Macroeconomics and Housing: A Review of the ♠ LiteratureCharles Leung♥ Chinese University of Hong Kong First Draft: August 2003 This version: September, 2004 Acknowledgement: This is prepared for the “Housing market and the Macro Economy: the nexus” workshop, Hong Kong, August 2003. The author thanks Stanley Engerman, Nobuhiro Kiyotaki, an anonymous referee, Robert Edelstein, and seminar participants for many useful suggestions. Edelstein in particular offers an usual amount of help which significantly improves the paper. Eric Hanushek generously assisted the author to gain access to documents at Stanford University. Youngman Leong has provided excellent research assistance. The financial support from RGC Earmark grant and Chinese University of Hong Kong Direct Grant are gratefully acknowledged. The usual disclaimer applies. ♥ ♠ Correspondence:
[email protected], http://www.cuhk.edu.hk/eco/staff/kyleung 1 Introduction In his encyclopedic collection of writings about Origins of Macroeconomics, Robert Dimand includes a set of important contributions to macroeconomics, by many of the most eminent contributors (in alphabetical order): W. H. Beveridge, Milton Friedman, Roy Harrod, J. R. Hicks, John M. Keynes, Frank Knight, Tjalling Koopmans, Simon Kuznets, Alfred Marshall, Karl Marx, Lloyd Metzler, Ludwig von Mises, Franco Modigliani, Bertil Ohlin, A. C. Pigou, Frank Ramsey, Paul Samuelson, Joseph Schempeter, Jan Tinbergen, James Tobin, and Allyn Young. Only one article therein is related to the housing market, which is the debt deflation-paper by Irving Fisher (1933). This compendium is not an exception but rather a reflection of the apparent disconnect between macroeconomics and housing research. Among the 40 papers selected for Landmark Papers in Economic Fluctuations, Economic Policy and Related Subjects (edited by Nobel Prize Winner Lawrence Klein), the only paper focusing on the housing market is “The Relation of Home Investment to Unemployment” by R. F. Kahn. Among the 11 papers contained in Landmark Papers in Economic Growth, (edited by Nobel Prize Winner Robert Solow), and the 32 papers in Landmark Papers in Macroeconomics, (edited by Nobel Prize Winner James Tobin), none is dealing directly with 2 the housing market.1 Standard macroeconomics textbooks either treat housing as one of many consumption goods, or neglect it all together. “Mainstream macroeconomics,” simply put, ignores the housing market. Conventional housing economics and urban economics research for its part virtually ignores interactions with the macroeconomy. At best, some of the theoretical and empirical analyses for urban and housing economics include macroeconomic variables (such as the inflation, the economic growth, GDP, the unemployment rate, etc.) as exogenous “control variables.” For instance, in the 4 volumes of Handbook of Regional and Urban Economics,2 the papers by Charles Becker and Andrew Morrison on “Urbanization in Transforming Economies” and Stephen Malpezzi on “Economic Analysis of Housing Markets in Developing and Transition Economies” attempt to relate the interaction between the macroeconomy and the housing markets.3 The adjacent field, Finance, borders on both macroeconomy and real estate housing in a much more responsive fashion. In Handbook of the Economics of Finance, Vols 1A-B, edited by G. Constantinides, M. Harris and R. Stulz, there are at least two macro oriented papers, “ConsumptionTobin includes several papers related to portfolio choices under uncertainty, and housing is arguably one of many different assets to hold. 2 Volume 1 is edited by Peter Nijkamp, Volume 2 is edited by Edwin Mills, Volume 3 is jointly edited by Paul Cheshire and Edwin Mills and Volume 4 is jointly edited by V. Henderson and J. F. Thisse. 3 There is a literature on whether real estate and/or real estate securities can be a hedge of inflation. However, it is mainly related to the portfolio choice rather than housing market behavior itself. 1 3 based asset pricing” by John Campbell and “The Equity Premium in Retrospect” by Rajinish Mehra and Edward Prescott. In addition, there are several chapters which take “macroeconomic” seriously.4 In light of this comparison with finance, it is indeed shocking that there has been so little overlap and interaction between the macroeconomics and the housing literatures. More recently, however, there is a small yet growing research effort that strives to bridge the gap between the two literatures and shed light on issues that are jointly consequential to macro and housing economists. This paper will review selectively and highlight the new directions of this joint research. This paper is organized into six subsequent sub-sections. The next section will provide underlying motivations for the “macro-housing” literature. It will be followed by a discussion about the important ways in which macroeconomics and housing economics overlap, with a brief summary of the existing research. Section 3 will examine the interplay of They include the chapters on “Financial intermediation” by Gary Gorton and Andrew Winton, “Intertemporal asset pricing theory” by Darrell Duffie, “Tests of multi-factor models, volatility, and portfolio performance” by Wayne Ferson, “Are financial assets priced locally or globally?” by G. A. Karolyi and Rene Stulz, “Finance, optimization, and the irreducibly irrational component of human behavior,” by Robert Shiller, “Fixed income pricing” by Qiang Dai and Ken Singleton, among others. 