A study of sale price and A study of sale price and marketing time for the marketing time for the new housing buildingnew housing building

Dr. Ming-Yi Huang Dr. Ming-Yi Huang

National Pingtung Institute of National Pingtung Institute of Commerce, Taiwan Commerce, Taiwan

1.1. In the past research, used houses are In the past research, used houses are targeted by most of literatures. targeted by most of literatures. Therefore, they can’t provide new Therefore, they can’t provide new housing buildings with reasonable housing buildings with reasonable explanation.explanation.

2.2. Transaction data of used house is Transaction data of used house is mainly a single product and new mainly a single product and new housing building is a set of combined housing building is a set of combined productproduct

IntroductionIntroduction

New housing building V.S Used houseNew housing building V.S Used house

Item New housing building Used house

Quantity80 units

one unit20F / 4 units on every floor

Age Zero Over one transaction

Quality Homogeneous Heterogeneous

Product combination

Room 2r, 3r, 4r

－Price Low, Middle, High

Area Low, Middle, High

Picture

3.3. There are many differences between a There are many differences between a new housing building sold by developer new housing building sold by developer and a used house sold by the real estate and a used house sold by the real estate brokerage.brokerage.

4.4. The study focuses how to sell all product The study focuses how to sell all product of new housing building in the shortest of new housing building in the shortest time and position room combination time and position room combination ratio, price and area?ratio, price and area?

5.5. When room combination ratio, price and When room combination ratio, price and area deviate from normal distribution, area deviate from normal distribution, does the distance of deviation influence does the distance of deviation influence sales time of a new housing building?sales time of a new housing building?

MethodologyMethodologyDataData The new housing building located in The new housing building located in

Kaohsiung, the second metropolis in Kaohsiung, the second metropolis in Taiwan.Taiwan.

192 samples collected from 2001 to 2006.192 samples collected from 2001 to 2006.

Model Model K-mean method of cluster analysis K-mean method of cluster analysis

Formula of measuring Formula of measuring deviationdeviation

where Xβi is the proportion of room I, Xαi is the proportion of normal room I

Simultaneous-equation modelSimultaneous-equation model

2

1

2

n

iii XXd

118171615

1413121110

FLOORDEVELOPERYCLE

UTILITYPARKINGREAOC

TMC

ALP

231

3029282726

252423222120

SUM

ADISTISTOOMISTFLA

YCLEPARKINGREAOC

PDRPD

CEALTM

(1)

(2)

List of variables List of variables

Variable Description

LOC Number of parks and schools within a radius of 500 m2

TIME(TM) Marketing time, days

PRICE(P) Sales price, USD

DEVELOPER

Type of developer of a new housing building. Famous developer, DEVELOPER=1, otherwise DEVELOPER=0; Normal DEVELOPER, DEVELOPER=1, otherwise DEVELOPER=0; base on new DEVELOPER.

PDIST The distance of price which deviates from normal housing

AREA Total floor area of one unit; m2

FLA Total floor area of a new housing building; m2

UTILITY Total area of public space / Total floor area of a new housing building,%

PARKING Parking space / total units of a new housing building,%

CYCLE Business cycle index

FLOOR Number of floor heights

ROOMDIST The distance of room combination ratio which deviates from normal housing

SUM Total sales amount

ADIST The distance of area which deviates from normal housing

Descriptive Statistics (N=192)Descriptive Statistics (N=192)

Item Mean Std. Deviation

PRICE(USD / m2) 1,140.7928 2.31092

AREA(m2) 126.5860 11.06625

2 ROOM(%) .2521 .25822

3 ROOM(%) .4208 .23188

4 ROOM(%) .3262 .31022

PARKING(%) .7421 .14095

UTILITY(%) .3102 .02265

TIME(DAY) 247.33 212.409

LOC 1.46 .970

CYCLE 131.6333 14.74092

NEW DEVELOPER 0.28 0.45

NORMAL DEVELOPER 0.49 0.50

MODERATE DEVELOPER 0.22 0.42

2 ROOMA(m2) 82.5033 3.1523

3 ROOMA(m2) 120.978 4.7752

4 ROOMA(m2) 169.8906 11.7970

FLA(m2) 24,949.221 4,697.432

SUM(USD) 20,987,000 5.471

FLOOR 14.55 2.755

Empirical resultsEmpirical results

Variable TypeCluster

F Sig.Cluster A Cluster B Cluster C

Area

2ROOM 81.51 89.1 139.59 56.267 0.000***

3ROOM 117.81 127.05 191.4 53.910 0.000***

4ROOM 151.8 201.3 257.4 142.050 0.000***

Variable TypeCluster

F Sig.Cluster A Cluster B Cluster C

Room

2ROOM 0.6 0.19 0 221.02 0.000***

3ROOM 0.3 0.58 0.2 131.54 0.000***

4ROOM 0.1 0.22 0.8 269.34 0.000***

Results obtained from area (m2)

Results obtained from Room (%)

VariableCluster

F Sig.Cluster A Cluster B Cluster C

Price 3,317 4,185 5,952 476.8 0.000***

Results obtained from Price (USD / m2 )

Variable2SLS 3SLS

Property Price Marketing Time Property Price Marketing Time

Constant .930(.267)*** 9.025(3.306)*** .907(.267)*** 9.368(3.389)***

LOC .098(.021) -.166(.126) .097(.021)*** -.156(.130)

TIME .158(.045)*** － .160(.045)*** －PRICE － -3.838(2.200)* － -4.055(2.255)*

Famous developer

.114(.041)*** － .133(.040)*** －

Normal developer

.014(.030) － .029(.029) －

PDIST － .385(.146)*** － .359(.148)**

AREA .003(.001)*** .022(.011)** .003(.001)*** .024(.011)**

FLA － .266(.144)* － .284(.142)**

UTILITY .285(.696) 13.614(4.361)*** .269(.699) 13.821(4.472)***

PARKING .259(.131)** -2.444(.458)*** .260(.131)** -2.430(.467)***

CYCLE .001(.000) .012(.006)** .001(.000) .012(.006)**

FLOOR .000(.000) － .000(.000) －ROOMDIST － 3.139(.800)*** － 3.276(.810)***

SUM － .519(.000) － -.537(.000)

ADIST － .000(.000)* － .000(.000)**

Adj R2 .105 0.284 .0972 .240

samples 192 192 192 192

Results obtained from 2SLS and 3SLS

ConclusionConclusion

The relationship of sales time and The relationship of sales time and sales pricesales price

1.1. The influence of sales time on sales price The influence of sales time on sales price is positive. It means that sales time will is positive. It means that sales time will increase with higher sales price.increase with higher sales price.

2.2. The influence of sales price on sales time The influence of sales price on sales time is negative. It means that sales price will is negative. It means that sales price will be higher with shorter time on sale.be higher with shorter time on sale.

1.1. When room combination ratio deviates When room combination ratio deviates from normal distribution, it will increase from normal distribution, it will increase sales time.sales time.

2.2. When price combination ratio deviates When price combination ratio deviates from normal distribution, it will increase from normal distribution, it will increase sales time.sales time.

3.3. When area combination ratio deviates from When area combination ratio deviates from normal distribution, it will increase sales normal distribution, it will increase sales time.time.

The deviation of room combination The deviation of room combination ratio, price and arearatio, price and area

Thanks for your listening !Thanks for your listening !