Herding Behavior in China Housing Market

Transcription

1 Inernaonal Journal of Economcs and Fnance; Vol. 6, No. ; 014 ISSN X E-ISSN Publshed by Canadan Cener of Scence and Educaon Herdng Behavor n Chna Housng Marke Tng Lan 1 1 Deparmen of Fnance and Busness Economcs, Unversy of Macau, Macau, Chna Correspondence: Tng Lan, oom: B1-A308, Faculy of Busness Admnsraon, Unversy of Macau, Av. Padre Tomas Perera, Tapa, Macau, Chna. Tel: Emal: olvalan@umac.mo eceved: November 11, 013 Acceped: November 6, 013 Onlne Publshed: January 3, 014 do: /jef.v6np115 UL: hp://dx.do.org/ /jef.v6np115 Absrac The essay ulzes a unque daase of 30 Chnese provnces and muncpal ces resdenal sellng prces from 1998 o 013, and examnes he herdng behavor. Usng a leas squares mehod and quanle regresson mehod, we sudy he herdng effec of Chna housng marke a boh naonal and ces levels. esuls show ha herdng formaon s sronger n ncreasng markes han ha n decreasng markes. Bu when he markes are urnng urbulen, n he hgh quanle regresson, here s herdng acvy n decreasng markes. Our resuls also suppor he asymmery of herdng behavor n ncreasng and decreasng markes. By examnng he fnancal crss on he level of herdng behavor, nvesors n Chna resdenal housng markes end o herd before he crss, and here s no herdng behavor durng and afer fnancal crss by quanle regresson. Ths sudy s mporan for hree man reasons. Frsly, alhough he exsng heorecal and emprcal sudes have nvesgaed abnormal ncreasng prce of Chna housng marke, o he bes of auhor knowledge, we are he frs o apply hs mehod o nvesgae herdng phenomena n Chna housng marke, whch hs essay focuses. Secondly, due o Chna resdenal housng marke unque characerscs, hs sudy makes a frs aemp o examne he herdng behavor by usng quanle regresson. Thrdly, our sudes of hs paper exend our knowledge of Chna real esae marke o praconers, academa and polcymakers. Keywords: herdng behavor, Chnese resdenal housng marke, quanle regresson, ncreasng and decreasng markes, fnancal crss 1. Inroducon In recen fnancal leraure, he decson makng process of marke parcpans has been receved consderable emprcal esng by academa and praconers. Numerous papers have been urned o sudy and focus on he herdng acves n global sock markes. For example, Chang, Cheng and Khorana (000) ndcae ha here s sgnfcan evdence of herdng n Tawan and Souh Korea and paral evdence of herdng n Japan. Bu hey ddn fnd herdng behavor exss n he Hong Kong and US sock markes. Zhou and La (009) focus on Hong Kong sock marke and found ou herdng s prevalen when radng small socks and nvesors prefer o herd when sellng socks raher han buyng sock. Tan e al. (008) nvesgae recen Chnese sock markes and her emprcal examne resuls show ha herdng occurs under boh up and down marke condons. And s more profound n A-share nvesors. Scharfsen and Sen (1990) ypcally defne Herdng as he elusve phenomenon ha ndvduals prefer o follow ohers n hnkng, feelng, and akng acons, whle gnorng her own orgnal decsons. Bkhchandan and Sharma (000) refer herdng behavor as an obvous nen by nvesors o mae he behavor of oher nvesors. Zhou and Anderson (013) nvesgae he marke-wde herdng behavor n US EIT marke and her fndngs show ha herdng behavor n real esae markes usually refers o envronmen n whch nvesors or resdenal buyers learn and mae ohers n he course of nvesng n EIT marke, whch lead hem o mpulsvely buy or sell propery. Then he EIT marke wll evenually ncrease or decrease durng he same perod of me. The academc leraure on herdng has been conduced on boh heorecal and emprcal research. On he one hand, heorecal research falls no he followng four ypes: concern for repuaon, payoff exernaly, nformaon cascade, and compensaon srucures. Scharfsen and Sen (1990) concern herdng behavor can occur n fund managers or analyss based on her repuaon concern. Graham (1999) has also developed heorecal models for repuaon based herdng. Damond and Dybvg (1983) refer o he payoff exernaly by whch an nvesor s whdraw or nvesmen behavor may affec he uly of oher agens, whch may lead o bank-runs. Banerjee (199) proves ha poor aggregaon of nformaon cascade lead nvesors o neglec real 115

