Japan's Real Esae Crisis -Wha Wen Wrong? Why? Wha lesson can be learned?- Yuichiro Kawaguchi Waseda Universiy Absrac This paper examines he Japanese residenial land marke in 1972-2006, a wo decades of residenial land price decline. We find ha he problem is no only a slowdown of he populaion growh bu also a huge oversupply in he housing marke despie of he prolonged economic sagnaion. The problem is high vacancy rae in he housing markes. If i remains higher pace of housing sars in Japan, Japanese residenial land prices furher decline. We do hink ha research effor should be focused on deermining wha policy reform allow he discouned presen value of houses (lands) o again grow in a long-run. 1 Inroducion The Japanese housing marke in he pos-1990s period was less han sellar. The average annual growh rae of naionwide real residenial land price was 3.7 percen in he 1992-2006. The comparable figure for he Unied Saes was 4.2 percen. The quesion is why. A number of hypoheses have emerged: he populaion growh slowing down, he los decade in he 1992-2001, and he deflaion in he 1998-2005. These hypoheses, while possibly relevan for real esae cycles, do no seem capable of accouning for he chronic slump seen ever since he pos-1990s. This paper offers a new accoun of he los wo decades based on an asse pricing model. Krainer, Spiegel, and Yamori (2004) examine he paern of price depreciaion in Japanese land values subsequen o he 1990 sock marke crash. While all land values fell heavily, he daa indicae ha Japanese commercial land values fell much more quickly han residenial land values. Using an error-correcion specificaion, hey confirm ha Japanese land price exhibied faser convergence o seady sae values han residenial land prices. They hen develop an overlapping-generaions model wih wo-sided maching and search o explain his dispariy. In he model, when fundamenals decline, he old agens opimally fish for high service flow young agens 1
by pricing above average valuaion levels. This leads o higher illiquidiy and defaul in imes of price decline, as well as price persisence which is increasing in he variance of average service flows. Moreover, Nakamura and Saia (2007) find he coinegraion relaionships beween land price indicaors and he discouned presen value of land calculaed based on he macro -economic fundamenals indicaors. They also find ha he demographic facor has impacs on real land prices. Three issues are worh noing. Firs, long-run equilibrium house (land) prices are deermined by he fundamenal economic deerminans of housing demand, he size of he marke, and housing supply. Second, expecaions play an imporan role in deermining shor-run house price adjusmens o long-run equilibrium. Third, he magniude of he expecaions influence is relaed o an urban housing marke s supply elasiciy. The previous lieraures do no seem capable of accouning for he housing supply issue and he marke s supply elasiciy. In paricular, he housing supply ends o exceed very much he marke demand in a bubble period. Furhermore, i seems unbelievable for non-japanese, bu he oversupply in he housing marke can be occurred in he long economic sagnaion. Economic simulus measures and moneary policies (zero ineres rae policy and ease money policy) have possibiliies o cause he excess supply in he housing marke. Housing invesmens may be couned on he enhancemen of domesic demands. In our esimaion, here may be 8 million vacan housing unis in Japan in 2008. There is a long lieraure on house price dynamics in US and UK. There is wide consensus ha he house price is srong relaed o is long-run srucural vacancy (Wheaon 1990). As summarized by a varian of sock-flow approach i akes several years for house prices adjus o equilibrium because of he inefficiency of he housing marke (DiPasquale and Wheaon(1992)). Moreover as recenly summarized by Cappozza, Hendersho and Mack (CHM.2004) house prices iniially adjus by abou 52% of he value of he new long-run equilibrium price and ha house prices exhibi serial correlaion. In such shor-run house price adjusmens o long-run equilibrium, a housing marke s supply elasiciy is relaed o he magniude of he expecaions influence (Goodman and Thibodeau 2008). This paper examine he characerisics of residenial land price dynamics beween 1972 and 2006 in Japan. Following he CHM.2004 s approach, o do his we calibrae our 2-sage Error Correcion model o he 1972-2006 daa and compare our empirical 2
resuls wih US resuls. This comparison may give a similariy beween US house price dynamics and Japan residenial land price dynamics. The only puzzle is why Japan residenial land price decline was so long subsequen o 1990. We discuss possible rasons for his decline in he conclusion of he paper. However, he CHM.2004 s ECM approach has been recenly quesioned by Gallin(2006). Our sudy revise he previous one in hree imporaan ways. Firs, CHM approach has posied a coinegraing relaionship beween house prices and fundamenals such as such as income, and hen esimaing an error-correcion specificaion. The level of house prices, however, does no appear o have sable long-run equilibrium relaionship wih he level of fundamenals such as income. Gallin(2006, 2008) has quesioned ha he levels regressions found in he approach are likely spurious, and he associaed