Can Investors Hedge Residential Price Dynamics of Australia s Capital Cities?

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Can Investors Hedge Residential Price Dynamics of Australia s Capital Cities?"

Transcription

1 30 Can Invesors Hedge Residenial Price Dynamics? INTERNATIONAL REAL ESTATE REVIEW 200 Vol. 3 No. : pp Can Invesors Hedge Residenial Price Dynamics of Ausralia s Capial Ciies? Le Ma School of Archiecure and Building, Geelong Waerfron Campus, Deakin Universiy, Gheringhap Sree, Geelong, Vic 327, Ausralia; Tel: ; Fax: ; Chunlu Liu School of Archiecure and Building, Geelong Waerfron Campus, Deakin Universiy, Gheringhap Sree, Geelong, Vic 327, Ausralia; Tel: ; Fax: ; The sudy described in his paper focuses on esing he shor-run and long-run relaionships beween house price and consumer price indices in Ausralia s capial ciies from 998 o The auoregressive disribued lag model is adoped o obain he esimaes of he shor-run relaionships, while he error correcion model is used o invesigae he long-run relaionships. The -saisic is used o compue he significance of hese relaionships. The research resuls give no evidence ha house price indices are correlaed wih consumer price indices in he shor run. However, he long-run relaionships beween house and consumer price indices exis in mos of he ciies. Keywords House price indices; Consumer price indices; Auoregressive disribued lag model; Error correcion model Correspondence auhor

2 Ma and Liu 3. Inroducion Real esae is convenionally regarded as an efficien hedge agains price inflaion. In Ausralia, he increase rae in he house price index (HPI) has far oupaced he growh rae of he consumer price index (CPI), which is widely used o measure he inflaion rae. For example, he annual average percenage increase of he Ausralian HPI from 986 o 2006 was abou 7.5%, while he annual average CPI increase was abou 3.6% (ABS 2009a; ABS 2009b). Since Fama and Schwer (977) firs esimaed he inflaion-hedging characerisics of differen asses and argued ha real esae is a complee hedge agains inflaion, numerous sudies have analysed inflaion-hedging characerisics of real esae asses in differen counries and concluded wih various findings. I was found ha commercial propery does no hedge agains he inflaion rae in he shor run, bu a posiive correspondence exiss beween such propery and inflaion (Maysiak e al. 996). In anoher sudy, Newell (996) compares he hedging characerisics of Ausralian commercial properies wih differen ypes, places and marke facors, which indicae ha he hedging characerisics of Ausralian commercial properies would be differen. I was concluded ha commercial properies can provide a perfec hedge agains acual inflaion in he observed ciies; namely, Adelaide, Brisbane, Canberra, Melbourne, Perh and Sydney, during 984 o 995. The commercial properies in Adelaide, Brisbane and Canberra can also hedge expeced inflaion while he oher ciies are no able o do so. Moreover, excep for Canberra, he unexpeced inflaion hedging characerisics of he commercial properies are proven in he oher six ciies. Liu e al. (997) sudies he performance of real esae in foreign counries given securiy design differences, and he resuls show ha real esae securiies ac as an efficien hedge in some counries, bu inefficien in ohers. Barber e al. (997) find ha commercial properies can provide a hedge agains inflaion in some forms, based on an invesigaion of saisical similariies among UK commercial propery capial and renal values, and he price levels. The relaionship beween he reurn of real esae invesmen russ and inflaion is deemed o be a manifesaion of he effecs of changes in moneary policies (Glascock e al. 2002). Kolari (2002) examines he long-run impac of inflaion on homeowner equiy and concludes ha here is a long-run relaionship beween he house prices and he non-housing goods and services prices. Anoher research sudies he relaionships beween Ausralian housing dynamics and macroeconomic facors; namely, all ordinaries index, he real household disposable income per capia, rade-weighed exchange rae, consumer price index, unemploymen rae, and deached housing sock per capia (Abelson e al. 2005). The resuls showed ha he consumer price index has a posiive and significan impac on Ausralian housing dynamics. Newell (2007) shows ha srong risk-adjused reurns are delivered by boh direc indusrial propery and indusrial lis propery russ. Furher research on

3 32 Can Invesors Hedge Residenial Price Dynamics? Ausralian residenial propery invesmens indicae ha he main facors which drive he invesmens, are wealh-relaed facors raher han life-syle facors (Brown e al. 2008). Previous research has invesigaed relaionships beween house and consumer prices a naional levels raher han regional levels, alhough he laer is valuable for boh local governmen and invesors. The presen sudy esimaes he shor-run and long-run relaionships beween he HPI and CPI in Ausralia s capial ciies. The nex secion will inroduce he economeric heories used in he sudy, including he auoregressive disribued lag (ADL) model and he error correcion model (ECM) for building shor-run and longrun relaionships beween he HPI and CPI, respecively. The following secion presens he colleced daa and a summary of preliminary es resuls. The empirical resuls secion idenifies he parameers ha are applied o he analysis, and he shor-run and long-run relaionships beween he HPI and CPI of Ausralia s capial ciies. The conclusions of his sudy are provided in he final secion. 2. Economerical Models for Relaionship Analyses Beween he HPI and CPI The mehodology invesigaes he relaionships beween he HPI and CPI. Previous research shows ha a linear relaionship exiss beween he naural logarihm values of he house prices and he CPI, when he annual ren and discoun rae are consan (Kolari 2002). In he research of Kolari, he relaionship a period, beween house prices, HP, and consumer price index, CPI, is esimaed as: ln HP = (ln R lnr) + β lncpi, () where R and r, which are consans, sand for he annual ren and he discoun rae respecively. In his sudy, he HPI and CPI are used o esimae he relaionships beween house and consumer prices hrough economeric mehods. Mos of he economic daa is influenced by is pas values, and herefore, he ADL model is inroduced o esimae he regression. The ECM is also adoped o es wheher long-run relaionships exis beween he HPI and CPI. 2. ADL Model and Opimal Lags The ADL model is ofen inroduced o esimae he regression because mos ime series are auo-correlaed. The model is expressed as: Y m m = a+ bi Y i+ c i= i= X i + ε, (2)

4 Ma and Liu 33 where m is he opimal lag, a, b, and c are he esimaes, and ε is he residual erm. In his sudy, he ADL model is esimaed via he firs differenced ime series, hus Eq. (2) is rewrien as: where HPI and respecively, and c, n HPI = c + α HPI + β CPI + µ i i= i i n i CPI is he differencing HPI and CPI a period α, i β are esimaes, while i (3) µ is he error erm. The problem of esimaing he ADL model is deermining ways o choose he number of lags in he model. If here are no enough lags included, he esimaes will be biased and he saisics will be unreliable. If here are oo many lags included in he model, muli-collineariy may exis, which can make he -saisic unreliable (Gujarai 2003). The Akaike informaion crierion (AIC) (Akaike 974) and Schwarz Bayesian crieria (SBC) (Schwarz 978) are used o choose he opimal lags for he ADL model. The formulae for he AIC and SBC are: AIC = ( 2) ln( ML) + 2( p / n) (4) SBC = ( 2) ln( ML) + 2 ln n( p / n) (5) where ML represens he maximised likelihood esimaes of he model, while n is he number of observaions and p is he number of esimaes including he consan. In mos cases, ML could be calculaed as he sum of squared errors, known as he residual variaion (RSS). RSS represens wha he model canno explain or how closely he model fis he daa. If a model fis he daa well, he values of hese crieria should be small. Therefore, he judgemen of wheher he model is efficien is based on comparing he values of he crieria wih differen lenghs of lag. Including an exra lag could lead o an increase in p and decrease of he RSS. If he degree of decrease in RSS is greaer han he degree of increase of p, only hen will he value of hese crieria fall. 2.2 Error Correcion Model The long-run relaionships beween he HPI and CPI can be idenified by compuing a -saisic o deermine wheher he lagged HPI and CPI resul in significan coefficiens, as shown in he following ECM: n n i HPI i + βi CPI i + δhpi + ϕcpi i= HPI = c + α + µ If δ = ϕ= 0, no long-run relaionship exiss beween he HPI and CPI. Alernaively, if δ and ϕ are boh significanly differen from 0, he long-run relaionship exiss. (6)

