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The Hedonic Pricing Model Applied to the Housing Market

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  • My-Linh Thi Nguyen

Abstract

Purpose: The article applies the hedonic pricing model to estimate house price in the housing market of Vietnam, which is a country with a fledgeling housing market, so the study is expected to bring interesting findings. Design/Methodology/Approach: By applying the hedonic pricing model, most of the previous studies have reported that house price is significantly influenced by the characteristics of the house itself, its location and surrounding facilities. Based on this, the article adopts the Ordinary Least Squares (OLS) regression in combination with robustness statistics in the model estimation, so the estimated results on house price are reliable and able to be widely applied. Data are collected through the survey into housing projects in Ho Chi Minh and Ha Noi city, which are the two largest cities in Vietnam. Findings: The findings reveal that the hedonic pricing model can be applied to estimate house price in Vietnam’s housing market. This can be said to be a big success in giving first empirical evidence in Vietnam on this matter. Specifically, house price is negatively affected by its proximity to the city center. Also, factors including house size, house type, house structure, number of bedrooms, amenities around the house exert a positive influence on the price. Practical Implications: The estimated results are typical and reliable, which can be applied universally. Originality/Value: The study confirms the hedonic pricing model can be well-applied to accurately estimate the price of houses in Vietnam. More than that, the findings are also essential for other countries, especially those with a nascent housing market like Vietnam.

Suggested Citation

  • My-Linh Thi Nguyen, 2020. "The Hedonic Pricing Model Applied to the Housing Market," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 416-428.
    • Handle: RePEc:ers:ijebaa:v:viii:y:2020:i:3:p:416-428
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    References listed on IDEAS

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    1. Jozef Zurada & Alan S. Levitan & Jian Guan, 2011. "A Comparison of Regression and Artificial Intelligence Methods in a Mass Appraisal Context," Journal of Real Estate Research, American Real Estate Society, vol. 33(3), pages 349-388.
    2. Limsombunchai, Visit, 2004. "House Price Prediction: Hedonic Price Model vs. Artificial Neural Network," 2004 Conference, June 25-26, 2004, Blenheim, New Zealand 97781, New Zealand Agricultural and Resource Economics Society.
    3. Chihiro Shimizu, 2014. "Estimation of Hedonic Single-Family House Price Function Considering Neighborhood Effect Variables," Sustainability, MDPI, vol. 6(5), pages 1-15, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Hedonic pricing model; house price; housing market; real estate; Vietnam.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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