Abstract
This PhD thesis contains three distinct papers divided into three chapters aiming at investigating the dynamics of flexible employment and economic growth in the Italian economy.
Using tax-based longitudinal microdata from 1985 to 2016, the first chapter analyses the impact of Italian labour market reforms on cohort-specific wage inequality by looking at the relationship between the number of temporary job spells and individual earnings. Results show that young and high-skilled new-entrants exhibit higher wage differential in comparison to older workers and that the increase in temporary jobs is a crucial factor in explaining the cohort wage gap.
The second chapter explores the consequences of the same institutional change on income instability. It estimates trends in the transitory and permanent variance of male earnings and compares specific-cohort earnings variability according to the number of non-standard contracts. The aim is to test the extent to which increasing income instability is related to the labour market deregulation for fixed-term contracts. Results show that the reforms which liberalized temporary contracts not only led to a short-run increase in earnings instability but also a long-term increase in inequality for younger cohorts.
The third chapter analyses another aspect of the Italian economy, moving from the labour market to regional GDP forecasting. The monitoring of the regional (provincial) economic situation takes on particular importance due to the high level of heterogeneity and interdependences among different territories.
This chapter evaluates the predictive performance of a spatial dynamic panel data model with individual fixed effects and some relevant exogenous regressors, by using data on total GVA for 103 Italian provinces over the period 2000-2016. A comparison with nested panel sub-specifications as well as pure temporal autoregressive specifications has also been included. The main finding is that the spatial dynamic specification reduces improve the forecast more than its competitors throughout the out-of-sample, recognizing an important role played by both space and time.