error-correcion models may be inappropriae. Our approach focuse a coinegraing relaionship beween house prices and heir presen discouned values of fuure service flows. From he long-run perspecive, he equilibrium price a household is willing o pay for a house should be equal o he presen discouned value. The level of house prices, empirically, may also appear o have sable long-run equilibrium relaionship wih he level of he presen discouned values. Second, This sudy develops a simple sock-flow model of house as a varian of he presen discouned values of house. As Poerba(1984) shown, he sock-flow approach induces ha a house price equals he presen value of fuure ne service flow discouned a homeowner s user cos. We consruc a log-linear approximaion of he equilibrium residenial land price based on he sock-flow model using he macro ecnomic fundamenals indicaors. I may no cause he problem of he spurious regression beween he level of residenial land prices and he level of he macro ecnomic fundamenals. Because he log-linear approximaion of he equilibrium residenial land price enshures he coinegraing relaionship beween residenial land prices and heir presen discouned values. Third, apar from he ECM argumen, we exend he long-run equilibrium prices as a rends for removing cycles. This sudy also analyze a relaionship beween he residenial land price cycles and moneary poloccy such as ineres rae changes based on VAR. In he VAR analysis, we show he usefulness of he removing rends based on he long-run equilibrium prices 3
Our conribuions are firs o offer a new accoun of he housing sock based on he asse pricing model. Second, o improve he deficiency of he 2-sep ECM approach based on CHM.2004. Third, we provided addiional evidence on he cause of he Japanese residenial land prices deflaion in he pos-1990s period using he modified 2-sep ECM and long hisorical land price daa. Our resuls are consisen wih earlier Japanese esimaes bu provide addiional causes of falling discouned presen values of Japanese residenial land in he periods. The remainder of he paper is organized as follows. In Secion2, we sar wih a brief caalogue of some facs abou he residenial land price deflaion. We hen proceed o examine he Japanese residenial land marke hrough he perspecive of real esae cycle in Secion 3. Finally, Secion 4 concludes. 2 The Japanese Residenial Land Marke 1970-2008 We begin wih an examinaion of he JREI (Japan Real Esae Insiuion) residenial land price index for he 1970-2008 period and repor he puzzle ha are mos germane o real esae deflaion in he 1990-2007, which absracs from he fundamenal economic deerminans of housing demand and supply, expecaions, and housing marke s supply elasiciy. In he nex secion, we will idenify deerminans of land price cycles in Japan Economy in 1972-2006. Poor r performance during he pos-1990 period Figure 1 show he los decade. Japan s anemic annual growh rae of 0.99% during he period 1992-2001 is a puzzle in view of is specacular growh performance during he previous hree decades. During he las decade period, asse price volailiy has been as high as i was during he Grea Depression. Table 1 compares Japan sock price volailiy and US one in erms of he panic which is quanified by idenifying as any ime when a daily sock closing price fell by a leas 10 percen from he highes prevailing close during he preceding 30 calendar days, wih no overlapping allowed. Among ohers, he negaive shocks generaed by sharp declines in asse prices in he early 1990s have been propagaed and amplified by heir ineracion wih he deerioraion in he condiion of he financial sysem. The larger decline of he sock prices may reflecs ha he sock prices migh be closely relaed o he deflaion of land price in Japan (Figure 2). 4
Puzzle on he deflaion d of residenial land price during he pos-1990 period Figure 3 documens Japan s residenial land price prolong slump since 1990. As he figure graph shown, Japan s residenial land price deflaion is somehing of a puzzle in view of US specacular inflaion of house price during he pos-1990 period. I would be hard o deny ha, Japan s residenial land marke experience during he las wo decades has been quie exraordinary. Figure 4 plos Japan s real residenial land prices (1986=100) in 1970-2008. The figure graph repors prices have no reurned o heir 1986 level. I is more han 20 years long. As can be seen in Figure 5, he raio of residenial land prices o household income has coninued o fall since 1990. In conras, during he previous 20-years period before 1990, he raio has had no cyclical movemen during he curren 18-years. In conrass o residenial land prices, prices of final goods and services have been fairly sable in Japan during he pos-1990 period. Figure 6 shows such conras. The average annual rae of change in he general prices is 0.3% and one in he residenial land prices is 3%, respecively, during he period 1992-2003. Even if here is lile evidence for coinegraion of residenial land prices and various fundamenals, his does no mean ha fundamenals do no affec he residenial land prices. The prolong decline in he raio of residenial land prices o household income remains anoher puzzle. Possible reasons for he residenial land price deflaion The simple idea is ha, if he naion s area is consan, he decrease in populaion