5 34 Can Invesors Hedge Residenial Price Dynamics? 3. Hisorical Daa of House and Consumer Price Indices in Ausralia As menioned before, his sudy focuses on he relaionships beween he HPI and CPI in he eigh capial ciies of Ausralia. The HPIs are a series of price indices ha measure changes in he prices for each of he eigh capial ciies of Ausralia. Two ses of HPIs, which are indices for projec houses and esablished houses respecively, are published by he Ausralian Bureau of Saisics (ABS). The index for projec homes is compiled by he ABS for use in calculaing he house purchase expendiure class of he CPI, while he index for esablished houses does no conribue o he CPI, which is he one used in his sudy. The HPI is consruced wih reference o he curren and hisorical marke prices of he enire sock of residenial dwellings (ABS 2005; ABS 2009b). The CPI measures quarerly changes in he price of goods and services which accoun for a high proporion of expendiures by he CPI populaion group (ABS 2009a). The CPI covers a wide range of goods and services, which are arranged in eleven groups: food, alcohol and obacco, clohing and foowear, housing, household furnishings, supplies and services, healh, ransporaion, communicaion, recreaion, educaion, and miscellaneous. The housing expendiure ha conribues o he CPI is made up of rens, uiliies and oher housing, such as house purchases, propery raes, house mainenance and so on. The caalogue numbers of he wo indices are and respecively. The observaion period is from he March quarer of 998 o March quarer of Boh of hese wo indices were esablished quarerly and calculaed on he reference base =00. Figure describes he movemens of he HPI in he eigh Ausralian capial ciies. All HPIs have been increasing during he las decade. The HPI of Darwin has he highes rae of increase among he eigh ciies, while Hobar s HPI experiences he lowes increase. The HPI began o decline in Sydney afer 2004, while a huge increase came abou in Perh s HPI afer The HPI of he oher four ciies; namely Adelaide, Brisbane, Canberra and Melbourne, grew moderaely during 998 o Table describes he populaion and number of dwelling unis in he Ausralian capial ciies for he laes hree years. More han 60% of he Ausralian populaion live in he eigh capial ciies, especially in Sydney and Melbourne. From 2006 o 2008, he populaion increased by abou 6.88%, 5.49% and 5.47% in Brisbane, Darwin and Perh respecively, while he proporions in he oher five ciies were less han 4%.

6 Figure HPI of he Ausralian Eigh Capial Ciies from Ma and Liu 35 Ma and Liu 35

7 36 Can Invesors Hedge Residenial Price Dynamics? The monhly average numbers of dwelling unis in Adelaide and Melbourne coninued o increase from 2006 o 2008, while a huge decrease is eviden in Perh. Moreover, he number in Brisbane flucuaes significanly and moderae movemens are observed in Canberra, Darwin, Hobar and Sydney. Surprisingly, he dwelling number of Sydney, which has he larges populaion, is fourh afer Melbourne, Perh and Brisbane. Darwin has he lowes number during hese hree years. Table Populaion and he Monhly Average Number of Dwelling Unis in Eigh Capial Ciies Ciies Populaion Number of dwelling unis ADE BRI CAN DAR HOB MEL PER SYD Moreover, Table 2 shows he means and sandard deviaions of he HPI and CPI for each capial ciy. Over he observaion period, Darwin has he highes average HPI a , while Hobar has he lowes one, a During 998 o 2008, surprisingly, he house prices of residenial propery in Darwin have he highes increase, followed by Brisbane, Sydney and Melbourne, while he house prices in Hobar have he smalles growh. Aside from he housing assisance o Ausralians, such as home purchase assisance, he special housing assisance policy for he Aboriginal and Torres Srai Islander people may parly accoun for he huge increase of house prices in Darwin (ABS 2008). The sandard deviaion of HPI in Perh is he highes among he eigh ciies, and he lowes one is in Hobar. This indicaes ha he residenial propery marke of Perh has he highes price volailiy. One of he poenial reasons for he high volailiy in he Perh residenial housing marke is ha is marke has he highes rae of increase, which is abou 0.87% yearly during he decade. Paricularly during he December quarer of 2005 o December quarer of 2006, he residenial house prices of Perh increase by nearly 50%. On he oher hand, he house prices in ciies, where sandard deviaions are low, move moderaely. House prices in Hobar, Sydney and Melbourne are less volaile han he house prices in he oher capial ciies. The saisic values for he CPI vary lile from ciy o ciy, compared o he resuls of he

8 Ma and Liu 37 HPI. The highes average CPI is in Adelaide a 42.26, and he lowes one is in Darwin a The sandard deviaions for each ciy s CPI do no appear as differen from each oher as he average CPI. Adelaide has he highes sandard deviaion a 3.48, while Darwin has he lowes a.. Table 2 Saisics for HPI and CPI of Ausralia s Capial Ciies HPI CPI ADE BRI CAN DAR HOB MEL PER SYD Mean Min Max Sd. Dev Mean Min Max Sd. Dev Numerical Resuls 4. Saionary Tes A ime series is said o be saionary if is mean and variance are consan and he variance depends on he disance of wo ime periods. The saionary process plays an imporan role in he ime series analysis. I is difficul o generalise valuable informaion from is behaviour because he non-saionary ime series behaviour is unpredicable over ime. Before esimaing he model wih a ime series, i is imporan o es he saionariy of hese daa. A uni roo es is used o deec he variable saionariy and he order of inegraion. Three mehods are widely used; namely, he Dicky-Fuller uni roo es, he augmened Dicky-Fuller (ADF) uni roo es (Dicky and Fuller 979) and he Phillips-Perron uni roo es (Phillips and Perron 988). In his sudy, he ADF es is adoped o es he saionariy of he ime series. y = δy p + βi y i+ + e i = 2 p + βi y i+ + e β0 i = 2 y = δ y + (8) p y = δ y + βi y i + + e + β0 + β i= 2 (7) (9)

9 38 Can Invesors Hedge Residenial Price Dynamics? Eq. (7) is used o es wheher he ime series are non-saionary, because of a p β is he lagged values simple random walk. Where δ is he esimae, i= 2 i y i+ of o eliminae auocorrelaion from he equaion, and e is he error erm. y If δ is equal o 0, which means ha he daa is generaed by a random walk, i is proven ha he daa is non-saionary, while β in Eq. (8) represens a drif 0 and Eq. (9) is used when esing for he presence of boh he drif and rend, where he rend is expressed byβ. Table 3 is he summary of he ADF uni roo es resuls for HPI and CPI. According o he ADF es, none of he house price indices are saionary. However, a he firs difference, mos of hem become inegraed, excep hose in Brisbane and Darwin. Table 3 also shows ha consumer price indices of he eigh capial ciies are inegraed a he firs difference. 4.2 Selecion of Opimal Lags Since boh HPI and CPI are saionary a he firs difference, he ADL model can be esimaed wih hose differenced variables. Several lags are inroduced ino he model, in order o find he opimal lag. In his sudy, lags, 2, 3, and 4 are involved. The lag, wih which he model has he smalles value of he AIC and SBC, is deermined o be he opimal lag. Table 4 shows he AIC and SBC values wih differen lags for he eigh ciies. According o he values of he AIC, he ADL models for Brisbane and Canberra are efficien wih lag, while he daa of Adelaide, Perh and Sydney fi he model well when lag 2 is also included. Moreover, more lags (lag 3) are needed for Darwin, Melbourne and Hobar. On he oher hand, he SBC values for Adelaide, Brisbane and Canberra poin o lag while he values for Hobar, Melbourne, Perh and Sydney poin o lag 2. I is also indicaed ha lag 3 is needed for he model of Darwin. Since a large number of lags will lead o loss of freedom of he regression, he models for each of he eigh capial ciies are esimaed under he SBC crierion.

