unlicensed maginal price of urban flooding in ho chi minh city

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ERASMUS UNVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE MARGINAL PRICE OF URBAN FLOODING IN HO CHI MINH CITY BY VO LE MINH PHUONG MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, December 2017 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE MARGINAL PRICE OF URBAN FLOODING IN HO CHI MINH CITY A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By VO LE MINH PHUONG Academic supervisor: Dr PHAM KHANH NAM HO CHI MINH CITY, December 2017 Abstract This study applies hedonic price function to estimate the effect of urban flooding of Ho Chi Minh city Instead of using the sale price, this study alternatively uses the rental price from three commercial banks located in Ho Chi Minh City as the dependent variable The explanatory variables are structural characteristic, locational characteristic and flood risk existence The result shows that the structure of house has positive correlation with the rental price, the location of real estate gives the negative effect on rental price and the flood risk existence makes the rental price decrease As the result of this, the marginal price of urban flooding of Ho Chi Minh City is -8,570,172 Viet Nam Dong in mean value of variables Chapter 1: Introduction Problem statements Ho Chi Minh City (HCMC) is the biggest flagship economic center of Vietnam and plays the role as an important marine transit station of the South East Asia This city has such a rapid population growth rate and urbanization development that make it a promise land in the view of labor force from other provinces (Kontgis et al., 2014) The increase of population and market economics has been causing an enormous pressure to the antique French colonial infrastructure in many aspect of the housing need, the garbage disposal solution, the adaptation of drainage system, the transportation, the education, the standard of living, etc To relieve this pressure as well as broaden the city, the authorities approved for many short term and long term projects, such as constructing many new houses, apartments and buildings, widening and zoning the existing streets in corporate with opening the new ones, bulldozing the rivers to supplement land resources, creating more jobs through licensing many industrial parks and production factories, etc Unfortunately, the old drainage systems are not renovated in a compatible way yet so that it is widely believed that solutions for Ho Chi Minh’s infrastructure conversely give the additional bad effects to the significant flooding condition of some low elevation areas of the city besides the well-known natural causal of high tides and climate change This synthetic flooding risk is considered as an environmental factor affecting the people’s lives, trading In the record of Steering Center of the Urban Flood Control Program of Ho Chi Minh City, in recent centuries, this city usually faces with the large-scale floods especially in the rainy season from June to October of each year in corporate with the annual highest tide peaks from October to November The high intensity rainfalls with enormous water level cannot drain quick enough through the old and overloading drainage system of the city make huge desperation for its citizens A research of Committee of Ho Chi Minh city’s government in 2012 alerted that the average affected area by flood of city is 5.944 hectares with nearly 700.000 inhabitants It is obviously that the flood risk in Ho Chi Minh City has caused a very serious impact and damage for the living and wealth of citizens so that it becomes the most concentrating subject in mainstream media channels as well as government programs After each flood event, people tend to give scattered complaint about the damage of wealth as well as the waste of time and efforts to overcome the flooding situation with taking inadvertently no notice of the long-term damage of flood risk which is expected to be more serious than the short-term one This research will capture the long-term effects of flood risk as the foundation for estimating the marginal price of flooding in Ho Chi Minh City which is so-called the willingness to pay for avoiding the flood risk with the application of a traditional and popular methodology