New quarterly indicators of public finance to strengthen official statistics within the national accounts
Conference
Format: CPS Abstract - IAOS 2026
Keywords: public finance statistics
Session: Economic and banking statistics innovation
Wednesday 13 May 11 a.m. - 12:30 p.m. (Europe/Vilnius)
Abstract
Authors: S. Cannavacciuolo, L. Corallo, M. L. Mattonetti, G. Ottaviani, M. Saiz, L.Sciandra, G.Zuchegna, M. Cosco (ISTAT)
This paper presents the results of an experimental exercise to estimate Italy’s quarterly non-financial accounts for the general government, disaggregated by sub-sector (central government, local governments, and social security funds). This work was developed as part of a European project funded by a grant, which was designed to improve the availability and timeliness of public finance statistics.
This initiative is an advancement in official macroeconomic statistics, fully aligned with the methodological framework of the European System of Accounts (ESA 2010). In particular, by integrating quarterly general government sub-sector estimates in the national accounts, cross-country comparability and coherence with annual data is ensured, while both non-seasonally and seasonally adjusted time series are provided to support cyclical analyses throughout the year.
From a policy perspective, newly quarterly fiscal indicators broken down by sub sector provide a high-frequency information base that enables more precise monitoring of public finance, including the net landing/net borrowing, the tax burden, net expenditure, and other key aggregates.
From a methodological perspective, this work improves the quality of government finance statistics (GFS) by producing short-term indicators at the sub-sector level. This pilot exercise will set a benchmark for the future development of quarterly public finance accounts and related cyclical indicators within the European Statistical System (ESS).
The present paper is organized as follows: Section 1 provides an overview of the methodological framework for the GG quarterly estimate. Section 2 describes the data sources and estimation techniques. Section 3 discusses and analyses the new short-term public finance indicators. Section 4 concludes.