Commercial Real Estate Returns: An Anatomy of Smoothing in Asset and Index Returns
利用投资物业数据库的大量个体物业评估数据，研究评估平滑在个体物业与聚合指数层面的关系，发现常用去平滑方法高估了个体层面的平滑程度，并支持指数层面用ARFIMA模型、个体层面用ARMA模型描述评估回报。
In this article, we investigate the commonly used autoregressive filter method of adjusting appraisal‐based real estate returns to correct for the perceived biases induced in the appraisal process. Many articles have been written on appraisal smoothing but remarkably few have considered the relationship between smoothing at the individual property level and the amount of persistence in the aggregate appraisal‐based index. To investigate this issue we analyze a large sample of appraisal data at the individual property level from the Investment Property Databank. We find that commonly used unsmoothing estimates at the index level overstate the extent of smoothing that takes place at the individual property level. There is also strong support for an ARFIMA representation of appraisal returns at the index level and an ARMA model at the individual property level.