for capturing the effect of environmental factors: the hedonic price function The Hedonic Price Function is established on the price of real estate However, in the lack of real house selling price data of Vietnam real estate market, this research examines the variability of rental price of properties in Ho Chi Minh City with the presence of flood risk beside the structural and locational attributes of the houses The rental price is also a transaction price This transaction price is better than sale price since it often reflects the market equilibrium price while sale price is often not equilibrium price since buyer and seller tend to hide the real price The rental price is considered as an accordant proxy for value of property instead of the house price Research objectives: The study aims to estimate the marginal price of urban flooding in Ho Chi Minh city By using the hedonic price function, this study will reveal the relationship between the value of properties and theirs physical and locational characteristics which incorporate with the urban flooding condition of Ho Chi Minh City Scope of the research This research is executed on the data of rental price of three commercial banks in Ho Chi Minh City collected in the period from January to March 2017 These banks have the enormous physical network of branches that spread all over the city Beside the important characteristics of structure and location of real estate, flood risk will become another essence element that affects to the value of properties The initial hypothesis of this research is that the flood risk may give a negative effect on the rental price of properties which is located in and surround the flooding affected areas Structure of the thesis This paper is constructed as follows Chapter is the literature review about the empirical research of house price and the effect of flood risk After that, chapter mention about the methodology and the data The research result and discussion will be presented in chapter Finally, conclusion will come in chapter Chapter Literature reviews Empirical studies of real estate (house) price In literature, there are many research about the real estate (house) price and its influencing factors According to Oxford English Dictionary Online, real estate is defined as “property consisting of land or buildings” Nevertheless, it is widely accepted that the price of house has to comprise the value of land where the house is built in, the cost of housing construction and other added tangible and intangible costs Glaeser et al (2005), indeed, stated that the increase of house price has been caused by the increase in construction costs, the price of land and the “price” of certificate for building a new house Similarly, Grimes and Aitken (2010) emphasized that the housing supply is significant affected not only by the cost of house and cost of construction but also by the value of land Kamal et al (2016) generally summarized that the house price is mainly affected by land, location, macroeconomic factors, demographic factors and industry factors Coming after the previous research, the targeted real estates in this thesis will be defined as aggregate properties that include lands, the houses attached to lands as well as other related factors The next parts will mention about the factors that give effects to the fluctuation of real estate price Buying a house can be considered as a residential investment or just an ordinary contemporary investment to resell in future to gain the profit As the result of this, the buyers of houses are usually classified into two groups: the first group buy houses for consumption purposes and the second group buy houses for investment purposes (Glzindro, 2008) Because the nature of real estate is an ownership transferable goods so that its price is believed to be influenced mostly by the demand – supply rule In other words, when the disparity happens between the house buyers and house sellers, the price of house will fluctuate consequently Figure generally described the factors that affect to the house price under the view of housing demand and supply In the demand side, Mourouzi Sivitanidou (2011) proposed a theory that the consumers would be induced to own a house by the basic residential demand caused by the increase of population and