囤房稅政策與房價效應：以臺灣大臺北都會區的實證為例

Abstract

本研究分析了2013年1月到2017年6月內政部不動產實價登錄中臺北市、新北市和基隆市行政區的資料集，運用享樂定價模型探究臺灣囤房稅政策對房價的影響。實證結果顯示，該政策並未達到降低房價的目標，反而導致房價上漲，整體形成正向的財政資本化現象。此外，我們進一步以交互作用函數瞭解正財政資本化在不同經濟程度的地區、建物類型和行政區之間的影響。\n實證結果顯示，囤房稅政策對於華廈的影響最為顯著，導致房價增幅最高。住宅大樓和套房也出現顯著的價格上漲，尤其是住宅大樓對市場需求的反應更為明顯。商店和辦公商業大樓的價格也有所上漲。然而，公寓的價格下降最多，這是因為其買者因稅負負擔增加，造成交易房價下降，間接導致了不同建物類型的屋主族群間出現財政資本化。\n儘管在政策實施前，本研究未發現房價與當地經濟狀況之間的明確相關性，但研究發現政策實施後正向財政資本化只會發生在高所得地區，意即直接受政策影響的臺北市。在綜合考慮行政區層面的因素時，我們證實土地公告現值的調整直接影響了房地產囤積的成本，進而對不同行政區的房價結果產生影響。

This study analyzes the impact of the multi-house tax policy on housing prices using sales records from the Actual Price Registration of Real Estate Transaction dataset in Taipei, New Taipei, and Keelung Cities. The findings from January 2013 to June 2017 indicate that the policy did not achieve its goal of lowering housing prices; instead, prices increased, showing a positive fiscal capitalization phenomenon. Besides, this paper utilizes the interaction function to know how positive fiscal capitalization impacts regions with different income levels, property types, and administrative districts.\nThe empirical results show that the multi-house tax policy had the most significant impact on mansions, resulting in the largest price increase. Residential buildings and suites also experienced substantial price increases, with residential buildings showing a more pronounced response to market demand. Shopfronts and office buildings also demonstrate price increases. Condominium prices, on the other hand, decreased due to increased tax expenses for buyers of condominiums particularly, indirectly leading to fiscal capitalization among homeowners of different property types.\nWhile no clear correlation between housing prices and local economic status was found before policy implementation, positive fiscal capitalization was observed only in high-income areas, specifically in Taipei City, which was directly affected by the policy. At the administrative district level, when considering general factors, adjustments in declared land present values directly influenced property hoarding costs, thereby affecting housing prices among different districts.