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From SHIW to IT-SILC: construction and representativeness of the new CAPP_DYN first-year population

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  • Emanuele Ciani
  • Donatella Fresu

Abstract

This paper describes the construction of the initial population in CAPP_DYN and illustrates the degree of representativeness of the Italian population in 2006. While the previous version of the model was constructed using the Bank of Italy Survey on Household Income and Wealth, the current version is based on the new ISTAT Survey on Income and Living Conditions. The first part of the paper discusses the reasons that led us to this switch. It also provides full details on the operations carried out on the original dataset in order to obtain a sample that can be used as the first year population of the Dynamic Simulation Model. In the second part of the paper, the demographic and socio-economic characteristics of the initial population sample are compared with information coming from other sources, such as administrative archives, national accounts and Labour Force Surveys. This exercise is crucial in assessing the capability of CAPP_DYN to represent the population's characteristics at the starting point.

Suggested Citation

  • Emanuele Ciani & Donatella Fresu, 2011. "From SHIW to IT-SILC: construction and representativeness of the new CAPP_DYN first-year population," Center for the Analysis of Public Policies (CAPP) 0092, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    • Handle: RePEc:mod:cappmo:0092
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    References listed on IDEAS

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    1. Andrea Brandolini, 1999. "The Distribution of Personal Income in Post-War Italy: Source Description, Data Quality, and the Time Pattern of Income Inequality," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 58(2), pages 183-239, September.
    2. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2003. "Evaluating the impact of education on earnings in the UK: Models, methods and results from the NCDS," IFS Working Papers W03/20, Institute for Fiscal Studies.
    3. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    4. Marina Murat & Barbara Pistoresi, 2009. "Emigrant and immigrant networks in FDI," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1261-1264.
    5. Giuseppe Marotta, 1997. "Does trade credit redistribution thwart monetary policy? Evidence from Italy," Applied Economics, Taylor & Francis Journals, vol. 29(12), pages 1619-1629.
    6. Sara Flisi & Marcello Morciano, 2011. "Trends and dynamics in the Italian labour market. An empirical evaluation using RFL data, 1993-2007," Center for the Analysis of Public Policies (CAPP) 0091, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
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    Cited by:

    1. Lidia Ceriani & Carlo V. Fiorio & Chiara Gigliarano, 2013. "The importance of choosing the data set for tax-benefit analysis," International Journal of Microsimulation, International Microsimulation Association, vol. 1(6), pages 86-121.
    2. Costanza Torricelli & Maria Cesira Urzì Brancati & Marco Santantonio, 2016. "Does Homeownership Partly Explain Low Participation in Supplementary Pension Schemes?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 45(2), pages 179-203, July.
    3. Costanza Torricelli & Maria Cesira Urzì Brancati & Marco Santantonio, 2016. "Does Homeownership Partly Explain Low Participation in Supplementary Pension Schemes?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 45(2), pages 179-203, July.
    4. Daniele Pacifico, 2010. "Estimating nonparametric mixed logit models via EM algorithm," Center for the Analysis of Public Policies (CAPP) 0072, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".

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    More about this item

    Keywords

    Dynamic micro-simulation; model validation; income distribution; pensions and social security;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • H55 - Public Economics - - National Government Expenditures and Related Policies - - - Social Security and Public Pensions

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