Contenuto in:
Capitolo

From annual to quarterly data: Challenges and strategies in the estimation of Italian general government compensation of employees

  • Sara Cannavacciuolo
  • Maria Saiz
  • Maria Liviana Mattonetti

This paper addresses the methodology for the quarterly estimation of Compensation of Employees paid by the General Government (GG) sector, in accordance with the European System of Accounts (ESA 2010). Due to the limited high-frequency data availability and the need to guarantee the consistency with annual constraints, quarterly estimation relies on indirect temporal disaggregation techniques. These methods use specific infra-annual indicators as proxies for the variables being estimated. The specific case of the quarterly estimation of Compensation of employees presents several additional challenges. Firstly, the information provided by the sources, based on cash or legal-accrual data, is elaborated to define indicators which respect the accrual ESA 2010 principle as the annual estimates, based on more compliant data sources such as final budgets of public entities. Secondly, at a quarterly level the extraordinary events - such as the recording of delayed collective bargaining agreements which result in arrears - have a strong impact on quarterly indicators, whereas their effect is mitigated at annual level. To attribute these flows to the period when the work is performed, multi-source data harmonization techniques are employed. Thirdly, to accurately reflect intra-annual dynamics, information is collected for specific groups of GG entities (e.g., municipalities, universities, regions and provinces) and aggregated into ESA 2010 GG sub-sectors (Central Government, Local Government and Social Security Funds) leading to three specific estimates. To validate temporal disaggregation models and ensure methodological rigor and data quality, statistical tests are applied throughout the process. The results confirm the effectiveness of this methodology in providing accurate and timely quarterly estimates of Compensation of employees for the GG sector, thereby supporting reliable short-term economic analysis and policy making.

  • Keywords:
  • Temporal disaggregation,
  • Government finance statistics,
  • Compensation of employees,
+ Mostra di più

Sara Cannavacciuolo

ISTAT, Italian National Institute of Statistics, Italy

Maria Saiz

ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0009-0006-1896-5195

Maria Liviana Mattonetti

ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0009-0006-1122-6699

  1. Bisio, L., Moauro, F. (2016). Disaggregazione temporale nei modelli dinamici: recenti avanzamenti nella pratica dei conti economici trimestrali. Istat Working Papers, 15.
  2. Chow, G., Lin, A. (1971). Best linear unbiased interpolation, distribution, and extrapolation of time series by related series. The Review of Economics and Statistics, 53(4), pp. 372-375. DOI: 10.2307/1928739
  3. Eurostat (2013). European System of Accounts - ESA 2010. Luxembourg: Publications Office of the European Union.
  4. Eurostat (2018). ESS Guidelines on Temporal Disaggregation, Benchmarking and Reconciliation. Luxembourg: Publications Office of the European Union. DOI: 10.1111/stan.12157
  5. Fernández, R.B. (1981). A methodological note on the estimation of time series. The Review of Economics and Statistics, 63(3), pp. 471-476. DOI: 10.2307/1924371
  6. Gómez, V., Maravall, A., (1998). Seasonal Adjustment and Signal Extraction in Economic Time Series. Working Papers 9809. Banco de España. DOI: 10.1002/9781118032978.ch8
  7. Litterman, R.B. (1983). A random walk, Markov model for the distribution of time series. Journal of Business and Economic Statistics, 1(2), pp. 169-173. DOI: 10.21034/sr.84
  8. Mattonetti, M.L., Saiz, M. (2025). Disclosure of Italian seasonally adjusted data for general government: It’s a matter of strategy. In E. di Bella, V. Gioia, C. Lagazio, S. Zaccarin (eds). Statistics for Innovation IV. SIS 2025. Italian Statistical Society Series on Advances in Statistics. Springer, pp. 13-18. DOI: 10.1007/978-3-031-96033-8_3
  9. Nasse, P. (1973). Le système des comptes nationaux trimestriels. Annales de L’Inssée. Institut national de la statistique et des études économiques. 14, pp. 119-165. DOI: 10.2307/20075174
  10. Pavía-Miralles, J.M. (2010). A survey of methods to interpolate, distribute and extrapolate time series. Journal of Service Science and Management, 3(04), pp. 449-463. DOI: 10.4236/jssm.2010.34051
PDF
  • Anno di pubblicazione: 2026
  • Pagine: 117-122

XML
  • Anno di pubblicazione: 2026

Informazioni sul capitolo

Titolo del capitolo

From annual to quarterly data: Challenges and strategies in the estimation of Italian general government compensation of employees

Autori

Sara Cannavacciuolo, Maria Saiz, Maria Liviana Mattonetti

Lingua

Inglese

DOI

10.36253/979-12-215-1062-1.22

Opera sottoposta a peer review

Anno di pubblicazione

2026

Copyright

© 2026 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Informazioni bibliografiche

Titolo del libro

Data, Statistics and AI for Well-Being of People and Organisations

Curatori

Luigi Fabbris, Alberto Franci, Pietro Renzi

Opera sottoposta a peer review

Numero di pagine

420

Anno di pubblicazione

2026

Copyright

© 2026 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Editore

Firenze University Press

DOI

10.36253/979-12-215-1062-1

ISBN Print

979-12-215-1061-4

eISBN (pdf)

979-12-215-1062-1

eISBN (xml)

979-12-215-1063-8

Collana

Applied Statistics Series

0

Download dei libri

0

Visualizzazioni

Salva la citazione

1.528

Libri in accesso aperto

in catalogo

3.744

Capitoli di Libri

6.674.567

Download dei libri

5.994

Autori

da 1219 Istituzioni e centri di ricerca

di 67 Nazioni

83

scientific boards

da 416 Istituzioni e centri di ricerca

di 46 Nazioni

1.439

I referee

da 400 Istituzioni e centri di ricerca

di 41 Nazioni