he disruptive impact of Chinese competitionThe Canadian textile and clothing sector recently experienced a series of negative shocks. The number of plants active in this sector halved between 2005 and 2013 as a consequence. Figure 1 depicts the evolution of textile and clothing employment, and shows that the sector also lost about two-thirds of its workforce between 2005 and 2013.
Figure 1 Employment in the Canadian textile and clothing industry, 2001-2013

Source: Behrens et al. (2017).
Meanwhile, textile and clothing imports from China increased by approximately 200% in a decade. A significant part of this increase was due to quota removals in 2005 at the end of the Multifibre Arrangement (MFA). The shift in trade protection was stronger in Canada than the US or the EU, because it did not limit the influx of textile imports (Audet 2007: 270). We investigate whether these shocks affected the plants located inside and outside clusters equally.
A bottom-up approachExisting research commonly uses industry-level aggregate data to evaluate the influence of geographic clustering on economic performance or resilience to shocks (Delgado et al. 2014). We look at the location of individual plants instead. Within a sector, plants operate in different locations – some belong to large geographic clusters, others to smaller but more specialised ones, and many plants are isolated.
We develop a bottom-up procedure that builds on point-pattern techniques from spatial statistics to identify clusters of geographically proximate plants from geocoded data. Figure 2 shows the location of textile and clothing clusters in Québec in 2001, the province with the highest share of textile and clothing employment in Canada.
Figure 2 Location of textile and clothing clusters in Québec in 2001

Source: Behrens et al. (2017).
As can be seen from the figure, there is substantial variation in the geography of individual plants and geographic clusters. With this procedure, we are thus able to compare plants' outcomes depending on whether they were inside or outside cluster