employment, the growth rate of household formation, the development of household income, the relative price of buying a house in compared with renting price and the expectation of citizens about the prospective reselling price in the future All these factors are considered to be positively correlated with the real estate demand This theory is quite similar to the statement of Hofmann (2004) that the macroeconomics determinants such as “economic growth, inflation, interest rate, bank lending and equity price” play an important role in explaining the fluctuation of the house price Firstly, the effect of population and employment growth expressed through the fact that the demand for a fixed own-occupied residence will become to be more essential when the city is gradually crowded with employees from other places MacDonald (2011) who had practically analyzed the Malaysia population growth rate, the migration and retire condition of citizens implied that those demographic factors made the housing demand in Malaysia increase significantly Likewise, a projection report of Council, M.M.A.P (2014) of Metro Boston estimated that when the household size is reduced by the larger number of single family, the increasing number of divorces and the fewer children in one American family, the quality requirement of housing units up to 2040 will increase 10% in compared with the present demand Furthermore, urban centers tend to attract the labor force from other regions which is believed to make the demand for house increase Besides, Voith (1999) proved that the house price in market will increase when employment grows but this phenomenon varies according to the characteristic of this growth Specifically, the fragment growth of job will only make the price of land and new houses in suburban region increases while the concentrated job growth, on the contrary, will give positive effect on the price of existing houses Secondary, the household formation rate has a very important impact on housing demand because each household essentially need a house to shelter The preferred consumption trend of young and single household is to rent house while the married people usually want their family to be settled down by owning a house As the result of this, the high household formation rate will cause the demand for housing increase Smith (1984) had examined the phenomenon of increasing in number of household of United States up to 150 percentages in period of 1961 – 1983 claimed that this increase of households made the housing demand go up because every household tend to occupy a house for their living, Flavin and Yamashita (2002) also showed that the demand of people to own a private house depends increase with the rate of population growth and household formation Besides that, these authors mentioned that the income of people also gave effect on housing demand The third element is the change in real household income and innovation in financial market and economics Actually, when the income of family is increased, they can obviously afford to the house price in the market which induces the ownoccupying housing needs upward Hashim (2010) proposed that the increase of household income would give positive effect on the family ability of paying financial debt which made the purchasing power as well as the housing demand increase Besides, it is widely recognized that the innovation of world financial organization and fluctuation of interest rate give the great advantages for many subprime individuals to enter the owned-occupied housing market through credit activities using the houses as collateral This fact is supposed by Hornstein (2009) to make the demand for housing increase which consequently pushes up the price of real estate The empirical research of Glaeser et al (2010), however, notified that the effect of low interest rate on the change of house price is very small when it could only explain for one-fifth of the house price increase Next, the expectation and preferences of consumers is the fourth factors that makes the house price changed The price of occupying a house gives consumers the information about the amount of money which have to paid for their dream house When consumers expect that the house price will go up in the future, they will be induced to buy houses to take the best price at