leads o he decline in demand for land. In general, he demographic facor may be hough as one of he causes for Japan s residenial land price deflaion during he pos-1990 period. As can be seen in Figure 7, Japan populaion growh rae has been slower since 1973, alhough he growh raes had never been declined during he pos-1990 period. If he slowdown of he populaion growh rae was he cause of he residenial land price deflaion during pos-1990 period, hen i remains a quesion. Why land prices had raised so much in coninuaion of he slowdown of he populaion growh rae during 1980s? I is difficul o answer he quesion from he view poin of he demographic facor. Thus he demographic facor may be no he only cause of he residenial land price deflaion during he pos-1990 period. Moreover, i reminds of he paper by Mankiw and Weil, which prediced (based enirely 5
on demographics) falling real housing prices during he 1990s and 2000s in US. Their argumen was: as he Baby Boom cohor reaches reiremen, many households will ry o rade down (i.e., sell heir large house, and buy a smaller house) o suppor reiremen consumpion, and, in urn, his will cause real house prices o fall. However, if housing is elasically supplied, i follows ha demography should have lile, if any, affec on house prices. Furher, in his environmen housing should always be priced a is reproducion cos, and (in he limi) demographic changes will no have any effec on house prices. So perhaps he real quesion you are asking is wha is he housing supply elasiciy in he US versus Japan? Sandard urban economic heory has radiionally assumed ha boh housing and land is perfecly elasically supplied (i.e., he consrucion marke is perfecly compeiive, wih firms earning zero economic profis). Of course, in pracice here are likely o be coss o adjusing he housing sock, which admis he possibiliy of a link beween demography and house prices. Furher, hese coss are likely o vary from counry o counry depending on land use conrols. In relaed o populaion changes, here are long-erm Kuznes cycles n he housing marke. Wha are he housing cycles in he US versus Japan? Figure 8 plos cycle componens of he de-rended Japan Residenial land prices by H-P Filered (1970-2008, daa: Annualized JREI Shigaichi-kakaku index). Figure 9 plos cycle componens of he de-rended US house prices by H-P Filered (1987m01-2008m06, daa: Semi annualized S&P-Case/Shiller index). As can be seen in hose figures, we may recognize abou 16-18 years cycles in US and Japan. We should more focus on vacan houses because recenly abou 8 million housing unis are vacan in Japan. As can be seen in Figure 10, i is equivalen o approximaely 15% vacancy raio. Figure 11 documens a balance of supply (new housing sars) wih demand (populaion growh rae) in Japan housing marke during 1970-2008. The figure graph shows he number of housing sar seemed o be mean reversion o he populaion growh rae during 1972-1985. The figure graph also shows he number of housing sar has been divergen oscillaion from he populaion growh rae since 1986, when had sared he Land Price Bubble in Japan. Ineresingly, such oversupply of housing unis has kep in many years since afer he bubble burs in 1990. Fiscal simulus policy and moneary policy had suppored he oversupply of housing sars during pos-1990 periods. 6
3 Japanese Residenial Land Marke from he Real Esae Cycle Perspecive 3.1 The discouned presened value of housing and is log-linear linear approximaion I is assumed ha in each period, in each house, here is a discouned value of housing ha is largely deermined by economic condiions and insiuional arrangemens. As can be seen in he equaion (3) of Poerba(1984), A house s real price( P ) equals he presen value of fuure ne service flow discouned a homeowner s real user cos. o (1) P o = R( z) e R( + 1) (1 θ ) i π {(1 θ ) i π }( z ) dz where, R(z) is ne service flow(impued ne operaing income of house), θ is marginal income ax rae, i is he Morgage rae, and π is he Inflaion rae of service flow (incorporaing mainenance and obsolescence). The second column of he equaion (1) is an approximaion of he rigorous discouned presen value, so called simple Gordon growh model in asse pricing lieraures. The Gordon growh model of (1) is rue in micro level (each house). In his sudy, we conver he micro-level discouned presen value equaion ino an aggregae-level one which is specified using macro ecnomic fundamenals indicaors and heir parameers. This is an approximaion of he micro-level model (1) according o; (2) P = Y c1 c3 ( ) U H S c2 where, P is he value of real house price index(aggregae-level house price), Y is he gross service flow (real GDP is used as a proxy of real gross ren), H is he number of household. S is he sock of housing, H/S is he house uilizaion rae (i is equivalen o 1 minus vacancy raio), U is he homeowner user cos, c 1, c2, c3 are he parameers for consrucion of he approximaion. The relaionship in he equaion (2) can be heoreically induced as he simple sock-flow model of housing similar o Poerba (1984) and Dipasquale and Wheaon(1996). In he sock-flow model, he desired quaniy of housing services (HSd) depends upon he real renal price of hose services. 7
