Interaction nexus between real estate market and macroeconomics

Interaction inter-group communication surrounded by original demesne market and macro economicalalsIn this chapter, I result review the subsisting interrogationes ab out(p) the fundamental interaction nexus between accepted ground market and macroeconomics while analyzing and summarizing the data structure and the methodologies used. Considering Chinas specific subject conditions and policies, I will shed light on Chinese hovictimization falsifiable studies, and estimate their seek from different economic aspects, expecting to provide a useful perspective for my further look for.Ho employ impairment is the expenditure form by two supply and supplicate sides in the very soil market. According to the fluctuations in prop wrongs in each country, house charges generally require three characteristics endicity, city differences, and blather. Periodicity refers to how historical state price fluctuations argon cyclically or periodically associated with both micr oeconomic and macroeconomics fluctuations.Early in the 1960s, after Richard Muth (1960) strictly developed a lodging market competitive theory, a lot of economist studied the ho apply market from the perspective of microeconomics. In 1969, under a lot of assumptions, Olsen (1969) imbed that if the house market were perfectly competitive, the poor would not pay more per unit for caparison. However, in the survey done by Richard Arnott (1987), which reviewed the microeconomic postureing of the housing sphere developed at that time, it was establish that even if the competitive theory of housing market is reasonably sophisticated and well developed, it is notwithstanding hard to as legitimate the adequacy of it in developing the effects of a particular housing insurance policy since there are no well-articulated alternative models.Then, in subsequently years, scholars focused more on the study of the birth between the accredited estate market and macroeconomic basics. Acco rding to personal line of credit cycle theory, there is interaction between real estate prices and macroeconomic fundamental variables. One or more macroeconomic variables will cause fluctuations in real estate prices, besides, in the meantime, changes in the real estate constancy in any case will lead to macroeconomic unpredictability. In the change process, they formed a mutually reinforcing interaction mechanism. On the basis of the existing literature, macroeconomics adjoin real estate prices primarily through the real estate supply and take aim, which stomach be subdivided into GDP, income, consumption, interest rates, exchange rates, puffiness, grammatical construction costs, place down prices, pious platitude cite, and other basic economic variables. In ramble to understand the violation of real estate price fluctuations on the macroeconomics, to the highest degree existing studies contemplated from the perspective that the prices affect total consumption and t otal investment.Since there is a close relationship between real estate prices and macroeconomic volatility, the empirical research of their interactive relationship has al expressions been very important in the field of economics. At present, the relevant research literatures can be divided into dickens categories (a) The first type importantly analyses the relationship between real estate prices and the whole macroeconomic basic principle (b) The second type analyzes the relationship between real estate prices and one or several specific macro-basic variables (GDP, income, interest rates, investment and so on). We will now detail the two types.2.2 Housing prices and macroeconomic fundamentalsThe real estate industry has become a mature industry in umpteen developed countries. According to existing literature, well-nigh of the economists empirical research is derived primarily from the perspective of equilibrium theory. Based on the traditional regression analysis model, they used more independent linear systems, numerical economic models and others to analyze the dataGenerally speaking, the macroeconomic fundamentals will affect the investment, credit, and overly, the change of interest rate will affect the supply of real estate. On the other hand, economic appendage will affect the income and thus affect the demand for real estate. According to equilibrium theory, under the market competition mechanism, the market will eventually be cleared through real estate prices.However, Case and Shiller(1987, 1989, 1990) found that the housing market does not appear to be very effective it is contrary to the efficient market hypothesis. Then, in Clapp and Giaccottos study (1994), they not only confirmed Case and Shillers (1987, 1989, 1990) result but also found macroeconomic changes have a estimable predictive ability for real estate prices. Clapp and Giaccotto (1994) used the data of East Hartford, Manchester, and West Hartford over the period from October 1 , 1981, to September 30, 1988, with 2 methods the repeat gross sales method and the assessed value (AV) method. They found that the local unemployment and expected inflation have considerable fortune telling ability for the housing prices and compare with the first-time house, the repeat housing exponent is more sensitive in the short run due to the lagged economic factors It showed the housing market does not meet the efficient market hypothesis (Clapp and Giaccotto, 1994).With a much dogged-life data set than common literature, Holly and Jones (1997) provided a more universal perspective on the behavior of housing prices in UK. In order to seek the co-integrating relationships between housing prices and long run, they ran a regression with the housing prices and economic factors such as real income, the user cost, and building