10 Ma and Liu 39 Table 3 Augmened Dicky-Fuller Tes for HPI and CPI of Ausralia s Capial Ciies ADE BRI CAN DAR HOB MEL PER SYD -es for level p-value HPI -es for firs difference p-value es for level p-value CPI -es for firs difference p-value Noes: es criical values: % level , 5% level , 0% level Ma and Liu 39

11 40 Can Invesors Hedge Residenial Price Dynamics? Table 4 Values of AIC and SBC of ADL Models for Ausralia s Capial Ciies AIC SBC Lag Lag 2 Lag 3 Lag 4 Lag Lag 2 Lag 3 Lag 4 ADE * * BRI 5.937* * CAN * * DAR * * HOB * * MEL * * PER * * SYD * * Noe: * indicaes he smalles values of AIC and SBC 4.3 Idenificaion of Relaionships beween he HPI and CPI of Ausralia s Capial Ciies The resuls show several characerisics of he relaionships beween he HPI and CPI. The esimaions and p-values of he -saisic of he esimaors are shown in Table 5. The ADL models for Adelaide, Brisbane and Canberra are esimaed wih one lag, while wo lags are inroduced in he models for Hobar, Melbourne, Perh, and Sydney. The model for Darwin is esimaed wih hree lags. In he firs row of he able, c denoes he consan, while α and β i ( i=, 2, and 3) sand for he correlaion coefficiens of he lagged movemens of he HPI and CPI respecively. The p-values of α sugges ha i he movemens of he HPI are influenced by hemselves significanly, in he shor run. The ciies of Adelaide, Brisbane, Canberra and Sydney have posiive relaionships wih he dynamics of HPI in he previous quarer. No only do he changes of he HPI in Perh have a posiive relaionship wih is value for he previous quarer, bu i also has a negaive relaionship wih he one quarer before he previous quarer. Hobar and Melbourne are influenced by he HPI dynamics a lag 2, while he HPI dynamics a lag 3 have a posiive significan influence in Darwin. According o he p-values of heβ i, none of he correlaion coefficiens of he HPI and CPI are significanly differen from 0 a he 5% criical level, alhough he coefficiens in he models for Hobar and Melbourne are significan a he 0% criical level. This implies ha shor-run relaionships beween he HPI and CPI do no exis in mos of Ausralia s capial ciies. i

12 Ma and Liu 4 Table 5 The Esimaes and he P-Values of he ADL Models for Ausralia s Capial Ciies ADE BRI CAN DAR HOB MEL PER SYD c α β α 2 β α 2 3 β 3 Esimaes n/a n/a n/a n/a p-value ** n/a n/a n/a n/a esimaes n/a n/a n/a n/a p-value ** n/a n/a n/a n/a esimaes n/a n/a n/a n/a p-value ** n/a n/a n/a n/a esimaes p-value ** esimaes n/a n/a p-value * ** n/a n/a esimaes n/a n/a p-value * ** n/a n/a esimaes n/a n/a p-value ** * n/a n/a esimaes n/a n/a p-value ** n/a n/a Noes: c denoes he esimaed consan in he regressions, α i and β i denoe he correlaion coefficiens of he lagged movemens of HPI and CPI. ** and * denoes ha he coefficiens are significanly differen from 0 a he 5% and 0% criical levels respecively. Ma and Liu 4

13 42 Can Invesors Hedge Residenial Price Dynamics? Table 6 shows he correlaion coefficiens of he lagged HPI and CPI Eq. (6) for each of he eigh capial ciies. The p-values of hese coefficiens can also be found in Table 6. The saisical es indicaes ha he coefficiens of he lagged HPI and CPI are significanly differen from 0 in he models for Adelaide, Brisbane, Canberra and Hobar a he 5% criical level. In he models for Melbourne and Sydney, hese relaionships only appear o be significan a he 0% criical level. Moreover, he coefficien of he CPI in he model for Darwin and he coefficien of he HPI in he model for Perh are no significanly differen from 0 even a he 0% criical level. This suggess ha long-run relaionships beween he HPI and CPI exis in he ciies of Adelaide, Brisbane, Canberra and Hobar. Weaker long-run relaionships are found in Melbourne and Sydney. The exisence of long-run relaionships beween he HPI and CPI canno be proven in Darwin and Perh. Table 6 Idenificaion of Long- run Relaionships of he HPI and CPI of Ausralia s Capial Ciies δ p-value ϕ p-value ADE ** ** BRI ** ** CAN ** ** DAR * HOB ** ** MEL * * PER * SYD ** * Noes: δ and ϕ denoe he correlaion coefficiens of he lagged HPI and CPI respecively. ** and * denoes ha he coefficiens are significanly differen from 0 a 5% and 0% criical levels respecively. The saisical resuls indicae ha from he March quarer of 998 o March quarer of 2008, he HPI does no correlae wih he CPI in mos Ausralian capial ciies, in he shor run. Weak shor-run relaionships can be found in Hobar and Melbourne. Long-run relaionships beween HPI and CPI are proven o exis in Adelaide, Brisbane, Canberra, Hobar, Melbourne and Sydney. This suggess ha he movemen of consumer prices is no an imporan facor in he dynamics of house prices in he shor run. In he long run, however, house prices in mos of Ausralia s capial ciies are correlaed wih consumer prices.

14 Ma and Liu Conclusion This paper has examined he shor-run and long-run relaionships beween he HPI and CPI in Ausralia s capial ciies. The ADL model and ECM are adoped o esimae he regressions, and he -saisic es is used o invesigae he significance of he shor-run and long-run relaionships. The empirical resuls and findings are discussed. In summary, he dynamics of he HPI srongly depend on heir pas values in he shor run. However, he lenghs of lags are differen in ciies. The movemens of he HPI in Adelaide, Brisbane, Canberra and Sydney are significanly impaced by he values in he previous quarer, while he HPI movemens in Hobar and Melbourne are impaced by he changes in he one quarer before he previous quarer. The movemens of he HPI in Perh are influenced no only by he values a lag, bu also by he values a lag 3. Darwin is he leas sensiive o he self-impac of he HPI, which is influenced by he HPI movemens of wo quarers before he previous quarer. The resuls of his sudy also indicae ha he relaionships beween he HPI and CPI are no saisically significan in mos of Ausralia s capial ciies in he shor run. This implies ha he inflaion risk may no be effecively hedged by shor-erm invesmen in Ausralian residenial real esae markes. Moreover, he resuls sugges ha inflaion hedging characerisics of Ausralian residenial properies vary across ciies in he long run. Invesors, herefore, may have o adop differen sraegies in differen markes. Since here is no evidence o suppor he exisence of long-run relaionships beween he HPI and CPI in he ciies of Darwin and Perh, he long-erm invesmens in hese wo residenial markes may no be a good choice for hedging he inflaion risk. As he relaionships are found o be significan in Adelaide, Brisbane, Canberra and Hobar, long erm invesors may selec he properies in hese markes as he inflaion hedges for invesmens. The weak long-run relaionships in Sydney and Melbourne reflec he uncerainy of inflaion hedges in hese wo larges residenial propery markes in Ausralia and hey are jus regarded as a diversified long-erm invesmen opporuniy.

