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The MRT system provides convenient transportation for traveling in the city. Due to

traffic congestion and the difficulty of finding a parking space in urban areas, the distance

to the MRT station has become a key determinant of property values in the city. Bajic

(1983) identified the impact of a subway line in Toronto on the housing prices. The result

showed that the direct savings in commuting from taking the subway should have been

reflected in the housing values. The average amount of savings is estimated to be around

$ US 2,273.

Coffam and Gregson (1998) estimated the impact of the railway on land prices in Knox

County, Illinois. The empirical results suggest that the value of lands increases when the

lands are closer to railroads. The value of lands closer to the railroads is 9% higher than

those that are not. Bowes and Ihlanfeldt (2001) found that proximity to the railroad station,

business activities and crime rates in the neighborhood, affect property values

significantly.

McMillan and McDonald (2004) examined the impact of the completion of rapid transit

line from downtown Chicago to Midway Airport on the prices of single-family houses.

The results show that housing prices are affected by the proximity to subway stations.

The increase in the value of real estate that is close to the transit point is $216 million

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compared with the real estate far away from transit station between 1986 and 1999.

Armstrong and Rodriguez (2006) suggested that housing prices are 9.6% to 10.1%

higher when residential properties are located within 0.5 miles of the station in Eastern

Massachusetts. In addition, the property values decrease 1.6% for every additional minute

of driving to the railroad station. Dewee (1976) showed that housing prices in Toronto

decrease when the distance to the subway stations increases and distance is one-third of

a mile from the stations.

Debrezion et al. (2007) found that the effects of railway stations on the values of the

commercial property are limited to short distances from the stations. In their study, there

are two different effects to estimate the railway station proximity. The first one is local

station effect, which measures the effect of distance within 0.25 mile from the station.

The second one is the global station effect that measures the effect of coming 250 meters

to the stations.

The empirical results showed that within 0.25 mile from the station, the residential

property value is 12.2% less expensive than commercial property. However, they also

found that at longer distances the effect on residential property values dominates. The

estimates suggested that the value of the residential property is 2.3% higher than that of

the commercial property when moving250 meters closer to the station.

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Damm et al. (1980) used data from Washington Metro and found that property values

are negatively related to the distance to the station. When the distance to a station

increases by 0.1 miles, the rent of an apartment will fall by 2.5% in Washington D.C.

(Benjamin and Sirmans, 1996). Kilpatrick et al. (2007) examine the impact of transit

corridor on the housing prices and the result reveals that proximity to the transit corridor

alone without direct access has negative impact on nearby housing prices

Chernobai et al. (2011) used Spline Regression to estimate the effect of highway on

housing prices in Los Angeles. They found that housing prices show a convex relationship

to the distance to highway. Waddell et al. (1993) also showed that the relationship between

housing prices and the distance of the station is U shape. They used a nonlinear model to

estimate the effect of the distance to the station on land value. The locations of MRT

stations have a different impact on land value. For instance, in downtown Chicago, the

17% increase in the values of residential lands within 1.5 miles from the station can be

attributed to the transit. (McDonald and Osuji, 1995).

In Taiwan, previous studies have shown that MRT system has a significant effect on

housing prices. Peng et al. (2009) examined the effect of the completion of Taipei MRT

Red Line on housing prices. The results revealed that the values of houses adjacent to

MRT stations increase by NT$440,000.

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Hong and Lin (1999) estimated the impact of Taipei MRT system and the road width

on housing prices in Taipei. They found that the road width does have a positive effect on

housing prices. Moreover, housing prices increase significantly in the area close to the

MRT stations. More importantly, the relationship between housing prices and the distance

to MRT station is convex.

Tai (2011) also use Taipei MRT System to show that the price effect of MRT station is

nonlinear. Meanwhile, the impact of MRT station is not the same in each distance interval.

Also, there are differences between urban and suburb area. The result showed that the

distance to MRT is station is within 300 meters, the impact on housing prices is more

statistically significant. Moreover, the results also showed that the closer the property lies

within the suburb area, the greater the effect to the housing prices is.

Feng et al. (1994) indicated that the distance to MRT station has a greater effect on

housing prices in downtown. Housing prices in the central business district usually

increase more than the housing price in the outskirt of the central business district and

suburban area. In addition, the increase in the value of land for commercial and office

purpose is greater than that for residential use.

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