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La SAM come strumento di integrazione e analisi

Author

Listed:
  • Federica Battellini

    (Italian National Institute of Statistics)

  • Alessandra Coli

    (University of Pisa)

  • Francesca Tartamella

    (Italian National Institute of Statistics)

Abstract

Compiling Social Accounting Matrices (SAM) allows to analyse the circular flow of income in a deeper detail compared to the traditional T-accounts. SAMs classify economic flows introducing social and demographic criteria with a special attention devoted to the households sector. Such a presentation of national accounts is particularly useful for analysis on the allocation, distribution and use of disposable income. This paper describes the method used by Istat to estimate a labour-oriented SAM, where labour income is simultaneously analysed by economic activity and by gender and education of the labourer. Moreover consumption expenditure is analysed by groups of household sharing the same main source of income (wages and salaries, mixed income, retirement income, property income). Besides methodological aspects the paper highlights the analytical potentialities of the SAM.

Suggested Citation

  • Federica Battellini & Alessandra Coli & Francesca Tartamella, 2009. "La SAM come strumento di integrazione e analisi," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 35-62, January.
  • Handle: RePEc:isa:journl:v:11:y:2009:i:2-3:p:35-62
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    File URL: http://www.istat.it/it/files/2011/05/2-3_20091.pdf
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    References listed on IDEAS

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    1. Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
    2. Little, Roderick J A, 1985. "A Note about Models for Selectivity Bias," Econometrica, Econometric Society, vol. 53(6), pages 1469-1474, November.
    3. Schenker, Nathaniel & Raghunathan, Trivellore E. & Chiu, Pei-Lu & Makuc, Diane M. & Zhang, Guangyu & Cohen, Alan J., 2006. "Multiple Imputation of Missing Income Data in the National Health Interview Survey," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 924-933, September.
    4. He, Yulei & Raghunathan, Trivellore E., 2006. "Tukey's gh Distribution for Multiple Imputation," The American Statistician, American Statistical Association, vol. 60, pages 251-256, August.
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