15 44 Can Invesors Hedge Residenial Price Dynamics? Reference Abelson, P., Joyeux, R., Milunnovich, G. and Chung, D. (2005). Explaining House Price in Ausralia: , The Economic Record, 8, 255, ABS (2005). Renovaing he Esablished House Price Index. from Documen (Rerieved in July 2009). ABS (2008). Year Book Ausralia from (Rerieved in July 2009). ABS (2009a). Consumer Price Index. from (Rerieved July 2009). ABS (2009b). House Price Indexes: Eigh Capial Ciies. from E3F?OpenDocumen (Rerieved July 2009). Akaike, H. (974). A New Look a he Saisical Model Idenificaion, IEEE Transacions on Auomaic Conrol, 9, 6, Barber, C., Roberson, D. and Sco, A. (997). Propery and Inflaion: The Hedging Characerisics Of U.K. Commercial Propery, , Journal of Real Esae Finance and Economics, 5,, Brown, R. M., Schwann, G. and Sco, C. (2008). Personal Residenial Real Esae Invesmen in Ausralia: Invesor Characerisics and Invesmen Parameers, Real Esae Economics, 36,, Dicky, D. A. and Fuller, W. A. (979). Disribuion of he Esimaors for Auoregressive Time Series wih a Uni Roo. Journal of he American Saisical Associaion, 74, 336, Fama, E. F. and Schwer, G. W. (977). Asse Reurns and Inflaion. Journal of Financial Economics, 5, 2, Glascock, J. L., Lu, C. and So, R. W. (2002). R.E.I.T. Reurns and Inflaion: Perverse or Reverse Causaliy Effecs, Journal of Real Esae Finance and Economics, 24, 3, Gujarai, D. N. (2003). Basic Economerics. Gary Burke, New York. Kolari, A. A. J. (2002). House Prices and Inflaion, Real Esae Economics, 30,,

16 Ma and Liu 45 Liu, C. H., Harzell, D. J. and Hoesli, M. E. (997). Inernaional Evidence on Real Esae Securiies as an Inflaion Hedge, Real Esae Economics, 25, 2, Maysiak, G., Hoesli, M., MacGregor, B. and Nanhakumaran, N. (996). The Long-erm Inflaion-hedging Characerisics of UK Commercial Propery, Journal of Propery Finance, 7,, Newell, G. (996). The Inflaion-Hedging Characerisics of Ausralian Commercial Propery: , Journal of Propery Finance, 7,, Newell, G. (2007). The Significance and Performance of Indusrial Invesmen Propery in Ausralia, Pacific Rim Propery Research Journal, 3, 3, Phillips, P. C. B. and Perron, P. (988). Tesing for a Uni Roo in Time Series Regression, Biomerica, 75, 2, Schwarz, G. (978). Esimaing he Dimension of a Model, Annals of Saisics, 6, 2,

INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS

INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS Ilona Tregub, Olga Filina, Irina Kondakova Financial Universiy under he Governmen of he Russian Federaion 1. Phillips curve In economics,

More information

Cointegration: The Engle and Granger approach

Cointegration: The Engle and Granger approach Coinegraion: The Engle and Granger approach Inroducion Generally one would find mos of he economic variables o be non-saionary I(1) variables. Hence, any equilibrium heories ha involve hese variables require

More information

Cointegration Analysis of Exchange Rate in Foreign Exchange Market

Cointegration Analysis of Exchange Rate in Foreign Exchange Market Coinegraion Analysis of Exchange Rae in Foreign Exchange Marke Wang Jian, Wang Shu-li School of Economics, Wuhan Universiy of Technology, P.R.China, 430074 Absrac: This paper educed ha he series of exchange

More information

Forecasting Malaysian Gold Using. GARCH Model

Forecasting Malaysian Gold Using. GARCH Model Applied Mahemaical Sciences, Vol. 7, 2013, no. 58, 2879-2884 HIKARI Ld, www.m-hikari.com Forecasing Malaysian Gold Using GARCH Model Pung Yean Ping 1, Nor Hamizah Miswan 2 and Maizah Hura Ahmad 3 Deparmen

More information

Vector Autoregressions (VARs): Operational Perspectives

Vector Autoregressions (VARs): Operational Perspectives Vecor Auoregressions (VARs): Operaional Perspecives Primary Source: Sock, James H., and Mark W. Wason, Vecor Auoregressions, Journal of Economic Perspecives, Vol. 15 No. 4 (Fall 2001), 101-115. Macroeconomericians

More information

SPECIAL REPORT May 4, Shifting Drivers of Inflation Canada versus the U.S.

SPECIAL REPORT May 4, Shifting Drivers of Inflation Canada versus the U.S. Paul Ferley Assisan Chief Economis 416-974-7231 paul.ferley@rbc.com Nahan Janzen Economis 416-974-0579 nahan.janzen@rbc.com SPECIAL REPORT May 4, 2010 Shifing Drivers of Inflaion Canada versus he U.S.

More information

Impact of Debt on Primary Deficit and GSDP Gap in Odisha: Empirical Evidences

Impact of Debt on Primary Deficit and GSDP Gap in Odisha: Empirical Evidences S.R. No. 002 10/2015/CEFT Impac of Deb on Primary Defici and GSDP Gap in Odisha: Empirical Evidences 1. Inroducion The excessive pressure of public expendiure over is revenue receip is financed hrough

More information

House Price Index (HPI)

House Price Index (HPI) House Price Index (HPI) The price index of second hand houses in Colombia (HPI), regisers annually and quarerly he evoluion of prices of his ype of dwelling. The calculaion is based on he repeaed sales

More information

Chapter 8: Regression with Lagged Explanatory Variables

Chapter 8: Regression with Lagged Explanatory Variables Chaper 8: Regression wih Lagged Explanaory Variables Time series daa: Y for =1,..,T End goal: Regression model relaing a dependen variable o explanaory variables. Wih ime series new issues arise: 1. One

More information

Usefulness of the Forward Curve in Forecasting Oil Prices

Usefulness of the Forward Curve in Forecasting Oil Prices Usefulness of he Forward Curve in Forecasing Oil Prices Akira Yanagisawa Leader Energy Demand, Supply and Forecas Analysis Group The Energy Daa and Modelling Cener Summary When people analyse oil prices,

More information

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005 FONDATION POUR LES ETUDES ET RERS LE DEVELOPPEMENT INTERNATIONAL Measuring macroeconomic volailiy Applicaions o expor revenue daa, 1970-005 by Joël Cariolle Policy brief no. 47 March 01 The FERDI is a

More information

An empirical analysis about forecasting Tmall air-conditioning sales using time series model Yan Xia

An empirical analysis about forecasting Tmall air-conditioning sales using time series model Yan Xia An empirical analysis abou forecasing Tmall air-condiioning sales using ime series model Yan Xia Deparmen of Mahemaics, Ocean Universiy of China, China Absrac Time series model is a hospo in he research

More information

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Invesmen Managemen and Financial Innovaions, Volume 4, Issue 3, 7 33 DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Ahanasios

More information

YTM is positively related to default risk. YTM is positively related to liquidity risk. YTM is negatively related to special tax treatment.

YTM is positively related to default risk. YTM is positively related to liquidity risk. YTM is negatively related to special tax treatment. . Two quesions for oday. A. Why do bonds wih he same ime o mauriy have differen YTM s? B. Why do bonds wih differen imes o mauriy have differen YTM s? 2. To answer he firs quesion les look a he risk srucure

More information

Lecture 12 Assumption Violation: Autocorrelation

Lecture 12 Assumption Violation: Autocorrelation Major Topics: Definiion Lecure 1 Assumpion Violaion: Auocorrelaion Daa Relaionship Represenaion Problem Deecion Remedy Page 1.1 Our Usual Roadmap Parial View Expansion of Esimae and Tes Model Sep Analyze

More information

Revisions to Nonfarm Payroll Employment: 1964 to 2011

Revisions to Nonfarm Payroll Employment: 1964 to 2011 Revisions o Nonfarm Payroll Employmen: 1964 o 2011 Tom Sark December 2011 Summary Over recen monhs, he Bureau of Labor Saisics (BLS) has revised upward is iniial esimaes of he monhly change in nonfarm

More information

Chapter 8 Student Lecture Notes 8-1

Chapter 8 Student Lecture Notes 8-1 Chaper Suden Lecure Noes - Chaper Goals QM: Business Saisics Chaper Analyzing and Forecasing -Series Daa Afer compleing his chaper, you should be able o: Idenify he componens presen in a ime series Develop

More information

Part 1: White Noise and Moving Average Models

Part 1: White Noise and Moving Average Models Chaper 3: Forecasing From Time Series Models Par 1: Whie Noise and Moving Average Models Saionariy In his chaper, we sudy models for saionary ime series. A ime series is saionary if is underlying saisical

More information

... t t t k kt t. We assume that there are observations covering n periods of time. Autocorrelation (also called

... t t t k kt t. We assume that there are observations covering n periods of time. Autocorrelation (also called Supplemen 13B: Durbin-Wason Tes for Auocorrelaion Modeling Auocorrelaion Because auocorrelaion is primarily a phenomenon of ime series daa, i is convenien o represen he linear regression model using as

