Study on Measurement of the Real Estate Bubble in Guangzhou

With the rapid development of the real estate industry, the real estate bubble has attracted more and more attention. Using the efficacy coefficient method, we measure the real estate bubble of Guangzhou city from 2007 to 2016. The results show that from 2007 to 2016, the comprehensive coefficient of the real estate market bubbles in Guangzhou is on alert and worthy of attention.

economic crises are always associated with the collapse of the real estate industry. The real estate industry has made a huge contribution to stimulating economic growth, but the overheating of the economy due to real estate is even more vigilant, which has caused concern about the real estate market bubble. There have been many incidents of bubble economy triggered by the real estate bubble in history.
A bubble is essentially a phenomenon of price movement, a phenomenon in which actual prices severely deviate from the theoretical value, and a real estate bubble refers to the continuous rise in real estate prices caused by factors such as real estate speculation and the market base. Some scholars believe that the real estate bubble is due to real estate developers and buyers having a systemic expectation of future real estate prices, and then adopting speculative behaviors individually, so that real estate prices continue to rise away from the basic value determined by the market foundation. Speculation, expectations, and bounded rationality are still the main reasons for the formation of a real estate bubble (Jiang, 2005). As one of the most developed cities in China, Guangzhou is worthy of attention whether there is a bubble in the real estate market and the extent of the bubble. It is hoped that this research can provide help for our government to effectively control the real estate bubble.
estate bubbles in China mainly includes direct test method, indirect test method, index method, and multivariate statistical method. As the real estate basic value data is difficult to obtain, the applicability of the direct inspection method is limited. The indirect test method can only test the presence or absence of bubbles, and cannot measure its size. At the same time, it is difficult to draw valid conclusions even on the issue of measuring whether there is a bubble, due to the accuracy of the data and the span of the time series. The index method and the multivariate statistical method do not require high time span of data, which can avoid the shortcomings of the direct test and indirect test. The simplicity and easy access to data make it the most important method for measuring the real estate bubble. The index method generally selects several evaluation indicators related to real estate development in production, trading, finance, consumption, etc., to compare the actual value of the indicator with the critical value, that is, the allowable value. If it is less than the critical value, there is normally no bubble. The index method can be divided into single index method, multi-index method and efficacy coefficient method. The single index method uses a single evaluation index to measure the existence and size of a real estate bubble by comparing the difference between the actual index value and the threshold value of the index. For example, Lu Jianglin calculated the housing market bubble levels in China's 35 large and medium-sized cities from 2006 to 2008 using the housing price-income ratio as an evaluation index, and concluded that there was a large bubble in general. The multi-indicator method uses a multi-indicator evaluation system that reflects aspects of production, trading, finance, and distribution to measure real estate bubbles, that is, the multi-indicator method. The multi-indicator method generally selects several indicators in the real estate industry such as production, trading, finance, and consumption to form an evaluation index system, and calculates a comprehensive index of indicators by setting thresholds and weights for different indicators. The power coefficient method generally determines a satisfactory value and an unallowable value for each evaluation index. The satisfactory value is the upper limit and the unallowable value is the lower limit. The degree to which each index achieves a satisfactory value is calculated, and the score of each index is determined by this. Then the weighted average is used for synthesis to evaluate the comprehensive status of the research object. Based on the current research status at home and abroad, this paper selects suitable measurement indicators for the real estate bubble. This article adopts the efficacy coefficient method to measure the real estate bubble in Guangzhou by comparing the difference between the actual index value and the threshold value of the index.
According to the principle of multi-objective programming, the efficacy coefficient method determines a satisfactory value and an unallowable value for each evaluation index, with the satisfactory value as the upper limit and the unallowable value as the lower limit. It calculates the degree to which each index achieves a satisfactory value, and uses this to determine the score of each index, and then integrates them through a weighted average to evaluate the comprehensive status of the subject. The specific steps are: 3) Use the formula to calculate the efficacy coefficient of each indicator. The calculation formula is as follows: 40 60 4) The weighting calculation is performed according to the calculated efficacy coefficient and the weight given to the measurement index to obtain the comprehensive early warning coefficient K of the real estate bubble in the place. The calculation formula is as follows:

Real Estate Investment Indicators
The current investment status of real estate reflects whether the real estate investment is overheating and how the pressure on the real estate bubble will be a warning in advance, so the indicators of real estate investment status can to some extent alert the extent of the real estate bubble.