2 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 values and nsead follow he marke, whch evenually leads o marke neffcency. Bkhchandan, Hrshlefer and Welch (199) menon ha publc pool of nformaon grows, s pecular, and easly crash. Maug and Nak (1996) ndcae ha he junor fund managers devae from reurn-maxmzng porfolo allocaons and follow hose of her benchmark ha shows a herdng phenomenon. On he oher hand, emprcal research can be classfed no wo groups. The frs group focuses on group-wde herdng. Tha s he endency of ndvduals or ceran groups of nvesors, such as muual fund managers or fnancal analyss, o follow each oher and rade he same asses a he same me. Lakonshok, Shlefer and Vshny (199) provde he frs sudy ha used he mehod o examne he herdng behavor on nsuonal nvesors and verfy he correlaon n radng paerns for a parcular group of raders and her endency o buy or sell he same se of socks. Grnbla, Tman and Wermers (1995) mprove he LSV model and laer on Wermers (1999) develops a porfolo-change measure (PCM) o es herdng by consderng he drecon and nenon of nvesors. The second group focuses on he exsence of marke-wde herdng, whch s he collecve behavor of all parcpans owards marke vews o buy or sell parcular asses a he same me. Chrse and Huang (1995, hereafer CH) provde he frs sudy ha proposes an approach o deec wheher he herdng behavor s presened n he marke-wde sense. The CH mehod consders he marke mpac of herdng s measured by dsperson, he cross seconal sandard devaon (CSSD) of reurns. If he marke-wde herdng occurs, reurns on ndvdual socks would be more han usually clusered around he marke reurn as nvesors suppress her prvae opnon n favor of marke consensus. Demrer and Kuan (006) use CH mehod o es Chnese sock marke and ge he resuls ha nvesors are followng her prvae nformaon durng nvesmen. Chang, Cheng, and Khorana (000, hereafer CCK) propose a modfcaon o he CH model, and defne he cross-seconal absolue sandard devaon () and examne an nernaonal sock marke. In hs model, CCK proves he nonlneary relaonshp beween dsperson and marke reurn. Usng he mehod, CCK fnd herdng behavor exss n emergng marke oher han developed marke. Followng he CCK mehod, Tan e al. (008) and Chang e al. (010) fnd evdence of herdng behavor whn Chna sock markes. In hs paper, we nvesgae he herdng behavor n Chna resdenal marke, whch s one of he prosperous emergng markes n he world. The Chna real esae marke was esablshed n year 1998, a shor perod of less han 15 years. In July 1998, cenral governmen announced he noce on he deepenng of housng reform and fasened housng consrucon polcy, whch spulaed he welfare-housng dsrbuon sysem, was abolshed; all ces mplemened he polcy of house monezaon allocaon and resdens need o buy commercal aparmens n he resdenal propery radng marke. Snce he real esae marke srucure s no perfec, s common for nvesors or buyers o mae he acons of one anoher. In he real esae marke, here s endency o follow prevous successful nvesmen choces, whch s called followng he leader, hs house prces go up and down ogeher n dfferen provnces or ces can be consdered as herdng behavor. Accordng o he Chna Naonal Sascs Bureau, he average growh rae of nvesmen and abnormal ncreasng of housng prces make people hnk Chna real esae marke s overheaed. The Chna Mnsry of Consrucon always ssues a seres of adjusmen measures for a raonal and healhy developmen of he real esae marke. Besdes he growng mporance of he real esae marke, we observe here s a very lle herdng leraure for Chna real esae marke. Based on he above ssues, here are herefore good reasons o deec he herdng for Chna resdenal housng marke. In hs paper, we examne wheher marke-wde herdng behavor exss whn Chna resdenal housng marke from he CCK approach and quanle regresson (Q) mehod. Usng 30 provnces and muncpal ces resdenal housng daa, we fnd evdence of herdng formaon n naonal wde