The Impact of Gambling Gross Income, Unemployment Rate, Money Supply and CPI on Residential Housing Value in Macau: Theory and Evidence

This paper uses the classical and easy-to-understand Vector Auto-regression Model Method to study the impact of economic and monetary policy variables on the residential property market in Macau. By using sample monthly data from Jan. 2005 to May 2021, the empirical results show the dynamic relationship among the residential property value, key economic and monetary variables. Furthermore, adopting the Granger causality test, generalized impulse response function, variance decomposition and co-integration test of the corresponding VAR specification, the tables and graphs clearly explain the residential housing value has a positive relationship with the gambling gross income; it has a negative relationship with the unemployment rate; it has a positive relationship with the money supply; it has a negative relationship with the consumer price index. Finally, this paper gives five policy actions to help government stabilize the residential property market in Macau and make it healthy develop.


Introduction
The the population density of 20,000 people per square kilometer is one of the highest in the world. The situation of "land is precious" is quite prominent in Macau.
In addition, the per capita GDP is MOP661,000 in the year 2019 and rapid economic development is among the top three in the world. These data sources come from the Statistics and Census Service (DSEC). Many factors work together to make the value of land resources in Macau, the value of houses and buildings and the value of people's investment in labor extremely high. These factors work together to promote the red-hot real estate market in Macau and thus cause the housing price of Macau to soar to the ground.
In Macau Special Administrative Region, the real estate industry is one of the four pillar industries, and the analysis of the regional economy is of certain significance to the study of Macau real estate market. Figure  After it returned to China in 1999, the government gave Macau a few preferential policies. In 2002, the 60-year gaming monopoly system was ended, and the gaming operation rights were opened. Subsequently, the tourism and gambling industries were brilliant, and the economic recovery promoted the development of the real estate industry. Figure 2  The remainder of the paper is structured as follows. Section 2 discusses literature review; Section 3 describes the data and hypotheses; Section 4 reviews the VAR model; Section 5 provides empirical test results, and Section 6 provides the conclusions and policy implications.

Literature Review
In this section, I provide an overview of the literature on the interactions between house prices and economic variables as well as relationships between house prices and monetary policy. Case and Shiller (2003) exam the housing affordability issue that is related to house prices-to-income ratio, a measure if the house is affordable to the average buyers. Black et al. (2006) develop an innovative way of computing the fundamental value of housing based on a time-varying present value of the real disposable income in the UK as the main factor that can affect the house prices. Using a dynamic present value model within a VAR framework to get market fundamental prices, Fraser et al. (2008) use a similar theory and methodology and confirm the house price in New Zealand is overvalued; Miller et al. (2007Miller et al. ( , 2009) provide the relationship between house prices and national wealth effect, and show the result for that there is a positive relationship between them. The national economy growth has a significant effect on the house prices. Costello et al. (2011) again use same present value model and find out there is deviation of actual price from its estimated fundamental prices spillover from cities over Australia. Typically, the above studies develop and exam the relationship between the house price prices and income determinants. Li and Chiang (2012) find that there are long term relationships among real estate price, CPI and GDP in China. There are many house price literatures review about deriving the market fundamentals from an equilibrium model containing economic variables such as population, rent, stock of vacant new dwellings and land price etc. And house prices can be significantly influenced by these factors. Hui and Lui (2002) use economic variables as the land supply factor that can affect real house prices in HK. Using demand equals supply equation to construct the log-linear function between real houses prices and market fundamentals. Introducing the co-integration test and error correction model which is developed by Engle and Granger (1987) and widely used in the field of real estate industry; the test is used for examining the time series of variables to be integrated are of the same order. The empirical research concludes that there is a big gap between actual house prices and market fundamentals in HK. That means HK house market is more volatile than before. Furthermore, Hui and Shen (2006) measure the relationship between house prices and market fundamentals in three cities; they are Beijing, Shanghai and HK. In order to test the economic variables are correspondence with real estate house prices, the authors use more advanced econometric models to exam the casual relationship between house prices and market fundamental. They find there are differences between house prices and market fundamentals in HK and Shanghai. One important influence house price factor is the supply of land price. Theoretical Economics Letters

A Large Part of Extant Literatures Examining the Interaction between House Prices and Economic Variables
In urban areas, the supply of land is becoming scarce and the land price is becoming expensive. Deng et al. (2009) investigate what are the factors of fundamentals affect the house prices in China during the period of 2000-2005. They report that the house prices are significantly affected by real residential land prices.
Another house price measure approach is using the price-to-rent ratio, which is used for evaluating the cost of buying a house versus renting it. OECD (2005) evaluates price-to-rent ratios with the user cost of housing for the OECD economies from 1995 to 2005. In countries with high real house price gains during this period (UK, Ireland, the Netherlands, Spain, Australia and Norway), they conclude that actual price to rent ratios were above fundamental levels, suggesting there is overvaluation existed and it is cheaper to rent. Smith and Smith (2006) use a present value model to measure the market fundamentals. Buyers can decide that if the net present value is positive, the house is worth to buy; otherwise, renting would be better than owning a house. They also collect data about the pricing of buying a house or renting in US metropolitan cities. If price keeps increasing, the price-to-rent ratio should be higher its long-run average. This approach helps buyers to decide that the prices are too high relative to rent a house; the buyers will find advantages to rent a house rather than buying it.

