OBJECTIVES, INSTRUMENTS AND DATASET Marco Cacciotti and Desislava Dankova IESS – Intermediate Workshop Rome - 27th of November, 2015

Outline Project’s objectives: intermediate and final Instruments: Models, data and software Focus on the Dataset: update and extension

Overall purpose of the project IESS objectives Overall purpose of the project IESS The project «Improving effectiveness in social security» (IESS) aims at assessing the cost effectiveness of the Italian Pension System in the short and long run focusing on its sustainability, adequacy and policy analysis. IESS follows up a previous project named «Innovative Datasets and Models for Improving Welfare Policies». It will provide innovative analytical tools to improve the effectiveness of public policy evaluation.

Main aspects of IESS Intermediate objectives Fields of interest Focus Tools/Results 1. Sustainability Effects on employment and productivity of ageing and increasing retirement ages Literature Survey Intermediate objectives 2. Adequacy A. Analyses of workers’ career paths B. Public Pension benefits for workers with discontinued careers C. Italian private second and third pension pillars Micro-econometric analyses. 3. Policy analysis A. Jobs acts and pension system. B. Workability and Labour supply of pensioners. C. Social determinants of health status and life expectancy Micro-econometric analyses. Final objective

Innovations vis-à-vis the previous project objectives Innovations vis-à-vis the previous project Extension and improvement of the dynamic microsimulation model T-DYMM; Updating the existing modules; Endogenous parameters for long run projections; Inclusion of complementary pension savings; Improvement of the estimates relative to the labour market; Updating and extension of the dataset used for the microsimulation by developing a new version of AD-SILC (Administrative SILC)

Main tools used in the microsimulations instruments Main tools used in the microsimulations A new microsimulation platform LIAM2 ensuring increasing benefits in terms of speed and data capacity. A new version of the dataset AD-SILC allowing to carry out more robust analyses about the individual dynamics on the labour market and the pension accumulation in the contributory scheme and to supply a more detailed database to the micro-simulation model TDYMM.

Administrative vs survey datasets Administrative data (INPS) Advantages: very wide coverage and very long time span Limits: only information needed for administrative modules Survey data (SILC) Advantages: rich information about individuals’ background and socio-economic characteristics Limits: very limited sample size and short time span

Merging administrative with survey data dataset Merging administrative with survey data AD-SILC (administrative SILC) Information about all workers paying contributions to INPS funds, gross wages, unemployment benefits, sickness allowances and maternity allowances; the workers’ qualification, typologies of work Large number of socio-economic variables at household and individual level Very large time span

Structure of the old version of AD-SILC dataset Structure of the old version of AD-SILC IT-SILC 2005 56,105 individuals AD-SILC 1,162,045 observations 56,105 individuals 43,388 registered at least once in the INPS archives INPS: working history of individuals surveyed in SILC and registered in INPS archives Longitudinal data in the period 1927-2010

Structure of the new version of AD-SILC dataset Structure of the new version of AD-SILC AD-SILC 3,355,801 observations 202,725 individuals 61,542 SILC 04 A4 B3 C2 D1 56,105 SILC 05 B4 C3 D2 E1 54,512 SILC 06 C4 D3 E2 F1 52,772 SILC 07 D4 E3 F2 G1 52,433 SILC 08 E4 F3 G2 H1 51,196 SILC 09 F4 G3 H2 I1 47,551 SILC 10 G4 H3 I2 J1 47,841 SILC 11 H4 I3 J2 K1 47,365 SILC 12 I4 J3 K2 L1 INPS: working history of individuals surveyed in SILC waves and registered in INPS archives Longitudinal data in the period 1927-2014 Number of observations: 5,016,214 number of individuals: 147,777

dataset Contents and features AD-SILC is an unbalanced dataset containing both: retrospective information on individuals’ working conditions before the year of survey of SILC, and forward-looking information on individuals’ working conditions after the year of survey of SILC. Panel INPS - longitudinal data of individuals’ working history since their entry in the LM: occupational status, income evolution, contribution accumulation, etc. Panel SILC - longitudinal data of individual socio-economic characteristics (up to 4 years): education, marital status, number of children, etc.

Advantages of the new AD-SILC dataset Advantages of the new AD-SILC Greatly enlarged sample size to analyze more in details smaller and specific subgroups of Italian labour force. Extending the dataset up to 2014 allows to study in comprehensive way the weaknesses engendered by the current macroeconomic crisis and its impact on labour market dynamics and income distribution. Updating the base data as a starting point for the simulations.

Regressions and projections dataset Regressions and projections Regressions used in the model are based on the entire dataset AD-SILC. All individuals in IT-SILC 2004-2012 and the respective working and contribution history carried out by INPS are considered on the period 1998-2011. The reference year of the simulations is 2011, where the data used are a single extract of AD-SILC. The base sample of the model includes individuals surveyed in SILC 2011 and the respective working, labour income and contribution conditions registered in INPS archives.

Annual composition by gender and sample share by year dataset – descriptive statistics Annual composition by gender and sample share by year Source: elaborations on AD-SILC data The large increase in the number of observations since 2005 is due to the fact that information provided by the Register of Retired is available only since that date.

Trend of employment status (absolute values) dataset – descriptive statistics Trend of employment status (absolute values) Source: elaborations on AD-SILC data

Employment composition (percentage values) dataset – descriptive statistics Employment composition (percentage values) Source: elaborations on AD-SILC data

www.iess-project.eu Il progetto IESS è finanziato dal Programma per l’Occupazione e la Solidarietà Sociale dell’Unione Europea – PROGRESS (2007-2013). Le informazioni contenute in questo documento riflettono solamente le posizioni dell’autore. La Commissione Europea non può essere considerata in alcun modo responsabile dell’uso che può essere fatto di quanto in esso contenuto.