society alter. The results showed that, with the riddance of population, al just about all the factors were rejected at the 1% level in the unit root test, and that the most important determinant of real housing prices was real income the dynamic adjustment of housing prices is asymmetrical it depends on whether housing prices are below or above the long run equilibrium. When housing prices are above equilibrium, they seem to adjust back more quickly (Holly and Jones, 1997).But, Br suffer, Haiyan, and McGillivray (1997) thought that since the early 1980s, the UK housing market had suffered a number of structural changes consequently, the parameter was in unchangeable, meaning those models that grow the underling data-generating process are not appropriate. Under an assumption that the economic system is unstable, they adopted the Time Varying Coefficient (TVC) methodology, and found TVC specification outperforms the alternative aeonian parameter specifications of housing prices. Because most of the models have failed to predict the 1992 housing price downturn, part of further research was planned to use the TVC specification to examine the models forecasting ability beyond 1992.Using the data in the past 25 years of 6 European countries (France, Germany, Italy, Spain, Sweden and the UK), Iacoviello (2002) established dynamics of house prices by using a tractable value at risk framework in a straightforward way, which we call SVAR model. He pointed out that house price inflation is highly sensitive to the forces movement economic fluctuations different housing and credit market institutions mash different role in the IS-LM Phillips curve paradigm, but this relationship might change with the ever-changing of institutions in admission, regulatory legal structure and new pecuniary policy also will affect that relationship (Iacoviello, 2002). Similarly, using the SVAR model, DeHaant and Sterken (2004) studied 13 developed countries real estate markets. Their results showed that, to one country, compared with stock, housing plays a more important role in consumption and output when housing price raise 1%, consumption will raise 0.75% when housing price raise 1.5%, GDP will raise 0.4% (DeHaant and Sterken, 2004).In the Asian market, Quigley (2002) pointed out that, although most of the existed models can generate patterns of housing price changes over time in response to varying conditions in economic fundamentals, there was little research on the effect of changes in property markets upon subsequent economic conditions. With his empirical study, he determined that economic fundamentals do not explain most of the variation in the housing prices in short run, and that there were many bubbles in Asian property market during the late 1990s (Quigley, 2002). At the aforementioned(prenominal) time, Miki Seko (2003) adopted the SVAR model to analyze the Japanese housing prices. In his paper, the results showed there is a strong relationship between Japanese housing market and its economic fundamentals and by analyzing the economic factors, the development of the real estate market can be pr edicted (Miki Seko, 2003).It is clear that housing is not just a traffic pattern consumption goods, it is a large share of the overall macro-economy. Significant fluctuations in macro-economy would cause significant volatility in housing market. On the other hand, the volatility in housing market also implies the fluctuations in macro-economy. However, the interactive nexus between housing market and the different aspects of macro-economy is different. Thus, besides the studies that analyzed the macro fundamentals-housing market, most economists study from different angles to examine the interactive nexus between housing market and one or several specified macro variables.2.3 macro-basic variables2.3.1 Supply and demandTheoretically, price is determined by supply and demand sides. In the housing market, the relationship between supply and demand is formed by many macroeconomic factors, and with the changes in these factors, supply and demand continues to change. Therefore, some ec onomists thought the greatest shock absorber on housing prices comes from the supply and demand, and have dedicated their research in this area.Normally, in the real estate industry, the supply side is mainly affect by land price, facilities costs, construction tax, construction exploration and design cost, and so on. And, among them, land price is the most important factor.Since housing is a product, it is not just a demand price, but also a supply price. In the real estate economic activities, land purchase and development is the beginning and the foundation, and land purchase cost is the most important part of housing costs. From the supply perspective, the land price fluctuations are an important factor in housing price volatility. On the contrary, due to land supply is restricted by the natural there is a lack of flexibility. Therefore, land price is mainly decided by its demand side, which is mainly composed by the real estate business. The real estate industry has a huge im pact on the land market as well.In order to examine the interactive nexus between housing price and land price, Peng and Wheaton (1994) analyzed the Hong Kong market. Because Hong Kong is a small island with a fixed boundary, it would be clear what the influence of land supply on housing prices. Using a modified stock-flow model, their results showed that the supply restrictions in Hong Kong have caused higher housing prices but not lower housing output (Peng and Wheaton, 1994). Similar outcomes can be found in Alyousha and Tsoukis (1999) study. They employed the quarterly data from England and Wales from the period Q1, 1981-Q2, 1994 to explore the implications of intertemporal optimization for