marke. The resuls help polcymakers o mplemen necessary polces o suppress he abnormal ncreasng housng prces n dfferen ces. The remander of hs paper s organzed as follows. Secon presens he mehodology used o deec herdng behavor. Secon 3 descrbes he daa. Secon 4 repors he emprcal resuls of herdng behavor based on he leas squares esmaor and also presens a quanle regresson mehod and apples o esmae he herdng equaon. Secon 5 concludes he paper.. Mehodology As menoned earler, Chrse and Huang (1995, CH) and Chang e al. (000, CCK) have proposed mehods o deec herdng behavor n equy reurn daa. CH proposed ha he marke mpac of herdng s measured by consderng dsperson he cross seconal sandard devaon (hereafer CSSD) of reurns. Ths measure shows ha he sock reurns spread around he average marke reurns. If he marke wde herdng occurs, reurns on ndvdual socks would be more han usually clusered around he marke reurn as nvesors suppress her prvae nformaon n favor of marke consensus. CSSD s defned as: 116

3 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 n (, m, ) 1 CSSD n 1 (1) Where N s he oal number of socks n he marke porfolo,, s he reurn of sock a me, and m, s he average reurn of he marke porfolo a me. The raonale s ha f herdng s prevalen durng perods of marke sress, reurns on ndvdual socks would be more han hose usually clusered around he marke reurn because nvesors who suppress her prvae opnons n he marke generally favor. CSSD s hen regressed as follow: CSSD L U D D () L D U D 1 Where and are he dummy varables whch respecvely represen marke reurns ha le n he exreme lower or upper al of he dsrbuon on day, and equal o zero oherwse; hence α s he mean marke reurn. The presence of negave and sascally sgnfcan β 1 and β would ndcae he exsence of herdng. CH approach has drawbacks. Snce requred defnng he exreme reurns frs, and also gnores he fac ha herdng could ake place durng normal perods. Addonal challenge akes place when applyng hs mehod o Chna resdenal housng marke daa because of he relavely shor hsory of he marke, s dffcul o denfy when exreme reurn occur. Chang, Cheng and Khorana (000, CCK) propose a modfcaon o he CH model, CCK model s a more sensve means of deecng herdng by nong ha he CH model s a more srngen es mehod because requres a far greaer magnude of non-lneary n order o fnd evdence of herdng, CCK used he cross-seconal absolue sandard devaon (), whch s calculaed as 1 N (3) 1, m, N Where,, s he reurn on any asse of he N asses, m, represens he reurn on he marke porfolo. Furhermore, he expeced cross-seconal absolue devaon (E) n perod as follows: 1 N E ( (4) ) ( ) 1 m E m 0 N Where, γ 0 s he reurn on a zero-bea porfolo, β s he me-nvaran sysemac rsk measure of a secury, =1 N and =1 T, β m denoes he me-nvaran sysemac rsk measure of an equally-weghed marke porfolo, and E ( ) denoes he expecaon operaor n perod. The me-varyng marke equy reurn and dsperson can be shown n a lnear and ncreasng funcon, because: E( ) 1 E ( ) N m And E( ) 0 (6) E ( m ) CCK consdered ha f herdng exss, he nonlneary nheren n he relaonshp beween dsperson and marke reurn can be wren no he new herdng equaon: (7) Where, he coeffcen (γ ) of he quadrac em s found o be negave and sascally sgnfcan, and hen we can say herdng s exsed. I also allows esng he degree of herdng n up versus down marke by runnng he followng emprcal equaons: up (5), f >0 (8) down down down down down, f <0 (9) 1 m, ( m, ) m 3. Daa We oban daa on resdenal housng prces for 30 ndvdual provnces and muncpal ces across Chna over he 1 N m, 1 m m, 0 up up up up 1 m, ( m, ) m,, 117

