Syftet med denna uppsats är att utreda vilka faktorer som påverkar de svenska småhuspriserna, och i så fall hur och i vilken utsträckning. Med stöd av tidigare studier som enhetlig pekar ut bolåneräntan och disponibel inkomst som de faktorer vilka har tydligast inverkan på fastighetspriserna i Sverige, utökas de förklarande variablerna i denna studie med hjälp av en stock-flow modell. Tidsseriedata från 1993-2013 behandlas för enhetsrötter och kointegration för att skattas i en regressionsanalys i form en "Error Correction Model", med avsikten att utreda både ett kort- och långsiktigt samband. Resultatet bekräftar reporäntan och disponibel inkomst som två viktiga faktorer för att förklara det långsiktiga sambandet med priserna på småhus i Sverige, tillsammans med ytterligare faktorer såsom BNP, hushållens skuldsättning och arbetslösheten. På kort sikt är dels den historiska utvecklingen av huspriserna en nyckelfaktor, men faktorer som disponibel inkomst, ränta, BNP och hushållens skuldsättning är också viktiga krafter för att förklara småhuspriserna. En slutsats som kan dras är att hushållens förmåga till ökad konsumtion, när inkomsterna ökar, avspeglas i småhuspriserna. En låg ränta gör samtidigt att fler än någonsin har råd att låna på en marknad med ett redan mycket begränsat bostadsutbud / The purpose of this study is to investigate which factors affect the Swedish real estate prices of small house dwellings, and if so, how and to what extent. With the use of earlier studies, that coherently claims mortgage rate and household disposable income to be the most valuable factors to explain the Swedish real estate prices, this study will consider additional determinant factors with the respect to a stock-flow model. 1993-2013 time series data will be tested for unit roots and cointegration before its run in a regression as an "Error Correction Model", which considers both long- and short run equilibrium. The result confirms the short run rate and disposable income as two determinant key factors when it comes to explaining the long run Swedish housing prices, together with other factors such as GDP, household debt and unemployment rate. In the short run, the historical development of housing prices act as a key determinant, but disposable income, short term rate, GDP and household debt are also important explanatory factors. The study shows that the increased income, and the ability to increase household spending, will be reflected in the housing prices. A low loan rate will concurrently make it possible for more households than ever to loan at a market with an already very restricted housing supply

Residential property price premia (‘premia’) have long fascinated investors, particularly in times of euphoria, but their social, climatic and urban ramifications are much wider. A proper understanding of premia is hindered by the variety of exogenous influences determining them. They occur within idiosyncratic, complex, and continuously reconfiguring metropoli, conditioned by topography, history, regime, commerce, and culture. Given imperfectly competitive housing markets, conventional explanations for premia are either restricted to their financial dissection, trawl though metrics or cast around for hedonic coefficients. However, premia illuminate affordability and other problems in the broader planning and social debate. With the general significance of premia clarified, the research question of the project becomes: ‘What drives residential property price premium evolution in a metropolis?’ A complete answer involves dissecting the nature and establishing the location of putative premia and disentangling the influence and interactions of their various price drivers. To provide it, the project conducts a property and urban literature review. Based on theory’s insight that higher order contains lower order systems, it develops and investigates a general systems model of residential premia with two modes. The system is conditioned by ideology but forced by population and capital inflows. Within it, premia mutate, influenced by a nested hierarchy of more or less contaminated information. To investigate the model and its different modes, the project employs tests across system pointers, at the macro, meso (all urban) and micro spatial resolutions. First, the turbulence and permeability of residential property markets to exogenous influences is assessed. The project then looks at the urban mosaic in the growing Sunbelt migration city of Brisbane, Australia, over the boom period from 1998-2004. Locally, it conducts a case study and survey in one micro-location, seeking clues in transaction patterns (output), property system agents (components) and the information they use (feedback mechanisms). Finally, the project draws some relevant policy implications. Its key findings are that urban housing markets are open, complex and polarised. In an exuberant economic climate, migration and debt fuel metropolitan price escalation. Public urban initiatives reinforce central incumbent affluence or spark fresh bouts of speculation. Individual premia are heterogeneous but often feed off local construction projects or iconic refurbishment. Reflecting their demographics and motives, agent risk appetites are diverse although investors are usually less averse to renewal. System feedback involves a congruence of media and local activity signals. Neither local conviviality nor Bohemian influences are, by themselves, significant. Rather, buyer rationality is validated by post-purchase infrastructure completions. The thesis of this project is, hence, that in euphoric capital markets, migration and debt accelerates the endogenous mutation of property from homes within a community towards speculative paper assets. The implication is that the excessive proliferation of premia indicates economic imbalance and urban malaise which requires recognition and treatment. While premia are paid for perceived privilege or prospects, cognitive risk representations and expectations evolve. Sometimes judgment is contaminated by media fantasy but often validated by accommodating government policy and central revitalisation projects. Yet, within a wider social and ecological remit, rampant premia suggest flaws in urban strategy, governance and planning practice. In terms of windfall events or unearned rent, the cumulative effects of ill-considered projects and price distortions can be ugly and wasteful. They alienate and accentuate spatial privilege without generating sustainable jobs. The project has procedural and substantive policy implications. The dynamics of residential premia cannot be disentangled from capital market volatility, urban fragmentation and reconstitution. Enlightened property development requires visionary urban planning beyond electoral cycles. Rather than unregulated markets or disjointed incrementalism, the project points to the advantages of cohesive projects and inclusive hubs. It impels ecological and people-focused development to nurture capable, connected and considerate edge communities. Its first steps are theoretical recognition, policy clarification, government reform, market constraints, price and tax rationalisation and spatial transparency.

