本研究探討風力發電機設置是否對台灣住宅房價產生影響。隨著再生能源與淨零排放政策推動，沿海地區逐漸出現風力發電設施，但其噪音、景觀與健康疑慮常引發居民關切，市場可能因此調整住宅價格。本文以桃園市與苗栗縣為研究範圍，蒐集2012年至2018年內政部實價登錄交易資料，並結合地理資訊系統進行距離分組。研究方法採用特徵價格法與差異中的差異法（Difference-in-Differences, DID），輔以平行趨勢檢定與預期效應檢驗，驗證因果推論的前提。最後透過重複抽樣估計、傾向分數加權（Inverse Probability Weighting, IPW）及傾向分數配對（Propensity Score Matching, PSM），以驗證估計結果的可信度。
實證結果顯示，在桃園市與苗栗縣的樣本中，均未發現風力發電機建造後對周邊住宅價格具有顯著影響。此結果與一般直覺認為風機必然會影響房價的看法並不一致。綜合分析可見，風力發電機對房價的影響並不顯著，房價變動仍主要取決於房屋自身特徵與周遭環境條件。

This study investigates whether wind turbine construction affects housing prices in Taiwan. Using transaction data from 2012 to 2018 in Taoyuan City and Miaoli County, housing units were grouped by distance through GIS analysis. The empirical strategy applies a hedonic pricing model and a Difference-in-Differences (DID) approach, supported by Inverse Probability Weighting (IPW), Propensity Score Matching (PSM), resampling, and parallel trend tests.
Results show no significant impact of wind turbines on nearby housing prices in either county. Although some subsample analyses indicate limited price variations, these effects are not consistent or statistically significant. Overall, the findings provide little evidence to support the hypothesis that wind turbines influence property values. Regional differences may reflect housing market structures, community acceptance, or policy environments.
This study provides empirical evidence from Taiwan to supplement international research on potential NIMBY effects of wind power facilities. The results suggest that market responses to wind turbines are limited. Future research should include more regions and longer periods to examine long-term impacts and underlying mechanisms.

目錄
第一章	緒論	1
第一節	研究動機與目的	1
第二章	文獻回顧	3
第一節	房屋價格影響因素與風力發電機相關研究	3
第二節	研究方法之相關研究	6
第三章	研究方法與資料	11
第一節	實證模型	11
第二節	資料來源與說明	14
第三節	變數定義	19
第四節	研究分組設計與描述性統計	21
第五節	模型假設檢驗	26
第六節	穩健性檢驗設計	27
第四章	研究結果	31
第一節	模型估計結果	31
第二節	模型假設檢驗	36
第三節	穩健性檢驗	43
第五章	結論與建議	50
參考文獻	52

 
圖目錄
圖3-1桃園地區風力發電機與房屋地理位置圖	16
圖3-2桃園地區土地利用類型分布圖	16
圖3-3苗栗地區風力發電機與房屋地理位置圖	17
圖3-4苗栗地區土地利用類型分布圖	17
圖4-1桃園市0-6公里與7–9公里平均房價變化	37
圖4-2桃園市0-3公里與7-9公里平均房價變化	38
圖4-3桃園市4-6公里與7-9公里平均房價變化	39
圖4-4苗栗縣0-6公里與7–9公里平均房價變化	40
圖4-5苗栗縣0-3公里與7–9公里平均房價變化	41
圖4-6苗栗縣4-6公里與7-9公里平均房價變化	42

表目錄
表3-1差異中的差異分析表	13
表3-2桃園市樣本之各組描述性統計	22
表3-3苗栗縣樣本之各組描述性統計	23
表3-4桃園市樣本之各組描述性統計	24
表3-5苗栗縣樣本之各組描述性統計	25
表3-6桃園市0-6公里與7-9公里之樣本數量（全部）	28
表3-7苗栗縣0-6公里與7-9公里之樣本數量（全部）	28
表3-8桃園市0-6公里與7-9公里之樣本數量（抽選）	29
表3-9苗栗縣0-6公里與7-9公里之樣本數量（抽選）	29
表4-1桃園市與苗栗縣DID主迴歸結果	33
表4-2桃園市與苗栗縣DID估計結果	35
表4-3桃園市0-6公里與7–9公里平行趨勢檢定迴歸結果	37
表4-4桃園市0-3公里與7-9公里平行趨勢檢定迴歸結果	38
表4-5桃園市4-6公里與7-9公里平行趨勢檢定迴歸結果	39
表4-6苗栗縣0-6公里與7–9公里平行趨勢檢定迴歸結果	40
表4-7苗栗縣0-3公里與7–9公里平行趨勢檢定迴歸結果	41
表4-8苗栗縣4-6公里與7-9公里平行趨勢檢定迴歸結果	42
表4-9預期效應檢驗結果	43
表4-10桃園市與苗栗縣樣本之重複抽樣穩健性檢驗	44
表4-11桃園配對前後	45
表4-12苗栗配對前後	46
表4-13桃園市樣本平衡性檢定	47
表4-14苗栗樣本平衡性檢定（加權前與加權後）	48
表4-15桃園市樣本以PSM與IPW進行迴歸之估計結果	49

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