4 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 perod March, 1998 o May, 013. The overall resdenal housng marke prce s colleced as well. The monhly daa source comes from economy research nsue of Chnese urban and rural consrucon. Wh monhly frequency, our sample has 183 observaons. Our analyss focuses on hese provnces and ces, hey are Bejng, Tanjn, Shangha, Chongqng, Jln, Helongjang, Laonng, Hebe, Shandong, Jangsu, Zhejang, Fujan, Guangdong, Hanan, Guangx, Anhu, Jangx, Hube, Hunan, Schuan, Guzhou,Yunnan, Henan, Shaanx, Shanx, Inner Mongola, Gansu, Qngha, Nngxa and Xnjang. The reurn for ndvdual provnces or ces and he overall marke porfolo are calculaed as =ln(p )-ln(p -1 ) and hen of equaon (3) as he measure of cross-seconal reurn dsperson. Table 1 presens he summary sascs of he wo varables a monhly daa frequency. As shown n he able, he mean of reurn m remans posve, and he reurn dsperson shows sgnfcan skewness and kuross, and s no normally dsrbued. Ths ndcaes ha OLS mehod s no effecve o es he herdng; we should use robus esmaon mehod o es for herdng. Table 1. Summary sascs of m and for Chna resdenal housng marke N Mean Mn Max S.D. Skewness Kuross m Ths able repors he summary sascs of he cross seconal average reurn ( m ) and he cross seconal absolue devaons () for Chna resdenal housng marke a monhly daa frequences. The daa are obaned from he Economy research nsue of Chnese urban and rural consrucon. They range from he sar of Mar o May N s he number of daa pons. Mn and Max are respecvely he mnmum and maxmum daa values. S.D s he sandard devaon. 4. Emprcal esuls 4.1 Esmaes of Herdng Behavor Table repors he esmaon resuls of herdng based on Equaon 7. We focus on he herdng coeffcen γ ; a negave value on he coeffcen γ suggess he exsence of herdng. The resuls based on he esmaed equaon for Chna resdenal housng marke has hgh explanaory power, as he -square s 0.67, he coeffcen on he marke reurn square γ dsplay negave sgn and sascally sgnfcan a he 1% level. Ths fndng provdes srong suppor for he exsence of herdng behavor n he marke. Table. Analyss of herdng behavor n Chna resdenal housng marke Marke γ 0 γ 1 γ Monhly OLS (5.66)** (1.80)** (-6.93)** Ths able repors he followng regresson resuls for Chna resdenal housng marke:. Where m, s he cross 1 m, m, seconal average reurn, and s he cross seconal absolue devaons of reurns. The sample perod s from Mar, 1998 o May.013. **represens sascal sgnfcance a he 5% level Herdng under Up And Down Markes ecen emprcal research (Tan e al., 008; Chang & Zheng, 010) hghlghs he asymmerc characerscs of asse reurn. The evdence shows subsanae asymmerc herdng behavor under dfferen marke condons. In our paper, s also neres o examne wheher herdng behavor presens an asymmerc reacon on monhs when he marke s rsng vs-à-vs monhs when he marke s fallng. Therefore, we can rewre equaon (8) and (9) no he followng expresson: (10) 0 1(1 D ) m, D m, 3 (1 D ) m, 4 D m, Where he dummy varable D=1 f m, <0 and D=0 f oherwse. 118

5 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 Table 3 presens he regresson esmaed asymmerc herdng coeffcen under up and down markes condons. We fnd a negave sgn (γ 3 ) for he herdng coeffcen n up marke. However, he esmaed coeffcen of γ 3 s no sascally sgnfcan. The evdence s o suppor ha he herdng can be only found n he down marke. We also es he equaly of he herdng coeffcen beween he up and down markes and conduc Wald es by subracng coeffcen on he decreasng marke from he coeffcen on he ncreasng marke. (γ 3 -γ 4 =0). The Ch-squared sascs, as shown n he las column of Table 3, ndcang he null hypohess of γ 3 -γ 4 =0 can be rejeced. Therefore, we can consder he herdng effec appears o be sronger durng down markes han durng up markes. Table 3. Conans regresson esmaon resuls of herdng n he up and down markes Marke γ 0 Up Marke Down Marke γ 1 γ 3 γ γ 4 γ 3 -γ 4 =0 χ Monhly OLS (9.75)** (4.7)** (-1.33) (3.3)** (-.90)** (0.000)** Ths able repors he followng regresson resuls for Chna resdenal housng marke: 0 1(1 D ) m, D m, 3 (1 D ) m, D 4 m,. Where he dummy varable D=1 f m, <0 and D=0 f oherwse. m, s he cross seconal average reurn, and s he cross seconal absolue devaons of reurns. The sample perod s from Mar, 1998 o May.013. χ s he Ch-squared sasc wh one degree of freedom for he Wald es. Numbers n parenheses are -sascs based on Newey-Wes (1987) conssen sandard errors. **represens sascal sgnfcance a he 5% level. 