This thesis analyzed and estimated the impact of the March 1, 2018 loan to income amortization requirement on residential real estate prices in Sweden. A four variables vector autoregressive model (VAR) was used to study the relationships between residential real estate prices, GDP, real mortgage rate and consumer price index over a time period from 2005 to 2017. First, a structural vector autoregressive (SVAR) model was used to test how a structural innovation in the error term for real mortgage rate affected residential real estate prices. Secondly, an unconditional forecast from our reduced VAR was produced to estimate post 2017 price growth of the Swedish housing market. The impulse response function results stand in contradiction to economic intuition i.e. the price puzzle problem. The unconditional forecast indicates that the housing market will enter a period with slower price growth post 2017, which are in line with previous research. This thesis vector autoregressive model can give meaningful results with regard to trend forecasts but with regard to precise statements as anticipating drastic price depreciation, it falls short. We recommend the use of reduced VAR forecasting with regard to the Swedish housing market.

Un nombre importants de défauts de prêts immobiliers ainsi que l'eff ondrement du march é immobilier ont entraî n é la faillite de plusieurs banques d'investissement aux Etats Unies. Ces facteurs ont aussi d éclench é la derni ère crise fi nanci ère. Ces év énements ont donné lieu à un pan de travaux cherchant à expliquer les facteurs d éterminant les d éfauts simultan és des prêts immobiliers. Cette th èse apporte des preuves suppl émentaires montrant l'importance de la d épendance des d éfauts lors de la gestion des portefeuilles des prêts immobiliers. Cette th èse comporte trois chapitres identifi ant les facteurs cl és d éterminants la d épendance des d éfauts de prêts immobiliers et des prix immobiliers. Nous montrons que mesure plus pr écise du risque de cr édit est possible en tenant compte des facteurs mentionn ées ci-dessous. Dans le chapitre 1, nous analysons la variation de la dépendance de 13 indices de prix r égionaux. Nous estimons une chaîne de Markov cach ée multivari ée avec deux r égimes équid epéndants. Nous mod élisons la probabilit é de transition en utilisant la croissance du taux d'int érêt, et du rapport prêt-valeur. Nos r ésultats montrent que la d épendance r égionale moyenne des prix immobiliers varie dans le temps. De plus cette d épendance est li ée an changement du taux d'int érêt et au rapport prêt-valeur. En consid érant un sous- échantillon de r égions m étropolitaines, nous montrons aussi qu'une baisse du rapport prêt valeur est associ ée à une plus forte probabilit é d'être dans un r égime de forte d épendance d écrite par une copule en arborescence canonique. Dans le Chapitre 2, nous utilisons une vraisemblance composite de copule (composite likelihood copula), et une fonction Mat érn, nous analysons la d épendance de d éfaut par paires d'un ensemble de prêts immobiliers titris és, a haut risques (subprime mortgages), provenant de la r égion de Los Angeles, entre 2000 et 2011. Nos r ésultats montrent que la d épendance des d éfauts est aff ect ée par la distance g éographique entre les prêts, la moyenne et la di fférences dyadiques de variables telle que le rapport prêt-valeur, le cr édit scoring FICO et le revenu au niveau l'arrondissement. De plus nous identifi ons un eff et de contagion o u un indice de changement des prix immobiliers r égionaux n égatifs et un haut taux de d éfauts augmente la d épendance des d éfauts. En fin notre mod èle donne une bonne estimation de la Value at Risk du nombre de d éfauts dans un bloc de prêts titris és. Dans le chapitre 3, nous analysons l'éfficacit e d'un portefeuille de prêts immobiliers titris és à haut risque (subprime). Nous estimons l'ésp erance et la variance des rendements en utilisant des probabilit e de d éfauts obtenu a partir d'un mod èle de d épendance de d éfaut par paires. Nous analysons les 13 plus larges bloc de prêts immobiliers, titris és entre 2001 et 2005. Nos r ésultats montrent que la diversi cation des blocs de prêts n' étaient pas optimale. De plus, nous montrons qu'il est possible de d'avantage diminuer le risque associ é bloc de prêts en tenant compte des risque non g éographique. / The high number of mortgage defaults along with the collective collapse in regional house prices have led to bankruptcies of Wall Street investment banks and triggered the last financial crisis. This phenomenon have led to a growing body of research seeking to understand how such mortgage defaults tend to occur together. This thesis adds to the body of evidence that dependence between mortgages as well as house prices needs to be seriously taken into consideration in managing the risk of mortgage pools. This thesis consists of three chapters that focus on identifying the factors affecting the dependence between house prices and mortgage defaults. We show how less risky mortgage portfolios can be constructed if we consider the factors mentionned below. In Chapter 1, we analyze time variations in the dependence of 13 regional house price indices. We estimate a multivariate hidden Markov copula model, with two equidependent regimes, and we allow the Markov transition probabilities to vary with changes in interest rates and leverage, measured by the Loan to value ratio (LTV). Our results provide evidence of time-variation in the average dependence in regional house prices. Besides they shows that house price dependence is strongly related to leverage and changes in interest rates. In addition, using a reduced set of Southwestern metropolitan statistical areas (MSAs), we further show that a decrease in leverage is associated with a higher probability of being in an asymmetric high dependence regime, described by a canonical vine copula. In Chapter 2, using a composite likelihood copula approach and a Mat'ern function, we analyze the pairwise dependence of defaults within a set of securitized subprime mortgages originated in Los Angeles between 2000 and 2011. Our results show that default dependence is affected by geographic proximity, as well as dyadic averages and differences in a number of mortgage-specific and local economic variables, such as FICO credit scores, Loan to Value (LTV) and zip code level income. In addition, we find evidence of a contagion effect, whereby negative local house price index returns and high lagged default rates increase default dependence. Our pairwise dependence model also delivers good estimates of Value at Risk for the number of defaults in a pool of mortgages. In Chapter 3, we analyze the mean variance efficiency of pools of securitized subprime mortgages. We estimate the means and variances of the returns from the default probabilities derived from a multinomial logit and a copula-based pairwise default dependence model. We examine the 13 largest mortgage pools that were securitized between 2001 and 2005. Our results first show that the mortgage portfolios were not optimally diversified. Secondly considering non-geographic risk factors leads to less risky optimal portfolios.

