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June 26 2014

Job Accessibility Effects on Apartment Rentals

Yu-Chun ChengNational Taiwan UniversityDepartment of Geography

Graduate Student

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Outline

1. Introduction2. Methodology and Design3. Data4. Result5. Discuss

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1 Background

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Introduction

1. Research Bias: the transaction price has the investment

demands •Osland & Thorsen (2008) employed the 2788 samples of

residential transaction price and accessibility index.•Osland & Thorsen （ 2013 ） set the Spatial Durbin Model to

explain the spatial characters 。Transaction Price

Consumer Demands

Investment Demands

Rental Price

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2

Introduction

2. Ignore the Sub-market in the residential real estate market•Levine (1998) shows that different accessibility would decide

different land cost and transportation cost.•Adair et al. （ 2000 ） discuss that job accessibility affect

totally residential market and sub-market by different price

Job accessibili

ty

Residential Price

Sub-market by different price

Sub-market by building price

Other sub-markets

Different Transportatio

n Mode

1 Background

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2 Purpose

1

Introduction1. Research gap

Job accessibili

ty

Rental priceSub-market

2. Research purpose• This study empirically investigates the job accessibility

effects on apartment rentals using sample data in Taipei

Metropolitan area, Taiwan.• This study examines the effects of job accessibility on

apartment rentals for different sub-markets.

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Methodology and Design

1 Topic Discuss

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3 Private Trans.

Public Trans.

Elevator building

Non-elevator

building

Suite

Room

House

Commutes trans. mode

choice

Different background of

job and salary

property

type

Building

Type

Job

Accessibility.Rental Price.

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3

2 Hypothesis

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Methodology and Design• H1: job accessibility positively affects

apartment rentals.

• H2: the effects of job accessibility on apartment rentals are different among various transportation modes.

• H3: the effects of job accessibility on apartment rentals are different among various building types.

• H4: the effects of job accessibility on apartment rentals are different among various property types.

• H5: the effects of job accessibility on apartment rentals are different among various rentals.

• H6: the impact of job accessibility by public transportation on apartment rentals is greater than the impact of job accessibility by private transportation on apartment rentals

Rental Price

q(0.1)

Job accessibility

Pub. Trans.

Internal features

Features of housing

External features

Private Trans,

q(0.25) q(0.5) q(0.75) q(0.9)

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1

3 Model

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Methodology and Design【 Control variables】

Building type

property type

Bedroom, Kitchen, Restroom

Located floor

House area

The house of the year

Distance to main road

Distance to bus stop

Distance to the railway

Distance to the station

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1

3 Model

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Methodology and Design

1. The linear regression for full sample

2. The quantile regression for full sample

ln𝑅𝑃𝑎𝑙𝑙 = 𝛽0+𝛽1𝐽𝐴𝑎𝑙𝑙 +𝛽2𝐻𝑠𝑡𝑦𝑙𝑒1+𝛽3𝐻𝑠𝑡𝑦𝑙𝑒2+𝛽4𝐻𝑎𝑟𝑐ℎ +𝛽5𝐻𝑟𝑜𝑜𝑚 +𝛽6𝐻𝑘𝑖𝑡+𝛽7𝐻𝑡𝑜𝑖 +𝛽8𝐻𝑓𝑙𝑜𝑜𝑟1+𝛽9𝐻𝑓𝑙𝑜𝑜𝑟2+𝛽10𝐻𝑎𝑟𝑒𝑎 +𝛽11𝐻𝑦𝑒𝑎𝑟 +𝛽12𝐻𝑟𝑑𝑖𝑠+𝛽13𝐻𝑏𝑢𝑠𝑑𝑖𝑠 +𝛽14𝐻𝑟𝑠𝑑𝑖𝑠 +𝛽15𝐻𝑟𝑙𝑑𝑖𝑠 +𝜀

Q(ln𝑅𝑃𝑎𝑙𝑙│ 𝑋𝑖,𝜃)= 𝛽0𝜃 +𝛽1𝜃𝐽𝐴𝑎𝑙𝑙 +𝛽2𝜃𝐻𝑠𝑡𝑦𝑙𝑒1+𝛽3𝜃𝐻𝑠𝑡𝑦𝑙𝑒2+𝛽4𝜃𝐻𝑎𝑟𝑐ℎ +𝛽5𝜃𝛽5𝐻𝑟𝑜𝑜𝑚+𝛽6𝜃𝐻𝑘𝑖𝑡 +𝛽7𝜃𝐻𝑡𝑜𝑖 +𝛽8𝜃𝐻𝑓𝑙𝑜𝑜𝑟1+𝛽9𝜃𝐻𝑓𝑙𝑜𝑜𝑟2+𝛽10𝜃𝐻𝑎𝑟𝑒𝑎 +𝛽11𝜃𝐻𝑦𝑒𝑎𝑟+𝛽12𝜃𝐻𝑟𝑑𝑖𝑠 +𝛽13𝜃𝐻𝑏𝑢𝑠𝑑𝑖𝑠 +𝛽14𝜃𝐻𝑟𝑠𝑑𝑖𝑠 +𝛽15𝜃𝐻𝑟𝑙𝑑𝑖𝑠 +𝜀