4.3 Quanle egresson Mehod and esuls I s generally recognzed ha leas squares esmaon s a mean based regresson mehod. When here are sascal problems exs, such as non-normal dsrbuon, sensvy o oulers, and errors n varables, he leas squares mehod wll have esmaon bas. However, Barnes and Hughes (00) argue ha hese problems can be allevaed by usng quanle regresson (Koenker & Basse, 1978). Comparng wh leas squares mehod, Q s able o analyss he enre dsrbuon of he dependen varable. For dealed echncal dscusson abou hs mehod, readers can refer o Koenker 005. In he prevous secon (Table 1), we have found ha he reurn dsperson () s non-gaussan dsrbuon; he sascs shows sgnfcan skewness and kuross. Therefore, we should consder quanle regresson, whch s more robus and effcen han he ordnary leas squares mehod (Buchnsky, 1998). Quanle regresson s a sascal procedure, whch esmaes he full range of condonal quanle funcons. (Koenker, 005). The lnear condonal quanle funcon s wren as: ' QY ( / X ) ( ) X ( ) ( ) (11) Where Y s he dependen varable, X s a vecor of ndependen varables and β(τ) s a vecor of coeffcen, and μ (τ) s he error erm. (τ) ~ (0, 1) ndcaes he quanle. The β(τ) can be found ou by mnmzng weghed sum leas absolue errors: ' ' ( ) argmn( Y ( ) X ( ) Y ( ) X ( )(1 )) (1) ' : Y ( ) X( ) The funcon (1) llusraes ha he quanle regresson coeffcen can be go by mnmzng he weghed sum leas absolue errors, where he weghs are dependen on he quanle values. When τ=0.5, he quanle regresson becomes he medan regresson. Oher common quanles are 0.1h quanle, 0.5 h quanle, 05 h quanle, 0.75 h quanle and 0.9 h quanle. We use hese quanles o esmae he relaonshps among he dependen varable and ndependen varables. Thus n our research paper, he mehod provdes a complee pcure n helpng us o undersand he relaon beween dsperson and cross seconal marke reurns. The lnear programmng can be solved by usng he sofware Evews8. In our research equaon, we use quanle regresson mehod o es he and a se of ndependen varables X, he τ quanles are characerzed as: Q 1 D ) D (1 D D (13) Where n equaon (13), D s a dummy varable by seng D=1, f m s less han zero, and D=0 f oherwse. ' : Y ( ) X( ), o, 1, ( m,, m, 3, ) m, 4, m,, 119

6 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 The esmaon s usng quanle regresson whch s based on he dsrbuons of he dependen varable and he esmaons use he sample pons condonal on a specfc quanle. Thus, he quanle regresson s more effcen and approprae for real esae reurn ha presens a skewness dsrbuon. Table 4 repors he quanle regresson resuls of herdng n Chna resdenal housng marke. We fnd overall sgnfcan and negave sgn of γ across quanles. Based on he Q resuls, he evdence shows ha he herdng exss n he marke durng Mar., 1998 o May, 013. Table 4. Analyss of herdng n Chna resdenal housng marke by quanle regresson Marke γ 0 γ 1 γ Pseudo τ =10% (0.00) (4.3)** (-1.84) τ =5% (0.00) (5.57)** (-.46)** τ =50% (3.63)** (10.18)** (-5.56)** τ =75% (5.67)** (8.50)** (-6.4)** τ =90% 1.30 (8.6)** 63.1 (8.76)** (-7.35)** Ths able repors he followng regresson resuls for Chna resdenal housng marke: 1 m, m,. Where m, s he cross seconal average reurn, and s he cross seconal absolue devaons of reurns. The sample perod s from Mar, 1998 o May, 013. **represens sascal sgnfcance a he 5% level. Table 5. Analyss of herdng n up and down markes by quanle regresson Marke γ 0,τ Up Marke Down Marke γ 1,τ γ 3,τ γ,τ γ 4,τ Pseudo γ 3 -γ 4 =0 χ τ =10% (0.00) (.88)** (-1.16) (1.90) (0.00) τ =5% ** (4.11)** (.63)** (-0.37) (0.58) (0.4) τ =50% ** (1.66) (3.59)** (-1.74) (0.61) (-0.59) τ =75% τ =90% 1.0 (3.17)** 1.4 (5.77)** (5.40)** (7.57)** (-3.43)** (-5.87)** (1.60) (3.74)** Ths able repors he followng regresson resuls for Chna resdenal housng marke: Q,, o, 1, ( 1 D) m,, D m, 3, (1 D) m, 4, Dm, (-1.59) (-3.76)** ** ** Where he dummy varable D=1 f m, <0 and D=0 f oherwse. m, s he cross seconal average reurn, and s he cross seconal absolue devaons of reurns. Sample perod s from Mar, 1998 o May, 013. χ s he Ch-squared sasc wh four degree of freedom for he Wald es. Numbers n parenheses are -sascs based on Newey-Wes(1987) conssen sandard errors.**represens sascal sgnfcance a he 5% level. 10