5 According to Chetty and Szeidl (2004), the mean expenditure share for shelter (i.e. housing) is about 20%, household income, supplies and furniture is about 6%, transport (including gas and maintenance) is 16%, food and apparel each is 15%, utilities, fuels, and public services is 7%, health care is 6%, the rest are for education, entertainment, and miscellaneous items. 4 4 here are stylized facts. Significant fluctuations in housing price would imply significant fluctuations in wealth.housing taxation with the macroeconomy. 5 . Housing constitutes a significant share of household expenditure as well as total wealth.5 Greenwood and Hercowitz (1991) find that the value of the residential capital stock is larger than than that for business capital. The focal point of section 6 will be the micro-structure of housing markets and urban form.6 Clearly. and usually. and vice versa? What is.he plain response is housing is a large share of the overall macro. Why Macro-housing? How are the housing market and the macroeconomy intertwined? Is it important to include the housing market in macroeconomic analysis.economy. housing is not just “another” consumption good. 2. The last section will conclude. and thus potentially significant household 6 See also Skinner (1994). the annual market value of residential investment is larger than that for business capital investment. To illustrate the significance of the housing market in the macroeconomy. Sections 4 and 5 will discuss the vibrant sub-fields of housing markets dynamics and cycles. and should be the scope of macro-housing research? These are fundamental issues that deserve a response. Auerbach and M. Case.S. 1996b). see Skinner (1989.1 Differential tax treatment on housing For instance. are about 30% and 60% of the GDP.8 3. the value of real balance for M1 and M2 in the U. Even this branch of the literature is voluminous.wealth effects. 1/V. M/(PY) is equal to the reciprocal of the velocity of money. edited by A. Notice that according to the quantity theory of money. 3. There is a large diverse literature related to the housing and taxation. Feldstein.7 Davis and Heathcote (2001) find that the market value of the U.S. Housing and Taxation It is easy to anticipate that property taxation of housing can be an important component of governmental budgets because of its immobility and magnitude.9 We will restrict our attention to those research treaties which examine the aggregate effects of taxation and the housing market. Quigley and Shiller (2001). Campbell and Cocco (2004). 8 7 6 . See Cheung (2003). As a comparison. including an explicit consideration of the government budget and the general equilibrium effects. respectively. and the discussion is therefore selectively developed. 9 See the Handbook of Public Economics series. Many of these papers have been previously surveyed. the ratio of nominal monetary stock to the nominal GDP. residential property stock is approximately equal to the annual average GDP. Second.6% increase in tax revenue. spatial general equilibrium model. the market value of housing stock is significant. Cooley and Salyer (1987) for related analysis. in one of the parameterization.13 Other general equilibrium models find that tax policies which favor the housing sector will cause a significantly negative impact on both the aggregate income and the housing sector. see Goulder (1989). the tax system seems to favor house ownership Hendershott and Hu (1981. as the policy distorts the accumulation of physical capital which is essential for goods production and economic growth.There are at least two predominant reasons why housing is taxed. Hendershott and Won (1992). in the United States. 13 Yet they find that even the latter is below one percent of income. 7 . 1983) study how differential tax treatment on residential housing and business capital affects the equilibrium allocation of capital and investment returns. and finds that eliminating the differential tax treatment on capital and land can lead to a significant social welfare gain.11 DiMasi (1987) solves a computable.14 More recent property tax research borrows sophisticated 10 See Ljungqvist and Sargent (2000) for an explanation why durable and immobile capital is more vulnerable to taxation. this change can lead to 6. 14 For instance. 11 See Hamilton and Whalley (1985). as in many countries. it is difficult to avoid taxation of housing because of its durability and immobility.12 Fullerton and Henderson (1989) also show that general equilibrium taxation induced distortions among industries are smaller than those across assets. 