present Similarly, if the rent fee is intended to be increased in the near future and becomes more asymptotic to the house price, the trend for occupying a private house is obviously in dorminance Hashim (2010) found that these expectations lead to the increase of speculative activities which in turn creates a pressure to make the own-occupied housing demand go up in Malaysia market Figure Factors affect to house price under the view of housing demand and supply (Moore and Goodman, 2012) The price of renting a house is moving upward because of high housing demand of increasing population in big cities, it is supposed that there is a transformation in consumers’ trend from renting a house with expensive price to contrive to own a private house with an equivalent price In this case, the high annual rent fee relative to the occupying price of monthly payment plays an important role in inducing people to own a private house Nevertheless, Hargreaves (2002) concluded empirically that the rent gives little effect on the house price in New Zealand and the house price is mostly affected by non-financial determinants of demographic opinion and traditional conception Similarly, Reed and Greenhalgh (2002) examined the Australia real estate market and captured the point that the increase of house price will be controlled if there is a surplus in stock of houses and the unsteadiness neighbors created by the rental activities In aspect of consumers’ preferences, beside the traditional positive effect of type of houses to the price, Van Weesep (2000) and Bryant & Eves (2011) also concluded that location of land where the house is situated significantly affects the house price by the surrounding infrastructure, facilities and services If owner-occupiers have chosen the suitable area for their preferences such as locating in frontage of the street, adapting to life enjoyment, entertainment, demographic characteristics, memories, chances for studying or environment, etc which bring them enough amount of willingness to pay for the amenities, their perception about the land value which is expressed through the price of the land will become higher, and vice versa Obviously, it is absolutely suitable when a house that is near to school, hospital, supermarket, bus station, restaurant, cinema or other common facilities has a high sale price Hilber and Vermeulen (2016) echoed that the difference in preferences of buyers about amenities surrounding a location is an important factor to determine the price of land It is noticeable that their research found no significant effect of land elevation on the house prices-earning elasticity which is one of the most concern determinant of climate change However, the impact of dis-amenities around a house such as waste, flood risk or pollution area also give a negative effect on the price of land as well Sivitanidou (2011) also noticed that another important group of determinants could affect house price in the view of the supply side of real estate The supply of real estate is simply the market ability to afford quantitatively to real estate demand which expresses mainly through the new housing construction, “expectations regarding demand/rents/prices (myopic or adaptive) and uncertainty and risk (volatility of local economy and real estate market) “ Initially, the new housing construction is defined as the completion of constructing a house in accordance to the approved design of authorities and qualification standards as well as having the final certificate of house There are many determinants that give effect to the new housing construction The important determinants are land cost and construction cost which includes materials and labor Theoretically, these elements are considered to give the negative effect to the availability of new houses in the market because when the availability and price of labor, land or materials increase, it is absolutely made the cost for completing the construction project increase as well As the result of this, the profit of investors will be lower which make their motivation of producing more new houses in the future become downturn, then, the supply resources of house will decrease as well 7) reg RentalPrice RentalAream2 FaadeSizem KindOfProperites 8) reg RentalPrice RentalAream2 FaadeSizem KindOfProperites