Time series observation of relationship between United States private residential construction spending and its indicators

Abstract

Purpose Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive studies on PRRESCON forecasting. This study aims to address the gap in knowledge by conducting a comprehensive exploration of indicators for PRRESCON using time series methods. Design/methodology/approach Granger causality test trials were conducted between PRRESCON and all of its potential indicators before the vector autoregression model was implemented. Extensive effort was exerted toward model interpretation in the form of impulse–response functions. Findings Impulse–response functions indicated that the escalation of labor supply, material/construction costs and issued building permits at any given time consistently had a positive impact on PRRESCON 10–11 months later, with a 95% confidence interval. Conversely, the unemployment rate and housing value escalations at any given time were found to have a negative impact on PRRESCON 10–11 months later in more than 95% of the instances. Furthermore, material/construction cost escalations at any given time were shown to have a negative impact on PRRESCON 7 months later in more than 95% of the instances. Originality/value Current forecasting literature on construction spending focuses exclusively on the parameter’s relationship with gross domestic product and the architectural billing index. This study reveals many additional indicators, many of which are directly related to the implementation of housing development projects. The paper is also the first in the body of forecasting literature, to the best of the authors’ knowledge, to conduct impulse–response analysis on residential construction spending.