The dataset built for this empirical exercise contains data on the cohesion policies implemented in the Italian regions, regional economic variables and political and institutional variables. We utilize annual regional data available from 1994 up to 2013. Regional data for real GDP, value added, gross fixed investment, and employment and labour units are taken from ISTAT's regional accounting (ISTAT being the Italian Statistical Office).European structural and national funds were both taken from the database Spesa statale regionalizzata of the General Accounting Office (Ragioneria Generale dello Stato) at the Italian Ministry of Economy and Finance, which allows us to rely for both kinds of funds on series based on the same methodology. Funds' series relate to the amounts actually disbursed by the various regions. A proportion of funds (both national and from EU) are not allocated to any single region, but to multi-regional aggregates. In our analysis, we shall assume that these funds are spread across regions proportionally to the shares of regionally allocated funds. This is the hypothesis most often maintained in the literature (see Aiello and Pupo, 2009) and that most makes sense from an a priori standpoint. We provide below a closeup of this database.Regional data on GDP, gross fixed capital formation, population and employment (labour units), and sectoral shares of employment and value added are taken from ISTAT Regional Accounting.Measures of the regional rate of unemployment are obtained from the ISTAT Labour Force Survey.As regards politically based indicators, we extracted data about regional governments for the 1990-2013 period from the Anagrafe degli amministratori locali e regionali database of the Italian
These solutions imply that that a higher a52 increases the long-run impact of funds on xnons and dampens the long-run impact of funds on xs. But of course, things would go the other way around if a52 was negatively signed.
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