More information

Chapter 7: Estimating the Variance of an Estimate s Probability Distribution

Chapter 7: Estimating the Variance of an Estimate s Probability Distribution Chaper 7: Esimaing he Variance of an Esimae s Probabiliy Disribuion Chaper 7 Ouline Review o Clin s Assignmen o General Properies of he Ordinary Leas Squares (OLS) Esimaion Procedure o Imporance of he

More information

Price elasticity of demand for crude oil: estimates for 23 countries

Price elasticity of demand for crude oil: estimates for 23 countries Price elasiciy of demand for crude oil: esimaes for 23 counries John C.B. Cooper Absrac This paper uses a muliple regression model derived from an adapaion of Nerlove s parial adjusmen model o esimae boh

More information

Lecture 18. Serial correlation: testing and estimation. Testing for serial correlation

Lecture 18. Serial correlation: testing and estimation. Testing for serial correlation Lecure 8. Serial correlaion: esing and esimaion Tesing for serial correlaion In lecure 6 we used graphical mehods o look for serial/auocorrelaion in he random error erm u. Because we canno observe he u

More information

Economics 140A Hypothesis Testing in Regression Models

Economics 140A Hypothesis Testing in Regression Models Economics 140A Hypohesis Tesing in Regression Models While i is algebraically simple o work wih a populaion model wih a single varying regressor, mos populaion models have muliple varying regressors 1

More information

PRICE VOLATILITY ON THE USD/JPY MARKET AS A MEASURE OF INVESTORS ATTITUDE TOWARDS RISK

PRICE VOLATILITY ON THE USD/JPY MARKET AS A MEASURE OF INVESTORS ATTITUDE TOWARDS RISK QUANTITATIVE METHODS IN ECONOMICS Vol. XI, No. 1, 010, pp. 37-44 PRICE VOLATILITY ON THE USD/JPY MARKET AS A MEASURE OF INVESTORS ATTITUDE TOWARDS RISK Kaarzyna Banasiak Deparmen of Economics of Agriculure

More information

Economic Factors in Determining the Penetration Coefficient of Mobile Phone in Iran

Economic Factors in Determining the Penetration Coefficient of Mobile Phone in Iran Iranian Economic Review, Vol.5, No.26, Spring 200 Economic Facors in Deermining he Peneraion Coefficien of Mobile Phone in Iran Mansour Khalili Araghi Ghahreman Abdoli Absrac n his paper we have sudied

More information

A Brief Introduction to the Consumption Based Asset Pricing Model (CCAPM)

A Brief Introduction to the Consumption Based Asset Pricing Model (CCAPM) A Brief Inroducion o he Consumpion Based Asse Pricing Model (CCAPM We have seen ha CAPM idenifies he risk of any securiy as he covariance beween he securiy's rae of reurn and he rae of reurn on he marke

More information

Issues Using OLS with Time Series Data. Time series data NOT randomly sampled in same way as cross sectional each obs not i.i.d

Issues Using OLS with Time Series Data. Time series data NOT randomly sampled in same way as cross sectional each obs not i.i.d These noes largely concern auocorrelaion Issues Using OLS wih Time Series Daa Recall main poins from Chaper 10: Time series daa NOT randomly sampled in same way as cross secional each obs no i.i.d Why?

More information

Advanced time-series analysis (University of Lund, Economic History Department)

Advanced time-series analysis (University of Lund, Economic History Department) Advanced ime-series analysis (Universiy of Lund, Economic Hisory Deparmen) 30 Jan-3 February and 6-30 March 01 Lecure Uni-roo esing and he consequences of non-saionariy on regression analysis..a. Why is

More information

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART TWO

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART TWO Profi Tes Modelling in Life Assurance Using Spreadshees, par wo PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART TWO Erik Alm Peer Millingon Profi Tes Modelling in Life Assurance Using Spreadshees,

More information

Graphing the Von Bertalanffy Growth Equation

Graphing the Von Bertalanffy Growth Equation file: d:\b173-2013\von_beralanffy.wpd dae: Sepember 23, 2013 Inroducion Graphing he Von Beralanffy Growh Equaion Previously, we calculaed regressions of TL on SL for fish size daa and ploed he daa and

More information

GRANGER CAUSALITY RELATION BETWEEN INTEREST RATES AND STOCK MARKETS: EVIDENCE FROM EMERGING MARKETS

GRANGER CAUSALITY RELATION BETWEEN INTEREST RATES AND STOCK MARKETS: EVIDENCE FROM EMERGING MARKETS GRANGER CAUSALITY RELATION BETWEEN INTEREST RATES AND STOCK MARKETS: EVIDENCE FROM EMERGING MARKETS Assoc. Prof. Dilek Leblebici Teker (Corresponding Auhor) Isık Universiy Deparmen of Managemen dilek.eker@isikun.edu.r

More information

Association Between Asian Equity Markets and Western Markets: Evidence from the Indexes of Equity Markets

Association Between Asian Equity Markets and Western Markets: Evidence from the Indexes of Equity Markets Universiy of Rhode Island DigialCommons@URI College of Business Adminisraion Faculy Publicaions College of Business Adminisraion 2013 Associaion Beween Asian Equiy Markes and Wesern Markes: Evidence from

More information

A DCC Analysis of Two Stock Market Returns Volatility with an Oil Price Factor: An Evidence Study of Singapore and Thailand s Stock Markets

A DCC Analysis of Two Stock Market Returns Volatility with an Oil Price Factor: An Evidence Study of Singapore and Thailand s Stock Markets Journal of Convergence Informaion Technology Volume 4, Number 1, March 9 A DCC Analysis of Two Sock Marke Reurns Volailiy wih an Oil Price Facor: An Evidence Sudy of Singapore and Thailand s Sock Markes

More information

Purchasing Power Parity (PPP), Sweden before and after EURO times

Purchasing Power Parity (PPP), Sweden before and after EURO times School of Economics and Managemen Purchasing Power Pariy (PPP), Sweden before and afer EURO imes - Uni Roo Tes - Coinegraion Tes Masers hesis in Saisics - Spring 2008 Auhors: Mansoor, Rashid Smora, Ami

More information

Why Do Real and Nominal. Inventory-Sales Ratios Have Different Trends?

Why Do Real and Nominal. Inventory-Sales Ratios Have Different Trends? Why Do Real and Nominal Invenory-Sales Raios Have Differen Trends? By Valerie A. Ramey Professor of Economics Deparmen of Economics Universiy of California, San Diego and Research Associae Naional Bureau

More information

4. International Parity Conditions

4. International Parity Conditions 4. Inernaional ariy ondiions 4.1 urchasing ower ariy he urchasing ower ariy ( heory is one of he early heories of exchange rae deerminaion. his heory is based on he concep ha he demand for a counry's currency

More information

Journal Of Business & Economics Research Volume 1, Number 11

Journal Of Business & Economics Research Volume 1, Number 11 Profis From Buying Losers And Selling Winners In The London Sock Exchange Anonios Anoniou (E-mail: anonios.anoniou@durham.ac.ak), Universiy of Durham, UK Emilios C. Galariois (E-mail: emilios.galariois@dirham.ac.uk),

More information

Time Series Analysis Using SAS R Part I The Augmented Dickey-Fuller (ADF) Test

Time Series Analysis Using SAS R Part I The Augmented Dickey-Fuller (ADF) Test ABSTRACT Time Series Analysis Using SAS R Par I The Augmened Dickey-Fuller (ADF) Tes By Ismail E. Mohamed The purpose of his series of aricles is o discuss SAS programming echniques specifically designed

More information

Exploring the Causality Relationship between Trade Liberalization, Human Capital and Economic Growth: Empirical Evidence from Pakistan

Exploring the Causality Relationship between Trade Liberalization, Human Capital and Economic Growth: Empirical Evidence from Pakistan Exploring he Causaliy Relaionship beween Trade Liberalizaion, Human Capial and Economic Growh: Empirical Evidence from Pakisan Dr. Imran Sharif Chaudhry Associae Professor of Economics a Bahauddin Zakariya

