The Spatial Impact of Commuting on Income: a Spatial Microsimulation Approach

Abstract

The Irish economic boom resulted in a substantial increase in car-ownership and commuting. These trends were particularly noticeable in the Greater Dublin Area (GDA), with an unprecedented increase in employment levels and private car registrations. While employment dropped by an overall 6 % during the recent economic recession, the already increasing process of suburbanisation around Irish main cities continued. The commuting belt around Dublin extended beyond the GDA with a substantial number of individuals commuting long distances. The aim of this paper is to examine the impact of both monetary and non-monetary commuting costs on the distribution of employment income in Ireland. The Census of Population is the only nationwide source of information on commuting patterns in Ireland. However, this data set does not include information on individual income. In contrast, SMILE (Simulation Model for the Irish Local Economy) contains employment income data for each individual in Ireland. Using data from the Census of Population of Ireland, discrete choice models of commuting mode choice are estimated for three sub-samples of the Irish population based on residential and employment location and the subjective value of travel time (SVTT) is calculated. The SVTT is then combined with the SMILE data to produce a geo-referenced, attribute rich dataset containing commuting, income, demographic and socio-economic data. Results show that the monetary and non-monetary costs of commuting are highest among those living and working in the GDA.