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Impact Analysis

 

Background

In many ways, the ESSLait-project picks up where the ESSLimit-project stopped. Within the latter project (and its predecessor,The Feasibility Study), the infrastructure that allows to link and coordinate the data management in the National Statistical Offices (NSI) was set up. This infrastructure enables the harmonized approach to analyse the impact of ICT usage by firms through the Distributed Micro Data (DMD) approach. In this approach, a common protocol is used to extract micro-aggregated information from each country’s firm-level datasets. This involves the assembly of firm-level datasets by participating NSIs, and the subsequent application of a common software which is tailored to extract the indicators and statistical moments from the data. By proceeding in this way, cross-country comparability of results is guaranteed as much as possible, while still allowing to obtain information on underlying distributions and correlations without impairing national rules of confidentiality. Moreover, the infrastructure allows external researchers to hook into the project software and metadata, in order to run their own analysis. Harmonized micro data-sets onsite at NSIs enables the easy implementation of additional analyses by writing analytical add-on modules for the code.

The data coverage was extended by adding more recent years, and by the inclusion of new potentially relevant variables. The impact analysis within the ESSLait project follow-up on research, lines started by the previous two projects (the Feasibility Study and the ESSLimit) and explored the new research topics in line with the Europe 2020 strategy(2010).

 

New Indicators of ICT usage

Within these ICT impact analysis themes, a new ways of measuring the intensity of ICT usage by firms were explored. Firstly, the work on a composite indicator that is based on the adoption of new forms of ICT(developed during the ESSLimit project) was continued. Secondly, the work on the adoption and performance effects of e-business systems (such as ERP and CRM) was extended.

 

Resilience and firm dynamics

It is widely believed that the usage of ICT allows firms to react to become more flexible and adapt faster to economic shocks. With this mind, the Project looked at the relation of firm-level employment dynamics with ICT usage vis-à-vis national employment protection legislation. Moreover, in the face of the economic downturn, the differences in the resilience and recovery of ICT-intensive firms, industries, and countries, as compared to less ICT-intensive counterparts were studied. It was found that economic growth is related to the allocation of production factors to the most efficient production units in an economy. It was further explored whether this allocative efficiency within countries and industries could be related to ICT usage or investment.

 

Intangibles

Given the nature of ICT as a general purpose yechnology, the project gave attention to its relation to other determinants of firm performance, in particular labour and labour skills, as well as technological and non-technological innovation. The project studied the interaction of skills with ICT in relation to firm performance, and whether it matters if (ICT) skills are sourced from inside or outside the firm. In addition, the relation between ICT usage and the innovative behaviour of the firm, as well as with firm performance, were investigated.

 

Selected topics

Within this theme, miscellaneous topics are included: the relation of ICT with firm exports (especially with an eye on the international aspect of web presence of a firm), the link between ICT and entrepreneurship (particularly the relation between ICT usage and firm age), and several other lines of research introduced by researchers outside of the consortium, who was able to make use of the existing data infrastructure. Among the themes initially proposed, a couple were reconsidered and not pursued due to data or resource limitations (see Final Report for more information). The analytical workstream also looks at the quality of both the input and the output datasets by addressing issues of measurement, representativeness, and cross-country comparability of results. Finally, the information on metadata that is input to the DMD analysis, was updated considering more recent years and, where relevant , potentially interesting new variables.