Cette thèse comprend quatre essais en macroéconomie internationale et théorie monétaire. Elle est constituée de deux parties. Les deux premiers chapitres, coécrits avec François Geerolf, étudient les conséquences macroéconomiques des cycles immobiliers sur les comptes courants (chapitre 1) et sur les dynamiques de l'emploi (chapitre 2). La seconde partie de cette thèse s'intéresse aux conséquences des récentes transformations intervenues dans les systèmes bancaires sur les mécanismes de la création monétaire. Ces transformations semblent en effet conduire à une privatisation de la monnaie. Le chapitre 3 étudie empiriquement la réalité d'une telle privatisation. Je développe dans le chapitre 4 un modèle pour analyser les conséquences de ces transformations sur la création monétaire et sur les mécanismes de propagation du risque. / This thesis includes four essays in international macroeconomics and monetary theory. It is divided into two parts. The two first chapters, coauthored with François Geerolf, investigate the macroeconomic consequences of housing cycles on current accounts (chapter 1) and employment dynamics (chapter 2). The second part of this thesis studies the consequences of modern banking features on money creation mechanisms, notably with the development of private payment arrangements and the globalization of banking. Chapter 3 looks at the issue empirically. In chapter 4, I develop a model to investigate the consequences of these modern banking features for the provision of money and for risk propagation mechanisms.

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.