Moreover, he renal price depends on he number of household (H), user cos of housing (U), house price (P), and household income. The flow supply of services (HSs) is produced by he sock of housing (S) according a producion relaionship. Equilibrium house price equae he demanded quaniy of services wih exising quaniy of services. We also accomplish log-linear approximaion of Equaion (1), aking logs of Equaion (2). p (3) = c1 y c2u + c3h c3s where, p,, y, u, h s are he log of P Y, U, H, S, in he equaion (2). We propose he relaionship of Equaion (3) as a subsiue equaion for specificaion of Equaion (1) on he sep1 of he CHM.2004 s 2-sep EC approach. Our log-linear approximaion of he discouned presened value of housing can avoid he spurious regression problem on he 1s-sep esimaion of he deerminans of house price dynamics. The log-linear approximaion like Equaion (3) is also accomplished via a firs-order Taylor Series approximaion of Equaion (1) around is seady sae. This is a nice characerisic for our 2-sep EC approach. If each of series ake individually is I(1), ha is, nonsaionary wih a uni roo, while he linear combinaion (3) of series is saionary, for some nonzero vecor c1, c2, c3, he vecor ime series is ensured o be coinegraed. In order o ensure i, he coinegraion mus be check empirically using an acual daa sample in he 2-sep EC procedure As we describe a he chaper 1 in his paper, our approach focus a coinegraing relaionship beween residenial land prices and heir presen discouned values which are provided by Equaion (3). Our approach has posied a coinegraing relaionship beween land prices and he forcased discouned presen values of hem, alhough CHM approach has posied a coinegraing relaionship beween house prices and fundamenals such as income. 3.2 Shor-run run dynamics In he CHM.2004 approach, shor-run house price dynamics are modeled wih mean reversion o he long-run equilibrium price, and serial correlaion in house prices. 8
Their heoreical house price model reduces o a second order difference equaion ha depends on hree parameers: * * (7) p = p + ( p p ) + p. α β γ 1 1 1 where, p is he log of real house value a ime and is he difference operaor. There parameers are he serial correlaion coefficien (α ) ; he rae of mean reversion (β ), and a parameer ( γ ;0 γ 1) ha measures he conemporaneous adjusmen o he long-run equilibrium price. Equaion (7) can be rewrien in anoher difference equaion form: p 1+ p 1 + p 1 = p + p (8) ( ) * ( ) * α β α γ β γ The dynamic behavior of (8) is sudied by he characerisic roos of he corresponding characerisic equaion of he differenial equaion in (8) given by he quadraic B 2 (1 + α β ) B + α = 0, and he characerisic pair roos given by 2 (1 + α β ) ± (1 + α β ) 4α (9) B 1, B2 =, 2 Which deermine he properies of house price dynamics (see CHM.2004 for deails)? Combinaions of he serial correlaion coefficien (α ) and he rae of mean reversion (β ) give he four differen reacions o shocks in he marke: (1) Prices ha gradually and monoonically a new equilibrium (wihou overshooing he new equilibrium);(2) Prices ha oscillae abou, and evenually reach, he new equilibrium; (3) Prices ha diverge from he new equilibrium exponenially; (4) Prices ha diverge from he new equilibrium in an oscillaory paern. As we menioned earlier in his paper, Japan s naionwide residenial land prices do no reurn o heir 1986 level. The real prices have coninued o fall since 1991. If he wo parameers of he land price dynamics { } 2 saisfied (1 + α β ) 4α and ( α < 1 and β > 0), hen he Japan s land price decline is he ype-(1) reacion. In his case, he land price movemen only reflecs cyclical movemen in heir discouned presen value. I means he land price deflaion may be mainly caused by heir discouned presen value decline. The ype-(3) isα 1 or β 0. 9
Such movemens are very exreme case and may no be susained for a long period. { } { } 2 If (1 + α β ) < 4α and ( α < 1 and β > 0) 2 ype-(4) is in (1 + α β ) < 4α ( α > 1 and β > 0) and., he movemens is he ype-(2). Finally, he 3.3 Land Price Shor-run run dynamics and Business CycleC If land prices adjused insananeously o economic shocks and if housing markes were perfecly efficien, henγ, he conemporaneous adjusmen of prices o curren shocks would 1 in Equaion (7). However, abundan academic research has shown ha γ is less han 1 and land (house) prices deviae from heir long-run equilibrium. In he hird-sage analysis, we also examine he ineracion beween he deviaion of he residenial land prices and he business cycle based on he VAR impulse responses. The hird-sage focuses on he cross-secional shor-run dynamics of land price wih macroeconomic fundamenals, alhough he second-sage described in he previous secion 3.2 in his paper focuses on he land prices own adjusmen process. The VAR evidence of he residenial land prices and he moneary business cycle may provide addiional facs of he Japanese residenial price behavior relaed a moneary policy. Moving rend issue is worh noing. In order o characerize he cycle behavior of a se of ime series and he ime series exhibi boh rends and cycles, he rends are eliminaed prior o analysis. The rends are eliminaed appropriaely and he analysis proceeds wih an invesigaion of cycle behavior. There are hree approaches o removing rends from macroeconomic ime series; derending, differencing, and filering. The goal under all hree is o ransform he daa ino mean-zero