More information

CAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND EXCHANGE RATE, FOREIGN EXCHANGE RESERVES AND VALUE OF TRADE BALANCE: A CASE STUDY FOR INDIA

CAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND EXCHANGE RATE, FOREIGN EXCHANGE RESERVES AND VALUE OF TRADE BALANCE: A CASE STUDY FOR INDIA CAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND EXCHANGE RATE, FOREIGN EXCHANGE RESERVES AND VALUE OF TRADE BALANCE: A CASE STUDY FOR INDIA BASABI BHATTACHARYA & JAYDEEP MUKHERJEE Reader, Deparmen of Economics,

More information

Relationships between Stock Prices and Accounting Information: A Review of the Residual Income and Ohlson Models. Scott Pirie* and Malcolm Smith**

Relationships between Stock Prices and Accounting Information: A Review of the Residual Income and Ohlson Models. Scott Pirie* and Malcolm Smith** Relaionships beween Sock Prices and Accouning Informaion: A Review of he Residual Income and Ohlson Models Sco Pirie* and Malcolm Smih** * Inernaional Graduae School of Managemen, Universiy of Souh Ausralia

More information

Estimating Time-Varying Equity Risk Premium The Japanese Stock Market 1980-2012

Estimating Time-Varying Equity Risk Premium The Japanese Stock Market 1980-2012 Norhfield Asia Research Seminar Hong Kong, November 19, 2013 Esimaing Time-Varying Equiy Risk Premium The Japanese Sock Marke 1980-2012 Ibboson Associaes Japan Presiden Kasunari Yamaguchi, PhD/CFA/CMA

More information

ElectricityConsumptionandEconomicGrowthinBangladeshCo-IntegrationandCausalityAnalysis

ElectricityConsumptionandEconomicGrowthinBangladeshCo-IntegrationandCausalityAnalysis Global Journal of Managemen and Business Research Volume 12 Issue 11 Version 1.0 July 2012 Type: Double Blind Peer Reviewed Inernaional Research Journal Publisher: Global Journals Inc. (US) Online ISSN:

More information

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Profi Tes Modelling in Life Assurance Using Spreadshees PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Erik Alm Peer Millingon 2004 Profi Tes Modelling in Life Assurance Using Spreadshees

More information

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya.

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya. Principal componens of sock marke dynamics Mehodology and applicaions in brief o be updaed Andrei Bouzaev, bouzaev@ya.ru Why principal componens are needed Objecives undersand he evidence of more han one

More information

Inflation and Growth: An Estimate of the Threshold Level of Inflation in Pakistan

Inflation and Growth: An Estimate of the Threshold Level of Inflation in Pakistan SBP-Research Bullein Volume 1, Number 1, 2005 Inflaion and Growh: An Esimae of he Threshold Level of Inflaion in Pakisan Yasir Ali Mubarik This sudy esimaes he hreshold level of inflaion in Pakisan [à

More information

The naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1

The naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1 Business Condiions & Forecasing Exponenial Smoohing LECTURE 2 MOVING AVERAGES AND EXPONENTIAL SMOOTHING OVERVIEW This lecure inroduces ime-series smoohing forecasing mehods. Various models are discussed,

More information

A Dollar or Yen Currency Union in East Asia. Lee K. Lim. School of Accounting, Finance and Economics Edith Cowan University

A Dollar or Yen Currency Union in East Asia. Lee K. Lim. School of Accounting, Finance and Economics Edith Cowan University A Dollar or Yen Currency Union in Eas Asia By Lee K. Lim School of Accouning, Finance and Economics Edih Cowan Universiy School of Accouning, Finance and Economics & FIMARC Working Paper Series Edih Cowan

More information

Market Liquidity and the Impacts of the Computerized Trading System: Evidence from the Stock Exchange of Thailand

Market Liquidity and the Impacts of the Computerized Trading System: Evidence from the Stock Exchange of Thailand 36 Invesmen Managemen and Financial Innovaions, 4/4 Marke Liquidiy and he Impacs of he Compuerized Trading Sysem: Evidence from he Sock Exchange of Thailand Sorasar Sukcharoensin 1, Pariyada Srisopisawa,

More information

Multiple Structural Breaks in the Nominal Interest Rate and Inflation in Canada and the United States

Multiple Structural Breaks in the Nominal Interest Rate and Inflation in Canada and the United States Deparmen of Economics Discussion Paper 00-07 Muliple Srucural Breaks in he Nominal Ineres Rae and Inflaion in Canada and he Unied Saes Frank J. Akins, Universiy of Calgary Preliminary Draf February, 00

More information

College of Business, Hospitality & Tourism Studies. School of Economics, Banking and Finance. Working Paper Series. No. 01/14

College of Business, Hospitality & Tourism Studies. School of Economics, Banking and Finance. Working Paper Series. No. 01/14 College of Business, Hospialiy & Tourism Sudies School of Economics, Banking and Finance Working aper Series No. 01/14 Tile Conribuion of Foreign Direc Invesmen o Tourism Secor in Fiji: An Empirical Sudy

More information

Cannibalization and Product Life Cycle Management

Cannibalization and Product Life Cycle Management Middle-Eas Journal of Scienific Research 19 (8): 1080-1084, 2014 ISSN 1990-9233 IDOSI Publicaions, 2014 DOI: 10.5829/idosi.mejsr.2014.19.8.11868 Cannibalizaion and Produc Life Cycle Managemen Ali Farrukh

More information

Financial Integration of Large- and Small-cap Stocks in Emerging Markets

Financial Integration of Large- and Small-cap Stocks in Emerging Markets Financial Inegraion of Large- and Small-cap Socks in Emerging Markes Ming-Chieh Wang * Associae Professor, Deparmen of Inernaional Business Sudies, Naional Chi-Nan Universiy Absrac This sudy examines he

More information

MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR

MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR The firs experimenal publicaion, which summarised pas and expeced fuure developmen of basic economic indicaors, was published by he Minisry

More information

Causal Relationship between Macro-Economic Indicators and Stock Market in India

Causal Relationship between Macro-Economic Indicators and Stock Market in India Asian Journal of Finance & Accouning Causal Relaionship beween Macro-Economic Indicaors and Sock Marke in India Dr. Naliniprava ripahy Associae Professor (Finance), Indian Insiue of Managemen Shillong

More information

Determinants of Capital Structure: Comparison of Empirical Evidence from the Use of Different Estimators

Determinants of Capital Structure: Comparison of Empirical Evidence from the Use of Different Estimators Serrasqueiro and Nunes, Inernaional Journal of Applied Economics, 5(1), 14-29 14 Deerminans of Capial Srucure: Comparison of Empirical Evidence from he Use of Differen Esimaors Zélia Serrasqueiro * and

More information

CHARGE AND DISCHARGE OF A CAPACITOR

CHARGE AND DISCHARGE OF A CAPACITOR REFERENCES RC Circuis: Elecrical Insrumens: Mos Inroducory Physics exs (e.g. A. Halliday and Resnick, Physics ; M. Sernheim and J. Kane, General Physics.) This Laboraory Manual: Commonly Used Insrumens:

More information

Social Media Content on Financial Markets

Social Media Content on Financial Markets Inernaional Journal of New Technology and Research (IJNTR) ISSN:2454-4116, Volume-2, Issue-3, March 2016 Pages 134-137 Social Media Conen on Financial Markes Juheng Zhang Absrac Socks are weeed by invesors

More information

Stability. Coefficients may change over time. Evolution of the economy Policy changes

Stability. Coefficients may change over time. Evolution of the economy Policy changes Sabiliy Coefficiens may change over ime Evoluion of he economy Policy changes Time Varying Parameers y = α + x β + Coefficiens depend on he ime period If he coefficiens vary randomly and are unpredicable,

More information

The Real Business Cycle paradigm. The RBC model emphasizes supply (technology) disturbances as the main source of

The Real Business Cycle paradigm. The RBC model emphasizes supply (technology) disturbances as the main source of Prof. Harris Dellas Advanced Macroeconomics Winer 2001/01 The Real Business Cycle paradigm The RBC model emphasizes supply (echnology) disurbances as he main source of macroeconomic flucuaions in a world