DistancetotheCenterofDistric DistancetothePalacekm Elevationm 9) reg RentalPrice RentalAream2 FaadeSizem KindOfProperites DistancetotheCenterofDistric DistancetothePalacekm Elevationm NumberofFloodhotspostsurround Floodriskexistence 10) predict r, resid Swilk r 11) imtest, white APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT Company Price ( monthly, Viet Nam dong) Bank1.CuChi 27,000,000 360 8.05 1.039075065 32.16015722 10.032 0 Bank1.TruongChinh 27,956,644 119 3.739887741 8.379643792 6.992 0 Bank1.TanPhu 28,350,000 173 8.2 0.267305652 6.927393755 7.904 0 Bank2.QuangTrung 31,150,000 264 9.86 0.972974414 5.875949042 10.032 0 Bank1.BinhThoi 31,500,000 325 1.857103961 5.742079625 6.992 0 Bank1.PhanVanTri 33,000,000 155 5.65 2.644545199 4.612166291 11.856 0 Bank1.CatLai 33,600,000 260 3.391341812 7.079332533 6.992 0 Bank1.DongKhanh 35,000,000 148 5.1 0.215741922 3.663269137 10.032 0 10 35,000,000 36,000,000 318 218 10 0 1.116878026 2.526459266 9.332884301 7.374399254 2.128 0 0 37,000,000 134 8.3 2.977552094 3.71707547 11.856 0 12 13 Bank3.BinhTan Bank1.AnLac Bank1.NguyenThuo ng Hien Bank3.QuangTrung Bank1.PhongPhu 38,500,000 39,688,000 165 175 5.3 2.709602245 2.331915531 7.264132463 5.054335925 13.072 6.08 0 0 14 Bank1.NguyenKiem 40,800,000 222 14.53 1.15237644 3.668613785 10.032 0 15 Bank1.TanHuong.Lo 42,000,000 205 5.187358129 10.078017 3.952 0 11 Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Company cNew5 Bank3.PhuMyHung Bank1.NamSaiGon LocNew5 Bank1.PhuTrung Bank3.LeVanSy Bank1.BinhDang.Lo cNew1 Bank2.Quan10 Bank1.LeQuangDin h Bank1.BinhTriDong Bank3.PhuLam Bank2.NhieuLoc Bank1.OngTa Bank1.Quan6 Bank1.BinhTan Bank2.PhuMyHung Bank1.TranQuangDi eu Bank1.TanQui Bank1.BeVanCam.L ocNew6 Bank1.HiepBinhPhư ớc Bank3.BinhPhu Bank1.NguyenThai Sơn Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 42,000,000 381 2.250573663 5.577272163 3.04 0 42,000,000 425 1.180442553 2.330947432 6.08 0 43,000,000 44,460,000 236 99 6.8 3.8 0 2.557804749 1.741021556 5.520719376 1.944569583 6.992 6.08 0 0 45,000,000 280 3.633418843 6.262738352 3.04 0 45,000,000 480 18 0.601165022 0.824443594 6.992 0 45,454,000 182 6.2 2.315155337 3.746156819 11.856 0 46,200,000 46,288,000 46,725,000 47,250,000 48,400,000 48,400,000 48,950,000 504 337 105 180 300 400 324 5.97 12.798 4.6 8.2 5.141 1 0 0 1.382988535 2.025341514 2.244238597 1.327396902 1.801552632 4.533887562 1.438901979 9.229623707 7.352162761 2.381818044 3.624641403 7.180049037 10.26709402 5.753796495 2.128 6.08 4.864 4.864 3.04 4.864 2.128 0 0 0 0 0 0 0 50,000,000 165 8.2 2.086403504 2.334308797 9.12 0 52,000,000 277 8.9 2.120952846 4.474915613 4.864 0 52,500,000 103 7.6 1.932501981 5.524929147 2.128 0 52,500,000 150 13.4 3.474842661 9.537446279 0.912 0 52,700,000 425 2.329739473 7.969309187 3.04 0 54,600,000 228 11 0.179991216 5.415668374 13.072 0 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT Company 36 37 38 39 Bank1.D32 Bank2.TanPhu Bank1.BinhPhu Bank1.BinhDang Bank1.BinhDang.Lo cNew3 Bank1.BinhDang.Lo cRef2 Bank1.BinhDang.Lo cRef1 Bank1.LeQuangDin h.LocNew1 Bank1.NguyenVanT roi Bank1.NamSaiGon LocNew4 Bank3.NguyenVanT roi Bank1.ToKy.LocRef Bank1.LeVanSy.Loc New4 Bank1.PhanDinhPhu ng.LocNew Bank1.BeVanCam.L ocNew5 Bank3.CachMangTh ang8 Bank1.NguyenSon 40 41 42 43 44 45 46 47 48 49 50 51 52 Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 56,000,000 57,850,000 59,000,000 59,500,000 260 117 195 665 9.375 19.669 0 0 1.616902 0.196832882 2.247067575 3.957071668 3.643621393 7.150285279 7.867234603 6.595188119 15.808 6.992 4.864 4.864 0 0 0 0 60,000,000 72 3.935740934 6.554385779 3.04 0 60,000,000 250 3.919108226 6.553055542 3.04 0 60,000,000 250 3.799857901 6.331528362 9.12 0 60,000,000 387 4.84 2.527073094 3.886912984 13.072 0 63,000,000 206 14.95 1.194164118 1.529769058 9.12 0 63,000,000 450 1.193583877 2.374501088 6.08 0 65,000,000 98 10.6 0.718927668 3.767043141 10.032 0 65,000,000 240 2.889770718 11.36841413 9.12 0 66,000,000 90 0.575346333 3.121704424 7.904 0 66,000,000 130 8.3 0.640841903 3.70362308 10.944 0 68,000,000 333 2.101122061 5.467843501 0.912 0 68,440,000 424 1.069030245 3.944662728 6.992 0 70,000,000 410 8.4 1.783862341 7.929098881 6.08 0 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT Company 53 54 Bank1.BinhHoa Bank1.HoaHung Bank1.NguyenChiT hanh Bank1.BaChieu Bank2.BinhThanh Bank1.3thang2.Loc