A Study of Small Area Estimation for Italian Structural Business Statistics

Bell, W.R. 2008. “Examining Sensitivity of Small Area Inferences to Uncertainty About Sampling Error Variances.” In Proceedings of Survey Research Methods Section, Denver, August 4, 2008. 327–334. Alexandria, VA: American Statistical Association.Search in Google Scholar

Brown, G., R. Chambers, P. Heady, and D. Heasman. 2001. “Evaluation of Small Area Estimation Methods – An Application to Unemployment Estimates from the UK LFS.” In Proceedings of Statistics Canada Symposium 2001. Achieving Data Quality in a Statistical Agency: A Methodological Perspective. Hull, October 17, 2011. Ottawa: Statistics Canada. Available at: http://www.statcan.gc.ca/access_acces/alternative_alternatif.action?l=eng&loc=2001001/session6/6247-eng.pdf (accessed October 2017).Search in Google Scholar

Caldera, A., M. Rasmussen, and O. Röhn. 2015. “Economic Resilience: What Role for Policies?” OECD Economics Department Working Papers 1251. Paris: OECD Publishing. DOI: http://dx.doi.org/10.1787/5jrxhgf61q5j-en.10.1787/5jrxhgf61q5j-enOpen DOISearch in Google Scholar

Chandra, H. and R. Chambers. 2011. “Small Area Estimation for Skewed Data in Presence of Zeros.” The Bulletin of Calcutta Statistical Association 63: 249–252.10.1177/0008068320110113Search in Google Scholar

Cressie, N. 1993. Statistics for Spatial Data. Revised ed. New York: John Wiley & Sons. Curatolo, S., V. De Giorgi, F. Oropallo, A. Puggioni, and G. Siesto. 2016. “Quality Analysis and Harmonization Issues in the Context of the Frame SBS.” Rivista di Statistica Ufficiale 2016(1): 15–46. Available at: https://www.istat.it/it/files/2016/11/RSU_1_2016_Testointegrale.pdf (accessed October 2017).Search in Google Scholar

Di Zio, M. 2016. “Estimating Population Size from Multisource Data with Coverage Unit Errors.” In Proceedings of the 5th International Conference on Establishment Surveys (ICES). Geneva, June 23, 2016. American Statistical Association.Search in Google Scholar

Di Zio, M. and O. Luzi. 2014. “Theme: Editing Administrative Data.” In Memobust Handbook on Methodology for Modern Business Statistics. Luxembourg: Eurostat. Available at: https://ec.europa.eu/eurostat/cros/system/files/Statistical%20Data%20Editing-07-T-Administrative%20Data%20v1.0_0.pdf (accessed October 2017).Search in Google Scholar

ESSnet AdminData. 2013. Project website: https://ec.europa.eu/eurostat/cros/content/use-administrative-and-accounts-data-business-statistics_en (accessed October 2017).Search in Google Scholar

ESSnet on Data Integration. 2011. “Report on WP2 – Methodological Developments.” Available at: https://ec.europa.eu/eurostat/cros/system/files/WP2.pdf (accessed October 2017).Search in Google Scholar

Eurostat. 2008. NACE Rev. 2. Statistical Classification of Economic Activities in the European Community. Luxembourg: Office for Official Publications of the European Communities. Available at: http://ec.europa.eu/eurostat/documents/3859598/5902521/KS-RA-07-015-EN.PDF (accessed October 2017).Search in Google Scholar

Fay, R.E. and R.A. Herriot. 1979. “Estimates of Income for Small Places: an Application of James-Stein Procedures to Census Data.” Journal of the American Statistical Association 74(366): 269–277.10.1080/01621459.1979.10482505Search in Google Scholar

Garda, P. and V. Ziemann. 2014. “Economic Policies and Microeconomic Stability: a Literature Review and Some Empirics.” OECD Economics Department Working Papers 1115. OECD Publishing. Doi: http://dx.doi.org/10.1787/5jz417mn2443-en.10.1787/5jz417mn2443-enOpen DOISearch in Google Scholar