house and land prices (Alyousha and Tsoukis, 1999).Adopting a simple housing flow supply model, which is establish on the Euler equation (Hall, 1978), they found that, under a perfect competition, house prices are co-integrated with land prices and house building costs. But, through the Grang er test, Hall (1987) found housing price is not the land prices cause. Also, after an econometric analysis of American cities, Edward, Joseph and Hilber (2002) determined that land price was positively correlated with regional economic development, the level of human capital, and have no direct relationship with housing price.As for demand side, existing research usually examined from the aspects which are disposable income, GDP, property taxation, population and so on. There is a large diverse literature related to the housing and taxation because it is clearly that property taxation would directly affect the housing purchasing decisions, and further affect the housing demand. Just like United States, the tax system seems to favor housing ownership in many countries. Thus, Dimasi (1987) employed a computable, spatial general equilibrium model and found out that differential tax treatment on land and capital can cause a significant social welfare loss. Many other general equilibrium models also found out tax policies that favor the housing sector would lead to a significantly nix impact on both housing sector and aggregate income.From another special perspective, Mankiw and Weil (1989) examined the relations between demography-induced changes in housing demand and real house prices in the United States. They thought that the Baby Boom generation into its house-buying ages was the major cause of the increase in housing prices in the 1970s and the housing demand would grow more slowly in the next decade because of the population structure. Changes in housing demand will further affect the housing price (Mankiw and Weil, 1989)). However, unlike the estimations of Mankiw and Weil (1989), Gary and James (1990) using postwar data from Canada, and found that even if the demographic patterns were similar in Canada and United States, the aggregate time series correlation between shifting demographics and real house prices is distinctly different. From the empirical an alysis, they considered there is a statistically insignificant, but in most cases, demographic demand is negative associated with house prices (Gary and James, 1990).2.3.2 Monetary policyGenerally speaking, as an overall policy, monetary policy is mainly relate to control the trend and fluctuations of aggregate demand the impact on the real estate market and the sensitivity of the housing price should be limited. However, as the changing in the structure of global pecuniary markets and developing in real estate industry, the nexus between them has become more and more close, monetary sector has become an important reference indication in the housing market. It is also proved in Alan, John and Brians (2005) study. They found, in eighteen major industrial countries, certain financial conditions (ample liquidity, low interest rates, and financial deregulation) were usually present in past housing price surges, and could conceivably raise the probability of the intensity or the occu rrence of the rise.As for interest rate, considering from the supply side, when it turn down, real estate investment and real estate mortgage loans will continuously pour into the real estate industry, and promote housing prices continuing to rise. But, as for the demand side increasing in interest rates will directly affect consumers credit repayment costs so that some consumers would out of the housing market, which affecting the real estate demand, and further led to corresponding changes in real estate prices. By studying the impact of real and nominal interest rates on real estate prices, Harris (1989) thought that changes in real interest rates could explain the market price level nominal interest rates affect housing price only when the real estate value is expected to rise.Among the monetary policy, bank credit and investment are the most important determinates. As the real estate industry is capital-intensive industry, and most of the funds come from the bank credit and in vestment, the change in bank load will significantly affect the supply of real estate industry. Besides, a large part of real estate loans are mortgage loans, the value of real estate products in the market determines the size of the loan amount in this industry. In 2004, Davis and Zhu (2004) discovered, in the long term, bank credit is positively correlated with house prices, and effect of housing price on the bank credit is very significant, but in their paper, the reverse impact was still uncertain.Matteo (2005) developed and estimated a monetary business cycle model with nominal loans and collateral constraints tied to housing values. Since collateral effects allow the model match the positive response of real spending to a housing prices shock, Matteo (2005) found fall in the housing prices will reinforced the impact negative monetary shock on real rate, consumption and output. Similarly, based on the Hong Kong sample, Gerlach and Pengs (2005) thought property prices would dete rmine bank dedicate, but, it was interesting that they found bank lending does not appear to influence property prices in Hong Kong.2.3.3 CyclesEmpirical evidence shows that there is a cyclical movements and volatility in the housing market, and obviously, this kind of cyclical movements would relate to the economic cycles. Economics found that it would be useful and interesting to explore these movements in the housing market, thus many studies examined the housing-economy cycle relationship from both qualitative and quantitative aspects. Greenwood