Impacts of transportation investment to property price in ha noi, viet nam

By estimatingthe change of office rental price, this research aims to analyze the impacts of Hanoimetro line 2A to property price in Hanoi by hedonic method.. But it still affect to the

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

NGUYEN THI THU HA

IMPACTS OF TRANSPORTATION

INVESTMENT TO PROPERTY PRICE IN

HANOI, VIETNAM

MASTER’S THESIS

HANOI NATIONAL UNIVERSITY

VIETNAM JAPAN UNIVERSITY

NGUYEN THI THU HA

ABSTRACT 5

ACKNOWLEDGEMENT 6

CHAPTER 1: INTRODUCTION 7

1.1 Introduction 7

1.2 Hypothesis and objective 11

1.3 Research framework 12

CHAPTER 2: LITERATURE REVIEW 13

2.1 Studies about property price and rent price by hedonic approach 13

2.2 Studies on land and property price in Vietnam 15

2.3 Effects of Hanoi MRT to office rental price 16

CHAPTER 3: METHODOLOGY 21

3.1 Data 21

3.2 Method 26

CHAPTER 4: GIS-BASED DATABASE DEVELOPMENT 30

4.1 Study area 30

4.2 GIS-based database 31

CHAPTER 5: DATA ANALYSIS 35

5.1 Data Characteristics 35

5.2 Estimation Results 42

CHAPTER 6: FINDING AND CONCLUSION 49

6.1 Finding and conclusion 49

REFERENCES 51

LIST OF FIGURES

Figure 1: Hanoi MRT Master Plan 2030, 2050 vision……….8

Figure 2: The benefit of using metro………9

Figure 3: Hanoi Metro Line 2A (Cat Linh – Ha Dong)……… 10

Figure 4: Two Cat Linh - Ha Dong trains leave the station in Hanoi during a trial run in September 2018……… 11

Figure 5: Samples in 11 urban districts in Hanoi by GIS……….21

Figure 6: Data samples……… 23

Figure 7: Type of building……… 24

Figure 8: Age of building……….24

Figure 9: Rent purpose……….24

Figure 10: Facilities of building……… 24

Figure 11: Population density of samples with buffer scale 500 meters………… 31

Figure 12: Employment density of samples with buffer scale 500 meters……… 31

Figure 13: Population density of samples with buffer scale 1000 meters…………32

Figure 14: Employment density of samples with buffer scale 1000 meters……….32

Figure 15: Number of samples inside MRT corridor in buffer 500 meter and 1000 meter……….33

Figure 16: Observed office rental price and estimated office rental prices……… 48

LIST OF TABLES

Table 1: Catalogue of variables………27Table 2: Descriptive statics of variables in buffer 500 meters used in property price functions……… 37Table 3: Descriptive statics of variables in buffer 1000 meters used in property pricefunctions……… 38Table 4: Correlations between potential explanatory variables with buffer scale 500 meters………40Table 5: Correlations between potential explanatory variables with buffer scale 1000meters……… 41

LIST OF ABBREVIATIONS

MRT Mass Transit Rapid

MRT 2A Hanoi Mass Transit Rapid Line 2A

BE Built Environment

TOD Transit Oriented Development

IRR Internal Rate Return

CBD Central Business District

GIS Geographic Information System

Viet Nam is a developing country which is similar to many developing countriesare experiencing rapid growth Along with these developments, there are manyexisted problems such as traffic congestion, water pollution, air pollution, green-house gas emissions, energy…etc

Transportation in Vietnam is improving rapidly both quantity and quality Roadtraffic is growing fast but the major roads are dangerous and slow to travel on due tooutdated design and an inappropriate traffic mix Construction of expressways hasaccelerated Air travel is also important for long distance travel in Viet Nam Metrosystems are under construction in the two metropolises of Vietnam, one in Hanoiand another in Ho Chi Minh City

Metro in Hanoi is a solution to solving traffic issues However, it still has somefinancial problems according from financial analysis of this project By estimatingthe change of office rental price, this research aims to analyze the impacts of Hanoimetro line 2A to property price in Hanoi by hedonic method

This study has found public transportation as bus frequency has positive significantimpact to office rental price in Hanoi But Hanoi metro line 2A has negativesignificant impact at the moment There are several reasons Such as, Hanoi metroline 2A has not operated yet at the moment, the noise has bad influenced andreputation of project has not influenced to surrounded property Hanoi is the citywhich has high motorbike dependent, currently number of private car has beenincreased and bus system are the most choices to travel for people in Hanoi now.And large area, office building, office in Old Quarter (Central Business District) andhigh employment density have positive impacts to office rental price in Hanoi city,Vietnam

