Chapter 5.4.2 --- Relative Importance among Districts in New Towns --- p.154 / Chapter 5.4.3 --- Pattern of Development --- p.158 / Chapter 5.4.3.1 --- Urban Core --- p.158 / Chapter 5.4.3.2 --- New Towns --- p.161 / Chapter 5.5 --- Spatial Variations on Floor Size --- p.171 / Chapter 5.6 --- Spatial Variations on Property Price --- p.176 / Chapter 5.7 --- Conclusion --- p.181 / Chapter CHAPTER VI --- STATISTICAL ANALYSIS --- p.183 / Chapter 6.1 --- Introduction --- p.183 / Chapter 6.2 --- The Data Set --- p.183 / Chapter 6.3 --- Stepwise Regression Modeling --- p.184 / Chapter 6.4 --- Correlation among Variables --- p.184 / Chapter 6.5 --- Validation of the Models --- p.186 / Chapter 6.6 --- Findings --- p.193 / Chapter 6.6.1 --- Pooled Market Results --- p.193 / Chapter 6.6.2 --- Submarket Level Analyses --- p.198 / Chapter 6.6.2.1 --- "Small-Sized, Low-Priced Flats " --- p.200 / Chapter 6.6.2.2 --- "Small-Sized, High-Priced Flats " --- p.203 / Chapter 6.6.2.3 --- "Medium-Sized, Low-Priced Flats " --- p.206 / Chapter 6.6.2.4 --- "Medium-Sized, High-Priced Flats " --- p.210 / Chapter 6.6.2.5 --- "Large-Sized, High-Priced Flats " --- p.213 / Chapter 6.7 --- Conclusion --- p.213 / Chapter CHAPTER VII --- CONCLUSION --- p.217 / Chapter 7.1 --- Summary of Findings --- p.217 / Chapter 7.1.1 --- Summary on Housing Development in Hong Kong…… --- p.217 / Chapter 7.1.2 --- Summary from Hedonic Price Models --- p.220 / Chapter 7.1.3 --- Significance of GIS --- p.222 / Chapter 7.2 --- Limitations and Recommendations --- p.222 / Chapter 7.3 --- Direction of Future Research --- p.226 / BIBLIOGRAPHY --- p.227 / APPENDICES --- p.237 / APPENDIX 1 --- p.238 / District Map of Hong Kong --- p.239 / APPENDIX II --- p.240 / List of Districts and its Components --- p.241 / APPENDIX III --- p.243 / Tertiary Planning Units (TPUs) - District Conversion List --- p.244

A great deal of research has been carried out on residential property values and numerous factors have been identified as having an effect on residential property values. The physical characteristics of properties of properties are the primary factors that determine the market value of residential property. However, factors concerning location are also thought to influence the value of residential properties. These locational factors include, among others, accessibility to highways, airports, schools, parks and public transportation centres. This study examines the effect of another locational factor, namely proximity to a newly built shopping centre. Shopping centres have been increasing in numbers throughout South Africa over the past few decades. These shopping centres are usually situated in close proximity to residential properties. As such, shopping centres that are in close proximity to residential properties can influence property prices. This study makes use of the hedonic price model to assess the price impact of the newly constructed Baywest Mall on the residential properties in the western suburbs of Nelson Mandela, namely Sherwood, Rowallan Park and Kunune Park. On 21 March 2012, the construction of the Baywest Mall was officially announced. This announcement created an area of interest as to whether its construction and completion would have an impact on the prices of residential properties situated in close proximity to the mall. The study period for this study was from 2004 – 2015. This time period is thought to be sufficient to assess the effect of the Baywest Shopping Mall on the residential property prices before and after the announcement of the construction of the mall. As the study period ranged from 2004 – 2015 it was necessary to adjust the sales prices over the years to constant 2015 prices. As such, the ABSA house price index was used in order to eliminate any inflationary effects on the property values over the study period. The results of the study revealed that the newly built Baywest Mall has a statistically significant positive effect on properties in close proximity to the shopping mall. This result enhances the scientific understanding of the effect of commercial land uses, such as, shopping centres, on the value of adjacent residential properties.