12 For instance. Skinner (1996a). a view clearly not shared by others.10 Yet. First. Goulder and Summers (1989). In a similar fashion. Lin and Zhang (1998).Casual observation suggests that the preferential tax treatment for housing exists in other countries.16 Hansson and Stuart (1989) demonstrate such a time-inconsistency by showing that under certain conditions. see Nielsen and Sorensen (1994). Future research should 15 Among others. If the preferential tax treatment on housing is undesirable. 8 . house ownership has significant social benefit. Most. There may be some positive externality of house ownership. First.analytical devices from the macroeconomics tool kit.S. multiperiod overlapping-generation model. Turnovsky and Okuyama (1994). while taxing the capital stock. 16 The literature on time-consistent policy is too large to be reviewed here.S.15 Gervais (2002) develops preferential tax treatment in a dynamic general equilibrium. tax system. why has it been implemented? There are some obvious candidate explanations. that is. see Glaeser and Sacerdote (2000). Leung (1999). then. of the current housing taxation research is focused on the U. short term elected democratic governments may not be able to commit to long term policy. housing may be a politically expedient tax target. if not all.17 Differential tax treatment on housing may be a tool to “internalize” the externality. Interested readers may consult Ljungqvist and Sargent (2000) for a textbook treatment. He concludes that the preferential tax treatment for residential property leads to a net welfare loss. calibrated for both the aggregate statistics and the income distribution of the U. 17 For instance. government would subsidize investment flows. . We will examine both 9 .K. the standard deviation of residential investment is more than twice that of non-residential counterpart. which is in turn more volatile than GDP. It would be interesting to explain these movements in the housing market. Housing and business cycles The housing market endures significant cyclical movements and volatility. 4.. are the difference related to some economic indicators. and to what extent they are related to macroeconomic movement in business cycles. although all three variables are correlated. or the political system? Can different treatments be Pareto ranked? Currently. in the U.address differences in the preferential tax treatment across countries? If so. financial development. Davis and Heathcote (2001) show that. and U. Ortalo-Magne and Rady (1998) find that. such as the demographic structure. the literature lacks both empirical and theoretical research about the effects of international differences of property taxation upon the macroeconomy. for the U. For example. the degree of economic development.S.S. the number of housing market transactions is more volatile than the aggregate housing price. K. see Baffoe-Bonnie (1998).. 20 See also Case (2000). it is not a trivial task to create a unifying theory of the business and the housing cycles.. whereas the non-residential investment lags the cycle. Jud and Winkler (2002) conclude that real housing price appreciation is strongly influenced by the growth of population and real changes in income. 10 . the residential investment leads the cycle (or GDP). In a model with 18 See Cooley (1995).20 However.19 For city level data. construction costs and interest rates. For instance.S. especially chapter 1. Wen (2001) for the case of U. effect on the capital stock adjustment in a small open economy model. Seko (2003) for the case of Japan.18 4. in the U. Bowen (1994) for the case of U.qualitative and quantitative aspects of the housing-business cycle relationship. without a residential housing stock. for a detailed discussion of why the quantitative implications of a theory are as important as the qualitative counterpart. The macroeconomy and the housing market are indeed interrelated and co-determined. a change in government purchases has little. Green (1997). Ito (1993). if any.1 Quantity Comovement An important portion of housing market movements is related to the business cycles. 19 For instance. As shown by Matsuyama (1990). See also Hwang and Quigley (2004). Davis and Heathcote (2001) find that.S. the dynamics of residential investment are fundamentally different from the non-residential counterpart.. The comovement of the housing market and the macroeconomy has been documented for several countries. To overcome this difficulty. Thus. who focus on the allocation of market versus non-market time.21 They assume reversibility between residential and business capital. and so forth. 22 A typical story is that both home production and market production sectors can take advantage of the modern microwave oven in the cooking process.S. while Greenwood and Hercowitz (1991) focus on the allocation of market versus non-market capital.” 11 .residential property. since housing is a normal good. and neither priced nor recorded. 