Firstly, I would like thank to my lecturers in Master of Infrastructure EngineeringProgram in Viet Nam Japan University for their inspiring in studying I have hadmeaningful studying time for two years with my master program

I would like to give my special thank and deep attitude to my supervisors, ProfessorHironori Kato and Dr Phan Le Binh for their advices and support in research work

I also would like to thank Ms Nguyen Thi Mai Chi for her guidance for myresearch

I would like thank all of my classmates for helping in studying This is my bigsupport in my master program I have much helps from them during my masterprogram

I sincerely thank to all members in Urban Planning Laboratory in KanazawaUniversity for one semester as exchange student I have learnt from many peoplefrom your acknowledge and their research work

Thanks for Viet Nam Japan University for all supports of my study for two years of

my master program I had learnt much academic knowledge and took part in manyseminars which held by Viet Nam Japan University, also I had joined many school’sactivities which were good memories with me My deep thank to my Japanese andVietnamese lecturers in Viet Nam Japan University for all time in the school

Thanks for Kanazawa University for one semester-exchange program that I haddone Thanks for my Japanese teacher and international students I had in thissemester in Kanazawa University Finally, I would like to send my love andgratitude to my family who always love, support and encourage me every time

CHAPTER 1: INTRODUCTION

1.1 Introduction

In developing countries, transportation systems are directly affected to economicgrowth Because of affected infrastructure support for trading, it leads to developingthe economy Railway is one kind of infrastructure which contributes to developnational economic, such kind of social benefit it brings to, many people will havebetter traveling

With many developed countries, for example like Japan, many company’s officesusually change the location near to metro stations according to its convenient whenurban railway has been used It is the cause of the increase in office rental prices inthe area around the metro line

But with a developing country like Vietnam which high motorbike dependent,people do not much rely on public transportation So the trend of change officelocation near to metro line in Hanoi will have a little different with a developedcountry like Japan But it still affect to the rental price along metro line corridor.Urban infrastructure system Hanoi City is a whole and covers many areas of botheconomic infrastructure and social infrastructure Within the scope of the studypublic transportation, railway network in Hanoi brings to economic profit and socialprofit for citizens who are living in the city

In general, in recent years, the urban infrastructure system of Hanoi City haschanged markedly, gradually changing the urban appearance towards synchronous,modern and increasingly important role in the city's socio-economic development.However, the infrastructure system still has many weaknesses and shortcomings that

do not meet the needs of the people, the socio-economic development requirementsand requirements of a civilized and modern city with stature

Hanoi Urban Metro is a rail system has been developed in Hanoi, Vietnam This project is part of an integrated development program for urban transport in Hanoi.

Figure 1: Hanoi MRT Master Plan 2030, 2050 vision (source: hanoimetro.net.vn)

Hanoi Metro System master plan consists 8 lines with 319 kilometers of totallength with high capacity for carrying passengers for Hanoi city and contributes toHanoi economic development.

Commuters in Hanoi use motorbike, buses, taxis and bicycles Recently, privatecars also have been raised in Hanoi because of enhanced living condition It is cause

of worse congestion and serious pollution in Hanoi Metro is part of VietnamMinistry of Transport Master Plan, the project aims to meet the demand half of localpeople travelling number by public transport, minimize urban pollution, andenhance the people’s living conditions It will support to ease traffic congestion andreduce green-house effects

Figure 2: The benefit of using metro (source: hanoimetro.net.vn)

Hanoi metro will change urban transport in Hanoi which has approximately 8million people are living in Opening of metro can be change the travel behavior ofpeople who are living in Hanoi by the change of built environment

Metro Hanoi also will promote the growth of areas along the route and createthousands of direct jobs as well as many other jobs involved in the process ofconstruction investment and operation exploitation

After the development of railway system, the office for lease demand in these areasincreases, thus lead to the boost of the rental price It is an example shows theimpact of Hanoi urban railway to the office rental price along MRT 2A corridor.Therefore, this paper aims to analyze the impacts of Hanoi MRT 2A which is oneline belong to Hanoi MRT system to office rental price in Hanoi, Viet Nam.