covariance saionary sochasic processes. The firs wo approaches o rend removal, derending and differencing, are conduced under he implici assumpion ha he daa follow roughly consan growh raes. House prices and residenial land prices may no behave on such consan growh raes. They may have inrinsic slowly evolving movemens (Charles, and Chen (2005)). Given he admission of he slowly evolving rend, he use of filers designed o separae rend from cycle is beer for he residenial land prices han he firs wo approaches. In fac, lieraures on a moneary business cycle model wih housing prices use he filer o remove frequencies from housing prices (Iacoviello.2005 e.al.). As we inroduce laer on his paper, however, here is he case in which he frequencies separaed by a filer do no make sense in erms of a response of he residenial land price wih ineres rae changes. There are some possible explanaions of such inappropriaeness in removing 10
rends(cogley and Nason.1995 and Murray.2003, e.al.) For example, he applicaion of he H-P and B-P filers o nonsaionary daa may resul in spuriousness. The residenial land prices are differen from he macroeconomic fundamenals indicaors such as GDP, GDP deflaor, and ineres raes in erms of heir long-run equilibrium values. There is a long-run equilibrium value for he residenial land price ha is deermined by economic condiions. This means ha here are wo candidaes of he long-run rends in he land marke, one is he equilibrium value and anoher is he saisical filered rend. Which candidae is he appropriae for removing frequencies from he land prices? We should check he appropriaeness of he candidaes empirically. On he conrary, he macroeconomic fundamenals indicaors have no long-run equilibrium values like residenial land prices. 3.4 Daa and empirical findings 3.4.1 Daa Our daa are a simple daa se. Included among he variables are residenial land prices, Gross Domesic Produc, populaion, housing sock, and long-erm prime rae. The daa are annual series. Table2 provides summary saisics on he daa series. The source and definiion of all he variables appear in Appendix A. User Cos The user cos is a derived variable. I is an aemp o capure he cos of home ownership. Our calculaion adjuss ownership coss for morgage raes and expeced appreciaion raes. Tha is; (10) User cos of capial = Morgage rae - expeced appreciaion rae. Four daa issues are worh noing. Firs, here is no income ax reducion in relaed o he morgage rae in owner housing invesmen in Japan. There is anoher income ax reducion reamen of owner housing invesmen in our counry. However, he ax reducion measure of he housing has changed over ime and is benefi for owner is relaive small in a long erm. We adap he before-ax cos of home ownership. Second, we use he long-erm prime rae in place of he morgage rae. Unil 2006, former Japan Housing Loan Corporaion (JHLC, public body) had direcly len morgages since afer WWII. Privae morgage lending had been crowding ou by he JHLC during periods of 11
1970-early2000. The JHLC s morgage rae had closely relaed he long-erm prime rae. Third, he expeced appreciaion rae is being measured by he real GDP growh rae during previous year, because he real GDP is used as a proxy of real gross ren in our empirical esimaes. Fourh, propery ax and mainenance and obsolescence coss are negligible in his sudy, since oher variables are naional series. The user cos is used as an explanaory variable in fiing a long-run equilibrium equaion for residenial land price levels in naionwide. The user cos described above is based on a myopic expecaion. In order o be economical consisency in he fiing, we use a saisical filered rend of he user coss as he proxy for a long-run expeced user cos. Our user coss are slowing evolving. So we inroduce he Hodrick-Presco (H-P) filer o exrac he long-run expeced user cos. Household and Toal populaion The number of households is unobservable annually. We use oal populaion in place of he number of households because he oal populaion is observable annually. The oal populaion is more accurae han he number of households annually. We adap he he oal populaion as he explanaory variable in he empirical esimaes. 3.4.2 Empirical esimaes (1) The Equilibrium relaionship We fi a long-run equilibrium equaion for residenial land price levels in naionwide using he annual daa described in he previous secion. The equaion is esimaed using OLS. As indicaed above, our choice of variables is moivaed by he discouned presen value approach relaed he simple housing sock-flow model. Esimaes for his equaion are given in Table 3. All variables of Table 3 have he expeced sign, and many coefficiens have he expeced magniude. The expeced magniudes of household variable and housing sock variable are he same in Equaion (3) in his paper. In paricular, he real residenial land prices are negaively relaed o he housing sock and he user cos of housing and hey are posiively relaed o he real GDP and populaion. The coefficien on housing sock suggess ha a 1% rise in a naionwide housing sock 12