Ref2 Bank2.Quan11 Bank3.KhanhHoi Bank1.NguyenVanL inh Bank1.LeVanSy.Loc New1 Bank2.Quan2 Bank1.NamSaiGon LocNew1 Bank1.PhanDinhPhu ng Bank2.PhuNhuan Bank1.NamSaiGon LocNew2 Bank1.LeVanSy.Loc New3 Bank1.NguyenOanh Bank1.PhanDinhPhu ng.LocRef1 Bank1.NamSaiGon LocRef1 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 70,000,000 70,350,000 512 170 8.4 0 2.110857134 0.981398129 4.196772798 2.402151423 11.856 6.992 0 0 73,000,000 116 7.2 2.11229345 3.973779778 13.072 0 73,500,000 74,092,500 180 277 12.25 1 1.516917004 1.780364398 3.073449021 3.34696788 10.032 10.032 0 0 75,000,000 220 1.554632721 3.579374042 11.856 0 75,000,000 75,000,000 328 480 8.922 0 1.773893746 1.166951037 5.566068404 2.288298534 6.992 4.864 0 0 75,350,000 558 12 1.430031399 5.749069419 2.128 0 77,000,000 440 1.069284048 3.617729393 6.992 0 77,875,000 164 10 0.74949786 3.87438572 6.992 0 80,000,000 150 1.186795924 2.352706244 3.952 0 80,000,000 188 6.1 0.400729517 3.214292087 9.12 0 80,589,500 178 12.86 0.773723092 3.820273747 6.992 0 82,080,000 192 20 1.042192628 1.912700024 6.08 0 82,500,000 276 4.6 0.580629638 2.976000932 7.904 0 83,600,000 402 0.966122013 6.029557817 11.856 0 83,990,000 170 0.847384382 2.974370233 9.12 0 85,000,000 160 1.141250727 2.091699985 4.864 0 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT Company 72 73 Bank1.TranNao Bank2.Quan Bank1.NamSaiGon LocNew3 Bank3.CongHoa Bank1.NguyenSon.L ocRef2 Bank1.LeVanSy Bank1.DongSaiGon Bank1.PhanDinhPhu ng.LocRef2 Bank1.NguyenTatTh anh Bank2.NguyenTriPh uong Bank1.KyDong Bank2.GoVap Bank1.LeVanSy.Loc New2 Bank2.Tan Binh Bank1.QuangTrung LocRef2 Bank1.TaySaiGon.L ocRef2 Bank1.AnPhu Bank1.TaySaiGon.L ocRef1 Bank1.NamSaiGon LocRef2 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 89,000,000 89,000,000 500 585 10.4 0 0.307679179 1.143773057 4.059174469 2.138228561 3.04 7.904 0 0 89,250,000 576 1.159133632 2.268971653 6.08 0 89,880,000 145 12.5 0.514684046 5.152750684 9.12 0 90,000,000 520 1.788531367 7.913280093 6.992 0 92,400,000 92,760,493 454 232 7.9 9.3 0.717080167 2.01595537 3.484910654 4.379195081 9.12 6.992 0 0 97,080,358 188 0.461113349 3.42796558 6.08 0 99,000,000 426 17.232 0.031950206 1.8187687 6.08 0 100,125,000 500 15.162 0.324526329 3.866355518 6.992 0 106,573,703 106,800,000 253 560 21 1.491222372 0.072447514 1.597144494 5.287090608 4.864 13.072 0 0 110,000,000 500 1.020479139 3.665312813 6.992 0 111,250,000 802 11.35 0.234316375 4.588751309 10.032 0 112,860,000 500 10 1.473663919 6.210989264 10.944 0 113,805,000 270 12 0.380989012 4.452711706 3.952 0 114,676,614 379 20.246 1.530675413 5.710878623 2.128 0 117,877,518 261 10 0.458936201 4.477525199 4.864 0 120,000,000 220 1.134458278 1.99634595 4.864 0 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 Company Bank1.NguyenTatTh anh.LocRef1 Bank1.ChoLon.Loc New1 Bank2.LeVanSy Bank2.TrungTamTh e Bank2.HoangVanTh Bank2.3Thang2 Bank2.NguyenDinh Chieu Bank2.BenNghe Bank1.ChoLon.Loc New2 Bank1.Pasteur Bank2.HuynhThucK hang Bank1.PhuNhuan Bank1.ChoLon.Loc New3 Bank2.CachMangTh ang8 Bank1.TanBinh Bank2.HoChiMinh Bank2.Quan1 Bank1.PhuMyHung Bank2.SaiGon Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 120,000,000 420 12 0.050994308 1.893789419 7.904 0 120,000,000 500 2.472466193 8.038443317 7.904 0 122,375,000 209 0.780070658 3.933903344 6.992 0 131,964,750 189 7.2 0.596736913 0.790278047 6.992 0 144,513,750 291 13.925 0.713604942 5.988212805 3.952 0 144,625,000 386 13.7 1.571326451 3.5984619 15.808 0 147,740,000 166 12.7 0.744210039 0.575109549 10.944 0 150,187,500 75 8.5 0.304601705 0.829678318 10.032 0 162,000,000 700 10.5 2.472466193 8.038443317 7.904 0 163,862,660 400 17.15 0.799208125 1.119052471 11.856 0 171,325,000 540 8.3 0.524565983 0.921124058 6.992 0 204,930,000 443 9.8 0.515671245 2.556856417 6.992 0 222,000,000 900 14 2.472466193 8.038443317 7.904 0 229,575,500 361 12 1.339248482 3.582910152 6.992 0 259,371,000 274,987,750 311,500,000 341,418,156 363,987,750 696 340 600 705 861 12.3 49.295 10.682 15.7 20 1 1 0.520536446 0.747680381 0.725546026 0.708631335 0.548655868 5.173419624 0.373467112 1.028752563 6.047208158 1.19700312 4.864 14.896 10.944 3.952 9.12 0 0 0 0 0 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT Company 110 111 112 113 114 Bank1.ThangLoi Bank2.CongHoa Bank1.DoXuanHop Bank1.HiepPhu Bank2.Quan3 Bank1.TruongVinhK y