23 “Output” of home production is not traded in the market. and washing machines with “micro-computers” installed in the laundry process.23 21 For related analysis. The productivity shocks to home production (such as home cooking. which is not traded in the market) and market production (such as food served in the restaurant) are assumed to be the same (or highly correlated). see also Benhabib. It follows that the theory cannot be easily “tested. which implies that the relative price of housing will always be unity. Rogerson and Wright (1991). the stock accumulation will be affected by a change in government purchases. Greenwood and Hercowitz (1991) and Baxter (1996) build a set of dynamic general equilibrium models to reproduce jointly the business and the residential investment cycles observed in the U. They intentionally suppress the “price dynamics” in order to focus on the “quantity dynamics”. The crucial assumption that the productivity shock in both the market and home sectors is highly correlated cannot be easily tested. the productivity shock to home production cannot be measured even in principle.22 These assumptions enable Greenwood and Hercowitz to reproduce the co-movement of business and residential investment in the macro model. both effects reinforce each other and lead to the investment comovement.As an alternative. but the process of generating utility from consumer durables (including housing). 1980). 25 It is well known that the supply of housing adjusts slowly to price changes. from human capital accumulation to market goods and home production. Thus. or simply buying a big home. Fisher (2001) observes that the effectiveness of 24 In other words. Chang (2000) shows that if there is an adjustment cost in capital accumulation. In an endogenous growth framework. and if consumer durables and time are substitutes in home production. Einarsson and Marquis (1997) show that a positive productivity shock in production leads to time re-allocation. home production is not just the purchase of durable goods (home).25 With substitutability between time and consumer durable in home production. Consequently. business and residential investment both increase. The existence of convex adjustment cost encourages agents to “spread” the accumulation between business and residential investment. thereby creating an observed comovement. For instance.24 then the business and residential investment will co-move in the equilibrium. 12 . an increase in residential investment during the current period will release more labor hours for goods production in subsequent time periods resulting in a higher level of business investment in the current period. Fisher (1997) explains residential and nonresidential investment comovement by assuming complementarity between the household and business capital in goods production. see Hanushek and Quigley (1979. For instance. respectively. Lane (2001) for more discussion. the time horizon for goods production and stock accumulation differ) and calibrate the model to emulate the U. generating higher levels of business capital and effective market labor hours. In sum. 28 See Ortalo-Magne and Rady (1998. general equilibrium models. 4. data. see Stockman and Tesar (1995). investment comovement will be observed.27 Davis and Heathcote (2001) employing the U.26 Predicated on this assumption.market labor hours is positively related to the quantity and quality of household capital. there are several theoretical explanations for the residential and non-residential investment comovement. 13 .e. national data. 2003b) for the analysis of the English experience.53 and statistically significant.. agents would naturally invest in both business and residential capital.S. Kydland and Rupert (2001) allow for time-to-built stock accumulation (i.28 In 26 For instance. a more comfortable home can make the sleeping time more “efficient” and lead to higher “productivity. In equilibrium. and the quantitative modeling is relatively satisfactory. Gomme.S. find that the correlation between the residential property price and the real output is 0. Their model obtains significant improvement in terms of fitting the data.2 Property prices. collateral and related issues Existing research has not been successful for explaining the price dynamics of the housing market.” 27 This seems to be true for a very large class of dynamic. 1475.S. cities is 0. it is also difficult to establish the existence of bubbles. 0. 