The COVID-19 Pandemic, Airbnb and Housing Market Dynamics in Warsaw

In this study, we analyse the impact of COVID-19 on house rents and prices in Warsaw, the capital of Poland. Hedonic indexes indicate a slight increase in prices (ca. 1.2%) and a substantial drop in long-term rents (ca. -7.7%) between March 2020 and December 2020. The largest decline in rents occurred in centrally located neighbourhoods, which was largely due to the inflow of new housing supply from the short-term rental market (the Airbnb Warsaw market shrank by almost 30% in December 2020 y/y). Using hedonic methods, we show the effect of the shrinking Airbnb market on the drop in long-term rents. The study indicates the elasticity of rents with respect to Airbnb supply, with a 1% change in Airbnb listings leading to a 0.031% change in rents.

COMPARATIVE ANALYSIS OF HEDONIC AND FILTERED INDEXES IN SELECTED CITIES

Property price indexes are difficult to determine both from the substantive and technical/organizational points of view. Various methods of constructing such indexes have been developed in order to overcome these difficulties. To this end, the author compares two types of indexes: hedonic indexes and ones termed filtered for the purpose of this particular paper. Hedonic index values come from Polish National Bank (NBP) publications, while the filtered indexes have been computed with the use of the 4253H filter on the basis of the NBP announcements on mean property prices. Thus, the results are comparable as both types of indexes are derived from the same input databases. The analysis covers both the comparison of the obtained results as well as a discussion of substantive and technical problems encountered when building the property price indexes.

Robust hedonic price indexes

Purpose – The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes. Design/methodology/approach – The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated. Findings – Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes. Practical implications – Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes. Originality/value – This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.

Hedonic Price Indexes: A Comparison of Imputation, Time Dummy and ’Re-Pricing’ Methods

SummaryThe main approaches to measuring hedonic indexes in the academic literature are the imputation approach and the time dummy approach. This paper compares both approaches, discusses an alternative method called hedonic re-pricing, and comments on a recent contribution by Diewert et al. (2009). The aim is to explain the differences between the various hedonic approaches as well as their similarities, and to point to the implications for statistical agencies. Hedonic price indexes can be weighted or unweighted and the paper addresses the issue of choice of regression weights. For unweighted indexes it is shown that the ’full’ hedonic imputation approach and the time dummy approach implicitly leave the matched part of the indexes unaffected, just like ’single’ and ’double’ hedonic imputation do explicitly.