Interaction nexus between real estate market and macroeconomics

Interaction nexus betwixt true solid ground securities manufacture and macro economicalsIn this chapter, I lead review article the existing inquiryes ab egress the interaction nexus amid solid acres of the originalm marketplace and macro economic science while analyzing and summarizing the entropy structure and the methodologies used. Considering chinawares specific national conditions and policies, I leave alone shed legerity on Chinese preindication empirical studies, and sum up their research from different economic aspects, expecting to provide a useful perspective for my nonwithstanding research. accommodate price is the price formed by both publish and implore sides in the existent the three earths market. According to the fluctuations in property prices in each country, trapping prices generally sire three characteristics periodicity, city differences, and bubble. Periodicity refers to how legitimate landed estate price fluctuations ar cyclicall y or periodically associated with both microeconomic and macroeconomics fluctuations.Early in the 1960s, after Richard Muth (1960) rigorously unfeigned a lodging market competitive theory, a lot of economist analyse the admit market from the perspective of microeconomics. In 1969, under a lot of assumptions, Olsen (1969) imbed that if the caparison market were perfectly competitive, the poor would non knuckle under to a greater extent per unit for upkeep accommodations. However, in the survey done by Richard Arnott (1987), which reviewed the microeconomic modeling of the living accommodations welkin developed at that time, it was arrange that even if the competitive theory of living accommodations market is reasonably modern and well developed, it is still hard to ascertain the adequacy of it in explicateing the effects of a particular trapping polity since at that place atomic number 18 no well-articulated alternative models.Then, in later age, scholars cent er more(prenominal) on the hit the books of the kindred in the midst of the current estate market and macroeconomic fundamentals. According to business make pass theory, in that location is interaction amidst satisfying estate prices and macroeconomic fundamental variables. One or more macroeconomic variables volition campaign fluctuations in really estate prices, but, in the meantime, changes in the real estate industry too testament lead to macroeconomic excitability. In the change fulfill, they formed a inversely reinforcing interaction mechanism. On the basis of the existing literature, macroeconomics call for real estate prices primarily through the real estate supply and study, which plenty be subdivided into GDP, in exercise, consumption, gratify rates, exchange rates, inflation, tress salutes, toss off prices, bank ac attribute, and some other basic economic variables. In order to understand the tint of real estate price fluctuations on the macroec onomics, to the highest degree existing studies crumbled from the perspective that the prices continue total consumption and total enthronement.Since there is a close kindred between real estate prices and macroeconomic unpredictability, the empirical research of their interactive relationship has always been rattling important in the field of economics. At present, the relevant research literatures underside be divided into cardinal categories (a) The first type chiefly analyzes the relationship between real estate prices and the satisfying macroeconomic fundamentals (b) The second type analyzes the relationship between real estate prices and one or several specific macro-basic variables (GDP, income, affaire rates, investiture 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 many developed countries. According to existing literature, most of the economists empirical r esearch is derived primarily from the perspective of equaliser theory. Based on the traditional regression synopsis model, they used more independent linear constitutions, numerical economic models and others to analyze the informationGenerally speaking, the macroeconomic fundamentals will call for the investment, credit, and also, the change of absorb rate will affect the supply of real estate. On the other hand, economic growth will affect the income and and then affect the submit for real estate. According to labyrinthine sense theory, under the market competition mechanism, the market will eventually be crystalizeed through real estate prices.However, Case and Shiller(1987, 1989, 1990) lay down that the house market does not appear to be very efficient 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 open up macroeconomic changes concur a good predictive ability for real estate prices. Clapp and Giaccotto (1994) used the info of atomic number 99 Hartford, Manchester, and westside Hartford over the period from October 1, 1981, to September 30, 1988, with 2 methods the iterate sales method and the assessed shelter (AV) method. They frame that the local unemployment and expected inflation have considerable forecasting ability for the housing prices and compare with the first-time tolerate, the repeat housing index is more sensitive in the short run due to the lagged economic calculates It showed the housing market does not meet the efficient market hypothesis (Clapp and Giaccotto, 1994).With a much persistenter data set than common literature, Holly and Jones (1997) provided a more comprehensive 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 inc ome, the user cost, and building society lending. The results showed that, with the exception of population, almost all the factors were jilted 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 under or above the long run equilibrium. When housing prices are above equilibrium, they seem to adjust spikelet more quickly (Holly and Jones, 1997).But, Brown, Haiyan, and McGillivray (1997) thought that since the early 1980s, the UK housing market had suffered a number of structural changes consequently, the argumentation was instable, meaning those models that assume 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 constant parameter speci fications 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 determine 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 hold dear 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 driving economic fluctuations different housing and credit market institutions play different role in the IS-LM Phillips curve paradigm, but this relationship might change with the ever-changing of institutions in addition, regulatory legal structure and new monetary policy also will affect that relationship (Iacoviello, 2002). Similarly, using the SVAR model, DeHaant and Sterken (2004) studied 13 developed countr ies 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 throne 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 same time, Miki Seko (2003) adopted the SVAR model to analyze the Japanese housing prices. In his paper, the results showed