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Income Inequality, Rapidly Rising Housing Prices and Overdevelopment of Houses in China

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Income Inequality, Rapidly Rising Housing Prices and Overdevelopment of Houses in China Clemson University TigerPrints All Dissertations Dissertations 5-2017 Income Inequality, Rapidly Rising Housing Prices and Overdevelopment of Houses in China Tao Guan Clemson University, [email protected] Follow this and additional works at: https://tigerprints.clemson.edu/all_dissertations Recommended Citation Guan, Tao, "Income Inequality, Rapidly Rising Housing Prices and Overdevelopment of Houses in China" (2017). All Dissertations. 1902. https://tigerprints.clemson.edu/all_dissertations/1902 This Dissertation is brought to you for free and open access by the Dissertations at TigerPrints. It has been accepted for inclusion in All Dissertations by an authorized administrator of TigerPrints. For more information, please contact [email protected]. INCOME INEQUALITY, RAPIDLY RISING HOUSING PRICES AND OVERDEVELOPMENT OF HOUSES IN CHINA A Dissertation Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Planning, Design and the Built Environment by Tao Guan May 2017 Accepted by: Dr. Thomas Springer, Committee Chair Dr. Elaine Worzala, Committee Co-Chair Dr. James Brannan Dr. James Spencer ABSTRACT Four phenomena can be observed in China’s housing market in the past 16 years. First, the vacancy rate of new condominium properties has increased significantly. Second, housing prices have been increasing very rapidly. In fact, the prices have rarely decreased even when strict housing policies have been mandated. Third, housing transactions are active, as indicated by the new condominiums that have been recently developed and have been sold very quickly. Finally, new construction/development had also been very active. Phenomena 2, 3, and 4 are inherently consistent, but the coexistence of phenomena 2, 3, and 4 with phenomenon 1 is very perplexing. Thus, the following research questions can be raised. 1. How can housing prices keep increasing despite high vacancy rates? 2. How can new condominiums be sold quickly when vacancy rates are high? 3. How can construction activities continue when vacancy rates are high? This is a puzzle. This puzzle is connected with another puzzle, the excessive liquidity in China’s housing market has been oddly coexisting with insufficient demand in China’s consumer market over the past 16 years. The second puzzle can is easily observed even though it has been largely ignored over past 16 years. The following hypotheses are put forward: Hypothesis 1: At a certain time point, higher-income households will spend a lower proportion of their income on consumption compared with lower-income households. If this hypothesis can be verified, then severe income inequality will lead to an overly-high aggregate savings rate and an extremely low aggregate consumption rate; Hypothesis 2: Overly-high aggregate savings rates and extremely low aggregate consumption rates caused by severe income inequality will induce high investment demand in the virtual sector rather than the real sector. As a result, the virtual sector will boom while the real sector will decline. Hypothesis 3: Given a declining real sector, investors will prefer houses as investments as opposed to other assets in the virtual sector due to their unique features. This leads to rapidly rising housing prices and overdevelopment. Testing the three hypotheses above is a big challenge because the typical measure for income inequality for a country, the Gini Coefficient, announced by China’s government is not trustworthy. The data about GDP and per capita disposable ii income are also not reliable. For this research, a significant amount of effort was exerted to collect primary data on these variables. These efforts include establishing rapport with officials in the National Bureau of Statistics of China, obtaining special access to the database of academic and non-profit research institutes and buying data from private institutes in China. Through these efforts, improved quarterly data of GDP, housing policy, and monetary supply for 70 cities from 2000 to 2016 were obtained. The theoretical work in this study includes: First, the economic relationship between income levels and consumption rates, that is, higher-income households will spend a lower proportion of their income on consumption compared with lower-income households, is confirmed by economic data. Moreover, the new economic relationship is explained using Modern Portfolio Theory and information cost. Second, by mathematical proof, it is shown that a more severe income inequality will lead to a higher aggregate savings rate as well as a lower aggregate consumption rate under this economic relationship. Third, a theoretical model further shows that the aggregate savings rate caused by income equality will result in investor’s preference for virtual assets rather than real assets or consumption goods. Fourth, unique feature of houses is found, which