This dissertation analyzes the complex relationships between language, immigration, and labor and housing market outcomes. First, I model the urban labor market as segmented by language barriers. The prediction of this segmentation theory is confirmed by Canadian Census data, which allow me to identify a worker's labor market segment by her work language. Second, I explore whether the housing market reflects people's willingness to pay for higher quality social-ethnic interactions. By combining housing transaction data and Census information, I am able to test such a relationship with positive results. Finally, I ask what properties housing price series have if some people have better knowledge of the future immigration/migration flows to a city. Under this setup, the price series become serially correlated and the price volatility varies over time. The model also explains the long-standing price-volume relationship in housing transaction data.

This dissertation analyzes the complex relationships between language, immigration, and labor and housing market outcomes. First, I model the urban labor market as segmented by language barriers. The prediction of this segmentation theory is confirmed by Canadian Census data, which allow me to identify a worker's labor market segment by her work language. Second, I explore whether the housing market reflects people's willingness to pay for higher quality social-ethnic interactions. By combining housing transaction data and Census information, I am able to test such a relationship with positive results. Finally, I ask what properties housing price series have if some people have better knowledge of the future immigration/migration flows to a city. Under this setup, the price series become serially correlated and the price volatility varies over time. The model also explains the long-standing price-volume relationship in housing transaction data. / Business, Sauder School of / Graduate

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This dissertation consists of three essays on housing and macroeconomics. The first chapter documents cross-country evidence on house prices, rental prices, and consumption volatility, especially, by focusing on comparison between emerging country group and rich country group. The second chapter develops a theoretical model framework for small open economy with housing and housing rental markets, and investigates how the model explains the empirical regularities documented in the first chapter. The third chapter discusses the excess consumption volatility observed in emerging countries using higher house price volatility in those countries through a theoretical model. In Chapter 1, I address business cycles in emerging economies exhibit both greater volatility of housing prices and relative consumption compared to business cycles in rich countries. This chapter provides evidence of a positive relationship between housing price and relative consumption volatility across countries. Furthermore, I suggest new stylized facts when housing and non-housing consumption are disaggregated: first, housing consumption is more volatile than non-housing consumption in emerging countries; and, second, even after controlling for housing consumption volatility, non-housing consumption in emerging economies is still more volatile than that in rich countries. In order to investigate the above empirical regularities, this chapter tries to figure out what is different between two country groups in terms of fundamental related to housing, by focusing on homeownership rates and housing rental market characteristics. In Chapter 2, I explore the linkage between house prices and aggregate consumption volatility by building a business cycle model of a small open economy with both housing and rental markets. While housing consumption, as measured through rental prices, is a non-negligible portion of total consumption, the role of the rental market has largely been overlooked in studies of consumption volatility. By explicitly modeling separate housing and rental sectors, this chapter is able to explain some new stylized facts suggested in the first chapter. Simulation results suggest that cross-country variation in the volatility of shocks to credit prices and availability is a driving force in generating the observed relationship between house price and relative consumption volatility. The model also suggests that a financial friction stemming from constraints in housing-collateralized credit can explain excess non-housing consumption volatility in emerging countries, while rental market frictions may account for the greater housing consumption volatility observed. In Chapter 3, I mainly discuss the causal effect of exogenous house price shock in explaining the excess consumption volatility puzzle observed in emerging countries. Specifically, first, this chapter compares the impulse responses of house price shock and income shock to show that house price is more relevant factor in understanding consumption fluctuation, and then analyses homeowners’ and renters’ behavior to figure out how the house price shock transmits to each agent’s consumption. As a result, given the highly volatile house prices in emerging economies, I show that homeowners play an essential role in amplifying the effect of house price fluctuations on consumption fluctuations through a simplified theoretical model. Therefore, this chapter argues that higher house price volatility in emerging countries leads to their excess consumption volatility.