More information

Inflation, exchange rates and interest rates in Ghana: An autoregressive distributed lag model

Inflation, exchange rates and interest rates in Ghana: An autoregressive distributed lag model Inernaional Journal of Scienific and Research Publicaions, Volume 5, Issue 1, January 215 1 ISSN 225-3153 Inflaion, exchange raes and ineres raes in Ghana: An auoregressive disribued lag model Dennis Nchor*,

More information

Working Paper nº 06/04

Working Paper nº 06/04 Faculad de Ciencias Económicas y Empresariales Universidad de Navarra Working Paper nº 06/04 Oil Prices, Economic Aciviy and Inflaion: Evidence for Some Asian Counries Juncal Cunado and Fernando Perez

More information

BALANCE OF PAYMENTS. First quarter 2008. Balance of payments

BALANCE OF PAYMENTS. First quarter 2008. Balance of payments BALANCE OF PAYMENTS DATE: 2008-05-30 PUBLISHER: Balance of Paymens and Financial Markes (BFM) Lena Finn + 46 8 506 944 09, lena.finn@scb.se Camilla Bergeling +46 8 506 942 06, camilla.bergeling@scb.se

More information

Time Series Modeling for Risk of Stock. Price with Value at Risk Computation

Time Series Modeling for Risk of Stock. Price with Value at Risk Computation Applied Mahemaical Sciences, Vol 9, 015, no 56, 779-787 HIKARI Ld, wwwm-hikaricom hp://dxdoiorg/101988/ams0155144 Time Series Modeling for Risk of Sock Price wih Value a Risk Compuaion Dodi Deviano, Maiyasri

More information

Applied Econometrics and International Development Vol.7-1 (2007)

Applied Econometrics and International Development Vol.7-1 (2007) Applied Economerics and Inernaional Developmen Vol.7- (7) THE INFLUENCE OF INTERNATIONAL STOCK MARKETS AND MACROECONOMIC VARIABLES ON THE THAI STOCK MARKET CHANCHARAT, Surachai *, VALADKHANI, Abbas HAVIE,

More information

Journal Of Business & Economics Research September 2005 Volume 3, Number 9

Journal Of Business & Economics Research September 2005 Volume 3, Number 9 Opion Pricing And Mone Carlo Simulaions George M. Jabbour, (Email: jabbour@gwu.edu), George Washingon Universiy Yi-Kang Liu, (yikang@gwu.edu), George Washingon Universiy ABSTRACT The advanage of Mone Carlo

More information

When Do TIPS Prices Adjust to Inflation Information?

When Do TIPS Prices Adjust to Inflation Information? When Do TIPS Prices Adjus o Inflaion Informaion? Quenin C. Chu a, *, Deborah N. Piman b, Linda Q. Yu c Augus 15, 2009 a Deparmen of Finance, Insurance, and Real Esae. The Fogelman College of Business and

More information

Title: Who Influences Latin American Stock Market Returns? China versus USA

Title: Who Influences Latin American Stock Market Returns? China versus USA Cenre for Global Finance Working Paper Series (ISSN 2041-1596) Paper Number: 05/10 Tile: Who Influences Lain American Sock Marke Reurns? China versus USA Auhor(s): J.G. Garza-García; M.E. Vera-Juárez Cenre

More information

MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jarita Duasa 1

MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jarita Duasa 1 Journal of Economic Cooperaion, 8, (007), 83-98 MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jaria Duasa 1 The objecive of he paper is wofold. Firs, is o examine causal relaionship

More information

The Impact of FDIs Flows on the Nigerien Economic Growth

The Impact of FDIs Flows on the Nigerien Economic Growth www.sciedu.ca/ijfr Inernaional Journal of Financial Research Vol. 2, No. 2; July 2011 The Impac of FDIs Flows on he Nigerien Economic Growh Ousseini Hamadou School of finance, Shanghai Universiy of Finance

More information

THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES

THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES Juan Ángel Lafuene Universidad Jaume I Unidad Predeparamenal de Finanzas y Conabilidad Campus del Riu Sec. 1080, Casellón

More information

Fair games, and the Martingale (or "Random walk") model of stock prices

Fair games, and the Martingale (or Random walk) model of stock prices Economics 236 Spring 2000 Professor Craine Problem Se 2: Fair games, and he Maringale (or "Random walk") model of sock prices Sephen F LeRoy, 989. Efficien Capial Markes and Maringales, J of Economic Lieraure,27,

More information

The Identification of the Response of Interest Rates to Monetary Policy Actions Using Market-Based Measures of Monetary Policy Shocks

The Identification of the Response of Interest Rates to Monetary Policy Actions Using Market-Based Measures of Monetary Policy Shocks The Idenificaion of he Response of Ineres Raes o Moneary Policy Acions Using Marke-Based Measures of Moneary Policy Shocks Daniel L. Thornon Federal Reserve Bank of S. Louis Phone (314) 444-8582 FAX (314)

More information

DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS

DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS Hong Mao, Shanghai Second Polyechnic Universiy Krzyszof M. Osaszewski, Illinois Sae Universiy Youyu Zhang, Fudan Universiy ABSTRACT Liigaion, exper

More information

Relationship between Stock Prices, Exchange Rate and Demand for Money in Pakistan

Relationship between Stock Prices, Exchange Rate and Demand for Money in Pakistan Middle Easern Finance and Economics ISSN: 1450-2889 Issue 3 (2009) EuroJournals Publishing, Inc. 2009 hp://www.eurojournals.com/mefe.hm Relaionship beween Sock Prices, Exchange Rae and Demand for Money

More information

Chapter 4. Properties of the Least Squares Estimators. Assumptions of the Simple Linear Regression Model. SR3. var(e t ) = σ 2 = var(y t )

Chapter 4. Properties of the Least Squares Estimators. Assumptions of the Simple Linear Regression Model. SR3. var(e t ) = σ 2 = var(y t ) Chaper 4 Properies of he Leas Squares Esimaors Assumpions of he Simple Linear Regression Model SR1. SR. y = β 1 + β x + e E(e ) = 0 E[y ] = β 1 + β x SR3. var(e ) = σ = var(y ) SR4. cov(e i, e j ) = cov(y

More information

Analysis on Influencing Factors on the Fluctuation of Commercial Housing Prices Based on ECM Model: Taking Changsha as an Example

Analysis on Influencing Factors on the Fluctuation of Commercial Housing Prices Based on ECM Model: Taking Changsha as an Example Advances in Naural Science Vol. 7, No. 4, 014, pp. 1-5 DOI:10.3968/6167 ISSN 1715-786 [PRINT] ISSN 1715-7870 [ONLINE] www.cscanada.ne www.cscanada.org Analysis on Influencing Facors on he Flucuaion of

More information

11/6/2013. Chapter 14: Dynamic AD-AS. Introduction. Introduction. Keeping track of time. The model s elements

11/6/2013. Chapter 14: Dynamic AD-AS. Introduction. Introduction. Keeping track of time. The model s elements Inroducion Chaper 14: Dynamic D-S dynamic model of aggregae and aggregae supply gives us more insigh ino how he economy works in he shor run. I is a simplified version of a DSGE model, used in cuing-edge

More information

CAUSAL RELATIONSHIP BETWEEN SAVINGS AND ECONOMIC GROWTH IN COUNTRIES WITH DIFFERENT INCOME LEVELS. Abstract

CAUSAL RELATIONSHIP BETWEEN SAVINGS AND ECONOMIC GROWTH IN COUNTRIES WITH DIFFERENT INCOME LEVELS. Abstract CAUSAL RELATIONSHIP BETWEEN SAVINGS AND ECONOMIC GROWTH IN COUNTRIES WITH DIFFERENT INCOME LEVELS. Ramesh Mohan Bryan Universiy Absrac This paper addresses he relaionship beween domesic savings and economic

More information

4. The Poisson Distribution

4. The Poisson Distribution Virual Laboraories > 13. The Poisson Process > 1 2 3 4 5 6 7 4. The Poisson Disribuion The Probabiliy Densiy Funcion We have shown ha he k h arrival ime in he Poisson process has he gamma probabiliy densiy

More information

Price-to-Earnings Ratios: Growth and Discount Rates

Price-to-Earnings Ratios: Growth and Discount Rates Price-o-Earnings Raios: Growh and Discoun Raes Andrew Ang Ann F. Kaplan Professor of Business Columbia Universiy Xiaoyan Zhang Associae Professor of Finance Kranner School of Managemen, Purdue Universiy

More information

Why Did the Demand for Cash Decrease Recently in Korea?

