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Potential Housing Bubble with Chinese Characteristics: Analysis and Policy Design Through an Operational Model by Xin Zhang

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Potential Housing Bubble with Chinese Characteristics: Analysis and Policy Design Through an Operational Model by Xin Zhang Potential Housing Bubble with Chinese Characteristics: Analysis and Policy Design through an Operational Model By Xin Zhang B.S in Electronics Engineering, Fudan University, 2003 Diplôme d'ingénieur in Conception Engineering, École des Mines de Paris, 2006 M.S. in Urban Studies and Planning and M.S. in Real Estate Development, MIT, 2008 M.S. in Civil Engineering, MIT, 2009 Submitted to the Institute for Data, Systems, and Society in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Engineering Systems at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2018 © 2018 Massachusetts Institute of Technology. All Rights Reserved Signature of Author…………………………………………………………………………………………………… Engineering Systems Institute for Data, Systems, and Society December 31, 2017 Certified by………………………………...……………………………………………………………………………………... Prof. Richard de Neufville Professor of Engineering Systems Institute for Data, Systems, and Society Thesis Committee Chair Certified by…………………...…………………………………………………………………………………………………... Prof. David Geltner George Macomber Professor of Real Estate Finance Dept. of Urban Studies and Planning Thesis Committee Member Certified by……………………………………………………………………………………………………………................. Prof. Siqi Zheng Dept. of Urban Studies and Planning Thesis Committee Member Accepted by……………………………………………………………………………………………………………………….. Prof. Stephen C. Graves Professor, Mechanical Engineering and Engineering Systems Abraham J. Siegel Professor, Management Science Graduate Officer, IDSS 2 Potential Housing Bubble with Chinese Characteristics: Analysis and Policy Design through an Operational Model by Xin Zhang Submitted to the MIT Institute for Data, Systems, and Society on December, 2017 in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy in Engineering Systems Abstract This thesis analyzes the potential housing bubble in the Chinese urban housing market. Using an operational model built on system dynamics (SD), it explores the unique housing market structures, information flows, key agents and their decision-making processes, and the system constraints that may contribute to the bubble forming phenomenon. Its SD models differ from intensive data-driven economic models. They are structural, operational, and focus on causal relationships. They can more easily accommodate non-market features and unique institutional components, where long-range historical data are not readily available. As the Chinese government heavily controls its housing markets, housing prices greatly depend on political decisions. The models incorporate the incentives and decisions of key agents in the market and have predictive power through simulation and scenario analysis. They can thus help decision-makers transform decisions, actively manage risks and opportunities, timely design and implement policies, and consequently change the system from within. This thesis specifically discusses three Chinese-specific features: 1. Rising housing price and the cap rate change; 2. High vacancy rates caused by speculators purchasing multiple housing units as money-storage investments they are unwilling to rent; 3. Land financing schemes where local governments rely on income from land sales to support their budgets which leads them to use their monopolistic position to short- supply the land. The research design starts from the DiPasquale-Wheaton model (D-W) which Western urban economics theory has validated for analyzing housing cycles. It operationalizes this by: 1. Converting the D-W to a basic SD model; 2. Augmenting this with additional generic features; 3. Incorporating unique Chinese market features to create China-specific models; and then 4. Creating an integrated overarching model for conducting a case study using historical data of Nanjing, China. The result is one of the first operational models for the Chinese housing market that has the explanatory mechanisms and somehow overcomes the data availability issues. It provides an intuitive and transparent structure that we can easily modify to address complex issues. 3 The main findings are: 1. The Nanjing case study demonstrates “why and how” the interaction of certain market features can create a significant bubble in housing prices. In particular, it indicates that the land supply component plays a dominant, amplifying role in the system. 2. It shows that under certain policy interventions or crises, the potential bubble may burst and drop prices. 3. Understanding these conditions, policy makers can transform the decision-making processes of key market agents and move toward long-term sustainable development. 