This thesis titled ``Essays in Private Capital" comprises of three essays focused on various parts of private capital. Private capital, also known as alternative assets are non-traded, broadly defined as private equity, real estate, venture capital, hedge funds, infrastructure and natural resource investments. The first chapter studies private equity, the second focuses on residential real estate, and the third is on commercial real estate. These are important asset classes given the low interest rate environment, and the recent COVID-19 and Silicon Valley Bank crisis which had large exposures to private assets. The first essay titled ``Desperate Capital Breeds Productivity Loss: Evidence from Public Pension Investments in Private Equity" studies investor heterogeneity in private equity and its ultimate effect on target firms. Using novel micro-data on individual investments in private equity funds funds and buyout deals combined with confidential Census data, I show that capital contributed by the most underfunded U.S. public pensions decreases efficiency at target firms, as pensions fuel the growth of low quality, new entrant private equity funds. These results get stronger post the financial crisis, when underfunded positions and their subsequent investments in private equity increased. The paper shows that traditionally positive post buyout efficiency results turn negative in recent years, as marginal investors matching with marginal private equity funds pull down the average. The most underfunded pensions also realize lower total private equity returns relative to the least underfunded ones. These results suggest possibility of a ``funding doom loop" as currently public pensions use assumed return on assets to calculate liabilities. The second essay titled ``Flattening the Curve: Pandemic-Induced Revaluation of Urban Real Estate" focuses on work from home with the onset of the COVID-19 pandemic and its effect on residential real estate prices across the U.S. We show that the COVID-19 pandemic brought house price and rent declines in city centers, and price and rent increases away from the center, thereby flattening the bid-rent curve in most U.S. metropolitan areas. Across MSAs, the flattening of the curve is larger where working from home is more prevalent, housing markets are more regulated, and supply is less elastic. Using a model predicting future residential price and rent evolution, we show urban revival in housing markets for the foreseeable future with urban rent growth exceeding suburban rent growth, as working from home recedes. In the third essay titled ``Work From Home and the Office Real Estate Apocalypse", we show remote work led to large drops in lease revenues, occupancy, lease renewal rates, and market rents in the commercial office sector. We revalue New York City office buildings taking into account both the cash flow and discount rate implications of these shocks, and find a 39% decline in long run value. For the U.S., we find a $413 billion value destruction. We show evidence of flight to quality, as higher quality buildings are buffered against these trends, while lower quality office is at risk of becoming a stranded asset. These valuation changes have repercussions for local public finances and financial stability.

published_or_final_version / Housing Management / Master / Master of Housing Management

published_or_final_version / Housing Management / Master / Master of Housing Management

Mental health group homes located in residential neighborhoods are considered a locally undesirable land uses. Most communities and neighborhood members are misinformed or unaware of numerous studies conducted in the United States concerning the impacts of mental health group homes. This study investigated several conflicting issues associated with the siting of mental health group homes and the three most expressed oppositions by the general public to the integration of these facilities into residential neighborhoods. This creative project determined what effects, if any, a mental health group home has on property values, crime and neighborhood stability using a Comparable Market Analysis, Muncie Police Department records, Multiple Listing Service information, interviews and records form Comprehensive Mental Health Services of East Central Indiana. A description of the process used and results are given along with a determination of the impacts mental health group homes have had on the Muncie, Indiana neighborhoods where one is located. / Department of Urban Planning

[Truncated abstract] This thesis examines informational efficiency and price discovery processes within the Perth housing market for the period 1988-2000 by utilising a rich source of Western Australian Valuer General’s Office (VGO) data. Fama’s (1970) classification of market efficiency as potentially weak form, semi-strong, or strong form has been a dominant paradigm in tests of market efficiency in many asset markets. While there are some parallels, the results of tests in this thesis suggest there are also limitations in applying this paradigm to housing markets. The institutional structure of housing markets dictates that a deeper recognition of important housing market characteristics is required. Efficiency in housing markets is desirable in that if prices provide accurate signals for purchase or disposition of real estate assets this will facilitate the correct allocation of scarce financial resources for housing services. The theory of efficient markets suggests that it is desirable for information diffusion processes in a large aggregate housing market to facilitate price corrections. In an efficient housing market, these processes can be observed and will enable housing units to be exchanged with an absence of market failure in all price and location segments. Throughout this thesis there is an emphasis on disaggregation of the Perth housing market both by price and location criteria. Results indicate that the Perth housing market is characterised by varying levels of informational inefficiency in both price and location segments and there are some important pricing-size influences.