Bank2.HungVuong Bank2.ThuDuc Bank1.TanHuong.Lo cNew3 Bank1.BeVanCam.L ocNew3 Bank1.VoVanNgan Bank1.LeVanTho Bank1.ApBac Bank3.CauOngLanh Bank1.BayHien.Loc Ref3 Bank1.AuCo.LocNe w Bank1.BayHien Bank1.PhuTho Bank2.AuCo Bank1.NguyenAnhT hu Bank1.LeDucTho Bank1.ThaoĐien 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 458,016,020 20,464,000 26,250,000 30,017,329 30,037,500 750 338 350 118 320 15.65 9.5 11.408 4.2 0 0.751741907 1.712070928 2.680100458 0.635223132 1.09230985 0.467172839 6.347385883 9.697374833 11.79533496 1.584095162 13.984 9.12 6.992 27.968 7.904 0 1 0 1 1 30,800,000 239 6.7 2.628559672 6.978307862 6.08 1 31,150,000 33,375,000 558 288 4.795 6.2 0 1.688082758 2.063704337 5.742818601 11.64178272 6.992 29.792 1 33,600,000 96 12 3.148839931 8.505198973 4.864 35,000,000 150 4.5 1.336611281 4.318135743 3.04 36,225,000 36,300,000 36,300,000 37,000,000 320 320 363 118 6.009 5.017 9.7 0 0.189121765 4.458275504 1.873816396 1.23675799 10.5331718 9.273170782 6.48620371 1.098924132 7.904 6.08 13.072 4.864 0 1 1 39,000,000 120 1.380131003 5.856907462 9.12 1 40,000,000 140 10 3.553417644 7.254147129 10.032 40,000,000 40,000,000 40,050,000 245 258 350 7.15 5.2 0 0.881625328 0.907749939 3.14267673 5.145898168 4.754518443 6.73326521 6.992 9.12 6.992 0 1 40,250,000 225 3.299498369 13.18871245 11.856 41,800,000 42,000,000 190 106 10.03 11 3.274416221 1.76819994 8.383457223 5.387253624 10.032 3.04 1 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 Company Bank1.TanHuong.Lo cNew1 Bank2.NguyenTrai Bank1.PhuXuan Bank1.ToKy Bank2.BinhTan Bank2.LeDucTho Bank1.BacHai Bank1.ĐinhBoLinh Bank3.PhamNgocTh ach Bank1.HuynhTanPh at Bank1.TanSonNhat Bank3.TanHuong Bank1.BayHien.Loc Ref2 Bank1.DinhBoLinh LocRef1 Bank3.HangXanh Bank1.PhuXuan.Loc Ref2 Bank1.PhoCoDieu Bank1.LanhBinhTha ng Bank1.AuCo.LocRef Bank1.AuCo Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 42,000,000 150 3.016198997 8.191031055 7.904 42,000,000 43,000,000 44,000,000 44,500,000 45,000,000 45,529,000 47,250,000 300 350 412 318 650 249 288 8.85 10 12 7.8 0 0 0 0.954850624 0.20653383 2.558985199 1.661309422 3.26573533 1.437429021 1.055263289 2.69337261 9.834568702 10.37225832 9.714929566 8.377834287 3.392901969 4.037808162 9.12 2.128 3.952 -0.912 10.032 7.904 4.864 1 1 1 1 47,608,704 87 0.335419749 0.879304614 11.856 48,300,000 172 11.099 0.5953345 6.275117743 2.128 1 48,620,250 49,432,000 192 562 8.3 0 1.936024849 2.353000348 5.087539269 7.967862196 13.984 4.864 1 49,500,000 220 4.5 2.281036024 6.847490731 7.904 49,500,000 252 0.637405453 3.658441125 3.04 52,300,000 267 0.257611597 3.006030574 3.952 1 54,000,000 240 0.129214857 9.759315675 2.128 55,000,000 96 20.419 0.607423027 4.613464928 10.032 55,000,000 160 1.285400325 5.335391289 10.944 55,000,000 180 3.203532543 7.339097839 4.864 55,000,000 203 2.375438054 5.810743088 7.904 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT Company 152 153 154 Bank3.NguyenTrai Bank2.TanThanh Bank1.ThuanKieu Bank1.PhamNgocTh ach Bank1.MinhPhung Bank1.TanHuong.Lo cNew4 Bank1.TanHungThu an.LocRef2 Bank1.TanHuong Bank1.AuCo.LocRef Bank1.HuynhTanPh at.LocRef1 Bank3.LeDaiHanh Bank1.HungDao.Lo cRef1 Bank1.TanHungThu an.LocRef1 Bank1.BinhTien Bank3.TranHungDa o Bank2.BauCat Bank1.SaiGonManor Bank3.VoVanTan Bank3.PhanDinhPhu ng 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 55,000,000 55,625,000 55,650,000 376 350 177 5.6 20.565 4.75 0 0.639314407 2.305535134 1.468679949 2.987623377 6.520376299 4.895947457 13.072 4.864 11.856 1 1 57,045,120 138 6.092 0.378985526 0.915368029 10.944 57,330,000 400 1.938211097 6.070789533 6.08 57,750,000 200 2.00751716 7.474613079 7.904 58,000,000 280 0.636967404 10.06506738 6.992 59,400,000 264 7.4 2.511386959 8.248404861 3.952 1 60,000,000 200 3.20687359 7.354626699 4.864 60,000,000 200 10 0.572418675 6.465523518 0.912 1 60,000,000 257 0.735242668 4.695521111 7.904 1 60,000,000 270 0.583772494 3.244871348 3.952 60,000,000 320 0.777189184 10.19649203 7.904 60,000,000 378 13 0.989723572 6.692899955 7.904 1 61,000,000 282 2.831220479 2.447497073 10.944 1 62,300,000 63,694,400 64,940,000 160 140 324 1 1.917310154 1.169717745 1.374610049 6.123200169 2.979294841 0.953051693 11.856 6.08 13.984 1 1 65,000,000 353 1.21795196 2.059830399 6.992 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 Company Bank1.PhanXichLon g Bank3.HauGiang