Please use this identifier to cite or link to this item:
Year of Publication:
52nd Congress of the European Regional Science Association: "Regions in Motion - Breaking the Path", 21-25 August 2012, Bratislava, Slovakia
In this study we evaluate a special form of business support – support to cover costs associated with business counselling. The policy question is whether firms that receive this support within the Regional Business Development programme have a positive outcome compared with firms that do not receive the support. However, the study also addresses some methodological issues based on the fact that impact evaluations of different kind of business support in general suffer from a number of methodological problems. A first problem relates to the fact that firms have a different and more complicated heterogeneity than is the case in e.g. labour market policy evaluations. This raises the question on how firms in the comparison group should be selected. Since the selection process is not known in most cases of business support, we use a stratified matching approach that allows matching in several dimensions. A second problem is that there are many ‘actors' on the state support market. This means that in absence of full information about other support givers we may end up in a situation where the firms in the comparisons group have received a similar support from another support provider, and is, in effect, treated. In the most extreme case the treated firms are compared with firms that have received exactly the same type of support from another provider. This problem is referrers to as contaminated data. A final problem is that business support is often a ‘two stage' process where firms has to apply for funding, and an administrative organisation decide if the application is granted. This gives raise to two types of selection; self–selection (whether to apply) and administrative selection (getting funding). In the final analysis we address the issue of selection. The results of our evaluation points some important facts: If we include selection and allow contaminated data business counselling give positive impacts on value added, growth in investments and employment and a more efficient production. Not allowing for contamination in the data reveals a positive, however, smaller impacts on value added and investments a slightly larger impact on employment. Finally, if we restrict the data so that self–selection is deleted we find no significant impacts. A preliminary conclusion from the analysis is that it is the fact that firms set time aside to formulate e.g. investments strategies, problems etc. that generate impacts rather than the support itself.
Appears in Collections:
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.