Submitted by Maria de Lourdes Mariano (lmariano@ufscar.br) on 2017-02-24T17:17:13Z No. of bitstreams: 1 REIS_Raphael_2015.pdf: 36675145 bytes, checksum: 3d5dcec15edaaf78d9fe698e288aafe8 (MD5) / Approved for entry into archive by Maria de Lourdes Mariano (lmariano@ufscar.br) on 2017-02-24T17:17:26Z (GMT) No. of bitstreams: 1 REIS_Raphael_2015.pdf: 36675145 bytes, checksum: 3d5dcec15edaaf78d9fe698e288aafe8 (MD5) / Approved for entry into archive by Maria de Lourdes Mariano (lmariano@ufscar.br) on 2017-02-24T17:17:34Z (GMT) No. of bitstreams: 1 REIS_Raphael_2015.pdf: 36675145 bytes, checksum: 3d5dcec15edaaf78d9fe698e288aafe8 (MD5) / Made available in DSpace on 2017-02-24T17:17:40Z (GMT). No. of bitstreams: 1 REIS_Raphael_2015.pdf: 36675145 bytes, checksum: 3d5dcec15edaaf78d9fe698e288aafe8 (MD5) Previous issue date: 2015-01-21 / Não recebi financiamento / In recent years, the Brazilian real estate market has faced structural changes, which has impacted the price of residences. As observed for the country, the city of Sorocaba also went through a real estate valuation process, which impacted in many ways different locations in the city. The formation of the price of residences, function of the cost of construction, also depends on external variables, commonly called urban amenities. Urban menities, even though they are part of the real price of residences, are not easily identified or valued by economic agents but are important, mainly for potential consumers of services since they have different perceptions of urban features that are priority. In this context, the objective of the study is to identify and quantify the impact of structural features and urban attributes in property prices in the city of Sorocaba, identifying if there is a regional distribution pattern of properties more and less valued as a result of these attributes. Additionally, this study spatializes the results by districts. The methodology used is the estimation of the values of the amenities is the hedonic pricing model. This methodology proposed by Rosen (1974), implies in practice, in the estimation of a "cost function", with property prices is the dependent variable and the amenities associated with it are independent variables. The data used were the property sales prices and structural characteristics of each property, accessibility variables (schools, hospitals, etc.) and neighborhood structure (population, income and crime). The results suggest that there are urban amenities that are considered by consumers in the formation of properties prices and that there is spatial dependence between the average real estate values in every area of influence of neighborhoods considered in the study. / Nos últimos anos o mercado imobiliário brasileiro tem enfrentado mudanças estruturais, as quais tem impactado o preço dos bens residenciais. Assim como o observado para o país, o município de Sorocaba também passou por um processo de valorização imobiliária, o qual atingiu de maneiras distintas as diferentes localidades do município. A formação do preço dos imóveis, além de ser função do custo de construção dos mesmos, também depende de variáveis externas, comumente chamadas de amenidades urbanas. As amenidades urbanas embora sejam parte da composição do preço dos imóveis não são facilmente identificadas ou valoradas pelos agentes econômicos mas são importantes principalmente para os consumidores potenciais dos serviços prestados uma vez que eles tem percepções diferentes das características urbanas que lhe são prioritárias. Neste contexto, o objetivo do estudo é identificar e quantificar o impacto das características estruturais e dos atributos urbanos nos preços dos imóveis no município de Sorocaba, identificando se existe algum padrão regional de distribuição dos imóveis mais e menos valorizados em decorrência desses atributos e , além disso, espacializando os resultados por regiões sorocabanas. A metodologia utilizada é a estimação dos valores das amenidades a partir do modelo de preços hedônicos. Essa metodologia, proposta por Rosen (1974), implica, na prática, na estimação de uma “função preço”, com os preços dos imóveis como variável dependente e as amenidades associadas a ele como variáveis independentes . Os dados utilizados foram os preços de venda dos imóveis, características estruturais de cada imóvel, variáveis de acessibilidade (escolas, hospitais, etc) e de estrutura do bairro (população, renda e crime). Os resultados sugerem que existem amenidades urbanas que são consideradas pelos consumidores na formação dos preços dos imóveis e que existe dependência espacial entre os valores médios dos imóveis em cada área de influência dos bairros considerados no estudo.