Bank1.BayHien.Loc New2 Bank1.TanThuan Bank1.Bau Cat Bank3.TruongChinh Bank1.BinhThanh Bank1.TanHuong.Lo cNew2 Bank2.ThongNhat Bank1.DinhBoLinh LocRef2 Bank1.ToHienThanh Bank1.3thang2.Loc Ref1 Bank3.TanDinh Bank1.LeQuangDin h.LocNew2 Bank1.TanHungThu an Bank1.HungDao.Lo cRef2 Bank1.ToKy.LocRef Bank2.ThanhDo Bank1.CaoThang Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 65,479,828 135 10.8 1.200411054 2.716418065 3.952 66,000,000 170 6.5 0.210106207 5.899638487 6.08 66,000,000 250 1.193684059 5.774432568 9.12 66,425,251 66,550,000 67,200,000 67,680,000 390 466 371 568 13.21 8.02 8 0 0 1.764551408 1.738894158 2.171390875 0.620090682 5.025611517 5.898672661 6.730508848 3.819837038 2.128 9.12 6.992 4.864 1 1 68,250,000 400 12 3.414116064 8.615523911 6.08 1 68,975,000 288 12 1.148922741 5.271579598 10.944 70,000,000 256 0.934005745 3.92578519 3.952 70,000,000 294 10.07 1.870544383 3.936514703 7.904 75,000,000 200 4.3 0.712373949 2.755178922 10.032 1 75,000,000 661 1.962856217 1.716333763 13.984 75,405,000 150 52 1.491686847 4.388493395 2.128 76,865,250 294 7.82 0.632027317 10.06062898 9.12 77,000,000 300 0.810976847 3.031426369 6.08 1 77,000,000 300 2.488963606 10.27553115 9.12 77,875,000 79,000,000 576 200 7.7 1.174322388 2.095918976 3.093039864 1.746847178 10.032 13.072 0 1 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 Company Bank1.BachĐang (HCM) Bank1.BeVanCam.L ocNew4 Bank1.ThaoDien.Lo cRef2 Bank3.NgoGiaTu Bank1.Quan10 Bank2.LeDaiHanh Bank2.ThanhDa Bank1.HungDao Bank3.3thang2.Loc Bank3.PhanDangLu u Bank2.ChauVanLie m Bank1.CachMangTh ang8 Bank1.BinhThanh.L ocRef2 Bank2.Quan9 Bank1.VanThanh Bank1.ThanhĐa Bank2.ChoLon Bank1.KyHoa Bank1.TanDinh.Loc Ref1 Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 79,000,000 280 7.05 0.218679641 3.266818003 7.904 1 80,000,000 179 5.2 0.531542089 2.52040755 9.12 1 82,500,000 150 1.97372083 5.372168697 0.912 83,214,209 84,000,000 84,550,000 84,550,000 84,700,000 574 268 400 692 369 6.6 8.4 7.7 5.95 0 0 1.67062937 1.185919607 0.96188496 1.217667017 0.905656999 3.429995607 2.537570808 4.779264905 4.414956029 2.94890228 13.072 10.944 9.12 3.952 9.12 1 1 1 85,000,000 432 0.959898672 3.009057344 10.032 88,102,880 375 2.328952971 3.007047858 9.12 89,000,000 345 5.61 1.482472784 4.914097092 13.072 1 89,250,000 120 6.3 1.344765954 0.717048769 15.808 91,000,000 510 8.5 0.484437142 3.622064012 6.992 93,450,000 99,000,000 101,640,000 102,350,000 105,000,000 1,407 167 284 546 396 15 8.5 6.7 0 0 2.111706555 0.942182078 1.131095971 0.101876634 0.845298936 9.904782223 3.587467531 4.307420613 5.800869293 2.911939603 11.856 4.864 3.952 7.904 9.12 3 1 1 110,000,000 250 10 2.050921581 1.745288101 7.904 APPENDIX DATA OF 218 OBSERVATIONS Note: To protect for bank’s information, the name of banks are hidden STT 209 210 211 212 213 214 215 216 217 218 Company Bank1.TanDinh.Loc Ref2 Bank1.BinhThanh.L ocRef1 Bank1.TanThuan.Lo cRef2 Bank1.BeVanCam.L ocNew1 Bank2.TruongSon Bank1.TânDinh Bank2.Quan5 Bank1.MinhKhai Bank1.Quan5 Bank1.BuiThiXuan Price ( monthly, Viet Nam dong) Rental area (m2) Faỗade size (m) Kind of Properties Distance to Center of District (km) Distance to the Palace (km) Elevation (m) Number of flood hotspost surround Flood risk existence 110,000,000 400 1.831040636 1.697072231 10.032 110,000,000 554 0.712113043 3.941778417 4.864 120,000,000 480 16 1.836289936 4.967844353 2.128 1 122,375,000 440 4.4 2.111477111 1.714378095 9.12 122,375,000 133,500,000 137,000,000 160,000,000 170,000,000 191,657,367 450 331 259 500 450 297 13.565 16.5 11.8 7.8 10.45 12.291 0 1 1.231357193 1.885691772 0.701631329 0.892102389 1.226084237 1.982336043 4.735394776 1.724622817 3.615401425 1.018757389 2.363498959 1.424050092 11.856 10.032 13.072 15.808 9.12 13.072 0 0 1 1 1 ... of the urban flooding problem in Ho Chi Minh city Urban flooding condition has become the serious problem in Ho Chi Minh City The reason for flooding is considered to come from three main sources... which incorporate with the urban flooding condition of Ho Chi Minh City Scope of the research This research is executed on the data of rental price of three commercial banks in Ho Chi Minh City. .. KHANH NAM HO CHI MINH CITY, December 2017 Abstract This study applies hedonic price function to estimate the effect of urban flooding of Ho Chi Minh city Instead of using the sale price, this