This paper examines the impact of confirmed shootings on the attractiveness of a neighborhood, measured through local housing prices, in Sweden’s major metropolitan areas during 2016-2019. A novel difference-in-differences approach is proposed where control groups are selected from areas that will be exposed to shootings in the near future but have not yet been so, thus mitigating the problem from previous studies that shootings might be a result of underlying unobserved factors for the neighborhood. The results are inconclusive overall apart from Uppsala, where the estimate is negative and significant, indicating a 4.8 percent drop in nearby housing prices after a shooting. Multiple alternative specifications are used to test the robustness of the results. Overall, the negative estimate for Uppsala seems quite stable, whereas the estimated impact in other regions remains insignificant. One potential explanation could be that gun-violence is a rather new phenomena in Uppsala relative to the other regions, which could make the effect of a shooting in Uppsala more pronounced. A consideration for policy makers may then be that programs aiming to reduce gun-violence will have a larger economic impact in areas where shootings are a relatively new and arising problem.

iv Abstract As real estate is an important part of the wealth composition of households, this the impact of the financial stimulus that was observed throughout 2020 and how it might have affected housing prices in various European countries. For this the thesis runs a Vector Error Correction Model with the following independent variables: population, exchange rate, inflation, short-term interest rate, unemployment rate and the compensation of employees. The time frame for this regression is restricted to 2000Q1 to 2019Q4 in order to exclude the housing price development throughout 2020 that is already affected by the financial stimulus. These regression results are then used in combination with the 2020 actuals of all independent variables to approximate the expected housing price without financial stimulus. This gives an indication of a potential overpricing in the markets and provides an understanding of how financial stimulus might be connected to housing prices. Another analysis in this thesis then provides an understanding of the leader-follower relationship of housing prices and rental prices and provides an analysis on how this might be connected to the level of home ownership in a particular market. JEL Classification F62, J11, R30 Keywords Real Estate, Covid-19, Financial Stimulus Title The effect...

published_or_final_version / abstract / toc / Real Estate and Construction / Master / Master of Science in Real Estate and Construction

published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy

Chan Yin-Sze. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 37-41). / Abstracts in English and Chinese. / Chapter 1. --- Background Introduction --- p.P. 1 / Chapter 2. --- Literature Review --- p.P. 3 / Chapter 3. --- Methodology --- p.P. 8 / Chapter 4. --- Data Description --- p.P. 10 / Chapter 5. --- Empirical Results --- p.P. 20 / Chapter A. --- Simple Linear Regression Model / Chapter B. --- Robustness / Chapter C. --- "Regression by running Physical, Location & Macroeconomic Factor Separately" / Chapter 6. --- Comparison with the Previous Literatures --- p.P. 34 / Chapter 7. --- Conclusion --- p.P. 36 / Chapter 8. --- Reference --- p.P. 37 / Chapter 9. --- Tables & Figures --- p.P. 42 / Chapter 10. --- Appendix --- p.P. 65

