The price of real estate is the result of economical operation and, most importantly, regulation mechanism of resource distribution for real estate industry. Since the process of economic reform began in 1978, there have been several times that the Chinese government imposed contractive measures intended to slow down the economic growth. This paper applies insights from economic theory to explain recent housing price patterns in China’s four largest metropolitan areas. (Beijing, Shanghai, Shenzhen and Guangzhou) and discusses how the Chinese Government’s stance and policy affect the development of real estate. By examining the degree of impact on the housing market as a result of Macro Control Measures, excluding other housing market drivers; the empirical results revealed the degree of effectiveness by the Chinese Government administrative control over the housing market vary across the regions.

This dissertation consists of two essays. The first essay focuses on developing a quantitative theory for a small open economy dynamic stochastic general equilibrium (DSGE) model with a housing sector allowing for both contemporaneous and news shocks. The second essay is an empirical study on the macroeconomic forecasting using both structural and non-structural models. In the first essay, we develop a DSGE model with a housing sector, which incorporates both contemporaneous and news shocks to domestic and external fundamentals, to explore the kind of and the extent to which different shocks to economic fundamentals matter for driving housing market dynamics in a small open economy. The model is estimated by the Bayesian method, using data from Hong Kong. The quantitative results show that external shocks and news shocks play a significant role in this market. Contemporaneous shock to foreign housing preference, contemporaneous shock to terms of trade, and news shocks to technology in the consumption goods sector explain one-third each of the variance of housing price. Terms of trade contemporaneous shock and consumption technology news shocks also contribute 36% and 59%, respectively, to the variance in housing investment. The simulation results enable policy makers to identify the key driving forces behind the housing market dynamics and the interaction between housing market and the macroeconomy in Hong Kong. In the second essay, we compare the forecasting performance between structural and non-structural models for a small open economy. The structural model refers to the small open economy DSGE model with the housing sector in the first essay. In addition, we examine various non-structural models including both Bayesian and classical time-series methods in our forecasting exercises. We also include the information from a large-scale quarterly data series in some models using two approaches to capture the influence of fundamentals: extracting common factors by principal component analysis in a dynamic factor model (DFM), factor-augmented vector autoregression (FAVAR), and Bayesian FAVAR (BFAVAR) or Bayesian shrinkage in a large-scale vector autoregression (BVAR). In this study, we forecast five key macroeconomic variables, namely, output, consumption, employment, housing price inflation, and CPI-based inflation using quarterly data. The results, based on mean absolute error (MAE) and root mean squared error (RMSE) of one to eight quarters ahead out-of-sample forecasts, indicate that the non-structural models outperform the structural model for all variables of interest across all horizons. Among the non-structural models, small-scale BVAR performs better with short forecasting horizons, although DFM shows a similar predictive ability. As the forecasting horizon grows, DFM tends to improve over other models and is better suited in forecasting key macroeconomic variables at longer horizons.

This thesis deals with the evolution of prices in the housing market within the Czech Republic. The model of capital stock was used for this purpose. The factors that affect the price evolution were the size of income, the size of the first time buyer population, and the anticipated VAT change on new housing. Various evolution scenarios were presented under various conditions. Housing market in the Czech Republic as a whole and the market in the capital particularly were considered. In the case of the Czech Republic both real and simulated prices reached their peak in 2009, simulated price was 7 % lower than real. Concerning Prague, the real price peak happened in 2008, while the estimated price was 19 % lower compared to real prices.

In a historical view, house prices have developed at the same rate as inflation. In the end of the 20th century the prices on the housing market started to differ from the inflation rate, and today the deviation is strong and the real price increase has been very strong. The financial crisis in 2008, which was a result of a subprime mortgage crisis on the American real estate market, has made several agents on the housing market in Sweden question today’s prices. Robert Schiller, an American economist who predicted the mortgage crisis in 2008, claimed during the Nobel Prize ceremony 2013, that Sweden shows signs of a financial bubble – "I think that people here in Sweden have an illusion that increasing prices is a lasting trend, but that is more suggestive of a bubble". Sweden has been in a recession for the last years, which has led to low interest rates and beneficial conditions on the real estate market. Despite the high unemployment and the recession, prices on the housing market in Stockholm County have continued to increase. This bachelor thesis aims to analyze the housing market in Stockholm County and investigate if there is a price bubble or not, or if the high prices can be explained by fundamental factors. The Thesis suggests that there is no price bubble on the housing market in Stockholm County. The increasing prices are based on fundamental factors, such as low interest rate, low supply on the housing market in combination with an increasing demand. Therefore it is unlikely that there is no existing pricing bubble on the housing market in Stockholm County.

