Land policy and property price in Hanoi, Vietnam, January 2009

cold and hot. Legal is defined as 1 if the house owns the land-use right certificate; and 0 else.Then, the estimated results are shown in Table 2. The relationship between the estimated priceand observed price are also shown in Figure 5. First, the estimated results in Ancient quartershows that the variables influencing significantly the property prices are Location, Age, Work,Transit, Roadratio and WaterSup. The reason for Floor is absent in the Ancient quarter isunderstandable since most of houses in this zone are shared-used houses. Households livingthere usually own only one or two rooms inside the house for residence; they have to sharethe common spaces as staircase, lobby, and toilet. Thus, the property price in Ancient quartermainly does not depend on Floor. The absent of Distance in Ancient quarter is alsoreasonable. In Ancient quarter, the most of houses mainly are tube-house and there are notlong alleys, so that distance from the house to the street usually around 50 m. As a result, thisfactor does not have many impacts on property price. Second, the results in French quartershows that the significant factors are CBD, Distance, Floor, Legal, Location, Lot, Park,Roadratio, Shape and Work. The high fitness of the estimated function may mean that theproperties in French quarter are traded in more reasonable or transparent way than other area.Third, the results in Area built during 1960-1990 shows that Built, Distance, Floor, Location,Safety, WaterSup are the significant factors. Figure 5 shows that the properties with over 120million VND/m 2 are underestimated although the most data are scattered around thecorrelation line. By checking the data sources, we found that the most of properties with highproperty prices are located mainly at the three streets named Kim Ma, Dang Van Ngu and VoThi Sau. These streets are located at the busiest areas in the zone and have extremely highprices compared to others. One of the hypothetical reasons for the underestimated prices ofthose properties is because they are traded in the different manners from other properties.Then, we re-estimated the price function after eliminating these samples. However, thecorrelation coefficient was not much improved (R 2 = 0.47). The further examination isTable 2 Estimation results of hedonic property price functionsAncient quarterFrench quarterArea built during1960-1990Area built after1990Outer dyke areaVariables Coeff. t-stat. Coeff. t-stat. Coeff. t-stat. Coeff. t-stat. Coeff. t-stat.CBD -0.01 -7.66Built 0.29 3.28 0.30 2.37Distance -5.65 -4.00 -3.01 -2.80 -6.01 -7.31Flood 12.45 2.30Floor 4.14 4.58 3.29 2.75 2.82 3.00 29.61 18.63Legal 10.93 5.48Location -25.22 -16.02 -16.95 -18.16 -12.41 -8.77 -12.52 -15.21Lot 0.12 8.02Park 13.56 2.91RoadRatio 6.37 5.89 3.14 14.52 1.41 5.77Safety 18.99 2.75School 18.77 2.15Shape -2.41 -4.18 -0.50 -1.94Transit 40.34 2.96WaterSup 46.41 2.16 9.29 3.68 5.14 3.20Work -5.81 -9.85 -4.15 -7.65 -0.96 -2.83Constant -478.98 -2.72 140.51 10.35 -534.06 -2.12 69.15 8.16 -10.81 -1.52R-squared 0.71 0.80 0.41 0.59 0.88Number of data 202 449 518 256 118