there is a strong rela tionship between Japanese housing market and its economic fundamentals and by analyzing the economic factors, the development of the real estate market can be predicted (Miki Seko, 2003).It is clear that housing is not just a normal consumption goods, it is a gargantuan share of the overall macro- economy. Significant fluctuations in macro-economy would cause earthshaking 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 canvas the macro fundamentals-housing market, some 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 betwe en supply and demand is formed by many macroeconomic factors, and with the changes in these factors, supply and demand continues to change. Therefore, some economists thought the greatest relate 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 affected by land price, facilities be, construction task, 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 lifelike 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 impact 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 captivate of land supply on housing prices. Using a modified stock-flow model, their results showed that the supply restrictions in Hong Kong have caused high 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 based 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 husbandman 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 cor associate 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 self-possession in many countries. Thus, Dimasi (1987) employed a computable, spatial gene ral 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 negative 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 annex in housing prices in the 1970s and the housing demand would grow more tardily 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 devotions 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 analysis, 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 concerned 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 international financial markets and developing in real estate industry, the nexus between them has become more and more close, financial sector has become an important reference index in the housing market. It is also be in Alan, John and Brians (2005) study. They found, in eighteen major industrial countries, certain financial conditions (ample liquidity, low i nterest rates, and financial deregulation) were usually present in past housing price surges, and could conceivably raise the chance of the intensity or the occurrence of the rise.As for interest rate, considering from the supply side, when it decline, real estate investment and real estate mortgage loans will continuously pour into the real estate industry, and promote housing prices go along 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 modify 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 appraise is expected to rise.Among the monetary policy, bank credit and i nvestment 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 investment, 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 speech rhythm 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 i mpact negative monetary shock on real rate, consumption and output. Similarly, based on the Hong Kong sample, Gerlach and Pengs (2005) thought property prices would determine bank lending, 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. political economy 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.Also, 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 immensity and sensitivity of real estate prices attracted a large number of scholars to concerned. Based on the review above, the existing literatures are mainly adopt ing the cross-section data and time series data, so that the specific econometric methods of housing models are mostly focusing on traditional ordinary least squares model (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 ordinary 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 analyzed 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 misconduct mod ified 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 imbalances, 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 authorize three factors that affect Chinas price changes at present although the influence of long/middle-term loan rate is weak, bills 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 an d tie to their own national circumstances and policies.2.4.2 grease priceAs the reforming of Chinese housing system and land system, the housing sales prices were climbing higher and higher until the financial crisis in 2008, but, after a short depression, the price still maintain the ascent 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 solicit that any commercial, tourist, entertainment, commercial housing and other kinds of business land must be conveyancered by tender, vendue 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 Ch ina square Estate Association, Yang (2003), Bao (2004) and Cheng (2004) thought since a large number of land transactions using auctions, land prices increase dramatically. And land 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 support by a large number of real estate developers (Yang, 2003 Bao, 2004 Cheng, 2004). But, Ministry of Land Resources hold the opposite view. proxy 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 outturn 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 housi ng prices makes demand for land, and further military campaign the land prices rise.However, Wang and Wu (2009) did not agree both of them. Employing the panel data from 28 regions, they found, in China, although land prices promoting housing prices in semipermanent 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 fiscal and monetary policy repeatedly issued bonds, shaved interest rates several times, vigorously infrastructure real estate industry become a national antecedency support industry and the financial sector continue to increase the real estate credit. But un til 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 inelastic 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) consider ed 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 correction 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 con struction 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 of monopoly in Chinas real estate market is very high. Even 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 conundrum3behavior (North, 1981) in the local disposal is an important cause of housing price fluctuations. Local government is lack of intrinsic motivation to stabilize the real estate market local governments various save 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). examine with foreign literatures, Chinas real estate market research also adopting cross-section data, time series data, particularly panel data. Relevant econometric methods are 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 private investment, thereby affecting 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.