This dissertation focuses on Austrian housing policy measures and regional housing markets. It places the Austrian situation into a European context and evaluates singular housing policy measures in detail. The evaluation includes aspects of effectiveness, equity, costs, and efficiency. This contribution brings together three empirical essays, each of which has a different focus and addresses particular elements of housing policy. All three papers use empirical methods, but with adjusted approaches according to their underlining research questions: from state finance comparisons, to subsidy calculations for specific households, to hedonic apartment price index construction. Quantitative methods, mainly based on administrative and survey data, are accompanied by qualitative research in the form of expert interviews. Across the three papers, the level of analysis differs and increases in focus: from the level of nation states, to the nine Austrian regions, to the 117 (as of 2015) administrative districts into which the Austrian territory is divided. The first two papers focus on state housing policy measures and evaluate them in an international comparative framework. Both follow different levels of aggregation. The first one takes a very broad view and quantifies the sum of expenses on various state housing policy measures in six EU countries at the level of nation states (Austria, Czech Republic, Great Britain, France, The Netherlands, and Spain). It investigates the structure of state support for the housing sector and establishes numeric estimates of its components (supply-side subsidies, housing benefits, tax advantages and concessions). The second paper focuses on a particular housing policy instrument in Austria: means-tested, income-dependent housing benefits. It analyses the nine regional housing benefit schemes in the context of minimum income schemes. The paper applies a comprehensive residual income approach to housing affordability and identifies market segments and household types where affordability is at risk, in spite of existing benefit schemes. The third paper calculates regional price indexes for second-hand apartments in Austria at the level of administrative districts. It is based on state-of-the-art hedonic methods of house price index construction that control for the varying distribution of apartment characteristics and locations over time. The resulting indexes are an important improvement over indexes based on average prices. All three papers address specific elements of Austrian housing policy and identify areas for policy improvements and necessary future research activity.

This thesis investigates if house price prediction models perform better when adding macroe- conomic features to a data set with only house-specific features. Previous research has shown that tree-based models perform well when predicting house prices, especially the algorithms random forest and XGBoost. It is common to rely entirely on house-specific features when training these models. However, studies show that macroeconomic variables such as interest rate, inflation, and GDP affect house prices. Therefore it makes sense to include them in these models and study if they outperform the more traditional models with only house-specific features. The thesis also investigates which algorithm, out of random forest and XGBoost is better at predicting house prices. The results show that the mean absolute error is lower for the XGBoost and random forest models trained on data with macroeconomic features. Furthermore, XGBoost outperformed random forest regardless of the set of features. In Con- clusion, the suggestion is to include macroeconomic features and use the XGBoost algorithm when predicting house prices.

Increasing urbanization in the US is leading to development or re-development of lands adjacent to solid waste facilities and these lands are being considered for residential communities and commercial projects. Thus, the potential for nuisance complaints against the pre-existing solid waste facility operations has become an increasing reality. The objective of this study was to develop a methodology to gather scientific and quantifiable data related to potential nuisances caused by landfills to determine setbacks and buffer zones near landfill and transfer station operations. Appropriate recommendations for these setbacks were made from case studies conducted at two landfills in Florida. The study involved making measurements related to odor, noise, litter and dust. Impact on housing prices was also evaluated by analyzing publicly available house price data. In this study volatile organic compound (VOC) concentration was used as a surrogate measure for gaseous impacts. The mass flux of VOCs was measured on the landfills using the dynamic flux chamber method. The ultimate purpose of flux measurements was to provide input data for dispersion modeling to analyze the extent of odor impact around the landfills, which is outside the scope of this study. Ambient measurements were also made around Landfill A for validating the dispersion model. Although there are no significant health and odor impacts caused by the landfill, higher background concentration extend 1.2-1.5 km from the landfill center on the Southeast side of the landfill. Litter from the road sides around the landfills was collected and catalogued based on size and material type. Litter count per site obtained for both landfills was less than the 2001 and 2002 state-wide counts. The difference was statistically significant. Noise measurements were made at landfills during incineration and landfilling. Based on average measurements (Leq) obtained at various distances from WTE facility and landfilling activity, and considering EPA recommended noise level of 55 dB(A) for a quiet neighborhood, a set back distance of 1.6-1.9 km was recommended. Impact on house prices near the landfills was done for four landfills in Florida. Analysis showed that three out of four landfills had significantly impacted the house price within 0.6-0.8 km from the edge of the landfill. Dust measurements were made at Landfill B using particulate samplers, quantifying the dust associated with landfilling. Measured values were below National Ambient Air quality Standard (NAAQ) for PM10. Finally, recommendations were developed to mitigate some of these nuisances

The relationship between debt and income is an indicator in the stability for households to face certain external shocks. A large debt to income will be costly if interest rates are high. This thesis will analyze the relationship between other economic factors regarding debt to income. Since monetary policy affects inflation and interest rates, analyzing their relationship with debt to income will give insight how they correlate. By using quarterly data over a period between 1987 and 2022, the regression model shows the largest positive correlation is between debt to income and house prices. Where inflation and unemployment have the two weakest correlation, both are negative, however, inflation becomes acceleration in inflation due to the transformationin percent. This meansthat the effect is displaying acceleration growth rather than one unit change.The negative relationship will result in a deceleration of growth regarding debt to income due to an increase in inflation which according to our study has a positive impact on the stability of the mortgage market in the short run.