Shopping malls, as an important type of commercial facilities, are growing dramatically.They have gradually become one of the most dominant factors that can influence people's daily life as well as a city's economic development. People's willingness to pay for dwellings is also primarily associated with the surrounding commercial layout.Hence, it is of interest to find out more from a quantitative perspective on the relationship between shopping malls and housing prices. This study aims to analyzehow the prices of condominiums will be affected by the proximity of shopping malls.Two aspects are considered and examined in the empirical study, namely a proximity to the shopping mall, and the number of shopping malls within 3 kilometers radius. Wetry to examine if there is any price premium for those apartments near the shoppingmall or with more shopping malls in the neighborhood. In this empirical study, 36shopping malls in different locations in the county of Stockholm, Sweden, is utilized.The sample of transactions consists of 336,914 apartments. By using regression analysis, based on the traditional hedonic model, the results show that there is an inverse relationship between the apartment prices and its distance from the shopping mall while the number of shopping malls is positively correlated with apartment prices. / Köpcentra som en viktig typ av kommersiella anläggningar växer dramatiskt dessa år. De har gradvis blivit en av de mest dominerande faktorerna som kan påverka människors vardag och en stads ekonomiska utveckling. Människors villighet att betala för husen på marknaden är också till stor del kopplad till den omgivande kommersiella utformningen. Därför är det nödvändigt för oss att ta reda på mer i ett mer kvantitativt perspektiv om förhållandet mellan köpcentra och bostadspriset. Denna studie syftar tillatt diskutera hur priset på bostäder kommer att påverkas av köpcentra. Två aspekter beaktas och undersöks under en empirisk studie, som är närheten till köpcentret och den andra är antalet köpcentra inom 3 km avstånd. Målet är att avslöja om det finns något prispremie för dessa fastigheter nära köpcentret eller med fler köpcentra i närheten. I denna empiriska studie tas 36 köpcentra på olika platser som prov i Stockholms län, Sverige. Sedan kommer transaktionsdata där proverna består av 336,914 lägenheter behandlas och analyseras i Stata. Genom att använda giltiga transaktionsdata, kombinera med matematiska ekvationer och obligatorisk statistiskkunskap, är syftet med denna studie att beskriva och sammanfatta data för att sedan genomföra regressionsanalys baserat på fyra hedoniska modeller, inklusive både linjär och log-linjär form. Regressionsresultatet är signifikant vid 1% konfidensnivå, vilket innebär att de förklarande variablerna verkligen har betydande effekter på de beroende variablerna. Resultaten visar att det finns en omvänd relation mellan bostadspriset och dess avstånd från köpcentret. Medan antalet köpcentra är positivt korrelerat med bostadspriset.

This paper aims to investigate whether changes in economic sentiment and major policy shifts have had any significant impact on Scandinavian real housing prices relative their fundamental value post year 2000. Fundamental housing price indices for each constituent of the region are estimated from macroeconomic fundamentals in a VAR framework. We then estimate impulse response functions from another VAR to test the effects of survey-based economic sentiment on the fundamental price spread in each housing market. In addition, we investigate how major housing related policies implemented during our sample period have affected the fundamental price spreads in an ARDL framework. The study concludes a substantially undervalued Danish housing market post 2008 and a marginally yet persistently overvalued Norwegian market, whereas Swedish and Finnish housing prices have developed fairly in line with levels motivated by macroeconomic fundamentals. Changes in economic sentiment show limited effect on closing the fundamental price spread in Denmark, but no significant impact on any other housing market considered. The elected policies representing major housing market shifts have had significant negative impact on the real housing price development in Denmark and Norway but not in Finland and Sweden. The policy shift in Finland has significantly yet marginally closed the fundamental price spread during the period investigated. Interestingly, implemented LTV- and DTI caps in Sweden have neither affected real aggregate housing prices nor the fundamental price spread.

