IDEAS home Printed from https://ideas.repec.org/a/isa/journl/v18y2016i3p83-97.html
   My bibliography  Save this article

Estimation procedure and inference for component totals of the economic aggregates in the “Frame SBS”

Author

Listed:
  • Paolo Righi

    (Italian National Institute of statistics)

Abstract

Recently the Italian National Institute of Statistics - Istat - implemented a Business frame where several variables are collected from administrative registers. Nevertheless, these variables do not cover all statistical interests and some variables are collected only by the Small and Medium Enterprise survey – SME survey. The paper deals with the estimation of totals of variables strictly observed in Istat SME survey and proposes an estimation procedure, based on the projection estimator, exploiting the variables of the Business frame and coherent with respect to the totals of the variables in the frame. The result is an integrated output in the Business frame and a flexible tool useful for other statistical purposes. Inferential properties are shown theoretically and empirically and conditions to obtain unbiased estimates are pointed out.

Suggested Citation

  • Paolo Righi, 2016. "Estimation procedure and inference for component totals of the economic aggregates in the “Frame SBS”," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 83-97.
    • Handle: RePEc:isa:journl:v:18:y:2016:i:3:p:83-97
    as

    Download full text from publisher

    File URL: http://www.istat.it/it/files/2016/11/5_righi.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jae Kwang Kim & J. N. K. Rao, 2012. "Combining data from two independent surveys: a model-assisted approach," Biometrika, Biometrika Trust, vol. 99(1), pages 85-100.
    2. Takis Merkouris, 2010. "Combining information from multiple surveys by using regression for efficient small domain estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 27-48, January.
    3. Orietta Luzi & Roberto Monducci, 2016. "The new statistical register “Frame SBS”: overview and perspectives," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 5-14.
    4. Takis Merkouris, 2004. "Combining Independent Regression Estimators From Multiple Surveys," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1131-1139, December.
    5. Maria Cristina Casciano & Viviana De Giorgi & Filippo Oropallo & Giampiero Siesto, 2011. "Estimation of Structural Business Statistics for Small Firms by Using Administrative Data," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 13(2-3), pages 55-74.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yves G. Berger & Ewa Kabzińska, 2020. "Empirical Likelihood Approach for Aligning Information from Multiple Surveys," International Statistical Review, International Statistical Institute, vol. 88(1), pages 54-74, April.
    2. Seho Park & Jae Kwang Kim & Diana Stukel, 2017. "A measurement error model approach to survey data integration: combining information from two surveys," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 345-357, December.
    3. Jae Kwang Kim & Zhonglei Wang & Zhengyuan Zhu & Nathan B. Cruze, 2018. "Combining Survey and Non-survey Data for Improved Sub-area Prediction Using a Multi-level Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(2), pages 175-189, June.
    4. Alessio Guandalini & Yves Tillé, 2017. "Design-based Estimators Calibrated on Estimated Totals from Multiple Surveys," International Statistical Review, International Statistical Institute, vol. 85(2), pages 250-269, August.
    5. Silvana Curatolo & Viviana De Giorgi & Filippo Oropallo & Augusto Puggioni & Giampiero Siesto, 2016. "Quality analysis and harmonization issues in the context of “Frame SBS”," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 15-46.
    6. Chipperfield James O., 2016. "Discussion," Journal of Official Statistics, Sciendo, vol. 32(2), pages 287-289, June.
    7. J. N. K. Rao, 2021. "On Making Valid Inferences by Integrating Data from Surveys and Other Sources," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 242-272, May.
    8. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2019. "A Generalized Calibration Approach Ensuring Coherent Estimates with Small Area Constraints," Research Papers in Economics 2019-10, University of Trier, Department of Economics.
    9. Anne Konrad & Jan Pablo Burgard & Ralf Münnich, 2021. "A Two‐level GREG Estimator for Consistent Estimation in Household Surveys," International Statistical Review, International Statistical Institute, vol. 89(3), pages 635-656, December.
    10. Jerry J. Maples, 2017. "Improving small area estimates of disability: combining the American Community Survey with the Survey of Income and Program Participation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1211-1227, October.
    11. Denis Heng Yan Leung & Ken Yamada & Biao Zhang, 2015. "Enriching Surveys with Supplementary Data and its Application to Studying Wage Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 155-179, March.
    12. Christopher S. Withers & Saralees Nadarajah, 2016. "M-Estimators for Regression with Changing Scale," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(2), pages 238-286, November.
    13. Andrzej Młodak, 2013. "Coherence and comparability as criteria of quality assessment in business statistics," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(2), pages 287-318, June.
    14. Jae Kwang Kim & Seho Park & Yilin Chen & Changbao Wu, 2021. "Combining non‐probability and probability survey samples through mass imputation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 941-963, July.
    15. Stefano Costa & Federico Sallusti & Claudio Vicarelli & Davide Zurlo, 2017. "To The Threshold And Beyond: Size, Productivity And (Scale) Barriers To Export," Working Papers LuissLab 17132, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    16. Perchinunno, Paola & Mongelli, Lucia & d’Ovidio, Francesco D., 2020. "Statistical matching techniques in order to plan interventions on socioeconomic weakness: An Italian case," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    17. Alleva Giorgio & Petrarca Francesca & Falorsi Piero Demetrio & Righi Paolo, 2021. "Measuring the Accuracy of Aggregates Computed from a Statistical Register," Journal of Official Statistics, Sciendo, vol. 37(2), pages 481-503, June.
    18. Takis Merkouris, 2010. "Combining information from multiple surveys by using regression for efficient small domain estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 27-48, January.

    More about this item

    Keywords

    Administrative data sources; projection estimator; design based inference;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:isa:journl:v:18:y:2016:i:3:p:83-97. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Stefania Rossetti (email available below). General contact details of provider: https://edirc.repec.org/data/istgvit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.