leads o almos a 5% decrease in real residenial land prices. The mean index value is 1.9% during he period of 1972-2006; herefore, he increase in he housing sock leads o a 9.3% decline in land prices. During he same period, mean index values of real GDP and populaion are 2.9% and 0.6% respecively. These increases lead o 8.6% increase in land prices. If real residenial land prices kep a leas zero percen growh, hen he user cos mus decline o offse effecs from changes in he housing sock, real GDP, and populaion. In fac, during he period, he user cos has been declined. In paricular, during he Los Decade and he deflaionary economy, mean values are 1% in real GDP and 0.2% in populaion. These lead o 3.5% increase in land prices. Despie his, he mean value of he housing sock is 1.5% and leads o 7.7% decline in land prices. The mean value of land prices is 3.7% afer 1992. This is almos equivalen o he gap beween he 3.5% increase by real GDP and populaion growh and he 7.7% decline by housing sock growh. In he nex procedure of our 1 s sep, we conduc a coinegraion es o check he spuriousness of he regression resuls, alhough our log-linear approximaion approach for he discouned presen value of residenial land ensures heoreically he coinegraed relaionship among he variables as we describe in he secion 3.1 of his paper. Table 4 shows he resul from he coinegraion ess for he acual residenial land price levels and heir forecased ones based on Johansen s Trace es and Maximum Eigen value es. Boh ess, wih deerminisic rend, rejec he null of zero coinegraing vecors. The hypohesis ha here is one coinegraing vecor canno be rejeced on he oher hand; ha is, based on he coinegraion es, here is no suppor for boh variables in he sysem being saionary. Based on he evidence in Table 4, we would conclude ha here is a coinegraing relaionship and he above regression is no spurious. The resuls from Uni Roo ess for all he variables appear in Appendix B. (2) The adjusmen equaion Following CHM.2004 approach, he second-sage analysis uses he esimaes of p* from he firs-sage equaion o anchor he esimaes of price changes. We esimae Equaion (7) where α represens he degree of serial correlaion, β is he exen of mean reversion and γ is he conemporaneous adjusmen of prices o curren shocks. Esimaes from his second-sage equaion are given Table 5. The empirical resuls in 13
Table 5 are consisen wih he previous lieraure (CHM.2004). The immediae adjusmen coefficien, γ, for example, suggess ha curren land prices adjus by 40% of he value of a shock o he equilibrium land price levels in he year of he shock. In addiion, residenial land prices also exhibi srong serial correlaion, wih a coefficien of 0.38. Furhermore, our esimaes show ha he oher 60% of land price adjusmen occurs only gradually over ime. Acual prices converge 40% (= β ) of his difference every year. { } 2 The esimaed coefficiens saisfy (1 + α β ) < 4α and ( α < 1 and β > 0). This means ha he paern of he Japanese land price dynamics falls in he ype (2) described in he secion 3.2 of his paper, prices ha oscillae abou, and evenually reach, he new equilibrium. Thus he Japanese land price movemen is no exreme case. One possible explanaion of he reason why he real prices have coninued o fall since 1991 is he coninuaion of oversupply in housing marke, ha is, long-run new equilibrium prices coninuously decline. (3) VAR evidence of residenial land price and business cycle The hird-sage analysis uses he esimaes of residuals from he firs-sage equaion as land price shor-run cycles. Figure 12 presens impulse responses (wih 90-percen confidence bands) from a VAR wih de-rended real GDP (G), change in he log of CPI (PI), de-rended real residenial land prices (q), and Long Term Prime Rae (R) from 1975 o 2006. The logs of real GDP are de-rended wih an H-P filer and real residenial land prices are de-rended wih he firs-sage equaion. The resuls sugges ha a model of he ineracion beween house prices and business cycle has o deliver: (a) A posiive response of nominal prices o igh money. A significan negaive response of real land prices o igh money alhough a small posiive response of real land prices o igh money in early ime. A significan negaive response of GDP o igh money.(figure12 firs row) (b) A negaive response of real land prices o a posiive inflaion disurbance. A significan posiive response and hen significan negaive response of oupus o a posiive inflaion disurbance. (Figure12 second row) 14
(c) A posiive co movemen of asse prices and oupu in response o asse prices shocks (hird row). No co movemen of asse prices and oupu in response o oupu shocks (fourh row). Taken ogeher, he wo rows highligh a one-way ineracion beween housing prices and oupu. Figure 13 also presens impulse responses from a VAR wih G, PI, q, and R during he same period. The only difference in boh figures is ha he real residenial land prices are de-rended wih he H-P filer in Figure 13 bu wih he firs-sage equaion in Figure 12. The boh resuls are similar excep for wo hings: (d) A significan posiive response of real land prices o igh money in early a few years alhough a negaive response of real land prices o igh money in laer ime. No response of GDP o igh money.(figure13 firs row) (e) A posiive co movemen of asse prices and oupu in response o asse prices shocks (Figure14 hird row). A posiive co movemen of asse prices and oupu in response o oupu shocks (Figure13 fourh row). Taken ogeher, he wo rows highligh a wo-way ineracion beween housing prices and oupu. By comparison above, he mehod of de-rended wih he firs-sage equaion (resuls in Figure 12) may dominae he mehod wih he H-P filer (resuls in Figure 13) in geing he shor-run cycles from land prices. 