Andrea Laura Bonfiglio, Nicola Pontarollo (p)

Carolina Foglia

In our study using cross-sectional quarterly dataset from the Labour Force Survey covering a period from 2014 to the first quarter of 2020 we evaluate the effects of earthquakes happened between August and October 2016 on labour market of nine provinces in Central Italy. Our quarterly microdata allows evaluating very precisely the short and long terms effects of natural disasters. Given the high number of observations it is the possibility to disaggregate microdata at very fine level makes possible to estimate the reaction of labour market by profession, age and type of contract for hourly wage. We find that Italian labour market is resilient to natural disasters and that for some categories of workers, especially those with open-ended contracts, wages increase.

Kenneth Fernando Castillo-Hidalgo, Carolina Foglia (p), Camilla Lenzi

Ana Viñuela

This work discusses the need for and the trade-offs emerging when employing firm-level data for regional analysis.
Specifically, this work advocates for a granular approach to economic phenomena that prioritizes firm-level data, while acknowledging both the pros and the cons of comprehensive micro-level databases, and the challenges of data representation for regional studies.
Following Kalemi-Ozcan et al. (2022), this study acknowledges the limitations of existing macro-level analyses that often overlook complex firms’ behaviours and interactions and proposes the use of the Orbis database, developed by Bureau van Dijk, as a tool to increase data representativeness at the firm level. While providing comprehensive information on both financial and operational aspects of firms, including ownership structures, the use of the ORBIS database is not free of challenges regarding data availability for regional measures, which may require careful imputation methods to ensure accuracy and completeness.
To illustrate the complexity of this approach, this work proposes operational guidelines for researchers to effectively utilize micro-level data in constructing regional outcome variables and offers evidence on a specific application aimed at assessing market concentration measures across European NUTS 2 regions by 3-digit NACE level industries.
In doing so, this work offers some inputs for theoretical inquiries and a practical framework for scholars and policymakers to analyse the implications of market concentration for regional macroeconomic outcomes.

Ana Viñuela (p)

Nicola Pontarollo

What part of our present, personal and quantifiable outcomes (from educational level to well-being or waged income) depend on things out of our control? What part of whatever individual or household economic phenomena can be explained by the characteristics and performance of the area (as opposed to region) where the household is located? How deterministic is our homus economicus existence, behaviour or outcome after including in the economic phenomena under analysis the attributes of the area where we reside?
Obviously one could claim that individuals have the option to abandon the area where they live (voting with their feet), but in most of the cases truth is that left behind places -and regions- might have a high concentration also of left-behind people.
Using EU SILC microdata, the aim of this work is aligned with the present territorial cohesion agenda, which emphasis has moved from “regions” to “individuals” and “places”. Multiple local indicators covering not only the economic characteristics of an area (as opposed to region) but also sociological, demographic and physical aspects of the localities obtained from the EXIT Project are also considered to reveal the importance of the left-behindness typology