應用特徵價格法探討航空噪音對於房地產價格之影響－以桃園國際機場為例

桃園國際機場所帶來的航空噪音污染，為機場的重要外部性成本之一。房地產價格是評估航空噪音外部性成本的重要依據。本研究以2016年到2018年噪音防制區內不動產實價登錄資料與18個航空噪音監測站資料，在考慮交易資料的空間群聚性及所提之航空噪音推估值與噪音回饋金為特徵變數下，應用線性、半對數、反對數與雙對數等不同特徵價格模式探討航空噪音對房地產價格的影響及與外部性成本之關係。實證結果顯示，所有模式中以地理加權迴歸線性模式的模型配適度與解釋力最佳。使用所提之航空噪音推估值為特徵變數的模式績效優於使用監測站噪音值變數；最後，航空噪音對於房地產價格有顯著影響，而噪音回饋金則無，代表現行補貼方式已維持在適當水準。

關鍵字

航空噪音；外部性成本；不動產實價登錄；特徵價格法；地理加權迴歸

並列摘要

The aviation noise caused by the huge passenger and cargo volume of Taoyuan International Airport has a major impact on the quality of the local residents' life. Aviation noise pollution is one of the important external costs of airports. This study applied the data of ＂Real House Value Registry Scheme＂ in noise control areas from 2016 to 2018 and the data of 18 aviation noise monitoring stations. Since the value of the noise monitoring station is easily affected by location and distance, this study proposes an estimated aviation noise as one of the explanatory variables. The noise prevention fee is also used as an explanatory variable. This study uses four different hedonic pricing models including linear, semi-logarithmic, anti-log and double logarithmic, under the consideration of spatial autocorrelation of data points, to explore the impact of aviation noise on real estate prices and the cost of airport externalities. Empirical results show that, among all the constructed models, the geographically weighted regression model with linear model has the best explanatory power. The model performance of using the proposed new estimated aviation noise as the explanatory variable are all better than that of using the traditional monitoring station noise. The results also revealed that aviation noise has a significant impact on the real estate prices of noise control areas, but noise prevention fee is not significant which means the current subsidy policy is at an appropriate level.