Why does access to jobs vary between city neighbourhoods?
Two households in one city may reach very different job opportunities because of their addresses and transport networks. The citywide job total does not reveal how many jobs each can reach. The relevant question is which suitable jobs can be reached from a specific home, at what time and cost; a city average hides this.
Locations of jobs and travel networks
1. Jobs are not evenly distributed across a city. Central business districts, industrial estates, hospital campuses and retail corridors concentrate different kinds of work. Measuring access from a neighbourhood requires more than counting establishments: qualifications and work schedules matter. Treating a nearby specialist vacancy as an opportunity for everyone conceals mismatches in skills. OECD research on divided cities highlights the spatial connection between transport infrastructure and economic opportunity. 2. Door-to-door travel includes walking to a bus, waiting, transfers and reaching the workplace from the final stop. One side of a city may have fast rail while another relies on infrequent buses. Two addresses can be the same number of kilometres from an employment centre yet differ because of peak-direction service, a bridge, congestion or transfer design. Calculate separately for households with a car and households that rely on public transport. 3. A common indicator counts jobs reachable within a chosen travel time, perhaps thirty or forty-five minutes. The threshold depends on the research question; it is not a universal entitlement boundary. A study should disclose the timetable, employment locations, walking network and time of day it uses. Drawing a straight-line circle can incorrectly include workplaces across a river that are difficult to reach on the actual network.
Inequality and sound comparison
4. The count of reachable jobs differs from a person's chance of being hired. Wages, shifts, caring responsibilities, discrimination and qualification requirements shape whether an opportunity is usable. If childcare hours conflict with a shift, even a strong transport connection may not be enough. A spatial map alone cannot explain every labour-market inequality. Personal information should be aggregated at a suitable level to protect privacy. 5. A new line to an employment centre can produce large time savings for underserved districts, or merely improve comfort in an area already served well. Compare the same time of day, job set and population before and after the change. New housing and relocation of firms can also influence results. OECD's inclusive growth guidance calls for granular neighbourhood-level data to target interventions and assess their effects. 6. A neighbourhood average must not be read as a description of every resident. Accessible vehicles, ticket costs and night services can change the map. Increasing the number of nearby jobs will not alone address job quality; safe travel, suitable wages and training need consideration together. Publish the data year, service timetable, transport mode, time threshold and boundary definition so results from different cities are not ranked using incompatible methods.