{"id":8,"date":"2015-04-08T11:14:00","date_gmt":"2015-04-08T09:14:00","guid":{"rendered":"http:\/\/people.unipi.it\/cloner\/?page_id=8"},"modified":"2024-03-18T16:58:59","modified_gmt":"2024-03-18T15:58:59","slug":"pubblicazioni","status":"publish","type":"page","link":"https:\/\/people.unipi.it\/monica_pratesi\/pubblicazioni\/","title":{"rendered":"PUBLICATIONS"},"content":{"rendered":"

My work takes place mainly in scientific communities identified by four fields of research: (I) Survey methods and sampling methodology, estimation for small areas; (ii) Poverty Studies; iii) Official statistics; iv) Data for policy planning and monitoring<\/p>\n

Recent Publications (selection):<\/strong><\/p>\n

    \n
  1. Pratesi M.<\/strong>, Marchetti S., Giusti C., Salvati N. (2023). The Use of Spatial Information in Area-level Models: An Evaluation Based on Auxiliary Data Availability. Calcutta Statistical Association Bullettin<\/em>, vol. 75, p. 155-172, ISSN: 0008-0683, doi: 10.1177\/00080683231198589<\/li>\n
  2. Schirripa Spagnolo, F., Bertarelli, G., Salvati, N. , Summa, D. , Scannapieco, M., Marchetti, S. and Pratesi, M<\/strong>.(2023) \u201cReducing selection bias in non-probability sample by Small Area Estimation<\/em>.\u201dIn Coretto, Giordano, La Rocca Parrella, Rampichini (eds.). CLADAG 2023 – book of abstracts and short papers. Pearson Italy. (pp. 288-291).<\/li>\n
  3. Pratesi M.<\/strong> (2022), Povert\u00e0 educativa: perch\u00e9 e come misurarla anche a livello territoriale. Alcune analisi e proposte. Politiche sociali<\/em>, Fascicolo 3\/2022, pp: 373-398<\/li>\n
  4. Biggeri L.<\/strong>,Pratesi M<\/strong>. (2022), Estimation of local Spatial Price Indices using scanner data: methods and experiments applied also for assessing poor-specific indices. Review of Official Statistics<\/em>, n.2, pp:9-42.<\/li>\n
  5. Tonutti, G., Bertarelli, G., Giusti, C. and Pratesi, M<\/strong>. (2022) Disaggregation of poverty indicators by small area methods for assessing the targeting of the Reddito di Cittadinanza national policy in Italy in Socio-Economic Planning Sciences<\/em>, vol. 82, pp. 101327 (ISSN 0038-0121)<\/li>\n
  6. Pratesi M<\/strong>., Schirripa Spagnolo, F. (2022). Small area methodology for measuring poverty at a local level. In Silber J. (Ed.). Research Handbook on Measuring Poverty and Deprivation, pp. 129-140. Edward Elgar Publishing Limited. ISBN: 9781800883444<\/li>\n
  7. Bertarelli G., Schirripa Spagnolo F., Salvati N., Pratesi M.<\/strong> (2021). Small area estimation of agricultural data in R. In Postiglione P., Benedetti R. and Piersimoni F. (Eds.), Spatial Econometric Methods in Agricultural Economics Using R, pp. 202-234. Taylor & Francis Inc. ISBN:9781498766814<\/li>\n
  8. Pratesi M<\/strong>, Ceccarelli C, Menghinello S. (2021), \u201cCitizen generated data and Official Statistics: an application to SDGs indicators\u201d, Discussion paper n 274<\/em>, Department of Economics and Management, University of Pisa<\/li>\n
  9. Bertarelli, G., D\u2019Agostino, A. , Giusti, C & Pratesi, M<\/strong>. (2021). Measuring Educational Poverty in Italy: a Multidimensional and Fuzzy Approach (in press: 2020). in Betti, G., Lemmi, A. (eds.), Analysis of Socio-Economic Conditions: Insights from a Fuzzy Multidimensional Approach<\/em>. London and New York: Routledge<\/li>\n
  10. Pratesi, M<\/strong>., Quattrociocchi, L., Bertarelli, G., Gemignani, A. & Giusti, C. (2020). Spatial Distribution of Multidimensional Educational Poverty in Italy using Small Area Estimation. Social Indicators Research<\/em>. https:\/\/doi.org\/10.1007\/s11205-020-02328-5<\/a><\/li>\n<\/ol>\n

    ResearchGate<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

    My work takes place mainly in scientific communities identified by four fields of research: (I) Survey methods and sampling methodology,…<\/p>\n

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