1) Amount of real estate investment/Social total fixed assets investment
The ratio of real estate investment to total fixed asset investment in the whole society reflects the current market's enthusiasm for real estate investment. This indicator can effectively reflect the rationality of real estate investment in social fixed asset investment. The ratio is too large, indicating that companies are keen to invest in real estate, and a large amount of funds in the society has flowed into the real estate industry, which has led to the overheating of the real estate industry, which reflects the existence of a real estate bubble to a certain extent. The internationally recognized alert level for the proportion of real estate development investment in fixed assets investment in the whole society is 10% (Wang &

1) Commercial housing construction area/completion area
The ratio of the construction area and the completed area of commercial buildings can reflect the supply of the real estate market in the future, and thus reflect the real estate market bubble. The construction area of commercial housing reflects the supply of existing housing in the next one to two years, and the completed area of commercial housing is the performance of real estate investment lagging by one to two years. When the indicator value is large, it means that the real estate supply is too large, which means that the real estate bubble will be larger. Therefore, the satisfaction value of this indicator is set to 3, and the allowed value is 4.

2) Real estate investment/GDP
Completion area/sale area of commercial buildings The ratio of the completed area of commercial housing to the sales area of commercial housing can reflect the supply and demand situation of the real estate market in a certain period. The completed area of commercial housing is a measure of supply in the real estate market, and the sold area of commercial housing is a measure of demand in the real estate market. The ratio of the two can tell the heat and prosperity of the real estate market during this period. This indicator is too large, indicating that the real demand in the real estate market is not as large as the market shows, that is, the larger the real estate bubble. Internationally, this indicator is usually set to 1.0 -1.2, so the satisfaction value of this indicator is set to 1, and the allowed value is 1.2.

Real Estate Price Indicators
This article selects seven indicators. The satisfaction value and allowable value of each indicator are shown in Table 2, and the observed value of each indicator is shown in Table 3.

1) Price-to-income ratio
The price-to-income ratio is designed based on excessive speculative demand in the causes of the real estate bubble, reflecting the relative purchasing power of residents and the affordability of households for the current year. The smaller the ratio, it means that the residents have a strong ability to consume housing. It also shows that the price of real estate is affordable by the income of the residents, and that the development of the real estate market is healthy. The higher the ratio, the lower the ability of residents to pay.  Some scholars believe that the price-to-income ratio is a good indicator of the bubble level in the urban residential market. The reason is that the price-to-income ratio is an index selected according to the causes of the real estate bubble and the actual value of the price-to-income ratio is easy to obtain (Wang & Liang, 2015). Internationally, the reasonable range of house price income ratio is generally between 3 -6. However, according to the actual situation in China, the house price income ratio in most years since 1998 has been above 6 (Wu & Yu, 2007). Some scholars believe that there is a bubble in China's real estate market. However, due to many factors such as the level of national economic development and the actual needs of residents, this international experience data is not applicable to China. According to China's national conditions, the satisfaction value of this indicator is set to 6 and the allowed value is set to 8. The calculation method adopted: the per capita housing area in the city is multiplied by the sales price per unit of commercial housing, which is then compared with the per capita disposable income of urban residents.
2) House price growth rate/GDP growth rate The real estate price growth rate is compared with the economic growth rate to reflect the degree of deviation between the virtual economy and the real economy (Jiang, 2009). The growth rate of real estate prices reflects the trend of housing prices over a certain period of time. If the growth rate of housing prices is much larger than the growth rate of GDP, it indicates that the growth rate of housing prices is too fast and exceeds the development rate of the real economy. The ratio of the two can measure the dynamic change of the growth rate of real estate relative to the real economy, and monitor the trend of real estate economic bubble. Therefore, the index satisfaction value is set to 1 and the non-permissible value is set to 2.
3) House price index growth rate/CPI growth rate The ratio of the growth rate of the house price index to the growth rate of the CPI reflects the attitude of residents to the real estate market. Real estate is used as an asset to maintain the purchasing power of money. The growth rate of the house price index should theoretically be synchronized with the change in the growth rate of the CPI. Exceeding the level of payment that residents can afford reflects the existence of a real estate bubble. Therefore, the satisfaction value of this indicator is set to 1, and the non-permissible value is set to 2.

