Capturing Resilience

There are a number of ‘models’ that have been developed by commentators on economic resilience in an effort visualise resilience.  Martin (2011) suggests that there are four key reactions to a recessionary shock; keeping in mind the regions’ prior structure and economic environment, this can be Re-Orientation, Renewal, Resistance and Recovery.  Re-orientation is the adaption of the regional economy in response to the shock; this can be changes in industrial, technological and workforce composition, business models, working practices and so on.   Renewal considers whether the regions’ growth path has altered to a new growth trend or resumed its pre-shock development path.  Resistance can also be thought of in terms of elasticity, mapping the degree of sensitivity or depth of reaction of the economy to the shock.  This can be reflected in the scale of decline in output and jobs amongst other factors.  The speed and degree of Recovery of the regional economy is significant, as is the extent to which the region returns to the pre-shock growth path.

Martin’s model of regional resilience forms a useful starting point for our assessment.  What we are interested in is what features lead to the observed response. 

System change models

As Martin highlights, system change is quite a central theme to resilience, with regions often face with the notion that to be resilient they must change and adapt in light of a shock that is thrust upon them.  This has been illustrated in the Panarchy model of system change put forward by Pendal et al (2010).  This views the system as in a constant state of flux with varying levels of resilience at each stage.  The conservation phase is at the bottom of the rung with resilience being low.  This is a time of stability, certainty and increased rigidity. Following this is the ‘release’ phase where there is a collapse, uncertainty and positive destruction that enables new thinking.  Whilst resilience is low entering this phase, it slowly increases as new ideas lead the system into the reorganization phase.  This is a time when innovation is abundant, restructuring is likely and there is the greatest level of uncertainty.  As a result of this pro-activity resilience is high.  This then leads to a time of growth and seizing of opportunity, the exploitation phase.  Resilience is high but slowly decreasing as confidence in the system grows and the ‘comfortable’ stability of the conservation phase is once again reached.

Whilst this model was originally used by Gunderson and Holling (2002) to understand the functioning and resilience of complex ecological and social systems, the ideas are easily translated to think of the economy, which, much like an ecosystem has an idendity and faces disturbances.  Gunderson and Holling assert that an ecosystem’s resilience expands and contracts throughout the four-phase cycle as slow variables change. Resilience is thus not a fixed asset but a continually changing, dynamic property or capacity (Gunderson and Holling, 2002).


A number of tools are being developed for both researchers and the wider public.  They will be available through the ESPON website (  Of interest will be the Mapfinder function, allowing access to maps produced by different projects, and the ESPON mapping tool, which will allow the user to create maps and graphs based on ESPON's Key Indicator database.  The Mapfinder is expected to be online early in 2013, with a prototype of the mapping tool available later in the year.

Also of interest will be the Hyperatlas.  This is already available and enables some limited data manipulation, which can illustrate, and potentially help analyse, a number of driving forces in territorial development.  Again it is based on the Key Indicators.  Of particular value is the Lorenz Curve analysis available in the 'expert mode'. We encourage you all to take a look and see whether it has value to your work.

The ESPON database is hosted at  This contains data for the Key Indicators provided by each ESPON project, some limited information on case studies undertaken by projects and a wide range of background data provided by each project.  The most comprehensive data is for each Key Indicator.  This must comply with the INSPIRE Directive and is subject to rigorous quality checks.  The data is intended to be available for download and independent analysis.  However, the user-interface remains under development and is still not very friendly. We do feel that this is worth exploration and could potentially form a powerful tool.