We determine winners and losers of immigration using a general equilibrium search and matching model in which native and non-native employees, who are heterogeneous with respect to their skill level, produce different types of goods. Unemployment ben
efits and the provision of public goods are financed by a progressive taxation on wages and profits. The estimation of the baseline model for Italy shows that the presence of non-natives in 2017 led real wages of low and high-skilled employees to be 4% lower and 8% higher, respectively. Profits of employers in the low-skilled market were 6% lower, while those of employers in the high-skilled market were 10% higher. At aggregate level, total GDP was 14% higher, GDP per worker and the per capita provision of public goods 4% higher, while government revenues and social security contributions raised by 70 billion euros and 18 billion euros, respectively.
In this paper we propose a theoretical model including a susceptible-infected-recovered-dead (SIRD) model of epidemic in a dynamic macroeconomic general equilibrium framework with agents mobility. The latter affect both their income (and consumption)
and their probability of infecting and of being infected. Strategic complementarities among individual mobility choices drive the evolution of aggregate economic activity, while infection externalities caused by individual mobility affect disease diffusion. Rational expectations of forward looking agents on the dynamics of aggregate mobility and epidemic determine individual mobility decisions. The model allows to evaluate alternative scenarios of mobility restrictions, especially policies dependent on the state of epidemic. We prove the existence of an equilibrium and provide a recursive construction method for finding equilibrium(a), which also guides our numerical investigations. We calibrate the model by using Italian experience on COVID-19 epidemic in the period February 2020 - May 2021. We discuss how our economic SIRD (ESIRD) model produces a substantially different dynamics of economy and epidemic with respect to a SIRD model with constant agents mobility. Finally, by numerical explorations we illustrate how the model can be used to design an efficient policy of state-of-epidemic-dependent mobility restrictions, which mitigates the epidemic peaks stressing health system, and allows for trading-off the economic losses due to reduced mobility with the lower death rate due to the lower spread of epidemic.
We analyse the distribution and the flows between different types of employment (self-employment, temporary, and permanent), unemployment, education, and other types of inactivity, with particular focus on the duration of the school-to-work transitio
n (STWT). The aim is to assess the impact of the COVID-19 pandemic in Italy on the careers of individuals aged 15-34. We find that the pandemic worsened an already concerning situation of higher unemployment and inactivity rates and significantly longer STWT duration compared to other EU countries, particularly for females and residents in the South of Italy. In the midst of the pandemic, individuals aged 20-29 were less in (permanent and temporary) employment and more in the NLFET (Neither in the Labour Force nor in Education or Training) state, particularly females and non Italian citizens. We also provide evidence of an increased propensity to return to schooling, but most importantly of a substantial prolongation of the STWT duration towards permanent employment, mostly for males and non Italian citizens. Our contribution lies in providing a rigorous estimation and analysis of the impact of COVID-19 on the carriers of young individuals in Italy, which has not yet been explored in the literature.
This paper presents a model where intergenerational occupational mobility is the joint outcome of three main determinants: income incentives, equality of opportunity and changes in the composition of occupations. The model rationalizes the use of tra
nsition matrices to measure mobility, which allows for the identification of asymmetric mobility patterns and for the formulation of a specific mobility index for each determinant. Italian children born in 1940-1951 had a lower mobility with respect to those born after 1965. The steady mobility for children born after 1965, however, covers a lower structural mobility in favour of upper-middle classes and a higher downward mobility from upper-middle classes. Equality of opportunity was far from the perfection but steady for those born after 1965. Changes in income incentives instead played a major role, leading to a higher downward mobility from upper-middle classes and lower upward mobility from the lower class.
We propose a general methodology to measure labour market dynamics, inspired by the search and matching framework, based on the estimate of the transition rates between labour market states. We show how to estimate instantaneous transition rates star
ting from discrete time observations provided in longitudinal datasets, allowing for any number of states. We illustrate the potential of such methodology using Italian labour market data. First, we decompose the unemployment rate fluctuations into inflow and outflow driven components; then, we evaluate the impact of the implementation of a labour market reform, which substantially changed the regulations of temporary contracts.
In a recent paper, using data from Forbes Global 2000, we have observed that the upper tail of the firm size distribution (by assets) falls off much faster than a Pareto distribution. The missing mass was suggested as an indicator of the size of the
Shadow Banking (SB) sector. This short note provides the latest figures of the missing assets for 2013, 2014 and 2015. In 2013 and 2014 the dynamics of the missing assets continued being strongly correlated with estimates of the size of the SB sector of the Financial Stability Board. In 2015 we find a sharp decrease in the size of missing assets, suggesting that the SB sector is deflating.
Using public data (Forbes Global 2000) we show that the asset sizes for the largest global firms follow a Pareto distribution in an intermediate range, that is ``interrupted by a sharp cut-off in its upper tail, where it is totally dominated by finan
cial firms. This flattening of the distribution contrasts with a large body of empirical literature which finds a Pareto distribution for firm sizes both across countries and over time. Pareto distributions are generally traced back to a mechanism of proportional random growth, based on a regime of constant returns to scale. This makes our findings of an ``interrupted Pareto distribution all the more puzzling, because we provide evidence that financial firms in our sample should operate in such a regime. We claim that the missing mass from the upper tail of the asset size distribution is a consequence of shadow banking activity and that it provides an (upper) estimate of the size of the shadow banking system. This estimate -- which we propose as a shadow banking index -- compares well with estimates of the Financial Stability Board until 2009, but it shows a sharper rise in shadow banking activity after 2010. Finally, we propose a proportional random growth model that reproduces the observed distribution, thereby providing a quantitative estimate of the intensity of shadow banking activity.
This paper analyzes the equilibrium distribution of wealth in an economy where firms productivities are subject to idiosyncratic shocks, returns on factors are determined in competitive markets, dynasties have linear consumption functions and governm
ent imposes taxes on capital and labour incomes and equally redistributes the collected resources to dynasties. The equilibrium distribution of wealth is explicitly calculated and its shape crucially depends on market incompleteness. In particular, a Paretian law in the top tail only arises if capital markets are incomplete. The Pareto exponent depends on the saving rate, on the net return on capital, on the growth rate of population and on portfolio diversification. On the contrary, the characteristics of the labour market mostly affects the bottom tail of the distribution of wealth. The analysis also suggests a positive relationship between growth and wealth inequality.
