Sunday, September 12, 2010

Measuring Resilience

The recent BBC commissioned research of resilience in the England by Experian ( factsheets are available at ) has produced some interesting results and highlights or confirms depending on your viewpoint, a clear north-south divide in terms the vulnerability and resilience of areas to the current economic climate, in particular to the expected government cuts in spending ( . The northeast is identified as the most vulnerable or least resilient area ( with explanation of this focusing on the number of people employed in public sector jobs, the history of closures in large tradition industrial employers such as iron and steel and the lack of likely job creation in the private sector. The vulnerability of the northeast is contrasted with locations such as St Albans where the entrepreneurial spirit and the knowledge based industry focus are highlighted.

Any attempt to measure vulnerability and resilience is a good idea. Trying to put numbers to these issues is useful in debate and in identifying factors that may be important in the ability of an area to resist major events, which an economic downturn and a round of spending cuts are, even if they are economic and political rather than geophysical events. Care needs to be taken, however, to understand that these figures, any figures, that try to capture such a complex and slippery set of concepts will never succeed in illuminating every conceptual facet. It should also be borne in mind that merely having the figures can begin to set the agenda for the debate by focusing on the particular metrics used in compiling the figures. Any data collection will have some model of reality behind it, some idea of what determines resilience and vulnerability, and so will always collect data in the light of that model. Experian have published their methodology in detail on the BBC website ( ) as well as the Excel data files upon which the analysis is based ( ). This is, in my view, an excellent idea as it allows everyone to understand how the final indices are created and provides hints about the model of reality behind the numbers.

Experian view economic resilience as describing the ability of an area to withstand and respond to shocks in an external environment. Economic resilience is composed of four themes: business, community, place and people. Each is weighed differently in terms of it contribution to the overall index, with the business variables accounting for 50%, with the other themes accounting for about 17% each. Each theme is described by a series of question. Business, for example, contains questions such as how strong is the local business base? Is it dependent on sectors that have been hit by recession? Are businesses dependent on local markets, or do they export? People contains questions about age of population, their jobs and earnings. Community contains questions about life expectancy, do neighbours look out for each other and long-term unemployment. Lastly, place contains questions on house prices, green space and GCSE attainment rates. Experian use 33 variables to create the index and do state that the variables used were dictated, at least in part, by the data available at local authority level.

The actual variables used are listed for each theme and range from insolvency rates, to business density, to % of population who are corporate managers, deprivation and crime rates.

This is the basic outline of the analysis and its methodology, so from the viewpoint of environmental geography what can be asked and interpreted from this analysis? Firstly, is the unit of analysis used, the local authority area, the most appropriate for what they are trying to analyse, economic resilience? The LA may be a unit for which there is lots of data as it is an administrative unit but is it the unit within which businesses operate? Do businesses locate within local authorities or within business parks (maybe with incentives from local authorities) or where successful business or businesses like them are already located? Similarly, is the local authority really an appropriate area within which to judge community? Are communities this big? You all probably know your own local authority area, do you think it is that homogeneous, are all parts of it really that similar or are there ‘good’ and ‘bad’ bits? The appropriate unit of analysis is a continual problem in geography and, to be fair to Exeprian, they have taken a unit for which there is a lot of data and for which data is collected. This data is not collected fro the type of analysis Exeprian have undertaken so it doesn’t exactly match what they would like to be available but virtually every survey has this problem as well. The important thing to bear in mind is that whatever spatial unit you select to use there will always be problems and there will always be a geography below or above the unit you select. It is down to you to decide if these other geographies are more appropriate.

Secondly, the method of ranking local authorities for different themes and then combining ranks can be misleading. A small, fractional percentage difference between two local authorities may be the difference between being ranked 5th adn 6th whilst a 10% difference may result being ranked 320th and 321st. You do not get any feel for the magnitude of the differences between areas. This is compounded once you combine ranks. So a drop between being 1st and 25th in the business themes may only reflect a slight difference in the absolute, numerical values of variables but is represented by a large number of places in the ranksing. A drop from 200th to 201st in the rankings may represent the same absolute differences in the magnitude of the variables as between the first 25 areas in the rankings. The raw data is needed to assess how the rankings and absolute changes match up. It shoudl be noted, however, that Experian do state that they have considered the correlation between variables in their analysis, another key issue in derving a meaningful statistic.

Thirdly, what do the variables used tell us bout the type of economy that Experian view as resilient and as vulnerable? The business variables depict resilience as being determined by a strong private sector and one that is not reliant upon its local market for its existence. Innovation, knowledge-based and able to draw on a reserve pool of skilled labour seem to be other important determinants of a strong business theme. Does this match your image of a strong, contemporary economy? What about the provision of infrastructure – or is that down to the private sector as well? Public services are viewed as a weakness in the local economy despite the need for provision of such services to support the private sector. If you have an aim to convert public to private then an area where private enterprise is strong are likely to be areas that rapidly take on public services once aspects of them are privatised. Likewise, people variable focuses on level of qualification and level of corporate managers in the population, once again highlighting the potential for a privatisation of the public. The focus on knowledge-based services may also suggest a preference for small firms as drivers of the local economy rather than large employers.

Thirdly, the community and place variables once again have a model of what is ‘good’ and ‘bad’ behind them. Indices such as long-term unemployment, claimant count and income vulnerability (likely to affect lower paid but increasingly the middle income as well) all point to a relatively inflexible work force in terms of skill development relevant for the sectors identified as important in the business variables, e.g. knowledge-based services. Place variables are a more mixed bunch ranging for educational attainment (related to skills again) through to crime rates and house prices. Do you feel these variables really reflect the feelings and strengths of communities and their networks of relations? The variables seem very static and unable to grasp the dynamic nature of such relations.

Overall, the Experian map is a great starting point in the debate over resilience and vulnerability to economic events and, potentially, other events as well. But it is only a starting point and like any analysis it is limited by the data available and will have underlying assumptions about what is ‘good’ and ‘bad’ based on a particular view of how the economy functions or should function. At least there is now a basis for discussion but the survey should not become an anchor point that sets the agenda without question.

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