7 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; Asymmerc Effecs of Dfferen Marke Condons Usng he OLS mehod, we have found a negave sgn (γ 3 ) for he herdng coeffcen n up marke. However, he esmaed coeffcen of γ 3 s no sascally sgnfcan. The prevous resul shows ha here exss an asymmerc effec n he marke. Nex, we use Quanle regresson, he more robus mehod o examne wheher nvesors or buyers behave asymmercally wh up and down marke condons. To do so, he sample s dvded no an ncreasng or up marke reurn means m >0, and a decreasng or down marke reurn means m <0. The resuls are shown n Table 5. From he Quanle regresson (Buchnsky, 1998) resul, we can see ha when marke s rendng up, herdng would exs. Because of he up markes, nvesors saw profs all he me, and here are always have posve feedback on nvesng he housng marke. Therefore, he herdng s very sgnfcan durng hs me. One possble explanaon for an asymmery n herdng beween up and down markes s he flow of posve and negave nformaon. In Chna, he real esae developers end o ssue more buyng recommendaons acvely han sellng recommendaons, and housng buyers or nvesors have less knowledge and experence wh he reasonable house prces, and ac dfferenly on he recommendaons, bu when he marke prces drop down much quckly, we could observe more herdng n he down marke. Anoher possble explanaon s he Chna resdenal housng marke s known o be guded by governmen polcy; he Chnese governmen frequen nervenes n he asse markes when he house prces ncreases dramacally. In order o cool down he abnormal housng marke reurns, Chnese governmen rases neres raes sx mes whn sx monhs n year 011. The Naonal People s Congress (NPC) passed he 1 h fve year plan of n March 011. The cenral governmen ssued he regulaons ha local governmens should help buld up 36 mllon uns of publc housng n nex fve years. Frs er ces or provnces follow he src mplemenaons or regulaons. In Shangha and Chongqng, he local governmens announced he propery ax on ral bass, so resdens n hese wo ces pay axes on new resdenal housng purchases afer July, 011. Besdes ha, n Bejng he local governmen banned he sale of homes o hose who have no lved n Bejng for fve years. Bejng also lmed he number of homes a nave Bejng famly could own wo, and allowed only one home for non-nave Bejng famles. Comparng wh hese bg ces, oher second er ces or provnces ac on slowly. When he marke average reurn declne ( m <0), he herdng s sgnfcan n he marke. We also fnd an neresng resul s ha γ 4,τ acheves sgnfcan negave a hgh quanles. (e.g., τ =90%) The hgh quanle means he marke s more urbulen, and he marke-wde housng prces are havng bg movemens. As we dscussed before, n order o suppress he abnormal ncreasng of housng prces, he cenral governmen mposed src moneary polcy and varous mplemenaons, such as ncrease morgages rae and down paymen, banned more homes buyng naonwde, mposed propery axes for n bg ces, and buld up publc housng whn fve years ( ). Accordng o he CEIS (01) CEIS Hundred Ces Prce Index ha was publshed on Aprl 13 h, 01, was comparng wh Mar. 011, he overall prce of Chna One Hundred represenave ces decreased by 0.34%. There are egh monhs connuous decreasng of house prces rend snce Sep In hese 100 represenave ces, here are only 9 ces housng prces ncreases, and 71 ces housng prces decreases sgnfcanly. The emprcal resuls are correspondng wh he offcal news; shows ha durng he perods of exreme urbulen, he more volale condon, he more lkely he herdng behavor exss. Snce he local governmens are srcly mplemenng he cenral governmen housng prce conrol polcy, he more overall marke prces decrease, whch wll cause he more lkely o herd. 4.5 The Fnancal Crss on he Level of Herdng Behavor ecall ha herdng behavor may occur when he marke s hghly uncerany. Prevous academc papers nclude Zhou and