Determination of Indicator Weights
This article integrates the subjective and objective and objective weighting methods, and adopts the objective entropy weight method and subjective analytic hierarchy process to weight the measurement indicators.

Entropy Method
The entropy weight method is an objective method to determine the weight. Entropy is a measure of the degree of disorder of the system, and information is a For bigger and better benefit indicators: For smaller and better cost indicators: 2) Defining Entropy In a system with m indicators and n evaluation objects, the entropy j H of the i-th indicator can be calculated as follows:

3) Defining Entropy Weight
The entropy weight j W is calculated as follows: The weight of each indicator calculated by the entropy weight method is as shown in Table 4.

Analytic Hierarchy Process
The analytic hierarchy process, or AHP for short, was formally proposed by the American operations researcher Thomas Setty in the mid1970s (Guo, Zhang, & Sun, 2007). Analytic Hierarchy Process (AHP) is suitable for situations where there is uncertainty and subjective information, and analysis is performed in a logical way using experience, insight and intuition.
The analytic hierarchy process includes the following steps: 1) establishing a hierarchical structure model; 2) constructing a pair comparison matrix; 3)

Calculation of Combination Weights
Assuming that the weight determined by the analytic hierarchy process (AHP) is j w′ and the weight determined by the entropy weight method is j w′′ , the combined weight j w of the two methods in Table 5 and Table 6:

Results and Analysis
The measurement results are shown in Table 6 and Table 7. From 2007 to 2016, Guangzhou's economy developed rapidly. The total GDP has increased from 714.03 billion yuan to 19.9544 billion yuan, an increase of 173.7% in 10 years.
Although the GDP growth rate has been reduced in recent years, it has maintained a growth rate of about 8%. In 2007, the per capita disposable income of   Comparing the overall economic development data of Guangzhou with the real estate industry development data, it is not difficult to see that the overall development momentum of the real estate industry far exceeds the overall economic development momentum, which can also prove the importance of the real estate industry as a leading industry that drives the development of the national economy. In addition, the real estate development momentum is rapid.
The real estate investment volume has maintained a high increase almost every year, and a large amount of capital has been invested in the real estate industry.
Comparing the increase in the construction area of commercial housing, the completed area of commercial housing and the sales area of commercial housing, we can make a preliminary judgment on the real estate industry. There may be overheating.

1) Investment in real estate/Investment in fixed assets
The

Foam Index Analysis
From the measurement results, from 2007 to 2016, the measured value K of the foam degree was higher than 60 in four years, which were 2007, 2008, 2009, and 2013, and the remaining six years were in the range of 60 -100. According to the judgment criteria of the bubble early-warning evaluation system, the K value was in a safe range in 2007, 2008, 2009, and 2013, and  a strong attractiveness to funds. In addition, Guangzhou has a huge market potential as a first-tier city. A large amount of investment funds came, the market showed a rapid development trend, the "property market fever" appeared, the bubbles of high housing prices gradually increased, and the real estate market 2) In addition to the bubble's comprehensive measurement coefficient rising to a safe value of more than 60 in 2013, Guangzhou's real estate market continues to face foaming risks after 2009, of which Guangzhou's real estate bubble was the worst in 2012.
3) As a whole, Guangzhou's real estate market is on alert, the market is facing the risk of foaming, and there is a possibility of further increase, and precautions are needed. 4) Facing the possible bubble risk, the government should control the unreasonable rise in commodity housing prices by adjusting the supply of land resources. In addition, the government should improve the land management system and strengthen the supervision of real estate developers.

Conflicts of Interest
The author declares no conflicts of interest regarding the publication of this paper.