Istat. 2014. “I Nuovi Conti Nazionali in SEC 2010 – Innovazioni e Ricostruzione Delle Serie Storiche (1995–2013).” Nota informativa. Rome: Istat.Search in Google Scholar

Istat. 2017. Rapporto Sulla Competitività Dei Settori Produttivi – Edizione 2017. Rome:Search in Google Scholar

Istat. Available at: http://www.istat.it/storage/settori-produttivi/2017/Rapportocompetitivita-2017.pdf (accessed October 2017).Search in Google Scholar

Jang, L. 2016. “Resolving Differences in Statistical Units: Statistics Canada’s Experiences with Using Administrative Data in Economic Programs.” In Proceedings of the 5th International Conference on Establishment Surveys (ICES). Geneva, June 23, 2016. American Statistical Association.Search in Google Scholar

Karlberg, F. 2014. “Small Area Estimation for Skewed Data in the Presence of Zeros.” Statistics in Transition new series and Survey Methodology Joint Issue: Small Area Estimation 2014 16(4): 541–562. Available at: https://stat.gov.pl/download/gfx/portalinformacyjny/en/defaultlistaplikow/3454/11/1/3d_karlberg_16_4_25_i_s541-562.pdf (accessed October 2017).10.21307/stattrans-2015-032Search in Google Scholar

Kim, J.K.K. and J.N.K. Rao. 2011. “Combining Data from Two Independent Surveys: a Model-Assisted Approach.” Biometrika 8: 1–16. Doi: https://doi.org/10.1093/biomet/asr063.10.1093/biomet/asr063Open DOISearch in Google Scholar

Laitila, T., A. Wallgren, and B. Wallgren. 2011. “Quality Assessment of Administrative Data.” Quality Assessment of Administrative Data. Research and Development – Methodology Reports from Statistics Sweden 2011: 2. Statistics Sweden. Available at: http://www.scb.se/statistik/_publikationer/OV9999_2011A01_BR_X103BR1102.pdf (accessed October 2017).Search in Google Scholar

Luzi, O., U. Guarnera, and P. Righi. 2014. “The New Multiple-Source System for Italian Structural Business Statistics Based on Administrative and Survey Data.” European Conference on Quality in Official Statistics (Q2014). Vienna, June 3, 2014.Search in Google Scholar

Memobust. 2014. “Theme: Collection and Use of Secondary Data.” In Memobust Handbook on Methodology for Modern Business Statistics. Luxembourg: Eurostat. Available at: https://ec.europa.eu/eurostat/cros/system/files/Data%20Collection-07-TSecondary%20Data%20Collection%20v1.0.pdf (accessed October 2017).Search in Google Scholar

Namazi-Rad, M.-R. and D.G. Steel. 2011. “Contextual Effects in Modeling for Small Domain Estimation.” In Proceedings of the 4th Applied Statistics Education and Research Collaboration (ASEARC) Conference. Sidney, February 17, 2011. 12–14. Wollongong: University of Wollongong. Available at: http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1049&context=smartpapers (accessed October 2017).Search in Google Scholar

Petrucci, A., M. Pratesi, and N. Salvati. 2005. “Geographic Information in Small Area Estimation: Small Area Models and Spatially Correlated Random Area Effects.” Statistics in Transition 7(3): 609–623.Search in Google Scholar

Rao, J.N.K. and I. Molina. 2015. Small Area Estimation. 2nd ed. New York: John Wiley & Sons.10.1002/9781118735855Search in Google Scholar

Righi, P. 2016. “Estimation Procedure and Inference for Component Totals of the Economic Aggregates in the New Italian Business Frame.” Rivista di Statistica Ufficiale 2016(1): 83–97. Available at: https://www.istat.it/it/files/2016/11/RSU_1_2016_Testointegrale.pdf (accessed October 2017).Search in Google Scholar

Wallgren, A. and B. Wallgren. 2007. Register-Based Statistics: Administrative Data for Statistical Purposes. New York: John Wiley & Sons.10.1002/9780470061350Search in Google Scholar

Wolter, K.M. 2007. Introduction to Variance Estimation. 2nd ed. New York: Springer-Verlag.Search in Google Scholar