Anderson (013), Chang and Zheng (010) and many research scholars have nvesgaed he magnude of he herdng behavor may be hgher durng a global fnancal crss snce he overall suaon s hghly unceran. Usng he cross counres sock markes daa, Chang and Zheng (010) confrm ha herdng behavor s more apparen for he developed counres and hs phenomenon s less obvous n developng counres durng he fnancal crss. Chrse and Huang (1995) sugges ha herdng wll be more prevalen durng he perods of marke sress. In hs secon, we need o use boh OLS and Q mehods o nvesgae he fnancal crss on he level of herdng behavor n Chna resdenal housng marke. As we have seen ha durng he global fnancal crss, here are exreme reurn movemens whch resuled n collapse of large fnancal nsuons, he balou of banks by naonal governmen, bankrupcy of mulnaonal companes, and worldwde sock markes downurns. In many counres, he housng markes are also suffered. 11

8 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 Because of prolonged unemploymen, a sgnfcan declne n global economy acvy, and declne n naonal czens wealh, marke sress evenually lead o a severe global economc recesson n 008. Alhough he global fnancal crss and downurns happened n 008 have brough emporary damage o he real esae marke and sock marke n Chna, Chnese cenral governmen and cenral bank responded wh unprecedened fscal smulus on November 9 h, 008. The Chnese economc smulus plans s a MB 4 rllon smulus package, whch s an aemp o mnmze he mpac of he global fnancal crss. The smulus provded funds for nfrasrucure projecs and housng developmens. Ths wll drve employmens n areas of manufacurng, seel, cemen and oher secors of he economy. Due o he success of he smulus plan, he cenral governmen n 011 has ghened regulaons n he fnancal sysems on banks o rase he morgage rae and reduce he fear of a propery bubble. The sample perod s se from Jan. 008 o Dec. 008 as he perod of fnancal crss. The years before 008 are esablshed as he perod before he fnancal crss, whle Jan., 009 o May, 013 s consdered o be he perod afer he fnancal crss. Table 6 and 7 llusrae he resuls by OLS and Q mehod respecvely. From Table 6, he marke appears o be rraonal before and afer he fnancal crss. The sgnfcan and larger negave coeffcen of herdng before he global fnancal crss shows ha Chna resdenal housng marke s exhbng herdng behavor. In conras, he herdng coeffcen s no sgnfcan durng he global fnancal crss. Furhermore, here s negave and sgnfcan coeffcen of herdng afer he crss. Accordng o our prevous dscusson, he OLS may be napproprae o examne he herdng, as we can see from he LM es for auocorrelaon, he es sascs sgnfcan ndcae auocorrelaon. Therefore, he OLS has es bas on he followng resuls. Table 6. The levels of herdng before, durng and afer he global fnancal crss by OLS Marke γ 0 Before Durng Afer γ 1 γ 4 γ γ 5 γ 3 γ 6 Monhly OLS 0.48 (5.57)** (11.45)** (-5.64)** 8.65 (0.4) 49.1 (-0.87) 34.4 (5.77)** (-.43)** 0.70 Seral Correlaon LM Tes: Obs*-squared: Prob.Ch-Square(1) Ths able repors he followng regresson resuls for Chna resdenal housng marke: 0 1D1 m D m 3D3 m 4D1m 5Dm 6D3 D1 represens he perod before he mos recen global fnancal crss (Mar.1998 Dec.007); D represens durng he crss self (Jan.008 Dec.008); and afer he crss (Jan.009 May, 013).The sample perod s from Mar, 1998 o May, 013. ** represens sascal sgnfcance a he 5% level. m In Table 7, we use Quanle regresson mehod o examne he resuls. The herdng coeffcen for he pre-crss perod γ 4 s found o be negave and sgnfcan durng he mos quanles. The evdence shows herdng exs before he fnancal crss akng place n Chna resdenal housng marke. Several addonal emprcal fndngs are also worh nong. Frs, durng he fnancal crss, he evdence suggess ha here s no herdng acvy n he marke. The reason s ha he fnancal crss ofen causes srucural break. The nvesors mgh raonalze hemselves away from a hgh loss durng a bad crcumsance and no o follow he marke sgnal o buy or sell houses. Second, urnng o he afer fnancal crss perod, he herdng