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The new “censimento permanente” of Italy: a self-learning, rolling census Fabio Crescenzi, - Chief Methodologist of the Department for Censuses, Administrative.

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Presentation on theme: "The new “censimento permanente” of Italy: a self-learning, rolling census Fabio Crescenzi, - Chief Methodologist of the Department for Censuses, Administrative."— Presentation transcript:

1 The new “censimento permanente” of Italy: a self-learning, rolling census Fabio Crescenzi, - Chief Methodologist of the Department for Censuses, Administrative and Statistical Registers UN Expert Group Meeting on Revising the Principles and Recommendations for Population and Housing Censuses, New York, 29 October - 1 November 2013

2 A magic triangle in the Digital Agenda of Italy

3 Moving to the age of the «censimento permanente»

4 Would you shop outside if you have a department store at home? SIM: At Istat there is a formidable archive containing integrated microdata from many Administrative Source

5 One Census - Two faces C face “To Count the population” D face “To Provide Data on the counted population”

6 C-Face - Statistical Test on the Count of ANPR Each year we will test the count of each municipal register of population Is the Count of ANPR(j) the true Population of Municipality j? Yes! the Null Hypothesis is accepted No! the Null Hypothesis is rejected

7 Ingredients for the Test A priori Knowledge derived from administrative sources (SIM – the Istat System of Microdata from Administrative Sources) Results of the C-sample, a rolling area-sample survey carried out by enumerators external to the Municipal Offices Logic of self-learning in the determination of sample sizes overweighting the most critical situations in previous years

8 C-sample Starting date 2016 Questionnaire Very Short! Few data for counting persons and households Tecnique Acquisition: CAPI by Handheld Monitoring: WEB Sampling design Area Sample-Capture Recapture About 650.000 households per year All Municipalities over 50.000 inhabitants Rolling inclusion under 50.000 inhabitants Self learning After each year the sample is revised. The sample of municipalities is over weighted if the null hypothesis was rejected.

9 The hamletic question Correct the count or do not correct the count? Whatever the answer, We have a strategy

10 In case of rejection of null hypotheses With Correction (after 2021)Without Correction (till 2021) ANPR Count is not correctedCount calculated from census population (2011) by adding and subtracting ANPR flows With Correction (after 2021)Without Correction (till 2021) Outstanding control of the register employing signals from Administrative Sources other than ANPR ANPR Count is corrected by a factor computed by Istat Count is calculated starting from census population count (2011) by adding and subtracting ANPR flows. Municipality is informed of which would be the Count corrected by Istat In case of acceptance of null hypotheses

11 The D face the D-sample Sampling design Two stage – About 1.500.000 households per year Questionnaire Long Technique Paperless: CAWI and CAPI Monitoring WEB (SGR)

12 D-sample. Plan of data accumulations by output area size Output area size (inhab.) Number of years Pooling Interval Central year >100.0001t t 35.000-100.0003 t, (t-1), (t-2)(t-1) <35.0005 t, (t-1), (t-2), (t-3), (t-4)(t-2)

13 D-sample. Dissemination Starting Plan

14 Rotation and “Revolution”, in an harmonious equilibrium of celestial bodies SIM ANNCSU C-sample D-sample ANPR PERMANENTE CENSUS


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