Hanoi MRT 2A is the first operating line in Hanoi There are 12 stations from CatLinh to Ha Dong and 13km of length The original cost estimate of $553 million buthas been ballooned to more than $868 million, including $670 million in loans fromChina

Figure 3: Hanoi Metro Line 2A (Cat Linh – Ha Dong) (source: hanoimetro.net.vn)According to plan, this line was already completed and can use in 2019 but in fact,this line still in trial It is an important project in Hanoi city currently

Figure 4: Two Cat Linh - Ha Dong trains leave the station in Hanoi during a trial

run in September 2018 (photo by Vietnamnet)

1.2 Hypothesis and objective

Hypothesis

Assume that the Hanoi metro line 2A will be increase the price of office for rent along metro corridor

Objective

Estimate a property function with cross-sectional data by hedonic approach

Analyze Hanoi metro line 2A factor to property function

Contributions of this research

First, this research contributes to quantity several factors affect to office rental price

in Hanoi city

Second, study also analyses the impacts of Hanoi metro line 2A to office rental price.

CHAPTER 2: LITERATURE REVIEW

2.1 Studies about property price and rent price by hedonic approach

Many studies research about factors affect to house price or land price in the world.Public transportation affects strongly to property price When we considering factoraffect to property price, several factors related

Public transportation investment increases property values (Cohen et al 2007) is aconclusion which prove the transportation effects to property

Olszewski (2019) study called hedonic analysis of office and retail rent andtransaction prices in Poland – data sources, methodology and empirical results hasbeen researched about rent price in Poland by hedonic approach

Follow Olszewski (2019):

The list of variables that describe the building includes such features as: sum ofparking spaces, modernization, year of the modernization, total rentable area,common space, share of vacant space, number of storeys, average size of the rentedpremises, location in or outside of the Central Business District, share of retail space,office building class A, B and C, age of the building, dummy for the age of thebuilding in the ranges of 5 to 10 years, from 10 to 15 and above 15 years Theyapply logarithms of the rent and all other continuous numerical variables, whichallows them to capture the elasticity of rents relative to renting factors By hedonicmethod with the list of variables above this study has found a negative relationshipbetween the size of the single premise on its rent, which can be interpreted aseconomy of scale A similar relationship can be found between house prices andtheir size

Fang (2018), Subway Opening, Traffic Accessibility, and Housing Prices: A

Quantile Hedonic Analysis in Hangzhou, China found that:

The average housing price within 2 km of the station is 2.1% to 6.1% higher than

those outside We also find that the impacts of the subway differ significantly acrossthe distribution of housing prices, wherein the absolute value of estimatedcoefficients increased from 0.023 for the 15th quantile to 0.086 for the 95th quantile.The subway opening strengthens the capitalization effect of traffic accessibility Theabsolute value of price elasticity increases from 0.044 to 0.053, and the range ofinfluence is expanded from 1500 m to 2000 m.

Zhang (2016) studied about “Do Urban Rail Transit Facilities Affect HousingPrices? Evidence from China” determined the Urban Rail Transit facilities hascritical role in citizen’s social activities and also markedly evaluate real estate price

in Chengdu, China

Zhang (2016) study found following:

Quantitatively, each 1% increase in rail transit mileage improves housing prices by0.0233% Effects are smaller than those of some other variables such as per capitaGDP, land price, real estate investment and population growth, which arerecognized as fundamental determinants of housing price

Same case study in Chengdu in China, Gaolu Zou (2015) found that house pricedecreased with distance from Central Business District and walking distance to thenearest underground station that mean house had further distance from center andpublic transportation system was cheaper That means the house closer to centraldistrict and public transportation system was more expensive than the house further

By hedonic approach, this study analyzed 11 features affected to housing price inChengdu and the results from analysis could suggest to government imposeproperty tax better

As viewing study Kato (2018), “Impacts of urban rail investment on regionaleconomies: Evidences from Tokyo using spatial difference-in-difference analysis”,

it has shown that the urban railway investment significantly positively influencedthe land price in Tokyo The land price was positively influenced by the populationand employment densities The railway introduction influences the land price

through anticipation of expected future development, but no indirect effect throughthe uplift of population density and employment density caused by the railwayintroduction.