and Hercowitz (1991) and Baxter (1996) build up a dynamic general equilibrium models to reproduce the co-movement of business and residential investment that observed in the US. Davis and Heathcote (2001) also considered that, in the US, the residential investment lead the cycle while the non-residential investment lags the cycle, and this co-movement between housing market and macro-economy has been documented for several countries.Al so, economics often analyze real property market tie to long cycles. Gottlieb (1976) considered, the amplitudes of housing cycles are larger than typical business cycles, and the periodicity might be significantly longer than those of the business cycle. For instance, Ball (1998) showed, in UK, new commercial property cycles have a 10 years duration while they are independent of the business cycle. Employing the cross-country data and the Kalman Filter technique, Ball (1999) again found significant long cycles of new construction, which with periodicity of 20-30 years in both residential and non-residential real estate markets.As we can see, the importance and sensitivity of real estate prices attracted a large number of scholars to concerned. Based on the review above, the existing literatures are mainly adopting the cross-section data and time series data, so that the specific econometric methods of housing models are mostly focusing on traditional run-of-the-mine least squares m odel (OLS), value at risk model (VAR), tractable value at risk framework in a straightforward way (SVAR), co-integration and so on.2.4 Empirical evidence in the Chinese contextCompare with developed countries, Chinese real estate market started relatively late. But along with Chinas rapid economic development, the real estate industry is also showing a good development trend. As real estate investment occupies a very high proportion of total investment in fixed assets, and the volatility in real estate market is closely related to macroeconomic and national policy, the issue of housing prices is not only related to a citys development, but also related to financial security and the living cost of frequent people. Thus, Chinese economists have also attached great importance to the development of the real estate market, and conducted extensive research. However, since the late development of Chinas statistical system, the database is not perfect, most of the Chinese scholars just ana lyzed the relationship between housing market and macroeconomic theoretically, empirical studies are relatively small.2.4.1 FundamentalsFirst, because of the importance impact of macro fundamentals on real estate prices, using appropriate data and models to estimate the nexus between them has always been the focus of Chinese economists. Adopting the housing index and macro fundamental data (1995-2002) of 14 cities, Shen and Liu (2004) employed a mixed regression, and empirically examined the relationship between housing prices and economic fundamentals. The results showed the impact of macro fundamentals on housing market is quite different in different cities. The explain model was significant affected by the city characteristics (Shen and Liu, 2004).Song and Wei (2009) using a co-integration and vector error modified model, and considered that, in long run, there is a long-term stability of the dynamic equilibrium between real estate prices and macroeconomic but when short-term im balances, it becomes into a negative feedback mechanism. Song and Wei (2009) also found that fluctuation of GDP and inflation is the Granger cause of housing price volatility and the impact of interest rates is not significant. Based on partial least-squares regression (PLS), Wang and Xie (2010) estimate the annual data of China within the period of 1999-2008. They thought land prices, capital size and national wealth are the top three factors that affect Chinas price changes at present although the influence of long/middle-term loan rate is weak, money supply do play a very prominent role in Chinas housing prices volatility (Wang and Xie, 2010).In addition to the analysis of real estate market and macro fundamentals, Chinese economists also studied the housing market from different economic perspective and tie to their own national circumstances and policies.2.4.2 bolt down priceAs the reforming of Chinese housing system and land system, the housing sales prices were climbing high er and higher until the financial crisis in 2008, but, after a short depression, the price still maintain the rising trend. General view is that, due to the land purchase cost is the main cost which constitute the housing costs, high land prices is the main reason of high housing prices. Especially after the Ministry of Land Resources released two new policy1of land sale, more people think that the skyrocketed of housing prices is because of the high land prices. The policies require that any commercial, tourist, entertainment, commercial housing and other kinds of business land essential be transferred by tender, auction or listing mode. After the new land policies, the land transfer cost rose sharply and almost in the same period, the housing prices have skyrocketed as well.Thus, from the point of view of China Real Estate Association, Yang (2003), Bao (2004) and Cheng (2004) thought since a large number of land minutes using auctions, land prices increased dramatically. And lan d purchase costs account for 30% percent of the housing prices, hence construction costs raised, further driving a rapidly rise in housing prices this Cost-push theory was also supported by a large number of real estate developers (Yang, 2003 Bao, 2004 Cheng, 2004). But, Ministry of Land Resources hold the opposite view. Deputy Minister Fu (2006) considered that even if the tender, auction or