The latest census of Italian nonprofit organizations – compared with the previous one – showed a significant development of the nonprofit sector between 2001 and 2011. The number of organizations increased more than 28 % while the growth of employees (about 61 %) was even more impressive.These results notwithstanding, the mere comparison of aggregate census data does not give a true understanding of the dynamic of the sector. The entry and exit of organizations, as well as their migration between different sectors of activity, or geographical areas, can be analyzed properly only using firm-level panel data, but these data are rarely available so that only a few authors had a chance to use them. In this paper, we try to fill this gap using firm-level panel data for the first time in Italy. Our analysis tempers the optimism arising from aggregate data. We show that: a) part of the growth is determined by the emergence of already active organizations that were not detected a decade ago; b) because of low barriers, the entry of new nonprofit organizations is very relevant, but their net contribution to the growth of employment is quite small; c) opposite to what happened in other countries, the exit of nonprofit organizations is very significant, and d) organizations that were already active a decade ago gave the most important contribution to the growth of employment. We also investigate geographical trends, showing that the slower growth of the nonprofit sector in Southern Italy depends on the very high exit rate of the area, while the entry rate is more or less in line with the rest of the country.
La povertà lavorativa è un fenomeno che solo marginalmente rientra nell'agenda dei policy-maker. Gli studi sui working poor, che di norma sono basati su dati campionari, non riescono a porre l'oeil-de-boeuf sui più vulnerabili. L'obiettivo è osservare i caratteri dei working poor ambrosiani con un focus sulla comparazione tra nativi e migranti mediante l'uso di dati amministrativi sperimentali Istat per identificare specifici ambiti di rischio di povertà. A tal fine sono state specificate regressioni logistiche e modelli ad albero della povertà nonostante il lavoro in funzione di variabili socio-demografiche. È stata considerata sia la dimensione individuale del lavoratore sia quella familiare. I risultati, in linea con la letteratura di riferimento, garantiscono inoltre approfondimenti territoriali e per sub-popolazioni risultanti dalla combinazione delle dimensioni di studio per le quali ci sono elevati rischi di povertà lavorativa, come ad esempio per la cittadinanza e l'intensità lavorativa del nucleo familiare.
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