coeffcen γ 6 s found o be negave bu no sgnfcan. Tha means here s also no herdng exsed afer fnancal crss. Ths s an neresng pon comparng wh OLS regresson. So based on he above resuls, he emprcal evdence seems conssen wh he prevous dscusson abou Chna economc smulus plans and cenral governmen announced varous src mplemenaons and regulaons on Chna housng marke. Because of he governmen effecve and effcency polcy measuremen durng he las hree years, he herdng phenomenon s no sgnfcan n he markes comparng wh he sronger herdng behavor before he global fnancal crss. The resuls are also oppose from he nernaonal asses markes, where he herdng behavor s more apparen n he crss perod. 1

9 Inernaonal Journal of Economcs and Fnance Vol. 6, No. ; 014 Table 7. The levels of herdng before, durng and afer he global fnancal crss by Q Marke γ 0 Before Durng Afer Pseudo γ 1 γ 4 γ γ 5 γ 3 γ 6 τ =10% (0.00) (4.74)** (-1.30) (1.40) (1.34) (3.77)** (-1.58) τ =5% (-76.90) 0.39 (0.53) (6.3)** (-.87)** (1.4) (-0.77) (.95)** (-1.06) τ =50% (3.5)** (5.96)** (-3.75)** (0.43) (1.9) (.99)** (-0.95) τ =75% (5.4)** (8.90)** (-6.96)** (-0.98) (.33) (8.88)** (-5.0) τ =90% 1.5 (8.58)** (8.5)** (-5.17)** (-3.47) (4.56) (9.9)** (-6.8)* 0.54 Ths able repors he followng regresson resuls for Chna resdenal housng marke: Q 0 1 D 1 m D m 3 D 3 m 4 D 1 m 5 D m 6 D 3 D1 represens he perod before he mos recen global fnancal crss (Mar Dec. 007); D represens durng he crss self (Jan. 008 Dec. 008); and afer he crss (Jan. 009 May, 013).The sample perod s from Mar, 1998 o May, 013. ** represens sascal sgnfcance a he 5% level. m 5. Conclusons Ths sudy examnes nvesor s herdng acvy across Chna 30 provnces and ces (Bejng, Tanjn, Shangha, Chongqng, Jln, Helongjang, Laonng, Hebe, Shandong, Jangsu, Zhejang, Fujan, Guangdong, Hanan, Guangx, Anhu, Jangx, Hube, Hunan, Schuan, Guzhou,Yunnan, Henan, Shaanx, Shanx, Inner Mongola, Gansu, Qngha, Nngxa and Xnjang) resdenal housng markes. To carry ou he nvesgaon, we apply monhly daa from Mar.1998 o May.013. We use Chang e al. (000, CCK) mehod o examne he herdng behavor. When he cross-seconal reurn dsperson () ncreases or decreases a a decreasng rae n response o an ncrease n he aggregae marke reurn, we wll have evdence o say here s herdng phenomena n he marke. By usng he quanle regresson mehod, we fnd ou he herdng n he full sample perods; furher, we fnd ha when here are ncreasng n marke reurn, he herdng s sronger. Durng a decreasng marke reurn, only n he perods of marke urbulen, he nvesors wll herd. Fnally, we also show ha durng and afer crss perod, he herdng phenomenon s no obvous n Chna resdenal housng marke. Herdng s more lkely o occur n pre-fnancal crss perod. Ths paper s mporan for hree man reasons. Frsly, o he bes of our knowledge, we are he frs o sudy he herdng phenomena n Chna resdenal housng marke across 30 provnces and ces by usng quanle regresson. Secondly, due o Chna resdenal housng marke unque characerscs, he herdng behavor n hs marke should be nvesgaed. Thrdly, our sudy provdes more mporance herdng behavor knowledge on Chna real esae marke o praconers, academa and polcymakers. Togeher, hese sudes and conrbuons ndcae ha s worhwhle o sudy he herdng phenomena for Chnese housng marke. eferences Banerjee, A. V. (199). A smple model of herd behavor. Quarerly Journal of Economcs, 57(3), hp://dx.do.org/10.307/ Barnes, M., & Hughes, A. W. (00). A quanle regresson analyss of he cross secon of sock marke reurns. Workng Paper, Federal eserve Bank of Boson. Bkhchandan, S., & Sharma, S. (000). Herd behavor n fnancal markes: A revew. Work paper. Inernaonal Moneary Funds.WP/00/48. ereved from hp:// Bkhchandan, S., Hrshlefer, D., & Welch, I. (199). A heory of fads, fashon, cusom, and culural change as nformaonal cascades. Journal of Polcal Economy, 100(5), hp://dx.do.org/10.307/13863 Buchnsky, M. (1998). ecen advances n quanle regresson models: A praccal gudelne for emprcal research. 13

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