• 沒有找到結果。

第六章 政策意涵與未來研究方向

第二節 未來研究方向

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價會愈低,而愈高房價房屋的房屋總價以及每坪房屋單價會愈高。在財產稅資本 化的敏感性分析方面,也得到當每坪地價稅支出、房屋稅支出或是財產稅支出愈 高,房屋總價或每坪房價將會愈高。

對於上述的結論,亦可以提供給台北市政府相關單位政策制定上建議。本文 研究發現台北市自用住宅的財產稅稅賦負擔太輕,尤其是地價稅,因此無法透過 提高財產稅的方式來抑制房價。此外,根據分量迴歸的結果發現,房屋稅支出愈 高,低房價的房屋總價會降低,這結果表示在低房價房屋稅的租稅負擔是高於最 適水準;然而高房價的房屋總價會因房屋稅支出愈高反而愈高,這結果表示在高 房價房屋稅的租稅負擔是低於最適水準。因此透過這些發現,建議台北市政府相 關單位應將高房價的房屋稅租稅負擔提高超過最適水準,藉由此才能有效的抑制 房價的上漲。

第二節 未來研究方向

Rosen (1974) 發展特徵方程式估計法來估計具有多種特性的商品之後,除了 產業界以及學術界大多以此法來分析影響房價的因素,許多的文獻利用特徵方程 式估計法來分析房屋價格,本研究利用分量迴歸模型並控制房屋特徵、房屋類型、

座落地區、屋齡等,分析台北市 2002 年至 2006 年「自用住宅」的個別資料,探 討台北市自用住宅財產稅的支出對於房屋價格的影響,而為了更可以控制更詳盡 的地區特性,將台北市 12 個行政區的地區虛擬變數改採用五碼的郵遞區號,五 碼郵遞區號是將地區細分到地址中「號」的部份,利用此法更可以將不動產之間 鄰接的特性、公共設施狀況、學區等做詳細的區分以及控制。

本研究利用 King (1977) 提出使用財產稅的支出替代財產稅有效稅率,解決

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模型設定錯誤問題的建議。雖然地價稅稅基土地公告地價及房屋稅稅基房屋評定 現值的評價上皆遠低於其市場價值,但是土地公告地價及房屋評定現值的評價過 程中也會將市場價值列入考量,為了避免可能會產生的內生性問題,未來研究方 面,可以先做內生性檢定,檢查變數之間有無內生性的問題,再用工具變數 (Instrumental Variables) 及兩階段最小平方法處理內生性問題。

在分量迴歸的模型設定中,為了避免衡量公共設施產生誤差,並沒有將公共 設施加入模型討論。在未來研究方面,可以利用 GIS (Geographic Information System) 地理資訊系統將會影響到不動產價格的區域性特性列入考慮,例如鄰近 學校數量、鄰近市場 (傳統市場、大型量販店以及超級市場等) 數量、鄰近公園 數量、鄰近主要幹道、鄰近醫療院所數量、鄰近捷運站數量以及人口結構等,利 用 GIS 技術將影響不動產價格的計量模型的建構更加完善。

估算財產稅有效稅率方面,在估算地價稅及房屋稅稅基過程中還是會有產生 誤差的現象,未來研究若可以取得民眾繳納房屋稅以及地價稅的實際資料,如此 不論在計算財產稅有效稅率,或是利用此實際資料探討財產稅資本化效果,皆可 以更準確的數據以及實證結果。最後,本研究不動產交易資料,從 2002 年到 2006 年共 166,098 筆資料,未來除了將其他縣市資料做進一步的研究分析之外,在未 來幾年各地方政府顯著調整地價稅以及房屋稅稅基之後,希冀可以有更新更完整 的資料,並透過多方面的分析與比較,提出改善財產稅制度的最佳方法。

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