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Title page

Contents

Abstract 3

1. Introduction 4

2. Methodology 5

2.1. The estimate of transitions with K states 6

2.2. The causal-ARIMA approach 7

3. The 2018 labour market reform Decreto Dignità 8

3.1. The Italian labour market 9

3.2. The content of the reform 10

3.3. The timing of the reform 10

4. Data 11

5. An empirical evaluation of Decreto Dignità 12

5.1. The casual evaluation of Decreto Dignità 12

5.2. Labour market shares 13

5.3. Transition probabilities 14

5.4. Quantifying the cumulative impact of the reform 16

5.5. Heterogeneous effects 17

6. Concluding remarks 21

References 23

Appendix 25

A. Bootstrap procedure for labour shares and transition probabilities 25

B. Heterogeneity 28

C. Composition effect in the transitions between labour market states driven by a Markovian process 31

Tables

Table 1. Labour market characteristics for a select sample of European countries 9

Table 2. Fitted versus forecasted statistics 17

Table 3. Fitted versus forecasted statistics - Females 18

Table 4. Fitted versus forecasted statistics - Males 19

Table 5. Fitted versus forecasted statistics - Young 20

Table 6. Fitted versus forecasted statistics - Low-educated 20

Table 7. Fitted versus forecasted statistics - North 21

Table 8. Placebo test. Quarters used in the forecast: 2016.I-2017.III and forecasted quarters: 2017.IV-2018.II 26

Table 9. Counterfactual labour shares. Quarters used in the forecast: 2016.I-2018.II and forecasted quarters: 2018.III-2019.II 27

Table 10. Fitted versus forecasted statistics - Adults 28

Table 11. Fitted versus forecasted statistics - High-educated 29

Table 12. Fitted versus forecasted statistics - South 30

Figures

Figure 1. Observed shares of individuals in different labour market states (% of working age population) 14

Figure 2. Transition probabilities across labour market states 15

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