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<p>This study developed a hedonic price model for Xaythany District, Vientiane, Lao PDR, utilizing key road-related variables for land valuation. To account for unobserved locational dynamics in this data-scarce context, residuals were spatially interpolated to generate a Locational Value Response Surface (LVRS), subsequently integrated into the mass valuation framework. Although road variables significantly influence land values, significant residual spatial autocorrelation revealed omitted locational factors. Incorporating the LVRS substantially reduced this autocorrelation and improved model performance across key indicators, including root mean squared error (RMSE) and mean absolute percentage error (MAPE). Notably, the coefficient of dispersion (COD) decreased from 27.199% to 12.678%, indicating enhanced valuation uniformity. These findings demonstrate that the LVRS effectively complements road-based valuation systems as a spatial diagnostic layer. By identifying areas requiring further investigation, the LVRS guides phased data collection and supports the advancement of public land appraisal in data-limited developing cities.</p>

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Spatial value modeling for public land appraisal in Lao PDR

  • 期刊论文

  • 发表日期：

    2026年7月16日

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  • Seong-Il Park,
  • Seung-min Joo

摘要

This study developed a hedonic price model for Xaythany District, Vientiane, Lao PDR, utilizing key road-related variables for land valuation. To account for unobserved locational dynamics in this data-scarce context, residuals were spatially interpolated to generate a Locational Value Response Surface (LVRS), subsequently integrated into the mass valuation framework. Although road variables significantly influence land values, significant residual spatial autocorrelation revealed omitted locational factors. Incorporating the LVRS substantially reduced this autocorrelation and improved model performance across key indicators, including root mean squared error (RMSE) and mean absolute percentage error (MAPE). Notably, the coefficient of dispersion (COD) decreased from 27.199% to 12.678%, indicating enhanced valuation uniformity. These findings demonstrate that the LVRS effectively complements road-based valuation systems as a spatial diagnostic layer. By identifying areas requiring further investigation, the LVRS guides phased data collection and supports the advancement of public land appraisal in data-limited developing cities.