4. Concluding Commens In examining he Japanese residenial land marke in 1972-2006, a wo decades of residenial land price decline. We find ha he problem is no only a slowdown of he populaion growh bu also a huge oversupply in he housing marke despie of he prolonged economic sagnaion. The problem is high vacancy rae in he housing markes. If i remains higher pace of housing sars in Japan, Japanese residenial land prices furher decline. Why had such higher pace of housing sars been kep during he Los Decade and he deflaion period? Governmen and Indusries had o ake a couner-cyclical measure o simulae domesic demands. The couner-cyclical measure may cause some side effecs o he housing marke. In paricular, zero ineres rae policy, ease money policy, and ax reducion on housing invesmens may disor he real esae cycles. 15
We do hink ha research effor should be focused on deermining wha policy reform allow he discouned presen value of houses ( lands) o again grow in a long-run. References Cappozza, Dennis., Paric Hendersho, and Charioe Mack (2004), An Anaomy of Price Dynamics in Illiquid Marke: Analysis and Evidence from Local Housing Markes, Real Esae Economics, V.32-1:1-32. Cogley, T. and M. Nason. (1995), Effecs of he Hodrick-Presco Filer on Trend and Difference Saionary Time Series: Implicaions for Business Cycle Research, Journal of Economic Dynamics and Conrol 19: 253-78. DiPasquale, Denise. and William Wheaon(1992) Housing Marke Dynamics and he Fuure of Housing Prices Gallin, J. (2008), The Long-run Relaionship beween House Prices and Income: Evidence from Local Housing Markes, on he web. Goodman, Allen. and Thomas Thibodeau (2008), Where are he speculaive bubbles in US housing markes?, Journal of Housing Economics 17:117-137. Iacoviello, Maeo (2005), House Prices, Borrowing Consrains, and Moneary Policy in he Business Cycle, The American Economic Review, Vol.95, No.3:739-764. Krainer, John. Mark Spiegel, and Nobuyuki Yamori (2004), Asse Price Declines and Real Esae Marke Illiquidiy: Evidence from Japanese Land Values, Federal Reserve Bank of San Francisco, Working Paper Series 2004-16. Leung, Charles. and Nan-Kuang Chen (2005), Inrinsic Cycles of Land Prices: A simple Model, on he web. Murray, C.J. (2003), Cyclical Properies of Baxer-King Filered Time Series, Review of Economics and Saisics 85: 472-76. 16
Nakamura, Koji. and Yumi Saia (2007), Land Prices and Fundamenals, Bank of Japan Working Paper No.07-E8. Poerba, J. (1984), Tax Subsidies o Owner-occupied Housing: An Asse-Marke Approach, Quarerly Journal of Economics 99: 729-52. Wheaon, W.C. (1990), Vacancy, Search, and Prices in a Housing Maching Model, Journal of Poliical Economy 98:1270-1292. Appendix A: Daa Sources and Definiions ions Residenial land prices: Naionwide residenial land price index ( Zenkoku Shigaichi Kakaku sisu ) based on semiannual repea-appraiser on 2,000 residenial lands in Japan. In our daa se, we conver he semi-annual value ino he annual value, aking he average in ime. Japan Real Esae Insiuion (JREI). Real Gross Domesic Produc: Bureau of Saisics in Cabine Office. Populaion: Toal populaion, Census Populaion and Populaion Regisraion, Bureau of Saisics in Minisry of Inernal Affairs and Communicaions Housing sock: Census housing sock, The quinquennial census. In our daa se, we esimae annual socks using he quinquennial socks, annual housing sars, and annual demoliion raes. The annual demoliion raes are inerpolaed using he quinquennial census daa. The quinquennial census is provided by Bureau of Saisics in Cabine Office. The housing sars daa by Minisry Land Infrasrucure and Transporaion. Long-erm prime rae: Bank of Japan Appendix B: Uni Roo Tess The null hypohesis of he exisence of uni roo for he acual residenial land price levels and heir forecased ones are no rejeced a he 5 percen significance level (Table B1). The null hypohesis of he exisence of uni roo for he independen variables levels is no rejeced a he 5 percen significance level excep for populaion (Table B1). Table B1 Resuls from Uni Roos Tess 17
(1) Real Residenial Land Prices Naionwide Japan s Real Esae Crisis 20090406 1s difference -4.02-4.33 es saics <0.017>*** <0.001>*** p-value Noe: p-value in parenhess <>. -4.41-10.50 es saics <0.000>*** <0.001>*** p-value Housing User Noe: Cos p-value Sock (Trend in parenhess componen)level <>. 1s difference -0.51 0.84-3.97-4.70 <0.970> <0.999> <0.022>*** <0.004>*** Acual Forecas Level -1.02-1.25 <0.920> <0.639> (2) Real Independen Variables Populaion GDP Level (-8.85) -1.73 Naionwide <0.000>*** <0.403> Figures and Tables 0.06 "Los Decade"and Real GDP Groh Rae in Japan (average gorwh rae = 0.99%:1992-2001) 0.05 0.04 0.03 0.02 0.01 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007-0.01-0.02-0.03 Real GDP Growh Rae average Figure 1 Los Decade and Real GDP Growh in Japan Table 1 Frequency of panics in US (1890-2008) and Japan (1980-2008) 18
