This publication is categorised as a CSO Frontier Series Output. Particular care must be taken when interpreting the statistics in this release as it may use new methods which are under development and/or data sources which may be incomplete, for example new administrative data sources.
This publication gives an early estimate of GDP for Ireland at approximately T+30 days after the end of the reference quarter. The development of this early estimate has been carried out to meet one of the key objectives of the EU Economic and Monetary Union (EMU) Action Plan. The aim is to provide users with Principal European Economic Indicators (PEEIs) for monitoring and analysing the economy of the Monetary Union that are comparable in timeliness and quality with those compiled by other international economies.
This preliminary GDP estimate is based on data sources that are incomplete compared with those used for compiling GDP in the CSO’s Quarterly National Accounts (QNA) which are issued with T+2 months timeliness and are subject to further revisions. The QNA for Quarter 2 2023 will be based on more extensive economic information and will provide a greater level of detail on the economic performance estimates for Ireland. The QNA for Quarter 2 2023 will be released in early September 2023.
This publication releases an early estimate of GDP in volume terms for Q2 2023. The estimate is based on information from the CSO Large Cases Unit, information on Retail Sales, Administrative Payroll Data and other indicators of activity in the Irish Economy. For this early estimation process, the Output Method for GDP compilation is followed, while the QNA results that are available at approximately T+2 months after the reference quarter, are based on both the Output & Expenditure methods for estimating GDP. Where information is not available in sufficient timeliness for this T+30-day estimate, RegARIMA modelling has been used. For this preliminary estimate, GDP data already published for earlier reference quarters remain unrevised.
Gross Domestic Product (GDP) represents the total value added in the production of goods and services in the country.
The National Accounts Explained section on the CSO website provides a clear and helpful guide to the terms used in National Accounts to help users make the most of the macroeconomic outputs. Terms like GDP are explained, for those who are unfamiliar with them or new users of the accounts.
Seasonally adjusted aggregates can be computed either by aggregating the seasonally adjusted components (indirect adjustment) or adjusting the aggregate and the components independently (direct adjustment). In this publication, seasonal adjustment is conducted using the indirect seasonal adjustment approach. This approach is in line with CSO’s Policy on Seasonal Adjustment and Eurostat’s recommendations on Seasonal Adjustment. The indirect approach can give the best results when the component series show very different seasonal patterns, which is a feature of some data series in the Irish National Accounts. Under this indirect approach, individual GDP output method time series are independently adjusted at the component level. These individual series are then aggregated to compute the seasonally adjusted result for GDP.
Each of the unadjusted component series are adjusted for seasonality and calendar days effects (using the latest T+2-month models) to provide seasonally and calendar adjusted series. These component series are aggregated and the implied quarter-on-quarter change in this volume estimate is then applied to the previous T+2-month result to derive the early quarterly GDP estimate. This means that the seasonal factors used for compiling the most recent QNA are used for the back quarter estimates in this publication and new factors are used only for the latest reference quarter.
Seasonally adjusting the T+30 Preliminary GDP Estimate will remain challenging until the full scale and shape of the impact COVID-19 has on the time series is better understood. Users should be aware that as further data observations become available in the months and quarters ahead, revisions to the seasonal adjustment models may result in revisions to the quarterly seasonally adjusted series.
The adjustments are completed by applying the X-13-ARIMA model, developed by the U.S. Census Bureau to the unadjusted data. This methodology estimates seasonal factors while also taking into consideration factors that impact on the quality of the seasonal adjustment such as:
For additional information on the use of X-13-ARIMA see US Census Bureau information on X-13ARIMA-SEATS Seasonal Adjustment Program.
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