2.2 Studies on land and property price in Vietnam

In Vietnam, there are several studies about house price which relate to housingdevelopment Kato and Nguyen (2009) is one of the first researchers analyzing thedeterminants of housing values in Hanoi by hedonic price analysis with more than1,500 samples collected from Hanoi Authority of Finance which covered 10 urban-districts in Hanoi

Recently, study was written by Mai Chi (2018) about potential impacts of BuiltEnvironment on travel behavior and property price in Hanoi shown that density,diversity and transit accessibility had positive effect on bus ridership and propertyprice

This research aims to providing empirical evidences about the association of builtenvironment (BE) with travel behavior in Hanoi and investigates empiricallyassociations of BE variables with property prices in Hanoi, particularly highlightingthe associations of density, diversity and transit accessibility with property prices.Iida (2018), his study used Mai Chi research results and his data for analyzed theimpacts of introducing Land Value Capturing for Mass Rapid Transit (MRTs) inHanoi, Vietnam Iida’s research used case study in Hanoi metro line 2A

Iida (2018) found when population/employment density becomes 20-50% higheraround MRT stations, capturing 2-5% of the total land price increment will bring theInternal Rate of Return (IRR) to positive By combining the office price functionwith a previously developed house price function, property prices after railwayconstruction was estimated Railway revenue estimation was conducted by adopting

a four step method to the origin-destination data A modal split model, a tripdistribution model, and a trip generation and attraction model was developed in

order to estimate the railway demand under different built environment.

There are several studies analyzing the house price in Hanoi but the studies aboutoffice rental price by itself stills scanty

2.3 Effects of Hanoi MRT to office rental price

Built Environment

Relationship between Built Environment (BE) and travel behavior (Mai Chi 2018)The BE consisted of three characteristics, which called 3Ds of built environment,there are: Density, Diversity and Design in developed countries by Ewing andCervero (2001)

Based on these three features of built environment, researches could be divided intofour groups The first group’s studies focused on the impact of neighborhood design

to travel behavior The second group’s studies, which focused on the relationshipbetween land use patterns and travel demand variables, were believed to isolate themain influence factor to travel behavior The third group, which looked closer toaccessibility dimension of the BE, investigated the influence between transportationnetwork and people travel behavior And the fourth group is studies which focusedmostly on a smaller scale of urban design features than the above mentioned threegroups

In recent years, many researchers focused more on the impact of some specific BEvariables such as development density, land use mixture (diversity) But almoststudies analyzed in developed countries

The first research focus in analyzing BE in developing countries Cervero et al.(2009) studied about the influences of BE on walking and cycling in Bogotá,Colombia The BE variables are expressed 3Ds that plus two new additional Ds,which are Density, Diversity, Design, Distance to transit and Destinationaccessibility Unfortunately, this trend between Built Environment and travelbehavior were not happen in Bogotá They found that street design was affected to

walking and cycling behavior.

In urban railway, 5Ds of BE are considered: Density, Diversity, Design, Distance totransit and Destination accessibility

Effects of Built Environment to property price

Effect of density on land price

Several studies have addressed the potential impact of density on housing prices Astudy concluded that increasing densities led to increased land value along Boston’shighway in US (Peterson 1974) but another study seen that high-density zoningassociated with lower housing prices (Mullins 2001)

Study in UK found that rise of population density made high and rising levels ofhouse prices (David Miles 2012)

Jonathan (2017) measured the residential density impacted to housing price inSingapore, this study had found increased in density causes non-trivial decreased inproperty values

Chang Doek Kang (2017), a study on condominium price in Seoul, the density hadtrivial impact on housing price

These results reflect that the effects of density on land price are inconsistent indifferent time and place

Effect of diversity on land price

Many researches were investigated the effect of diversity on land price Thediversity was presented by land-use mix Mixed land use is defined as a mixture ofcommercial, residential and industrial land within a certain area (Koster et al 2012)

By presumed that mixing land uses yields socioeconomic benefits and therefore has

a positive effect on housing values, Koster et al (2012) demonstrated that a diverseneighborhood is positively valued by households There were various land use types

that have a positive impact on house prices, e.g., business services and leisure andthere was substantial heterogeneity in willingness to pay for mixed land use.

The previous study, Song and Knaap (2004) also investigated the effect of diversity

on house prices in Portland in the US, found that mixing certain types of land useswith residential led to the premium in property values

But in the contrast, Li and Brown (1980) focused on the negative externalitiescaused by the appearance of commercial land inside residential area Theyconcluded that housings, located near commercial areas, had lower price caused bynoise, visual pollution and congestion Malaitham (2013) showed that theappearance of residential, industrial and road in land-use attributes decreased theland values, while commercial, education, vacant land and side walk would lead toprice premium, case study in Thailand

Effect of accessibility on land price

Central Business District (CBD) is the most typical characteristic in accessibility.Gaolu Zou (2015) found that CBD had effected to housing price in Chengdu, China.The house located closer, priced higher

Similarly, the shorter the distance to the CBD, the higher the land values(Bartholomew, K., 2011) Study had found the positive impacts of distance of CBD

on land price This trend has been seen in both developed and developing countries

Effect of distance to transit on land price

Commercial property prices increased when they located within a quarter mile of astation (Cervero and Duncan 2002) depended on type of transit And another studyalso concluded the shorter distance to station, the more valuable properties are(Malaitham 2013) Fang (2018) concluded that the average housing price within 2

km of the station was higher than those outside

But other study found that housings located too close to the railway tracks were

suffered to price reduction.