listing transaction mode will lead an increase in land prices, it might not raise the housing price, the most important factor affecting housing prices is still supply and demand in the housing market. On the contrary, Fu (2006) thought, land is a production factor of real estate industry the demand for land is generated by the demand for housing, therefore, huge demand in housing market and the rapidly increase in housing prices makes demand for land, and further drive the land prices rise.However, Wang and Wu (2009) did not agree both of them. Employing the panel data from 28 regions, they fo und, in China, although land prices promoting housing prices in long-run and housing prices driving an increase in land prices in both long-run and short-run, this mechanism depends on the region. Wand and Wu (2009) thought that the interaction between land prices and housing prices is different in different regions, so the relationship between them should be implement regional studies and cannot be generalized.2.4.3 Bank creditAfter the 1997 Asian financial crisis, in order to stimulate economic growth, China implemented a proactive monetary and monetary policy repeatedly issued bonds, reduced interest rates several times, vigorously infrastructure real estate industry become a national priority support industry and the financial sector continue to increase the real estate credit. But until now, Chinas banking system is still not perfect most of the loans are mortgage loans, therefore, value of real estate products in the market will directly determine the size of credit.Typically , the credit will play two roles in the housing market. If the real estate prices cyclical rising, since financial institutions anticipate the housing prices can keep rising in the following, banks will relax lending conditions, thus, the increasing housing prices will directly lead to the upswing in real estate bank credit. Because of land and real estate products supply is very springless in the short-term, to some extent, the upswing in real estate bank credit will further push up house prices increase. By the same token, the decline in house prices leads to a decline in the quality of bank assets, reduce the size of bank funds, so banks will abate the amount of credit, which will further decrease the housing prices.Based on the panel data of credit and housing market, Li (2004) considered that among Chinas current macro-economic control policy, credit policy play the most significant role in the real estate market. He also believed the flexibility of supply side and demand side is different, so the impact of monetary policy on the supply is greater than that on demand (Li, 2004). Employing the error subject field model and VAR model, Zhong and Yan (2009) thought that there existed a stable equilibrium relationship between the volatility of real estate prices and credit in long-run. After the Granger test, Zhong and Yan (2009) found real estate prices and the amount of real estate credit influence each other and they both are the Granger cause for each other. Studying on the East Asian financial crisis, Xiang and Li (2005) also believed bank credit expansion played a very important role in the formation of the real estate bubble in East Asian countries. Thus, in order to ensure the health of Chinas real estate development, it should strengthen the financial system construction and regulation (Xiang and Li, 2005).2.4.4 OthersIn addition, through calculating the Lerner index2(Lerner, 1934) of the real estate market in China, Li (2005) considered the level o f monopoly in Chinas real estate market is very high. evening if as the market economy developing, the competition in the real estate market will gradually get better, but this process will be very slow (Li, 2005). And from another special perspective, Yin (2010) thought the existence of North paradox3behavior (North, 1981) in the local government is an important cause of housing price fluctuations. Local government is lack of intrinsic motivation to stabilize the real estate market local governments various rescue policies are also mainly based on the purpose of obtain more land transfer fees thus just depends on local governments behavior can not maintain healthy and sustainable development of the real estate market, the central government should implement more effective macroeconomic policies (Yin, 2010).Comparing with foreign literatures, Chinas real estate market research also adopting cross-section data, time series data, especially panel data. Relevant econometric methods ar e co-integration approach, Granger test, error correction model (ECM), and panel data model in the meantime, the analysis about the impact of macroeconomic policy is also Chinese economists priority concerns.2.5 DeficienciesHowever, for the following aspects, Chinas research is still inadequateThe studies on macroeconomic policy are more focused on the theoretical analysis they are lack of a comprehensive empirical analysis.Currently, the analysis of macroeconomic fluctuations is mainly under an assumption of closed economy. But, with economic globalization, Chinas real estate market will be more affected by international economic development, so the discussion of the relationship between the real estate prices and macro economic fluctuations that under an open economy is more meaningful.There is no analysis of government expenditure in Chinas real estate literatures. However, according to macroeconomic theory, government investment will promote mystical investment, thereby affecti ng the real estate investment and price. So, the empirical quantitative estimation about the real estate prices and government spending will contribute to the in-depth analysis of the relationship between the government and the real estate market.