Statistics and data: enhancing cooperation across borders
Collecting, processing, validating and publishing statistical data are delicate processes, which require sound guidelines and structures in order to produce reliable, comparable and valid data. As data is an abstract representation of concrete reality, it is always connected to specific assumptions and calculations. As an example, regional employment statistics have to follow a concrete set of rules with regards to how they determine the place of employment and thus attribute it to a region.
While it can be safely assumed that data collected by one particular institution can be considered comparable, as it is collected and processed in the same manner, this is not necessarily true when data is collected by multiple institutions in different countries.
While on EU-level institutions such as EUROSTAT collect harmonized data either through the primary collection (such as surveys) or by publishing guidelines for national statistical offices on how to collect and process them, data is not necessarily harmonized and thus comparable when collected by national or regional institutions without such guidance.
As the methods applied by national- or regional statistical offices are in many cases not even publicly accessible, this also prevents attempts to apply estimation techniques and corrections in order to harmonize the data in retrospect.
Considering the need for improved data in cross-border areas, the ESPON TIA CBC project identified various suggestions for improvement of data collection and coordination. As the case studies in the ESPON TIA CBC project revealed, the problem goes even further, as various valuable indicators on a regional level are only collected within one of the two countries involved. Therefore a clear need for coordination and cooperation on multiple levels and especially across bordering regions has been identified.
Coordination and cooperation on a general level is not only the goal of Cross-Border-Cooperation programmes, but it is also a prerequisite on the level of statistical institutions in order to assess the effectiveness and the impact of such programmes. Harmonization of data collection and processing is important for the benefit of monitoring of cross-border interventions even if no guidance at an EU-level exists.
Apart from collection methods, the question of what to actually collect is another crucial one. In particular, in a cross-border setting, it is necessary to involve multiple actors which are interested in such data collections, bringing together their interests into a comprehensive “product” that can be provided by the relevant statistical offices, that should be also involved in this process.
Cooperation and coordination is not only a key target of cross-border programmes but also a vital basis for assessing their impacts.