Abstract
The aim of this paper is to evaluate the consequences of the financial crisis on the Italian labour market by analysing the determinants of individuals’ transitions between occupational states. For this purpose, we use micro-data from the ISTAT Labour Force Survey, a repeated cross-section dataset. In order to identify the determinants of transitions, two strategies are followed: firstly, we consider the “perceived” employment condition, available at the individual level for the previous year. Then, following the “ecological inference” approach, we get quarterly transition probabilities for the “official” employment condition. The economic crisis has mostly penalized young, migrants, men, and people living in the North as well as couples without children and single parents with children.
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- 1.
- 2.
We refer to Sect. 11.1 of the questionnaire.
- 3.
It is a sort of almost temporary layoff with a wage compensation mechanism, which preserves (juridically and statistically) the employment relationship, even if there is no possibility for the worker to re-entering the firm. Employees in small firms had also enjoyed CIG thank to the institute of “Cassa Integrazione in deroga”.
- 4.
We remind that information at time t and at time t − 1 are available for the perceived employment condition but not for the official one.
- 5.
Have you worked at least one hour during the last week? Have you made at least one effective action in order to find a job during the last month? The official employment condition complies with the Council Regulation (EC) No. 577/98 of 9 March 1998 on the organisation of a labour force sample survey in the European Community.
- 6.
We consider individuals working zero hours (“CIG a zero ore”), individuals working less than the contractual hours (“CIG a orario ridotto”) and we include also individuals who did not work during the previous week because of reduced firm’s activity.
- 7.
To avoid major inflows into inactivity, we excluded all the individuals aged more than 55.
- 8.
RRR are equal to the ratio between two different relative risks, both calculated with respect to the base category for a marginal increase in the independent variable; as an example, the RRR for the male dummy in the first column of Table 11.5 (base category: employed, category of interest: unemployed) should be written as: \( {\raise0.7ex\hbox{${\frac{{{P}({Y}_{i} = {Unempl}|{X} = {Male})}}{{{P}({Y}_{i} = {Empl}|{X} = {Male})}}}$} \!\mathord{\left/ {\vphantom {{\frac{{{P}({Y}_{i} = {Unempl}|{X} = {Male})}}{{{P}({Y}_{i} = {Empl}|{X} = {Male})}}} {\frac{{{P}({Y}_{i} = {Unempl}|{X} = {Female})}}{{{P}({Y}_{i} = {Empl}|{X} = {Female})}}}}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${\frac{{{P}({Y}_{i} = {Unempl}|{X} = {Female})}}{{{P}({Y}_{i} = {Empl}|{X} = {Female})}}}$}} \).
- 9.
This methodology has been widely used by political science researchers, particularly in the analysis of vote flows between parties in different elections.
- 10.
We remind that the database ISTAT-RCFL in our hands has the structure of a repeated cross-section dataset, because the identifier for the same individual across waves is different.
- 11.
For a two-state graphical example of the described methodology, see King (1997). Our analysis has been carried out using the plugin Ecol on the program Stata.
- 12.
Obviously, the modal value of the change of state inside a given group is inversely related to the dimension of the groups.
- 13.
The analysis is based both on the ISTAT official definition of employment condition and on the perceived employment condition.
- 14.
In order to consider the sample significance and consistently with the aggregate figures from ISTAT, data were rounded to thousands.
- 15.
ISTAT allows the respondent to refuse the identification of the family to which he/she belongs to. Less than 7% of surveyed individuals choose this option.
- 16.
By doing so, we preserve a sufficient reliable size for the population in each condition for each group.
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Lilla, M., Staffolani, S. (2012). Labour Market Transitions During the Financial Crisis in Italy. In: Parodi, G., Sciulli, D. (eds) Social Exclusion. AIEL Series in Labour Economics. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2772-9_11
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