Modelling the supply of new residential construction in Aberdeen, UK

Abstract

Purpose

The purpose of this paper is to use local-level time series data to examine the determinants of housing starts and the price elasticity of supply for the Aberdeen local housing market.

Design/methodology/approach

Seven time series models are used in the analysis. The basic model treats housing starts as a function of the changes of current and lagged house prices, interest rate and construction cost. The other six models which are extensions of the basic model include other variables like time on the market, planning constraints and future expectations.

Findings

It is found that the local variables – changes in house prices, time on the market, planning regulation, lagged stock and lagged and future housing starts – are the main factors that influence new residential construction in Aberdeen. None of the national variables is significant, confirming the importance of limiting housing market analysis to the local level. The price elasticity of supply estimated is in the range of 2.0 to 3.2 for housing starts and 0.01 to 0.02 for housing stock. These estimates are higher than most of the elasticities for the other UK local markets.

Originality/value

There is the need to better understand the supply of housing at the various local housing markets. Unfortunately, however, most housing supply studies use national data. Because national data are aggregation of local data, using national studies results for local markets may be uninformative. Also, the few existing local studies use typically cross-section data or at least time series over relatively short time spans. This paper makes an effort to use quarterly time series data over a 25-year period for a local market and also include a planning variable which is different from local markets and often ignored in national or regional studies.

Citation

Owusu-Ansah, A. (2014), "Modelling the supply of new residential construction in Aberdeen, UK", International Journal of Housing Markets and Analysis, Vol. 7 No. 3, pp. 346-362. https://doi.org/10.1108/IJHMA-07-2013-0043