Over the years, CompNet has collected a number of indicators in order to provide a robust background to enhance the analysis of competitiveness. In the following sections, you will find more information regarding the CompNet dataset, its methodological documentation as well as instructions for accessing them.
The 6th Vintage CompNet Competitiveness Dataset
CompNet has created a competitiveness indicator dataset including a number of European countries. The dataset is unique in terms of its coverage and cross-dimensional analysis potential because it links, for example, trade or the financial status of firms with their productivity.
What can the CompNet data do for my research?
CompNet allows to analyse virtually every aspect of European firms. We collect information from representative competitiveness indicator datasets for a number of countries. The dataset includes variables on employment, trade, productivity, mark-ups, financial constraints and more. From existing competitiveness indicator datasets available within each of our data providers, the information is aggregated up to the sector level and only then circulated to preserve confidentiality. The common methodology used to collect and process the data, ensures the harmonisation of industry coverage, variable definitions, target firms, use of deflators, treatment of outliers, and estimation methodologies across countries.
What does the data look like?
After computing a host of indicators within each country, we gather moments of the distributions for these variables. Joint distributions are also available. This allows you to analyse, for instance, whether more productive firms grow faster or whether firms with high mark-ups are less financially constrained. These distributions are available for each country.
What are the novelties of the new 6th Vintage dataset?
The country coverage of this new 6th Vintage has grown from 15 (5th Vintage) to 18 countries, including the six biggest EU economies (DE, FR, IT, ES, NL and PL). The current data vintage incorporates fundamental developments regarding the content of the dataset; we have updated the methodology to estimate some of our main indicators, such as total factor productivity (TFP). We have also included new indicators capable of contributing to the ongoing policy debate, as for example, a new module on distressed firms still operating in the market, as well as their characteristics. Moreover, job creation and destruction rates have been computed for narrowly defined sectors or across-size classes in order to single out such components of gross job flows. For the first time information has been collected also at the regional level (i.e. NUTS2 level). This will make it possible to explore, for instance, the productivity distributions across different regions within a given country. Regarding the improvements in data procedures, the CompNet code has been totally rewritten to increase its efficiency and robustness, correct small glitches, include a better weighting system and incorporate confidentiality checks which the data providers can adjust to their respective country-specific requirements.
Another key feature of the 6th CompNet data vintage is the considerable progress made to further enhance cross-country comparability. More on this in the Cross-country Comparability Report (link).
How else can the network aide my research?
CompNet is a network of dedicated researchers with considerable experience in firm level cross-country analysis. The Network provides a forum for discussion with its working paper series and its conferences. It offers the opportunity to get in touch with leading experts in competitiveness indicator datasets and productivity studies.
Which documentation should I refer to understand the dataset before using it?
CompNet is producing a series of methodological papers explaining in detail all the features of the competitiveness indicator 6th Vintage dataset:
All researchers can apply to have access to the firm-level-based CompNet data by submitting the data request form to the CompNet team via the IWH Research Data Centre.
More information about the 4th and 5th Vintage datasets can be found here.
More information about the toolkit can be found here.