建立以單一函數推估租賃住宅之供給及需求選擇機率彈性－台北都會區與台南都市地區之比較分析

Estimating the Supply and Demand Elasticity of the Rental Housing Choice Probability, via a Single Model Aporiach-An Empirical Comparison of Taipei and Taipei

陳彥仲(Yen-Jong Chen) ； 許佑全(Yu-Chuan Hsu)

《都市與計劃》 31卷4期 (2004/12) Pp. 413-426

https://doi.org/10.6128/CP.31.4.413

摘要

文獻中，在推估供給彈性與需求彈性之方法，一般是分別建立需求函數及供給函數，再各自推估彈性係數。即供給面與需求面各自獨立。然而，這樣的推估方式雖然普遍被接受，但卻仍存有其理論上的不足之處。那就是忽略了供給與需求之間的互動關係。意即，當在推估供給彈性係數時，假設需求不變；反之，當在推估需求彈性係數時，假設供給不變。本研究嘗試透過實際租賃住宅市場之交易，以單一函數，同時建立供給函數及需求函數之實證模型，並推估租賃住宅之供給彈性與需求彈性。本研究以出租住宅中達成出租交易之個案，並以其交易價格為房東及租戶之市場價格共識。經以Probit模型分別建立房東之「出租」與「不出租」以及租戶之「承租」與「不承租」之二項選擇模型。並以完成交易之個案建立供需短期期望均衡之交易價格函數，用以推估房東及租戶在租金價格及租戶所得變動下之選擇機率彈性。推估的結果，台南地區租賃住宅市場的需求機率彈性介於0至-0.41之間，而供給機率彈性則介於0至0.33之間。而台北地區的需求機率彈性是介於0至-0.58之間，供給機率彈性則介於0至0.30之間。此結果顯示，房客對價格變動的敏感程度會相對高於房東。此現象台北與台南皆然。另，台北地區的租賃住宅市場之需求機率彈性，比台南地區高。此或可被解釋為台北之承租者的所得比較高，因而租賃之選擇機會相對較大。另一方面，也可能意含由於台北之都會地區的租賃住宅市場比台南之一般都市地區的租賃住宅市場大，需求者有較大的租賃選擇空間。且其對租賃住宅的選擇要求比台南之承租者來得敏感，對價格的敏感性也自然會高於台南地區。

關鍵字

租賃住宅 ； Probit模型 ； 選擇機率 ； 彈性

並列摘要

In the literature, housing price and income elasticity are estimated separately on the supply side and demand side. In this study, we develop an approach with a single model that can be used to estimate the supply and demand elasticity at the same time. We firstly applied the well-developed Probit model to establish the binomial-choice model on the rental housing supply side and also on the demand side. Based on real dealing prices in the rental market, we then solve the 'equilibrium' of the expected probability of the rental decision, and derive an equation of the rental price to be a function of the housing attributes and also the socio-economic attributes of the home owner and of the tenants. Finally, by plugging the calibrated coefficients back into the supply and demand models, we are then able to estimate the elasticity of the choice probability on the supply and demand sides with respect to the changes in the housing rental price. The probability elasticity was also estimated with respect to the changes in tenants' family income. The approach was empirically used to estimate the elasticity for the Taipei metropolitan area, and also the Tainan city area for comparison. We conclude that: (1) The probability elasticity is inelastic, both on the supply side and demand side, in our selected cities of this study. (2) When the rental price increases at 1% in the Taipei case, the probability elasticity is -0.58 on the demand side and 0.30 on the supply side respectively. For Tainan city, the same probability elasticities are estimated to be -0.41 (demand) and 0.33 (supply) respectively.

並列關鍵字

Rental housing ； Probit model ； Choice probability ； Elasticity

參考文獻

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