1 Abstract This thesis investigates the housing price determinants and possibilities of housing price bubbles in the residential real estate markets of Central and Eastern Europe before and during the economic crisis of 2007-2009. Using data from international institutions, national central banks and national statistical offices three quantitative methods are applied. Price-to-income ratios suggest housing price bubbles that were eliminated during the crisis in three out of five countries covered. Second approach of simple panel data models sheds additional light on housing price bubbles and indicates GDP growth, unemployment and average real wage as the main determinants of housing prices in the region. First indication of severe housing price persistence in CEE is demonstrated by the results of the models as well. More reliable results for housing price determinants are obtained from variance decomposition and impulse response functions of vector autoregression models. Each country is modeled separately and substantial differences exist between the countries. Poland is the only country that does not exhibit housing price persistence and dynamics in Austria are less volatile as compared to the new EU members in the sample. JEL Classification G12, E39, R21, R31, R32 Keywords residential real estate, housing...

Using MSA level data, the paper shows, that geographic areas which experienced the largest housing bubble generally suffered a more serious subsequent economic downturn. More specifically, the paper establishes that MSAs with larger declines in housing permits had larger increases in unemployment. There also appears to be strong evidence of a correlation between the magnitude of a housing boom and the timing of the decline in housing permits. MSAs which experienced larger real housing inflation offered early indications of the subsequent Great Recession.

Shanghai’s residential property prices have been consistently rising for the past decade. Both the municipal and national governments have announced a series of alternately restrictive and encouraging house purchasing policies that aimed at adjusting housing prices. This paper studies all of the policies announced from January 2011 to October 2016. Using residential house price data of houses of different sizes and in different locations, this paper shows that two out of the six restrictive policy events achieved their intended negative impact on housing prices, while two out of four encouraging policy events delivered their intended positive impact. When aggregated, encouraging policies had a significant impact and restrictive policies did not.

2008年5月，在新政府上台後兩岸間經貿往來越來越密切，兩岸間勢必將面對一個新的互動關係，也將對兩岸產業間的互動產生直接及間接的衝擊。在兩岸交流日益活絡的情形下，熱錢湧入，包括陸資、外資、與回流的台商資金等「三資」正悄悄的進入台灣。市場各種訊息顯示，這股錢潮對房市、股市已迅速產生相當的衝擊。在國際資金眼中，台灣已成了佈局大陸大戰略棋局中極優質的選擇，本文研究之目的在於探討兩岸三通後對於台北市房價之影響。 本研究係採用2000年至2009年之信義房屋房價指數資料為樣本，藉由迴歸分析來做實證研究。實證結果顯示，台北市人口總數對於房價變動的影響為負向影響；股價加權指數、平均每人國內生產毛額、台北市消費者物價指數、台北市家庭收支、匯率及兩岸三通等，對於台北市房價均有顯著正向之影響；而台北市結婚對數、勞動力參與率及金融海嘯等，則對於台北市房價的變化無顯著關係。 / As new government inaugurated in May 2008, economic and trade exchanges cross Taiwan Strait became intent. A new and friendly interaction model across the strait was born and it would inevitably cast direct and indirect impacts on business activities of both sides. Hot Money, including Chinese funds, international funds and oversea Taiwanese funds are gradually inflowing to Taiwan. Market statistics show that, this wave of Hot Money has had rapid and significant impacts in property market and stock market. From international investment community’s point of view, Taiwan has become a quality target to deploy into the gigantic market of China. The purpose of this research aims to discuss the impacts Three Links will have impacts on Taipei City property market. This research adapts housing price index from 2000 to 2009 provided by Sinyi Real Estate, using regression analysis to provide empirical studies. Empirical studies show that, population of Taipei city versus housing price alteration is negative correlated, where as TAIEX, GDP, CPI, Family Income & Expenditure, Exchange Rates and Three Links have direct impacts on Taipei City property market. As for Marriages, Labor Force Participation Rate and financial crisis show no significant correlation in Taipei city property market.