14 . Driffill and Sola (1998) demonstrate that bubbles and switching processes are not easily distinguished.1346.) Though they are still statistically significant. See Loewenstein and Willard (2000) for the case of continuous trading. Kan. Kwong and Leung (2003) using city data. A satisfactory joint explanation awaits future research with a unifying theory.30 Empirically. An obvious explanation for this discrepancy is that there is important reallocation of consumption as well as production activities across cities over the business cycles. the conditions for the existence of bubbles are very fragile. Chen (2001a) finds that a rational bubble model is unable to explain the movements in stock prices 29 30 See Wang (2003) for a review of the related literature. Yet the recent researche finds that the “bubble” is not an attractive explanation. the magnitudes for aggregate U. and local city data are remarkably different. (The average correlation between commercial property and real output is similar. Santos and Woodford (1997). For instance. among others. show that for discrete time models with rational agents. An often-cited reason for failure of theory and reality is the existence of “housing price bubble”.contrast.S. Montrucchio and Privileggi (2001).29 Quantitative analysis of the property prices frequently are found to be less than satisfactory. find that the average correlation between residential property price and the real output for about 50 major U. For earlier related contributions. Ortalo-Magne and Rady (1998) are perhaps the first to differentiate residential housing from other kinds of capital in a dynamic general equilibrium. overlappinggenerations model.32 Their work is built around the variable severity of 31 32 See Hamilton and Whiteman (1985) for discussion on rational expectation and econometrics. or proffer an alternative explanation. Venti and Wise (1984. Sheiner and Weil (1992). 1989).31 Another alleged explanation for housing price cyclicality and volatility is the structure of the residential lending market. Thus.and property prices in Taiwan. researchers either may need to either reject the rational expectation hypothesis. see Li and Yao (2005) (dynamic partial equilibrium model) and Chambers. See also Ben-Shahar (1998. 2004) for alternative approaches. Garriga and Schlagenhauf (2005) (dynamic general equilibrium). For more elaborate models. 15 . see Skinner (1989). 2003a.33 For instance. 16 . 35 Lusardi.collateral constraints over the life cycle. young agents do not own houses and an increase in the housing price would make it more difficult for them to buy. The significant interactions between the collateral value and the aggregate economic activities are also confirmed by a number of case studies for 33 See Bardhan et.35 Other “middle aged” households may have already “moved up”. 36 As a matter of fact. homeowners. (2003) for the case of Singapore.e. In contrast. b). See also Ortalo-Magne and Rady (2002a. Thus. even a temporary income shock can generate very rich dynamics in such an endowment economy.. b) extend this framework to explain the interactive dynamics among housing prices. 1999. Cossa and Krupka (2001) provide evidence that many young parents have little net worth. al. which is consistent with the prediction of OrtaloMagne and Rady’s model. Some of the middle group may be waiting for the opportunity to “tradeup”. Ortalo-Magne and Rady (1998. demographic change.36 housing transactions. and would possibly exchange for small units (i. These theoretical analyses are buttressed by empirical research. trade down) to increase their available financial wealth for retirement consumption. income distribution changes and aggregate economic activity.34 The case of “middle-aged” households is subtle. Ortalo-Magne and Rady (1998) find that the price of “houses” (large units) relative to “flats” (small units) vary systematically over the business cycle. 34 See Davidoff (2004) for evidence that the elders indeed de-accumulate the housing stock by reducing maintenance. (old agents) benefit from housing prices increases through capital gain without altering their housing demand (or supply). Among others. Ortalo-Magne and Rady (2003a) for England. Eichenbaum and Rebelo (2001) and the references therein. For instance. 38 There are alternative theories for financial crises. Using micro data for Japan. 1992) build general equilibrium models for the housing and portfolio choice.38 The collateral role of housing may have important implications for asset pricing. and forces firms to rely more upon internal funds to finance investment. Lau and Leong (2002). 37 17 . and Kim (2003) for the case of Korea. see Chen and Wang (2003) for the case of Taiwan.residential price cycles. Collateral is recognized as playing an important role as a determinant for “financial crises.39 Those households with significant mortgage debt may need to adjust non-durable consumption when confronted by a negative. unanticipated economic shock the (“lock-in” effect). Gomes and Maenhout (2002). Ho and Wong (2003). a 10% rise in net housing equity would increase the number of new businesses by 5%. Seko (2003) for Japan. Liu and Shen (2003) for China.” Mera and Renaud (2000). 40 See Davidoff (2003) for empirical evidence.37 Black. Leung. 