4. Although demand side policy interventions are less effective in controlling housing prices than supply side interventions, they are preferable for the social stability. Thesis Supervisor: Richard de Neufville Professor of Engineering Systems Institute for Data, Systems, and Society 4 Acknowledgments I would like to begin my acknowledgement by first thanking my PhD committee. My biggest thank you to my thesis advisor, Richard de Neufville. The coaching and knowledge you provided is invaluable. With my OCD, I always got stuck at the tree level of my research but you always managed to drag me out and fly above the forest to get another view. You got me “nervous” every time before our research meeting but little did you know, earning a praise at the end of a meeting meant so much. I do want to emphasize that you are the most caring teacher a student can dream for. You put the interests of your students in the forefront and work for their best interests. In order to have me concentrate on my thesis, you eliminated my teaching assistant responsibilities, which I honestly really loved. Indeed, the teaching experience you gave me access to has helped me build up my confidence and strengthened my communication skills enormously. Most importantly, you know how to enjoy life beyond academics. You show wisdom, kindness, and guidance to people around you (even with total strangers). Especially, with the help of your bow tie, you can turn on your charm within seconds. You are like a father figure to me and I will always cherish my years working for/with you. I hope that I can be half as wise and healthy when I reach your age. David Geltner, purely by accident, your class on real estate finance was the first class I took at MIT when I was doing my Master’s degree. I was so drawn by the subject that I took on a dual-degree with Center for Real Estate and also wrote my Master’s thesis under your guidance. After working in the industry for three years, you helped me get back to MIT for the PhD program. Your expertise and critiques were of great help at the most critical moments of my research. You are sharp, quick, and energetic. My favorite moments are those spent in your office to scratch out research ideas on the little whiteboard. It was always so useful and you know why? Because every time we took a picture of what we had drawn, and I have a private folder on my computer collecting those pictures along the years. I also want to thank you for being so understanding and being such a good friend that I can talk about almost everything with. When I was frustrated, you helped me to get back to sane over a cup of Dunkin’ Donuts coffee. Siqi Zheng, you were the last to join my committee and at the most crucial moment of my research. You are like the Doraemon () of our team that whenever we need field knowledge, personal connections, or data, you got them. I am so glad that you made the move to teach full time at MIT. It gave us more opportunities to work together. I always tell my friends, when Siqi was at my current age, she was already full professor and department head at the most prestigious university in China. You are intelligent needless to say, but you are also so focused and can stay focused. I also always tell my friends that I crave for 3/5 of your diligence. Because with that, I will also be very successful. I want to thank you for your contributions to my research. You are THE irreplaceable piece of my research world. I am so happy to see the establishment of the China Future City Lab and glad that I could be of some help. David and I always jokingly said that we wonder how much energy and power was stored in your body. 5 My work would not have been possible without the financial support of the two organizations as well as the TA/RA support of Richard de Neufville. The Singapore University of Technology and Design (SUTD), and the Samuel Tak Lee MIT Real Estate Entrepreneurship Lab provided support during my tenure and also supported my extensive travel and research in Asia. Thank you! I would like to thank my peers in the Engineering Systems Division who helped me integrate into the PhD program and provided support during my qualification exam. Special love is sent to my PhD cohorts, along with all the beer, pizza, happy hour, and memories we shared. Many thanks to the laughter brought to me by Ros Sani at SUTD, you rock! Also, many thanks to Beth Milnes, Erica Bates, and Barbara DeLaBarre and everyone else in ESD (or IDSS) who provided support. Hey Beth, not sure how I could survive MIT without your help. One thing I am great at is procrastinating on administrative tasks and simply put, if it were not for you, I would have had to pay thousands of dollars on late registration and other fees. To survive my PhD work would not have been possible without the true love and support from my close friends and my family (yes, you guys are my family). My deepest thank you, in alphabetical order, to Kevin Acorace, Nasos Balios, David Biro, Craig Capone, Jerry Cooper, Brian Chadbourne, Kenny Cho, Greg Eller, Dennis Hall, Chris Leach (who proof read my entire thesis), Steve Norton, Kenny Peabody, Jean Ouellet, Rick Pratt, Dennis Rudder, Gary Streck, Jean-Pierre Villemain, and Roger York. Lastly, thank you Dad and Mom, for everything.
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