Analysis of Firm Location and Relocation Around Maryland and Washington, DC Metro Rail Stations
Iseki, Hiroyuki and Robert P. Jonesview report
Transit Oriented Development (TOD) is commonly adopted in regional transit plans as a tool to
achieve economic growth, sustainable land use patterns, and pedestrian-friendly communities.
Some critics, however, have questioned TOD as an agent for net job creation. While some
research has used case studies and agglomerated regional datasets to examine changes in
employment near transit with positive results, there is a paucity of literature examining the
relationship between rail stations and employment by industry at the transit station level.
This is a descriptive study that seeks to address three key questions about the effects of
station proximity: 1) What is the overall distribution of firms in relation to metro station
locations? 2) What industries, if any, are more likely to locate near transit stations? 3) Does a
new transit station result in a net gain of firms within the station proximity and for the region or
does it merely redistribute existing firms? This study applies GISs to examine the National
Establishment Time Series (NETS) dataset within the region comprising Washington DC,
Montgomery, and Prince George’s Counties in Maryland. The NETS dataset contains
longitudinal and cross-sectional firm-level data for the years 1990 - 2010, which allow us to look
at changes in the number of firms within relatively small geographic areas around Metro stations,
several of which were constructed during the 21-year period. The NETS dataset also provides
firm-level relocation information for the same time period to assess firm movement within and
outside of the study area as they relate to transit stations.
First, we identify firms within station buffers and conduct a location quotient analysis.
Second, we conduct a spatial analysis of firm locations over time, applying choropleth maps,
descriptive spatial statistics, and hot spots analysis. Third, we plan to apply a space-time cluster
analysis that visualizes the distribution of spatial- temporal data, taking into account the time
dimension, and enables us to identify clusters of events constrained by both space and time.
Finally, using NETS firm relocation data for the period of 1990 to 2010, we conduct an analysis
of firm locations before and after each relocation. The analysis is conducted for all industries as
a group and a few specific industries that show a strong presence in the region, including finance,
insurance, and real estate (FIRE) industries, which have been found to predominate in dense
This study contributes to the literature on the effect of transit investment and TOD on
economic development, particularly addressing the question of net effects for locations beyond
the immediate station area, which is an important implication from a regional planning