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Accounting for sampling design in the SHIW

Author

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  • Ivan Faiella

    (Bank of Italy - Economic and Financial Statistics Department)

Abstract

This paper analyses how sampling design affects variance estimates and inference using the data collected by the Survey on Household Income and Wealth (SHIW). The SHIW combines three basic features: stratification, clustering, and weighting to correct for unequal probabilities of selection among sampling units. A model to assess variance is presented and a Jackknife Repeated Replication method is suggested to estimate variance. Empirical evidence shows that: 1) simple random sampling formula for variance underestimates by a factor of between 3 and 2 the estimates that take into account all the design features; 2) the bias of unweighted estimates may be fairly substantial; 3) all these factors can seriously mislead inference based on SHIW data.

Suggested Citation

  • Ivan Faiella, 2008. "Accounting for sampling design in the SHIW," Temi di discussione (Economic working papers) 662, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_662_08
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    Citations

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    Cited by:

    1. Eurosystem Household Finance and Consumption Network, 2013. "The Eurosystem Household Finance and Consumption Survey - Methodological report," Statistics Paper Series 1, European Central Bank.
    2. Giarda, Elena, 2013. "Persistency of financial distress amongst Italian households: Evidence from dynamic models for binary panel data," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3425-3434.
    3. Loschiavo, David, 2021. "Big-city life (dis)satisfaction? The effect of urban living on subjective well-being," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 740-764.
    4. Lisa Rodano & L Federico Signorini, 2008. "Measuring the value of micro-enterprises in financial accounts," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 56th ISI Session, Lisbon, August 2007, volume 28, pages 145-155, Bank for International Settlements.
    5. Alessandro Gallo & Silvia Pacei, 2020. "Economic Insecurity in the Italian Macro-Regions," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(8), pages 1-65, August.
    6. C. Giannetti & M. Madia & L. Moretti, 2013. "Job Insecurity and Financial Distress," Working Papers wp887, Dipartimento Scienze Economiche, Universita' di Bologna.
    7. Alessandra Bettocchi & Elena Giarda & Cristiana Moriconi & Federica Orsini & Rita Romeo, 2018. "Assessing and predicting financial vulnerability of Italian households: a micro-macro approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(3), pages 587-605, August.
    8. Ana Almeida & Rita Biscaya & Anabela Cardoso, 2008. "Measuring the market value of shares and other equity in the Portuguese financial accounts," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 56th ISI Session, Lisbon, August 2007, volume 28, pages 132-155, Bank for International Settlements.
    9. Ivan Faiella, 2010. "The use of survey weights in regression analysis," Temi di discussione (Economic working papers) 739, Bank of Italy, Economic Research and International Relations Area.
    10. Romina Gambacorta & Maria Iannario, 2013. "Measuring Job Satisfaction with CUB Models," LABOUR, CEIS, vol. 27(2), pages 198-224, June.
    11. Daniele Di Giulio & Carlo Milani, 2013. "Plastic Money Diffusion and Usage: An Empirical Analysis on Italian Households," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(1), pages 47-74, February.
    12. Romina Gambacorta & Maria Iannario, 2012. "Statistical models for measuring job satisfaction," Temi di discussione (Economic working papers) 852, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    Keywords

    Survey Methods;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods

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