Institutional quality and firms’ productivity in European regions

Abstract

The European Quality Index (EQI) constructed by Charron et al. ( 2014) is a survey-based index of the quality of government at the regional level for European member states. The index is based on a survey of European citizens' perceptions about the quality of institutions. EQI specifically measures the levels of quality of government among 172 EU regions based on the experiences and perception of citizens. Sixteen survey questions are asked, in accordance with the four 'pillars' of the World Bank's WGI: rule of law, government effectiveness, voice and accountability, and control of corruption. 1 Questions are centred on three public services that are often funded or administered at subnational levels: education, healthcare and law enforcement. The survey asks respondents to rate the provision of these three categories of public services with respect to three related concepts of institutional quality, i.e., quality, impartiality and level of corruption. Data are aggregated using different weighting schemes to obtain a robust indicator of EQI and its single components. Full details are given in Charron et al. (2014).For firms' micro-data, we resort to the EU-EFIGE Bruegel-UniCredit dataset provided by the Belgian non-profit international association Bruegel. This dataset contains both survey and balance-sheet data (the latter drawn from the BvD Amadeus database) on a representative sample of approximately 15,000 manufacturing firms with at least ten employees operating in seven European countries: Austria, France, Germany, Hungary, Italy, Spain and the United Kingdom. Details on the criteria, the sampling design and the weighting schemes employed to ensure standard statistical representativeness of the collected data (ex-ante and ex-post for each country) are too technical to be reported hereand we refer to the extensive discussions in Altomonte et al. (2012). From the EFIGE dataset, we draw a measure of firms' TFP for each year in the 2010-2014 period. To compute this measureovercoming endogeneity problems and allowing for industry-specific production functionsobservations have been assigned to sectors (at NACE 2 digit levels), and then, the Levinsohn and Petrin model has been applied to each sector, con-

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