These studies said the inconsistent results about the impacts of distance to transit toproperty price over time and location among different kind of transit technologiesand its service

Studies on rent price

Eda (2003) concluded that locational characteristics explain the spatial rentvariations of the office property in Ankara to a large extent There were 3 groups inthis studies included physical characteristics, lease characteristics and location ofbuilding

The negative relationship between the size of the single premise on its rent inPoland (Olszewski 2019) Study focus on rent by two characteristics which wereoffice characteristics (city size, location, building class, age, leasable area, parkingspaces, time dummy) and retail characteristics (city size, location, retail type, age,size of an average store, parking lots, time dummy)

Development around Hanoi MRT

The concept of Transit Oriented Development (TOD) is introducing for an effectiveurban development in line Based on the “Hanoi Capital Construction Master Plan

up to 2030 with vision 2050” the TOD plan was first introduced in 2011 The MRT

is believed to restructuring the Central Business District (CBD), more competitiveurban development along MRT corridor, connect urban areas and sub urban areas inHanoi Improvements of access environments to MRT stations are the keys for asuccessful TOD introduction The field survey was conducted in 2018 has shownthe development of both commercial and residential buildings could be seen alongMRT construction areas (Iida 2018)

5Ds in Hanoi MRT

Density

Density characteristic is an important factor in BE analysis, population density andemployment density are typical features.

Population density is number of residents in the specific area Urban railwaypurpose to carrying passenger place to place in big city where has high populationdensity

Hanoi MRT 2A line has been constructed from Cat Linh to Ha Dong run throughhigh population density areas to lower population density areas

Employment density was affected by Hanoi MRT line Because of BE change,employment density inside change

Diversity

This characteristic belongs to land use mixed index According to developmentaround Hanoi MRT, commercial and residential buildings surround MRT hasdeveloped It due to change the land use mixed

Destination accessibility

In Hanoi MRT, distance to Central Business District (CBD) which is Hanoi citycenter was recognized Guom Lake has counted as center which located in HoanKiem district and Old Quarter surrounded

CHAPTER 3: METHODOLOGY

3.1 Data

Dataset: location in Hanoi

Figure 5: Samples in 11 urban districts in Hanoi by GIS (created by writer)

Data collect about office rental price in Hanoi city From reputable Vietnam Real

Estate website batdongsan.com.vn and some other real estate website, I already

collected 578 samples from this source and some other website relate to office forlease in Hanoi

Office rental price was collected from eleven districts in Hanoi in 2019:

Figure 6: Data samples (created by writer)

Information about collected from real estate news batdongsan.com.vn:

Several features of collected data (created by writer)

Figure 7: Type of building Figure 8: Age of building

Figure 9: Rent purpose Figure 10: Facilities of building

GIS data

The GIS data of Hanoi used was developed by Mai Chi (2018) Based on the DWGfiles created by the Hanoi Urban Planning Institute, she developed a GIS-baseddatabase All geographical analysis was conducted using ArcGIS

• , : the population density in a buffering zone (R) for the individual n

• : the average population density in a ward k

• : the area in ward k

• : the area of the buffering zone (R) for the individual n.

Employment density

Employment density is measured following in the same formulation as population:

,

• , : the employment density in a buffering zone (R) for the individual n

• : the average employment density in a ward k

• : the area in ward k

25

• : the area of the buffering zone (R) for the individual

n Entropy Index

The entropy index measures the heterogeneity of the spatial unit, and thus a higherindex value relates to a decrease in travel

,

• , : the entropy index of the buffering zone (R) for the individual n

• , : a share of land-use category l in the buffering zone (R) for the individual n

• , : the number of land-use categories observed in the buffering zone (R) for the individual n.

In this study, land price was determined by hedonic method Hedonic regression use

to study the impact of factors that affect housing prices

Office Rental Price estimate by total of variables which affect to Office Rental Price

P is office rental price

0, , are unknown coefficient

26

D is dummy variable value 0 or 1

X is independent variable

ε is error term

Variables

There are two groups of variable: office characteristics and area characteristics

Table 1: Catalogue of variables

Catalogue

Office Characteristics

Area Characteristics (BE)