Current Research

We analyse the patterns and evolution of labour market power in Italy over the period 2002--2019, distinguishing between white- and blue-collar workers. We document a shift in labour market power from firms to both types of employees over the sample period. In the most recent year, blue-collar workers' costs are about 10% above their marginal revenue product of labour (MRPL), while white-collar workers' costs are about 10% below their MRPL. We find significant heterogeneity across economic sectors and Italian regions, with higher labour wedges in the southern part of the country. We analyse the evolution of labour market power in the context of two recent labour market reforms (i.e. the 2012 ``Fornero'' reform and the 2015 ``Jobs Act'') and provide evidence that the greater flexibility introduced by the change in employment protection legislation (EPL) has increased the labour market power of large firms, particularly on white-collar workers.


This paper investigates whether and how foreign market penetration influences the demand for credit by manufacturing firms, and its supply by  banks.We expect exporters to ask for more credit in order to finance the sunk entry costs into foreign markets. For what concerns credit supply, exporting may send a signal about firm-type, which is used by banks to grant more/less credit to exporters based on their perceived quality or riskiness. We find that exporting firms tend to demand more bank credit. Moreover, whereas the total number of  destinations served by a firm does not have a significant impact  on credit supply, the ability to sell in non-EU OECD countries is positively perceived  by banks, and thus improves a firm's access to credit, even after controlling for a number of firm characteristics (profitability, size, the amount of available collateral, etc.). However, the impact of foreign market penetration is not always benign: exporting t

It is commonly found that distributions that seem to be lognormal over a broad range change to a power-law (Pareto) distribution for the last few percentiles. The distributions of species abundance, income and wealth as well as file, city and firm sizes are examples with this structure. We present a new test for the occurrence of power-law tails in statistical distributions based on maximum entropy. This methodology allows to identify the true data generating processes even in the case when it is neither lognormal nor Pareto. The maximum entropy approach is then compared with alternative methods at different levels of aggregation of economic systems. Our results provide support to the theory that distributions with lognormal body and Pareto tail can be generated as mixtures of lognormally distributed units.