Frequency of Panics, 1890-2008 Decade Beginning Numbers of Panics Numbers of Panics Dow Jones Indusrials Nikkei 225 1890 11 1900 9 1910 7 1920 9 1930 38 1940 4 1950 2 1960 3 1970 9 1980 4 3 1990 1 33 2000-2008 9 28 250 Asse Price in Japan(Nominal, 1986=100) 200 150 100 50 0 1965/1S 1966/1S 1967/1S 1968/1S 1969/1S 1970/1S 1971/1S 1972/1S 1973/1S 1974/1S 1975/1S 1976/1S 1977/1S 1978/1S 1979/1S 1980/1S 1981/1S 1982/1S 1983/1S 1984/1S 1985/1S 1986/1S 1987/1S 1988/1S 1989/1S 1990/1S 1991/1S 1992/1S 1993/1S 1994/1S 1995/1S 1996/1S 1997/1S 1998/1S 1999/1S 2000/1S 2001/1S 2002/1S 2003/1S 2004/1S 2005/1S 2006/1S 2007/1S 2008/1S 2009/1S Japan(6 ciies) Sock Price(Nikkei 225) Figure 2 Residenial Land prices in 6 large ciies s and Sock prices in Japan 19
500 Residenial Land Prices in Japan(1965.1s-2008.1s) and House Prices in US (1986.2s-2008.1s) 1986.2s=100(nominal, Semi annual) 450 400 350 300 250 200 150 100 50 0 1965/1S 1966/2S 1968/1S 1969/2S 1971/1S 1972/2S 1974/1S 1975/2S 1977/1S 1978/2S 1980/1S 1981/2S 1983/1S 1984/2S 1986/1S 1987/2S 1989/1S 1990/2S 1992/1S 1993/2S 1995/1S 1996/2S 1998/1S 1999/2S 2001/1S 2002/2S 2004/1S 2005/2S 2007/1S Japan Japan(6 ciies) San Francisco New York Source: Japan( Shigaichi-kakaku land price index by JREI, Naion residenial land price and 6 large ciies residenial land price index), US(S&P.Case&Shiller index, San Francisco and New York) Figure 3 Residenial Land Prices in Japan(1965.1s-2008.1s) and House Prices in US(1986.2s-2008.1s)(Semiannual, 2008.1s)(Semiannual, 1986.2s=100) Wriing 200903 daa200903 Japan and US sock and house.xls 20
250 200 150 100 50 0 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Naion 6 Large Ciies Figure 4 Japan s real residenial land prices (1986=100) in 1970-2008. 1.4 Housing (Land) price vs. Annual Income (1970=1.0) 1.3 1.2 1.1 1 0.9 0.8 0.7 0.6 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Figure 5 Residenial land prices o household incomes s Raio 21
0.14 Price Changes in Deflaional Economy in Japan (Axis:Lef=Housing Land Price, Righ=CPI(ex.food) 0.12 0.12 0.1 0.08 0.06 0.07 0.04 0.02 0.02 0-0.02-0.04 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007-0.03-0.06-0.08 Housing Land price Annual Percen Change CPI(ex.food) Annual Percen Change -0.08 Figure 6 Residenial Land Prices and General Good Prices in Japan (1988-2007) 0.025 Annual Populaion Growh Rae In Japan 0.02 0.015 0.01 0.005 0 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007-0.005 Figure 7 Japan populaion growh rae (Annual, 1971-2007) 22
Figure 8 Cycle componens of he de-rended Japan Residenial land prices by H-P Filered (1970-2008, daa: Annualized JREI Shigaichi-kakaku index) Noes; CYCLEJP represens Naionwide residenial land prices and CYCLETY is 6 large ciies residenial land prices. 23
Figure 9. Cycle componens of he de-rended US house prices by H-P Filered (1987m01-2008m06, daa: Semi annualized S&P-Case/Shiller index) Noes; CYCLE_CM (Chicago), CYCLE_CS (San Francisco), CYCLE_MI (Miami), CYCLE_NY (New York). 24
1,000 800 600 400 200 Source( Auhor esimaion using daa on Land and housing Census) 15% 13% 11% 9% 7% 5% 3% 0-200 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Vacan house(10000 unis) Vacancy Rae 1% -1% -3% Figure 10 Vacan housing unis and vacancy raio in i Japan s housing marke 2000000 Populaion Growh Rae and Housing Consrucion in Japan(1971-2006) 0.025 1900000 1800000 0.02 1700000 1600000 0.015 1500000 1400000 0.01 1300000 1200000 0.005 1100000 1000000 0 House Consrucion Populaion Growh Rae Figure 11 Populaion Growh rae and Housing Sars in Japan 25
Real Residenial Land Price Index in 1986=100 Mean 98.5 Sandard Deviaion 2.7 74.8 Minimum 132.5 Maximum Table 2 Summary saisics. Dependen variable: log of real residenial land prices OLS Coefficien T-Saisics Table Log of Real Populaion* Housing 3 user GDP 2.41 12.2 Seady cos** sock 3.22-4.90 9.1-9.9 sae regression. ** The log of populaion use cos is he used -6.00 rend in place componens of he household. -2.7 removed by H-P filer. Null hypohesis <0.005> J (race) J (max) <0.174> <0.174> <0.005> Table 4 Resuls from Coinegraion Tes Noe: p-value in parenhess <>. Dependen Persisence variable: real house price inflaion/deflaion Mean Model(Naionwide):OLS Table Conemporaneous reversion parameer(alpha)0.38 Coefficien 4.1 T-Saisics 5 Second-sage adjusmen0.43 4.5 price regressions. parameer(gamma) 0.40 3.3 Real Populaion GDP (\rillion) Real Populaion (million) Price GDP 120.4 386.9 2.9% 0.6% -0.2% 0.4% 1.0 17.6 1.1% 105.9-2.5% 213.1 0.0% -14.7% 127.1 2.2% 8.1% 534.8 17.2% Housing Change User Cos in Sock Housing (million) Sock 2.8% 43.1 1.9% 0.5% 1.3 0.1% -1.9% 29.9 1.1% 10.8% 56.1 3.9% Adjuseed R2 0.82 r=0 r=1 1.841 22.034 1.840 20.193 Adjuseed R2 0.64 26
Figure 12 VAR evidence of residenial land price cycle and business cycle Noes: VAR esimaed from 1975 o 2006, using residuals from he firs-sage equaion as land price shor-run cycles. The dashed lines indicae 90-percen confidence bands. The Choleski ordering of he impulse responses in R (long erm prime rae), PI (Inflaion), q (land price), G (GDP). Coordinae: percen deviaion from he base line. 27
Figure 13 VAR evidence of residenial land price cycle and business cycle Noes: VAR esimaed from 1975 o 2006, using cycles land price shor-run cycles by H-P filer. The dashed lines indicae 90-percen confidence bands. The Choleski ordering of he impulse responses in R (long erm prime rae), PI (Inflaion), q (land price), G (GDP). Coordinae: percen deviaion from he base line. 28