Why Did the Demand for Cash Decrease Recently in Korea? Why Did he Demand for Cash Decrease Recenly in Korea? Byoung Hark Yoo Bank of Korea 26. 5 Absrac We explores why cash demand have decreased recenly in Korea. The raio of cash o consumpion fell o 4.7% in

More information

Hedging with Forwards and Futures

Hedging with Forwards and Futures Hedging wih orwards and uures Hedging in mos cases is sraighforward. You plan o buy 10,000 barrels of oil in six monhs and you wish o eliminae he price risk. If you ake he buy-side of a forward/fuures

More information

The Relationship Between Consumer Sentiment and Stock Prices

The Relationship Between Consumer Sentiment and Stock Prices The Relaionship Beween Consumer Senimen and Sock Prices by Kevin P. Chris Assisan Professor of Economics, Rose-Hulman Insiue of Technology and Dale S. Bremmer Professor of Economics, Rose-Hulman Insiue

More information

The Greek financial crisis: growing imbalances and sovereign spreads. Heather D. Gibson, Stephan G. Hall and George S. Tavlas

The Greek financial crisis: growing imbalances and sovereign spreads. Heather D. Gibson, Stephan G. Hall and George S. Tavlas The Greek financial crisis: growing imbalances and sovereign spreads Heaher D. Gibson, Sephan G. Hall and George S. Tavlas The enry The enry of Greece ino he Eurozone in 2001 produced a dividend in he

More information

Investing in Gold: Individual Asset Risk in the Long Run

Investing in Gold: Individual Asset Risk in the Long Run CENTRAL BANK OF CYPRUS EUROSYSTEM WORKING PAPER SERIES Invesing in Gold: Individual Asse Risk in he Long Run Anonis Michis June 2014 Working Paper 2014-02 Cenral Bank of Cyprus Working Papers presen work

More information

Dynamic co-movement and correlations in fixed income markets: Evidence from selected emerging market bond yields

Dynamic co-movement and correlations in fixed income markets: Evidence from selected emerging market bond yields P Thupayagale* and I Molalapaa Dynamic co-movemen and correlaions in fixed income markes: Evidence from seleced emerging marke bond yield Dynamic co-movemen and correlaions in fixed income markes: Evidence

More information

A Note on Using the Svensson procedure to estimate the risk free rate in corporate valuation

A Note on Using the Svensson procedure to estimate the risk free rate in corporate valuation A Noe on Using he Svensson procedure o esimae he risk free rae in corporae valuaion By Sven Arnold, Alexander Lahmann and Bernhard Schwezler Ocober 2011 1. The risk free ineres rae in corporae valuaion

More information

Chapter 7. Response of First-Order RL and RC Circuits

Chapter 7. Response of First-Order RL and RC Circuits Chaper 7. esponse of Firs-Order L and C Circuis 7.1. The Naural esponse of an L Circui 7.2. The Naural esponse of an C Circui 7.3. The ep esponse of L and C Circuis 7.4. A General oluion for ep and Naural

More information

THE IMPACT OF INFLATION AND ECONOMIC GROWTH ON UNEMPLOYMENT

THE IMPACT OF INFLATION AND ECONOMIC GROWTH ON UNEMPLOYMENT The Impac of Inflaion and Economic Growh on Unemploymen 1 THE IMPACT OF INFLATION AND ECONOMIC GROWTH ON UNEMPLOYMENT The Impac of Inflaion and Economic Growh on Unemploymen: Time Series Evidence from

More information

International Business & Economics Research Journal March 2007 Volume 6, Number 3

International Business & Economics Research Journal March 2007 Volume 6, Number 3 Weak Form Efficiency In Indian Sock Markes Rakesh Gupa, (E-mail: r.gupa@cqu.edu.au), Cenral Queensland Universiy, Ausralia Parikshi K. Basu, (E-mail: pbasu@csu.edu.au), Charles Sur Universiy, Ausralia

More information

Online Open Access publishing platform for Management Research. Copyright 2010 All rights reserved Integrated Publishing association

Online Open Access publishing platform for Management Research. Copyright 2010 All rights reserved Integrated Publishing association ASIAN JOURNAL OF MANAGEMENT RESEARCH Online Open Access publishing plaform for Managemen Research Copyrigh 2010 All righs reserved Inegraed Publishing associaion Case Sudy ISSN 2229 3795 Global Financial

More information

Research Question Is the average body temperature of healthy adults 98.6 F? Introduction to Hypothesis Testing. Statistical Hypothesis

Research Question Is the average body temperature of healthy adults 98.6 F? Introduction to Hypothesis Testing. Statistical Hypothesis Inroducion o Hypohesis Tesing Research Quesion Is he average body emperaure of healhy aduls 98.6 F? HT - 1 HT - 2 Scienific Mehod 1. Sae research hypoheses or quesions. µ = 98.6? 2. Gaher daa or evidence

More information

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS RICHARD J. POVINELLI AND XIN FENG Deparmen of Elecrical and Compuer Engineering Marquee Universiy, P.O.

More information

The Influence of Positive Feedback Trading on Return Autocorrelation: Evidence for the German Stock Market

The Influence of Positive Feedback Trading on Return Autocorrelation: Evidence for the German Stock Market The Influence of Posiive Feedback Trading on Reurn Auocorrelaion: Evidence for he German Sock Marke Absrac: In his paper we provide empirical findings on he significance of posiive feedback rading for

More information

Appendix D Flexibility Factor/Margin of Choice Desktop Research

Appendix D Flexibility Factor/Margin of Choice Desktop Research Appendix D Flexibiliy Facor/Margin of Choice Deskop Research Cheshire Eas Council Cheshire Eas Employmen Land Review Conens D1 Flexibiliy Facor/Margin of Choice Deskop Research 2 Final Ocober 2012 \\GLOBAL.ARUP.COM\EUROPE\MANCHESTER\JOBS\200000\223489-00\4

More information

Wages and Unemployment. 1. Pre-Keynesian economics. Equilibrium in all markets, FE of labor in labor market equilibrium. 2. Keynes' revolution

Wages and Unemployment. 1. Pre-Keynesian economics. Equilibrium in all markets, FE of labor in labor market equilibrium. 2. Keynes' revolution Wages and Unemploymen 1. Pre-Keynesian economics Equilibrium in all markes, FE of labor in labor marke equilibrium 2. Keynes' revoluion 3. Inflaion His ideas developed in he hisorical conex of pos-wwi

More information

Supplementary Appendix for Depression Babies: Do Macroeconomic Experiences Affect Risk-Taking?

Supplementary Appendix for Depression Babies: Do Macroeconomic Experiences Affect Risk-Taking? Supplemenary Appendix for Depression Babies: Do Macroeconomic Experiences Affec Risk-Taking? Ulrike Malmendier UC Berkeley and NBER Sefan Nagel Sanford Universiy and NBER Sepember 2009 A. Deails on SCF

More information

Chapter 6: Business Valuation (Income Approach)

Chapter 6: Business Valuation (Income Approach) Chaper 6: Business Valuaion (Income Approach) Cash flow deerminaion is one of he mos criical elemens o a business valuaion. Everyhing may be secondary. If cash flow is high, hen he value is high; if he

More information

A Robust Exponentially Weighted Moving Average Control Chart for the Process Mean

A Robust Exponentially Weighted Moving Average Control Chart for the Process Mean Journal of Modern Applied Saisical Mehods Volume 5 Issue Aricle --005 A Robus Exponenially Weighed Moving Average Conrol Char for he Process Mean Michael B. C. Khoo Universii Sains, Malaysia, mkbc@usm.my

More information