ADMINISTRATIVE DATA AND MODEL BASED ESTIMATION IN ITALIAN AGRICULTURE STATISTICS | Zendy

Roberto Gismondi | Zendy; Massimo Alfonso Russo | Zendy

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ADMINISTRATIVE DATA AND MODEL BASED ESTIMATION IN ITALIAN AGRICULTURE STATISTICS

Author(s) -

Roberto Gismondi,

Massimo Alfonso Russo

Publication year - 2017

Publication title -

management theory and studies for rural business and infrastructure development

Language(s) - English

Resource type - Journals

eISSN - 2345-0355

pISSN - 1822-6760

DOI - 10.15544/mts.2017.29

Subject(s) - estimation , statistics , reliability (semiconductor) , econometrics , agriculture , lag , sampling (signal processing) , regression analysis , small area estimation , work (physics) , computer science , mathematics , geography , economics , engineering , computer network , power (physics) , physics , management , archaeology , filter (signal processing) , quantum mechanics , computer vision , mechanical engineering

Actually, agricultural surfaces are estimated by the Italian National Statistical Institute (ISTAT) through experts evaluations. The present work has two purposes: 1) to improve the use of administrative data for increasing reliability of crop statistics; 2) to improve methodology for releasing crop early estimates. IACS administrative data are available within a short time lag, cover all the main crops and may substitute estimates gradually. As regards early estimates, the usual design based estimation strategy may be improved through double sampling and model based regression. Results show good reliability of administrative data and decrease of estimates variances using model based estimation. JEL Codes: Q10, Q11, C13, C83.

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