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In this paper we study the structural robustness of Italian business system, using Covid-19 pandemic as an exogenous event to test it. To this aim, we use the ROC (Receiver Operating Characteristics) methodology, quite new for Economics, to classify Italian firms according to their economic solidity, obtaining a taxonomy based on a wide set of characteristics. Our results show that the number of 'Solid' firms are less than one fifth of the universe of Italian enterprises but they represent the lion share in terms of employment and value added. 'Fragile' and 'Risky' firms, albeit much less relevant for the creation of value added, account for over one third of total employment, so that they are a worrisome issue for policy makers. The pandemic crisis has clearly both a size and sector-related dimension: Risky and Fragile conditions prevail among firms with smaller economic size (a broad definition of firm size) and among those operating in Construction and Other services. Finally, we find that factors such as firms' performance, internal and external organization, although significant, play a less relevant role than economic size and digitalization/innovation in determining Italian firms' solidity to shocks such as the Covid-19 one.

This paper analyses the potential mismatch between the conditions required for a manufacturing firm to become exporter and the pattern of technology adoption within the industry. The "export threshold", which is estimated using the ROC methodology, is the minimum combination of productivity and "economic size" (a broader measure of firm size) that firms need to achieve in order to access export markets. To consider the pattern of technology adoption we also estimate a "technology line". The relative positioning of the "technology line" and the export threshold generates a new taxonomy of firms allowing for better policies for internationalization.

Least Orthogonal Distance Estimator (LODE) of Simultaneous Equation Models’ structural parameters is based on minimizing the orthogonal distance between Reduced Form (RF) and the Structural Form (SF) parameters. In this work we propose a new version – with respect to Pieraccini and Naccarato (2008) – of Full Information (FI) LODE based on decomposition of a new structure of the variance-covariance matrix using Singular Value Decomposition (SVD) instead of Spectral Decomposition (SD). In this context Total Least Square is applied. A simulation experiment to compare the performances of the new version of FI LODE with respect to Three Stage Least Square (3SLS) and Full Information Maximum Likelihood (FIML) is presented. Finally a comparison between the FI LODE new and old version together with few words of conclusion conclude the paper., Statistica, Vol 73, No 2 (2013)

Drawing from confidential firm-level balance sheets in 11 European countries, the paper presents a novel sectoral database of comparable productivity indicators built by members of the Competitiveness Research Network (CompNet) using a newly developed research infrastructure. Beyond aggregate information available from industry statistics of Eurostat or EU KLEMS, the paper provides information on the distribution of firms across several dimensions related to competitiveness, e.g. productivity and size. The database comprises so far 11 countries, with information for 58 sectors over the period 1995-2011. The paper documents the development of the new research infrastructure, describes the database, and shows some preliminary results. Among them, it shows that there is large heterogeneity in terms of firm productivity or size within narrowly defined industries in all countries. Productivity, and above all, size distribution are very skewed across countries, with a thick left-tail of low productive firms. Moreover, firms at both ends of the distribution show very different dynamics in terms of productivity and unit labour costs. Within-sector heterogeneity and productivity dispersion are positively correlated to aggregate productivity given the possibility of reallocating resources from less to more productive firms. To this extent, we show how allocative efficiency varies across countries, and more interestingly, over different periods of time. Finally, we apply the new database to illustrate the importance of productivity dispersion to explain aggregate trade results.

Drawing from confidential firm-level balance sheets in 11 European countries, the paper presents a novel sectoral database of comparable productivity indicators built by members of the Competitiveness Research Network (CompNet) using a newly developed research infrastructure. Beyond aggregate information available from industry statistics of Eurostat or EU KLEMS, the paper provides information on the distribution of firms across several dimensions related to competitiveness, e.g. productivity and size. The database comprises so far 11 countries, with information for 58 sectors over the period 1995-2011. The paper documents the development of the new research infrastructure, describes the database, and shows some preliminary results. Among them, it shows that there is large heterogeneity in terms of firm productivity or size within narrowly defined industries in all countries. Productivity, and above all, size distribution are very skewed across countries, with a thick left-tail of low productive firms. Moreover, firms at both ends of the distribution show very different dynamics in terms of productivity and unit labour costs. Within-sector heterogeneity and productivity dispersion are positively correlated to aggregate productivity given the possibility of reallocating resources from less to more productive firms. To this extent, we show how allocative efficiency varies across countries, and more interestingly, over different periods of time. Finally, we apply the new database to illustrate the importance of productivity dispersion to explain aggregate trade results. JEL Classification: L11, L25, D24, O4, O57