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1

3 Model

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Methodology and Design

𝐽𝐴𝑐𝑎𝑟𝑖 = 𝐸𝑗 × 𝑓൫𝐶𝑐𝑎𝑟𝑖𝑗 ൯σ ቄ𝑎𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑐𝑎𝑟𝑘𝑗 ൯+𝛽𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑚𝑜𝑡𝑜𝑟𝑘𝑗 ൯+𝛾𝑘𝑊𝑘(𝑡) × 𝑓ቀ𝐶𝑝𝑢𝑏𝑘𝑗 ቁቅ𝑘𝑗

𝐽𝐴𝑚𝑜𝑡𝑜𝑟𝑖 = 𝐸𝑗 × 𝑓൫𝐶𝑚𝑜𝑡𝑜𝑟𝑖𝑗 ൯σ ቄ𝑎𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑐𝑎𝑟𝑘𝑗 ൯+𝛽𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑚𝑜𝑡𝑜𝑟𝑘𝑗 ൯+𝛾𝑘𝑊𝑘(𝑡) × 𝑓ቀ𝐶𝑝𝑢𝑏𝑘𝑗 ቁቅ𝑘𝑗

𝐽𝐴𝑝𝑢𝑏𝑖 = 𝐸𝑗 × 𝑓൫𝐶𝑝𝑢𝑏𝑖𝑗 ൯σ ቄ𝑎𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑐𝑎𝑟𝑘𝑗 ൯+𝛽𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑚𝑜𝑡𝑜𝑟𝑘𝑗 ൯+𝛾𝑘𝑊𝑘(𝑡) × 𝑓ቀ𝐶𝑝𝑢𝑏𝑘𝑗 ቁቅ𝑘𝑗

𝐽𝐴𝑎𝑙𝑙𝑖 = 𝐸𝑗 × 𝑓൫𝐶𝑎𝑙𝑙𝑖𝑗 ൯σ ൛𝑎𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑎𝑙𝑙𝑘𝑗൯+𝛽𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑎𝑙𝑙𝑘𝑗൯+𝛾𝑘𝑊𝑘(𝑡) × 𝑓൫𝐶𝑎𝑙𝑙𝑘𝑗൯ൟ𝑘𝑗

3. Job accessibility index Commuting time, Distance cost, Parking

cost

Commuting time, Wating time, Fee, Uncomfortable

cost

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Data

1 Background

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3 Residential market

High

Low

Prediction of

return on

investment

High capital gain

Investment demand ＞ Consumer demand

Low capital gain

Investment demand ＞ Consumer

demand

P/I ratio High

Prefer to RENT

P/I ratio Low

Prefer to BUY

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Data

1 Background

2

3

Taiwan New Taipei

Taipei Taoyuan & Hsing Chu

Taichung Kaohsiung0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2009 Motivation of buying residentail housing in Taiwan

Consumer demands Investment demands

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Data

2

3

【 Empirical space】1 Background

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2 Variables

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1

Data

External Features

distance to main road 2013 +distance to bus stop 2013 -

distance to the station 2013 -distance to the railway 2013 -

Variable items Year Expected sign

Rental price 2009Job

Accessibility

Job accessibility by car 2009 +Job accessibility by motor 2009 +

Job accessibility by public transportation 2009 +overall job accessibility 2009 +

Internal Features

the property type 2009 +the building type 2009 +

the numbers of the bedroom 2009 +the number of the kitchen 2009 +the number of the restroom 2009 -

located floor 2009 -house area 2009 +

the house of the year 2009 +

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3 Descr. statistical

Sample distribution1

2

Data

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Description statistical of rental1

2

Data

3 Descr. statistical

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Result

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Original Model

significanceVIF

Basic Model

Extend model

(Linear)

Extend model

(Quantile)

1. Analysis of Correlation

•Correlation coefficient （ continuous variable ）： Using the

measurement of Pearson product-moment correlation coefficient.

•Contingency Table Analysis （ categorical variable ）： Using the measurement of chi-square test.2. Decision of independent variables: Xn, Xn

1/2, Xn 2, Xn

3, ln Xn

3. Test of independent variables

distance to the station distance to the railway High correlation

1 Model calibrat.

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Result

1 Model calibrat.

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4. Basic and extend model for linearOverall Job Accessibility Exp.

