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This book is devoted to fill the ‘urban economics niche’ and conceptualize a framework for valuing the urban configuration via local housing market. Advanced network analysis techniques are employed to capture the centrality features hindered in street layout. The author explores the several effects of urban morphology via housing market over two distinct contexts: UK and China. This work will appeal to a wide readership from scholars and practitioner to policy makers within the fields of real estate analysis, urban and regional studies, urban planning, urban design and economic geography.
The task of modelling the evolution of cities – the dynamics – is one of the major challenges of the social sciences. This book presents mathematical and computer models of urban and regional dynamics and shows how advances in computer visualisation provide new insights. Models of non-linear systems in general have three characteristics: multiple equilibria, ‘path dependence’ over time and phase transitions – that is, abrupt change at critical parameter values. These phenomena all exhibit themselves in reality, and it is an ongoing task to match model-based analysis with real phenomena. There are three key features of cities and regions to be represented in models: activities at a location – residence, health, education, work and shopping; flows between locations – spatial interaction; and the structures that carry these activities – buildings, transport and communications networks. Spatial interaction and many elements of activities’ location can be modelled by statistical averaging procedures, which are related to Boltzmann’s methods in statistical mechanics. This is while the evolution of structure can be represented in equations that connect to the Lotka-Volterra equations in ecology. Within this broad framework, alternative approaches can be brought to bear. This book uses entropy-maximising versions of spatial interaction models. The authors explore the dynamics in more detail, using advanced visualisation techniques. These ideas have wide potential uses, and the book illustrates this with applications in history and archaeology.
The Economics of The Modernisation of Direct Real Estate and The National Estate - A Singapore Perspective Chapter 1 takes a close look the vector auto regression (VAR) model, offering a dynamic system of solely direct real estate variables, for international direct real estate investors and policy makers, to enable their decision-making. Chapter 2 examines the association of residential price and aggregate consumption. A cross-spectra analysis is helps to so validate, because of its model-free characteristics Chapter 3 is concerned with the underlying housing market dynamics and housing price time-series variation, via the Singapore (SG) generalized dynamic factor model (GDFM). Chapter 4 is concerned with the in-depth market analysis and empirical analysis of the structural behavior of the important SG private housing sector. Chapter 5 acknowledges that an in-depth sector analysis and an empirical analysis are imperative to better understand the structural behavior of the SG office sector. Chapter 6 is concerned with the Main Upgrading Programme (MUP), a highly targeted subsidized Housing Development Board (HDB) policy, since the 1990s. Chapter 7 recognizes the ‘National Estate’, denoting SG’s built environment, due to physical planning, integrated urban design, and the direct influence of the SG government in providing physical infrastructure via government ministries, statutory boards and public authorities. Chapter 8 offers the book’s conclusion.
This booklet discusses some major methodological issues relating to the construction of house price models on a macro level. There is no single method that always produces the optimal results; the choice of a particular approach, method, theory, model and technique is context-dependent. This is especially true in housing markets, where a multitude of different submarkets exist. The methodology chosen should be based on sound theory, from which the basic concepts of analysis can be derived. This booklet discusses the use of potential models, which can be constructed using a general field theory, and which act as a theoretical foundation for further analysis. If we use potential models for house price analysis we can discover additional features from the data set that other approaches would simply miss. This e-book presents a pragmatic overview of key methodological concerns with the emphasis on the use of potential models. Theoretical methodological questions are left unanswered, and are not even presented in this text, since they have little relevancy to real-world modelling questions.
This paper investigates the developments in house price synchronization across countries by a dynamic factor model using a country- and city-level dataset, and examines what drives the synchronization. The empirical results indicate that: (i) the degree of synchronization has been rising since the 1970s, and (ii) a large heterogeneity in the degree of synchronization exists across countries and cities. A panel and cross-sectional regression analysis show that the heterogeneity of synchronization is partly accounted for by the progress in financial and trade openness. Also, the city-level analysis implies that the international synchronization is mainly driven by the city-level connectivity between large and international cities.
This booklet is a final complement to the series of investigations (”A Field Theory of House Prices”, ISBN 978-952-6613-36-9 and ”Nonstandard House Price Theory”, ISBN 978-952-6613-66-6) on the fundamental nature of house prices, which is, strictly speaking, a mathematical question. As in the earlier e-books on the scientific essence of house prices by the author, this booklet analyses house prices using the concept of a vector field. The fundamental idea underlying this e-book is that housing demand, housing supply and house prices can be investigated not as scalar functions but as genuine vector fields.
Explains how we got into the current economic disaster that developed out of the economics and politics of the housing boom and bust. The "creative" financing of home mortgages and "creative" marketing of financial securities based on these mortgages to countries around the world, are part of the story of how a financial house of cards was built up--and then collapsed.
These proceedings represent the work of contributors to the 23rd European Conference on Research Methodology (ECRM 2024), hosted by ISCAP in Porto, Portugal on 4-5 July 2024. The Conference Co-Chairs are Dr Ana Isabel Azevedo and Dr José Manuel Azevedo, both from ISCAP Portugal. ECRM is a well-established event on the academic research calendar and now in its 23rd year and remains an opportunity for participants to share ideas and meet. The aims and scope of this conference is to bring together researchers from a range of disciplines and sectors to share expertise and novel approaches in business and management research methods. ECRM is interested in contributions on the subject of research methods used in business and management research. The papers tend to either focus directly on creating and implementing innovative methodologies or research papers which highlight an interesting use of methodologies in their study. The opening keynote presentation is given by Marta Agostinho, Executive Director of EU-LIFE with the title Excellent Scientific Research: What Does it Mean and Why Should we Care About it? On the second day, Professor Susanne Tietze from The University of Sheffield Hallam, UK will give a talk on the subject Cross-Language Research Methods: Translation and Linguistic Reflexivity. With an initial submission of 90 abstracts, after the double blind, peer review process there are 30 Academic research papers, 1 PhD research paper, 1 Masters Research paper and 1 work-in-progress paper published in these Conference Proceedings. These papers represent research from India, Australia, Brazil, Canada, China, Czech Republic, Estonia, Germany, India, Ireland, Italy, Latvia, Morocco, Norway, Oman, Poland, Portugal, Slovakia, South Africa, Sweden, UK and the USA.
The rapid increase in house prices in the past few years, including during the COVID-19 pandemic, raises concerns about housing affordability. The price-to-income ratio is a widely-used indicator of affordability, but does not take into account important factors such as the cost of financing. The aim of this paper is to construct a measure of housing affordability that takes these factors into account for a large set of countries and long period of time. The resulting dataset covers an unbalanced panel of 40 countries over the period from 1970Q1 to 2021Q4. For each country, the index measures the extent to which a median-income household can qualify for a mortgage loan to purchase an average-priced home. To gauge the performance of the constructed indices, we compare them to other readily-available mesures of affordability and examine the evolution of the indices over time to understand the relevant drivers, including in a regression analysis to assess the extent to which government housing programs could contribute to improving affordability.