can be used to explain why houses are preferred over other virtual assets and why housing bubbles can last longer than speculative bubbles of other virtual assets, such as commercial properties, stocks and mutual funds. The unique feature of housing is that the utility an owner obtains from living in his own house is greater than the utility a tenant gets from living in the same house if it was leased. Therefore, market rents, which are the “price” of the utility a tenant get, does not fully reflect the market fundamentals of a house due to the existence of non-rent utility. As a result, house prices lose the signal for market fundamentals and, in the case of China, have continuously increased in the long term. This is the reason why houses are preferred by investors. Finally, a new measure which we call the Ratio of Gross Domestic Income to Gross Domestic Product (RGG) is built to replace of the Gini coefficient as a measure of income equality. Since, the official data are not trustworthy due to the absence of iii unreported income a, a better measure for income inequality can be obtained. The following is the problem-solving process used to create the new measure. First it is basic fact that the high income level families possess nearly all of the unreported income in China. Therefore, a high proportion of unreported income in total income implies a severe income inequality. Step 2, Gross Domestic Product (GDP) should be equal to Gross Domestic Income (GDI). Hence, when GDI is less than the GDP, the gap between the two statistics represents the unreported income in an economy. As a result, a high Ratio of GDI to GDP (RGG) indicates a severe income inequality. In this way, a new index RGG is built to be used to measure inequality. The empirical study is conducted after the theoretical work and the results show the following: First, for all of the econometric models and for all of the groupings of the 70 Chinese cities, the coefficient of RGG, or our measure for income inequality, is consistently negative. Since a high RGG implies severe income inequality, the negative coefficient shows that the correlation between income inequality and housing prices is positive. In other words, the more severe the income inequality the higher the housing prices will be. Second, for all of the econometric models and for all of the groupings of the 70 Chinese cities, the housing prices are always significantly affected by RGG. The positive correlation between the income inequality and the housing prices is confirmed statistically. Third, in order to show how important income inequality is to the determination of housing prices, the degree of fit (R2) is checked after the independent variables are removed one by one from the econometric models. In all models, we find that the goodness of fit drops the most when the RGG variable is removed. This again shows that income inequality plays the most important role in housing prices. Finally, the coefficient of Housing Policies（X3）is positive, which means the enactment of housing policies is correlated with the high housing prices. This result is counterintuitive because the purpose of restrictive housing policies is to suppress rapidly rising housing prices. But this result is reasonable. On one hand, it is the fact that all housing policies could rarely suppress housing prices in past 16 years iv in China. On the other hand, releasing the housing policies was actually a reaction to the rapidly rising housing prices, and terminating the housing policies is a response to the stagnant or slightly decreasing housing prices. In other words, when housing prices increased rapidly, the housing policies were enacted but rarely served to stop the increasing housing prices. And, when the housing prices were stagnant or decreasing slightly for some reason, the restrictive housing policies were not enacted or were terminated and as a result, the relationship between housing prices and housing policies is was found to be positive in the models. Then the following conclusions are drawn based on the theoretical models and the empirical evidences. 1. At a given point in time, a high-income family will spend a lower proportion of their income on consumption compared with a low-income family. As a result, severe income inequality will lead to very -high aggregate savings rate and very low aggregate consumption rate. 2. Very high aggregate savings rate and very low aggregate consumption rate caused by severe income inequality will induce high investment demand in the virtual sector and weak demand in the real sector. As a result, the virtual sector will progress, whereas the real sector will decline. 3. In the context of a declining real sector, investors prefer houses to other types of assets in the virtual sector owing to the unique features of houses. Thus, housing prices will increase even though there is a high vacant rate, increased new construction and the high transaction volume for the housing construction. Those phenomena are “weird” but can be observed everywhere in China in 2017.
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