SignA-1

B-1 B-2

Elevator Non-elevator Suite Room House

Adj R2 0.491 0.449 0.568 0.110 0.166 0.172the property type 1 ＋ ＋ *** ＋ *** ＋ *** the property type 2 ＋ ＋ *** ＋ *** ＋ ***

the building type ＋ ＋ *** X X ＋ ***

the numbers of the bedroom ＋ X X X X ＋ * Xthe number of the kitchen ＋ ＋ *** ＋ *** X ＋ *** X X

the number of the restroom － X X X X X ＋ *

located floor ＋ X X X X X － *

house area － － *** － *** X － *** － *** － ***

the house of the year － － *** － *** X － *** X XDistance to main road － X － *** ＋ * ＋ *** － * － *

Distance to bus stop － X X X X X XDistance to station － － *** － *** － *** － *** － *** － ***

Overall job accessibility

＋ ＋ *** ＋ *** ＋ *** X X ＋ ***

Geoghegan et al.(1997) ： Uncomfortable for near the main road

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Result

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4. Basic and extend model for linear 

Exp. Sign

A-1 B-1 B-2

ElevatorNon-

elevatorSuite Room House

Adj R2   0.575 0.540 0.641 0.258 0.316 0.321Job accessibility by motor ＋ ＋ *** ＋ *** ＋ *** ＋ *** ＋ *** ＋ ***

Job accessibility by car ＋ ＋ *** ＋ *** ＋ *** ＋ *** X ＋ ***

Job accessibility by public transportation ＋ ＋ *** ＋ ** ＋ *** ＋ *** X ＋ *

1 Model calibrat.

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Result

2-0

.02

0.00

0.02

0.04

0.06

Gen

eral

job

acce

ssib

ility

0 .2 .4 .6 .8 1Quantile

5. Extend model for quantile• Model A-1 : Overall job accessibility1 Model

calibrat.

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Result

2

Job accessibility

by motor

Job accessibility

by car

Job accessibility by public

transportation

0.01

0.01

0.01

0.02

0.03

0.03

Job

acce

ssib

ility

of m

otor

cycl

e

0 .2 .4 .6 .8 1Quantile

0.00

0.00

0.01

0.01

0.01

Job

acce

ssib

ility

of c

ar

0 .2 .4 .6 .8 1Quantile

-0.0

00.

000.

000.

000.

01Jo

b ac

cess

ibili

ty o

f pub

lic tr

ansp

orta

tion

0 .2 .4 .6 .8 1Quantile

1 Model calibrat.

5. Extend model for quantile• Model A-2 : Different transportation modes of job accessibility

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Result

2 Hyp. Test

1• H1: job accessibility positively affects apartment rentals.

• H2: the effects of job accessibility on apartment rentals are different among various transportation modes.

Overall

Market

J.A. by car

J.A. by

motor

J.A. by pub.

The effects are different

The effects are different

The effects are different

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Result

1 • H3: the effects of job accessibility on apartment rentals are different among various building types.

Rentals of Elevator Building

Rentals of Elevator Building

Overall job accessibili

ty

Job accessibility by motor

Job accessibility by car

Job accessibility by pub. Trans.

Rentals of Elevator Building

Rentals of Non-

elevator Building

The effects are different

The effects are same

2 Hyp. Test

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Result

1 • H4: the effects of job accessibility on apartment rentals are different among various property types.

Overall J.A.

Suite

Room

House

J.A. by

motor

Suite

Room

House

J.A. by car

Suite

Room

House

J.A. by Pub.

Suite

Room

House

2 Hyp. Test

The effects are different

The effects are same

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Result

1• H5: the effects of job accessibility on apartment rentals are

different among various rentals.

[Overall job accessibility]

[Different transportation modes of job accessibility] The effects of job accessibility by motor on High rentals for q(0.9)

and q(0.75) are same, others are different. The effects of job accessibility by car on High rentals for q(0.9) and

q(0.75) are same, others are different. The effects of job accessibility by car on rentals are same.

q(0.5) q(0.9)q(0.1)

2 Hyp. Test

The effects are different The effects are different

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Result

1• H6: the impact of job accessibility by public transportation on

apartment rentals is greater than the impact of job accessibility by private transportation on apartment rentals

2 Hyp. Test

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Discuss

1 Conclusion

2Co

ntri

buti

onAcadem

ic

Job accessibility positively affects apartment rentals.The effects of job accessibility on apartment rentals are different among various transportation modes.Different sub-markets have different effects.

Job accessibility positively affects on mid or low level rentalsJob accessibility negatively affects on high level rentalsIn Taipei Metropolitan area, renters prefer to private transportation(especially motor).

Practical

供需雙方的價格選擇參照政府國宅選址與租金補貼政策

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Discuss Job accessibility index: using the traffic zone with peak time at

morning to measure. Samples ； The distance of external features using the google map to measure

have some errors. It could be measured accurately in the future. Some features (such as service features) couldn’t be collected in

this study. This study didn’t consider the spatial variation (including the

space and time) because of data limitation.

2 Limitation

1

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The EndThank you for your attention