國際碳中和趨勢對不動產供給面、需求面及 價格之影響分析The Impact of International Trend of Carbon Neutralization on the Supply Side, Demand Side and Prices of the Housing Market

本研究探討國際碳中和的趨勢下，課徵碳稅對不動產市場的衝擊。首先探討需求面，消費者能接受碳稅所致的房價漲幅；其次探討供給方中影響課徵碳稅的因素；最後進行課碳稅對於不動產價格影響的模擬。結果發現，在需求面，多數受訪者認為徵收碳稅費後房價將上漲，但超過半數的受訪者不願意接受因碳稅所致的上漲。在供給過程中，影響碳排之重要性排序為：(1)建材生產與運輸；(2)建設階段；(3)拆除與回收。最後，模擬結果指出，市場將因技術進步或政策調整，最終房價仍可能接近初始價格的水平，顯示課徵碳稅之政策對市場之長期影響依然可控制。
關鍵詞：碳中和、淨零碳排、碳稅、層級分析法(AHP)、Logit迴歸、二項式評價模式(BPM)

This study explores the potential impact of the “carbon tax” on the real estate market through three dimensions. First, on the demand side, to what extent of the increase of house prices is acceptable for consumers? Second, on the supply side, what are the important factors affecting the carbon tax and their ranking? Third, what is the potential impact of carbon tax on house prices? This study conducts surveys on the consumers and suppliers, and then employs the Logit Regression Model and “Analytical Hierarchy Process” (AHP) for analysis, respectively. Lastly, the “Binomial Pricing Model” (BPM) is employed to simulate the potential price change from the carbon tax.
Results show that, on the demand side, most respondents expect that house prices will increase after the imposition of carbon tax, but over a half are reluctant to pay for the price increase. On the supply side, the AHP analysis shows that during the construction period, the procurement of construction materials and the transportation is the most important stage affecting the house prices, followed by the construction stage and then the destruction and recycle stage. In the simulation, the BPM result shows that as time passes, the market will get accustomed to the new system, and the technique will improve, and the policy will make adjustment accordingly. The house prices may return to its original level. This result indicates that as the policy engage in the de-carbonization, the impact of carbon tax is still controllable.
Key words: carbon neutralization, net-zero carbon emission, carbon tax, Analytical Hierarchy Analysis (AHP), Logit Regression, Binomial Pricing Model (BPM)