Literatures about the Impact between House Prices and Monetary Policy
As indicated by the above summary of the fundamental house price literatures, the focus has typically been on various measures of "fundamentals". The impact between house prices and monetary policy is another important issue. In western countries, especially where the real estate market is relatively matured country, both academic and central bank have broadly pay attention to how the asset prices are influenced by monetary policy. (Mishkin, 2001(Mishkin, , 2007Iacoviello, 2005;Taylor, 2007Taylor, , 2008Taylor, , 2009 Giuliodori (2005) provides some quantitative and qualitative evidence of the house price and monetary transmission mechanism across nine European countries. The paper presents the response of house prices to interest rates and the consumption as well. Using several VAR models, the author finds out the countries with more advantage of mortgage markets and efficient housing system, the relationship between interest rate and house prices will be stronger. Ahearne et al. (2005)  China and find the impact of income on housing prices is positive, the interest Theoretical Economics Letters rate is not significant impact on housing prices, and the population has significant impacted on housing prices. Wang et al. (2020) use the wavelet analysis method and find a positive co-movement between money supply growth and housing boom in China. Guo et al. (2020) find that expansionary monetary policy not only promotes total investment but simultaneously also leads to substitution towards financial assets.

The Studying Literatures about Macau are Very Limited
Comparing  riables' monthly time-series data in section 3 to examine the residential housing value in Macau, the classical VAR model will be explained in section 4 and empirical results will be provided in section 5. Also based on these results, I will provide conclusions and policy implications in section 6 as well.

Data and Hypotheses
The monthly data sources come from the Statistics and Census Service ( (Figure 2). From year 2017 to 2021, the average residential housing value shows a stable trend. The time-series data period starts from Jan. 2005 to May 2021. "N" is the number of data points. "Min" and "Max" are respectively the minimum and maximum data values. "S.D" is the standard deviation.  H2: Unemployment rate has negative relationship with the residential housing value.
In Macau, a region lacking natural resources and land resources, the demand for real estate resources exceeds the supply and the price is relatively high. Moreover, residents' income level also determines residents' quality of life to some extent, and the increase of residents' quality of life will also increase people's demand for real estate, thus leading to the rise of the housing price.
Under the influence of the global epidemic, the number of visitor arrivals in Macau has dropped sharply, the development of various industries in Macau has slowed or even stagnated, and the unemployment rate has also been rising. The unemployment rate has a negative impact on real estate industry, that is, the higher the unemployment rate is, and the lower the real estate value will be.
People have no time to protect their own lives, and affect the confidence of in- The monetary policy of Macau is to ensure that Macau has full currency convertibility and to expand the scope of exchange of Macau currency. The money supply mainly causes price changes by affecting the money market and the amount of money in circulation in the capital market. The cost of various materials and labor will also be changed. Finally, the real estate price will inevitably change accordingly. For the real estate industry, if investors find the real estate industry profitable, and the profit is considerable, it will attract many investments, and then cause the housing price to continue to rise. From the perspective of money supply, if there is excess money entering the market, the excess money will go to the industry with very considerable return rate, such as the real estate industry, which will lead to the rise of housing prices.
H4: CPI has negative relationship with the residential housing value.
The consumer price index mainly reflects the price level and is usually used

Research Method
In order to know whether the time series of residential housing value and various proxies of economy and monetary policy variables are interacted and causality effect with each other. This paper uses the vector auto regression technique model that is suggested by (Sims, 1980) to predict the interconnected time series system and analyze the dynamic influence of random disturbance on variable system. The methodology has been widely used in many econometrics models in the field of real estate industry. For example, Chen and Patel (1998) use the VAR to investigate the house prices in Taiwan, Hui and Shen (2006) conduct stationary and Granger causality tests on three metropolitans house prices and economic variables in China.
The VAR model can be introduced in the following Equation (1): (1)

Unit Root Test Results
I need to test the order of integration of the time series data. After many tests, I find the three information criteria are the smallest when the lag period is 4. Table 3 shows the results from the Phillips-Perron unit root tests, the number of lags (4) included in the tests was defined by the information criteria.
The results of PP test in Table 3 indicate that these variables are not stationary in level, which means have a unit root; but are stationary after first differencing.
The test results show that all the time series variables are I (1).
Since the VAR model requires that the variable sequence are stable, I use the inverse roots of AR characteristic polynomial to test the stability again, it can be seen from the test in Figure 4 that the five unit roots are all in the circle, which shows the VAR system is stable.

