Purpose

The purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate appraisal. In these models, price is a dependent variable and real estate features are explanatory variables. Moreover, these kinds of models might support individual and mass appraisals.

Design/methodology/approach

A mixed estimation procedure was discussed in the research. It enables using sample and prior information in an estimation process. Prior information was provided by real estate experts in the form of parameter intervals. Also, sample information about the prices and features of undeveloped land for low-residential purposes was used. Then, mixed estimation results were compared with ordinary least squares (OLS) outcomes. Finally, the estimated econometric models were assessed with regard to both formal criteria and valuation accuracy.

Findings

The OLS results were unacceptable, mostly because of the low quality of the database, which is often the case on local, undeveloped real estate markets. The mixed results are much more consistent with formal expectations and the real estate valuations are also better for a mixed model. In a mixed model, the impact of each real estate feature could be estimated, even if there is no variability in the sample information. Valuations are also more precise in terms of their consistency with market prices. The mean error (ME) and mean absolute percentage error (MAPE) are lower for a mixed model.

Originality/value

The crucial problem in econometric property valuation is that it involves the unreliability of databases, especially on undeveloped, local markets. The applied mixed estimation procedure might support sample information with prior knowledge, in the form of stochastic restrictions imposed on parameters. Thus, that kind of knowledge might be obtained from real estate experts, practitioners, etc.

中文翻译：

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计量经济学房地产评估中的先验信息：混合估计程序

目的

本文的目的是展示如何在房地产评估的计量经济学模型中利用关于房地产特征对价值影响的先验知识。在这些模型中，价格是因变量，房地产特征是解释变量。此外，这些类型的模型可能支持个人和集体评估。

设计/方法/方法

研究中讨论了混合估计程序。它能够在估计过程中使用样本和先验信息。房地产专家以参数区间的形式提供了先验信息。此外，还使用了有关用于低居住用途的未开发土地的价格和特征的样本信息。然后，将混合估计结果与普通最小二乘法 (OLS) 结果进行比较。最后，对估计的计量经济模型进行了评估，包括正式标准和估值准确性。

发现

OLS 结果不可接受，主要是因为数据库质量低下，当地未开发的房地产市场通常就是这种情况。混合结果与正式预期更加一致，混合模型的房地产估值也更好。在混合模型中，即使样本信息没有变化，也可以估计每个房地产特征的影响。估值在与市场价格的一致性方面也更加精确。混合模型的平均误差 (ME) 和平均绝对百分比误差 (MAPE) 较低。

原创性/价值

计量经济学财产估值的关键问题在于它涉及数据库的不可靠性，尤其是在未开发的本地市场上。应用的混合估计程序可能以对参数施加随机限制的形式支持具有先验知识的样本信息。因此，这种知识可能是从房地产专家、从业者等那里获得的。