Abstract
The age–period–cohort problem has been studied for decades but without resolution. There have been many suggested solutions to make the three effects estimable, but these solutions mostly exploit non-linear specifications. Yet, these approaches may suffer from misspecification or omitted variable bias. This paper is a practical-oriented study with an aim to empirically disentangle age–period–cohort effects by providing external information on the actual depreciation of housing structure rather than taking age as a proxy. It is based on appraisals of the improvement values of properties in New Zealand to estimate the age-depreciation effect. This research method provides a novel means of solving the identification problem of the age, period, and cohort trilemma. Based on about half a million housing transactions from 1990 to 2019 in the Auckland Region of New Zealand, the results show that traditional hedonic prices models using age and time dummy variables can result, ceteris paribus, in unreasonable positive depreciation rates. The use of the improvement values model can help improve the accuracy of home value assessment and reduce estimation biases. This method also has important practical implications for property valuations.
Highlights
The hedonic price method, known as hedonic regression, has been extensively used in real estate and urban economics research over the past forty or fifty years1. Some of these applied areas include the adjustment for quality in constructing a housing price index, mass valuation of properties, the analysis of demand for urban and housing characteristics, and the testing of assumptions in spatial economics
The models are empirically tested using housing transaction data recorded by Auckland Council, New Zealand, from January 1990 to December 2019 (360 months), which, after all the outliers are excluded, provides about half a million housing transactions
In addition to Yiu and Cheung (2021), Cheung and Yiu (2022), and many hedonic pricing modeling applications in New Zealand housing market, the major distinction in this study is the use of the variable ‘building age’
Summary
The hedonic price method, known as hedonic regression, has been extensively used in real estate and urban economics research over the past forty or fifty years. The most common specification of the hedonic price model is to use time dummy variables to estimate house price inflation over time These attempts either omit age or cohort (year-built) variable. Since they do not have any a priori information on the actual separate effects of the age–period–cohort APC, there is no way to tell whether their approaches are promising or not Since they take age as a proxy of deterioration, their methods cannot reflect changes in housing conditions, such as renovations or rehabilitations. We took a practical-oriented approach by exploiting the appraised improvement values of housing as a direct indicator of the depreciation/appreciation due to the changes in the physical conditions of the structures This approach is novel in tackling omitted variable bias of APC effects on housing prices.
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