39 Berkovec and Fullerton (1989. Cocco. Leung and Feng (2003) for Hong Kong. show a clear interrelationship between and among real estate collateral values and aggregate economic activity. Gan (2003) confirms the intuition that losses in collateral value significantly reduce investments. see Burnside.40 Chetty and Szeidl (2004). Edelstein and Lum (2003) for Singapore. de Meza and Jeffreys (1996) find that for the United Kingdom. Flavin and Nakagawa (2004). “Long Cycles” in Housing Empirical research repeatedly documents “long cycles” in the real property market. 5. Ball. Ball.Gomes and Michaelides (2004). Adelman (1965) claims that “long cycles” do not exist. are approximately 10 years. Wheaton (1987) finds that the cycles of office vacancy and office development in the U. Piazzesi. with periodicity of 20-30 years (so-called “Kuznets cycles”) in both residential and non-residential real estate markets. and are independent of the business cycle in the United Kingdom. 18 . Kwok (2003). 1999). Employing the Kalman Filter technique and cross-country data. Klotz and Neal (1973) verify the existence of “long cycles” with spectral and cross-spectral analysis. For instance. Lizieri and MacGregor (1998) show that new commercial property cycles have a duration of 10 years. However. See Kelley (1969) for a literature review. among others.S. Morrison and Wood (1996. discover significant long cycles of new construction.41 41 There is a large literature on “long swings” or “long cycles” or “Kuznets cycles”. develop models that demonstrate that collateral and portfolio effects are closely interrelated and affect asset price volatility. Piazzesi and Schneider (2004). Schneider and Tuzel (2003). Vacancy rates also display dramatic cyclical movements. The periodicity of housing cycles may be significantly longer than typical business cycles. This general finding can be traced back to Conklin (1935). Interestingly.The NBER monograph by Gottlieb (1976). . 42 43 The mean periodicity is 19. Adopting the Burns and Mitchell methodology.0 years and a mean deviation is 4.finds that local building cycles exhibit the mean periodicity of 19. Derksen (1940). investigating more than 100 real estate related time series from different cities in different countries. and a mean standard deviation of 5.0 years. They tend to “lead” the new building cycle.42 and local. 19 . is perhaps the most systematic analysis of the cycles in the real property market. (1999) for more discussion. National building cycles are similar. See also Dokko et.7 years.4 years. al. in the Gottlieb micro data. and amplitudes are larger than those of the business cycle. vacancy rates in different communities at different time periods are similar. All these empirical regularities demand an explanation and the next section will provide a quick review on that. regional and national cycles typically move together. Gottlieb. and shocks (such as wars and natural disasters) are the driving forces behind cycles. Once the real estate development project starts. credit. Lewis (1965) examines housing cycles between 1700. Campbell (1963) shows that it is the “swings” or “cycles” in population that lead to “swings” in housing starts from 1890. strategic activities among real estate developers. For the United States.1960. it has been suggested that the change of construction costs over time leads to the fluctuations of new building. since the landowner can always leave the land idle for the current period and develop it later.1. However. Also. 44 See also Wickens (1941). it is costly to terminate or to reverse.5. this explanation is not consistent with the evidence. For instance. The changes of new buildings seem to be much more in line with the change in supply and vacancy than changes in cost. 20 . the value of a development is not independent of other developments nearby. and finds that the changes in population. The decision for constructing new buildings is an option.44 An alternative explanation for real estate cycles hinges upon the. the question is: what changes the supply and vacancy? For England.43 Therefore. Why building cycles exist? Why does new building displays dramatic cyclical behavior? Many explanations have been proposed.1950. RossiHansberg (2004). There is a large literature on agglomeration. According to Bogart (1998). b). and the need for pioneering research. among others. Lucas and Rossi-Hansberg (2002). For some recent development on the structure of cities. al. among others.45 These models are technically involved and partial equilibrium in nature. Much of housing market fluctuations may 45 46 See also Downing and Wallace (2002a.”46 Fundamental research on the relationship between city for and structure and housing is needed for several reasons. among others. Wang and Zhou (2000). 