經歷十三年風雨，香港樓價再創歷史新高。有云：「禍兮福所倚」，業主得益於財富增長的同時，亦擔心高速增長埋下泡沫爆破的伏線。因樓價高企，年青人置業困難，社會不滿亦日漸升溫。 / 在國際貨幣基金組織出言警告後，香港金融管理局連同財政司相繼推出措施如額外印花稅，以及收緊不同物業種類的按揭上限，希望保持樓市健康及穩定發展。一石激起千重浪，政策推出後輿論不絶，但至今仍未有人以嚴謹的邏輯推論分析新政策的影響。本文以Stein (1995)的模型作藍本，稍作修改，以分析新政對樓價的影響。 / 按照文中模型計算，於當前經濟環境下，新措施確能維持樓市健康及穩定發展。額外印花稅能壓抑樓價時，收緊不同物業種類的按揭上限能保持樓價平穩。理論模型同時指出，兩樣政策都不是萬能丹，政府於調控樓市時應先評估當前經濟基礎，否則有機會事與願違。 / House price in Hong Kong is reaching its historical high. People start to worry a sudden drop of house price as what they had experienced in year 1997. Social disputes emerged and the Hong Kong government has taken several measures in reaction. Policies such as the Multi-down payment constraint by the HKMA and special stamp duty by the Financial Secretary are implemented in response to the soaring house price. The Media and the general public are keen to explore the effects and the consequences of the policies. However, little effort has been done to study the impact of the enacted policy in a systematic way. / This thesis augmented the model developed by Stein (1995) to examine the housing price behavior of Hong Kong. Simulation results justified the government’s policies. SSD helps to lower the house price while multi-down payment policy helps to stabilize the house price. However, for the policies to be effective, the government needs to spend a lot of efforts to examine the underlying economic fundamentals to avoid unintended results. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wong, Long Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 53-54). / Abstracts also in Chinese. / Abstract --- p.i / 擇要 --- p.ii / Acknowledgement --- p.iii / Chapter 1. --- Introduction --- p.1 / Chapter 2. --- Hong Kong’s Post-Tsunami Economic Background --- p.4 / Chapter 3. --- Characteristics of the Hong Kong Residential Property Market --- p.7 / Chapter 3.1. --- Price and Transactions --- p.8 / Chapter 3.2. --- Market Structure --- p.10 / Chapter 3.3. --- Mortgage Financing --- p.11 / Chapter 4. --- Policies Launched --- p.11 / Chapter 4.1. --- Increasing supply --- p.12 / Chapter 4.2. --- Combating speculation --- p.12 / Chapter 4.3. --- Preventing excessive expansion in mortgage lending --- p.13 / Chapter 4.1. --- To enhance the transparency in the market --- p.13 / Chapter 5. --- Literature Review --- p.14 / Chapter 6. --- Choice of Model --- p.17 / Chapter 7. --- The Stein’s Benchmark Case --- p.19 / Chapter 7.1. --- General Form --- p.20 / Chapter 7.2. --- The Log Linear Form Utility --- p.22 / Chapter 8. --- The SSD Case --- p.23 / Chapter 8.1. --- General Form --- p.23 / Chapter 9. --- The Multi-Down Payment Case --- p.25 / Chapter 9.1. --- General Form --- p.25 / Chapter 9.2. --- The Stone-Geary Form log Utility --- p.29 / Chapter 9.3. --- The CES Utility --- p.29 / Chapter 10. --- Simulation and Results --- p.30 / Chapter 10.1. --- Choosing the parameter --- p.30 / Chapter 10.2. --- Results using Log Linear Utility --- p.32 / Chapter 10.2.1. --- Changing the SSD --- p.32 / Chapter 10.2.1. --- Changing the down payment requirement γ --- p.33 / Chapter 10.2.3. --- Changing the threshold in multi-down payment case --- p.35 / Chapter 10.2.4. --- Changing ý --- p.36 / Chapter 10.2.1. --- Changing the fundamental --- p.37 / Chapter 10.3. --- Results using Stone-Geary form Utility --- p.38 / Chapter 10.3.1. --- Changing the degree of necessity --- p.38 / Chapter 10.3.2. --- Changing SSD --- p.39 / Chapter 10.3.3. --- Changing the down payment portion γ --- p.39 / Chapter 10.3.4. --- Changing the down payment portion ý --- p.40 / Chapter 10.3.5. --- Changing the fundamental --- p.41 / Chapter 10.4. --- Results using CES form Utility --- p.41 / Chapter 10.4.1. --- Changing the elasticity of substitution by --- p.42 / Chapter 10.4.2. --- Changing SSD --- p.42 / Chapter 10.4.3. --- Changing the down payment portion --- p.43 / Chapter 10.4.4. --- Changing the down payment portion --- p.44 / Chapter 10.4.5. --- Changing the fundamental --- p.45 / Chapter 10.5. --- Summary of the results and policy implications --- p.45 / Chapter 11. --- Conclusion --- p.48 / Chapter 12. --- Tables and Charts --- p.49 / Chapter 13. --- References --- p.53 / Chapter 14. --- Appendix --- p.54