Granger Causality Test Results
Under the VAR system, Table 4 concludes that all variables have predictive power for housing prices in Macau. Each variable is the Granger cause of residential housing value when its lag behinds the first order. For the null hypothesis that gambling gross income does not Granger cause residential housing value, the null hypothesis is rejected with the P value at 0.034. It can be explained that the residential housing value is due to the gambling gross income; while the residential housing value is not the cause of the gambling gross income. There is a one-way causality from gambling gross income to residential housing value in  Macau. This empirical result is the same as the research paper of Chen (2016).
Also, there is one-way causality from money supply to residential housing value and one-way causality from consumer price index to residential housing value as well. Based on the tests results, there is only a two-way causality from unemployment rate to residential housing value in Macau.

Impulse Response Function Results
I want to know the interconnected relationship among these variables, and the level of impact, one of the methods is to analyze the case when a disturbance term is changed or when the model is hit by some sorts of shock, what the dynamic effects of the system will be, and this method is called the impulse re- As shown in Figure 5, there is evidence that the gambling gross income has positive impact on residential housing value. Positive impacts on gambling gross income are described to increase the residential housing value for up to more than 12 periods. This graph result confirms the hypothesis 1.
As shown in Figure 6, it indicates clearly that the unemployment rate has negative impact on residential housing value. Negative impacts on unemployment rate are described to decrease the residential housing value for up to more than 12 periods. This graph result confirms the hypothesis 2.
As shown in Figure 7, the graph indicates in the longer trend, after 10 periods, the money supply has positive impact on residential housing value. Since money supply is a very important monetary policy instrument as mentioned before in this research paper, it takes time to invest in the real estate industry,  therefore, it shows a lagged impact. But for a long time period, the graph result shows it has positive impact on residential housing value. The graph result confirms the hypothesis 3.
As shown in Figure 8, it indicates clearly that the consumer price index has negative impact on residential housing value. Negative impacts on consumer price index are described to decrease the residential housing value for up to more than 12 periods. This graph result confirms the hypothesis 4.

Forecast Error Variance Decomposition Results
The forecast error variance decomposition method is to evaluate the importance of different structural shocks by analyzing the contribution of each structural   shock to the change of variables. Variance decomposition results are shown in Table 5. It can be observed that the contribution of residential housing value in the 2 nd period is affected its own shock for 99.377%. As the period increases to 12 th period, the variance in shock to residential housing value is affected by its own shock decreases to 55.364%, money supply accounts for 28.502% of the residential housing value variance, showing that money supply is powerful in affecting housing value. CPI and unemployment rate also shows increasing shocks to residential housing value. These results are consistent completely with the findings from Granger causality test result and impulse response function test results.

Co-Integration Test Result
From the previous analysis results, all the variables are integrated in order 1, they satisfy the condition of co-integration test, I use Johansen and Juselius (1990) co-integration test to examine the relationship among these variables.
The null hypothesis of the maximum eigenvalue test is that there are at most r  Table 3 reports that all the variables have unit roots at their levels. Table 6 shows the results for the rank tests results by using co-integration method. The tests are based on 1 lag for the entire period. The results show that there are at least two cointegration equations among these variables. Both trace statistics test and maximum eigenvalue test reject the null hypothesis of r less than 1 at the 5% significance level, therefore, the null hypothesis of no integration is rejected by both the trace and max-eigenvalue statistics at the 5% significance value. The results show the residential housing value and the economic and monetary variables are co-integrated over the entire period. This implies that there is a long-run relationship between residential housing value in Macau and its determinants.
To sum up, based on the VAR model and its test methods, I use the time series data from Jan. 2005 to May 2021, and obtain the following results.
The gambling gross income has significant positive relationship with the residential housing value. Currently, the gambling industry in Macau continues to decline, in this background, the future development of the real estate industry will be greatly affected too. This result is consistent with the research papers of Gu et al. (2017Gu et al. ( , 2020. Unemployment rate has significant negative relationship with the residential housing value. Based on the data source from QianZhan Database, the average unemployment rate from March to June 2021 is 2.9%. The local citizen unemployment rate in June 2021 increased to 3.9%. By industry, gambling agencies and hotels are the main source of unemployment in Macau. As can be seen from the data, there is a lag in the real estate market. Under the influence of the rising unemployment rate, the housing value in Macau has generally decreased. Among them, the high residential housing value in May was Note: 1 lag is used in all the co-integration vectors based on three information criteria. The null hypothesis in which there exists at more r co-integration vectors in the system. The co-integration tests are done under the assumption of a trend in data and an intercept and trend in the co-integration eq. C.V. (5%) is the critical value of the trace statistics and maximium eigenvalue statistics for cointegration tests.*indicates significant at the 5% level. A long period of deflation may lead to the instability of the economy, the government is actively taking measures to avoid this situation, CPI may go back up soon, the real estate industry will keep heating up.

Conclusion and Policy Implications
Based on the above summary, in order to promote the healthy development of the real estate industry in Macau, I put forward the following five suggestions. Finally, it is to vigorously develop tourism and the gambling industries. The year 2020 is difficult. Not only Macau, but all human beings across the country have suffered a great recession. The recovery of the national economy has become a major focus of current development. Therefore, while ensuring the pre- under control and disappears, Macau's economy will surely be recovered, and the real estate industry will also achieve good development as well.