21 . the city is “a spatial concentration of a large number of people. Lai. There is a related literature on the spatial structure of cities. combining the option feature of real estate development with the strategic interactions of different developers is a difficult task.Clearly. Lai (2003). Wang and Zhou (2004). Early attempts to model this complex behavior have been conducted by. the world is becoming more urban.2 City and housing This section will discuss briefly the relationship between the urban city and the housing market. (2000). The fundamental characteristic of a city is its density. there is an increasing tendency for both population and economic activities to concentrate in cities. which is reviewed by Wang (2003). Arnott and Small (1998). First. surveyed by Anas. 5. Wang et. see Lucas (2001). Much remains to be devised to reconcile the “strategic theory of cycles” with the empirical realities of long housing cycles. Rossi-Hansberg and Wright (2004). Third. Second. suggesting that there may be significant reallocations of economic activities and resource (including both capital and labor) across cities over time. Perhaps when the Amsterdam real housing price rises above a certain threshold. though often mentioned in the media. Alternatively. such as the neighborhood effects. has yet to be irrefutably and scientifically established. the micro-structure and non-market interactions. see Chatterjee (2003). may have important impacts upon household 47 For instance. we would observe a relationship between the growth and decline of cities. and housing prices. If this were the case. some cities “substitute” for other cities.actually emanate from fluctuations in urban areas. the correlation between housing prices and city output is much lower than that for the national economy. This conjecture. although it has experienced dramatic volatility. understanding urban city fluctuations may enhance our understanding of the relationship between the macroeconomy and the housing market. Torto Wheaton Research (2002) presents evidence that the real price of housing in Amsterdam over the 300 years displays no trend.47 Thus. businesses and households move to other cities. 22 . and the relative housing prices across cities may have changed significantly as well. see Glaeser (2000). 49 For instance. how will housing market performance and the housing-macro finance system and capital markets change in the 48 Among others. new building. Ioannides and Zabel (2000). 50 See Jeske and Krueger (2004). There are many other interesting research topics about the nexus of the macroeconomics and housing. 5. and housing markets and urban structure. Perhaps macro-housing market fluctuations (prices. vacancy. etc. see Leung (2001). Among these.) may be explained better by aggregating micro-behavior within cities. Bardhan. the impacts of collateral upon housing and its “long cycles” for the housing market. Edelstein and Tsang (2004) for some preliminary attempts. and Ioannides (2003). two questions deserve special highlighting.ownership behavior. It examines the relationship between and among housing and taxation.48 How “non-market interactions” interact with the aggregate economic activities is an under-explored economic phenomena. Glaeser and Scheinkman (2003). Edelstein and Leung (2003). Glaeser and Gyourko (2001). How will the housing market change in the era of globalization and financial integration?49 Second. housing cycles and business cycles. Glaeser and Kahn (2003).3 New research frontiers for the macro-housing nexus This paper selectively reviews the existing literature about the nexus of the the macroeconomy and the housing market. Bardhan. 23 . future. especially in developing economies? How has the integration of the housing finance system changed the risk-sharing across the economy?50 Both of these issues deserve special research attention in the future. 24 . London and New York: Routledge. G. "Expenditure allocation across nondurables. Michael. “Globalization and real estate returns. services. 444-463. 83-105. Robert Edelstein and Lum Sau Kim (2003). Rajarshi Datta. Anderson. Irma (1965). Anas. “Long cycles—fact or artifact?” American Economic Review. Baffoe-Bonnie. Robert Edelstein and Charles Ka Yui Leung (2004). durables and savings: an empirical study of separability in the long run. mimeo. 55(3). Alan and Martin Feldstein (different years). Ball. John (1998).” University of California. 179-97. 516-536. forthcoming. “Urban spatial structure. Colin Lizieri and Bryan MacGregor (1998). Ball. Bardhan.” Urban Studies.Reference Adelman. 25 . 12. Aghion. Ashok. 1426-1464. Aiyagari. 27. Philippe. 88. Ashok. “Globalization and urban residential rents.” Journal of Real Estate Finance and Economics. 1359-97. 1687-1706. 6(2). Costas and Bruce Smith (1998). 311-331. Richard Arnott and Kenneth Small (1998). Robert Edelstein and Desmond Tsang (2004). New York: North-Holland.” Journal of Housing Economics.J. Abhijit Banerjee and Thomas Piketty (1999). (1991)." American Economic Review. Bardhan. Alex. Tanya Morrison and Andrew Wood (1996). “A tale of two sectors: upward mobility and the private housing market in Singapore. “Structures Investment and Economic Growth: A Long-Term International Comparison. 33(9). 1-3. vol. The Economics of Commercial Property Markets. Ashok. "Financial intermediation and regime switching in business cycles. 36. 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