Ireland [Ireland] - Industrial Production

Ireland [Ireland]: Industrial Production

Mnemonic IP.IIRL
Unit Vol. Index 2015=100, NSA
Adjustments Not Seasonally Adjusted
Monthly 21.18 %
Data Nov 2020 151.6
Oct 2020 125.1

Series Information

Source Central Statistics Office (CSO)
Release Industrial Production & Turnover
Frequency Monthly
Start Date 1/31/2015
End Date 11/30/2020

Ireland [Ireland]: Business

Reference Last Previous Units Frequency
Business Confidence Nov 2020 96.95 96.11 Index long term avg=100, SA Monthly
Industrial Production Nov 2020 151.6 125.1 Vol. Index 2015=100, NSA Monthly
Change in Inventories 2020 Q3 -119 1,141 Mil. EUR, SA Quarterly
Real Change in Inventories 2020 Q3 -343 1,299 Mil. Ch. 2018 EUR, SA Quarterly

Release Information

The Industrial Production Index for Ireland covers manufacturing; mining, quarrying and turf; electricity, gas and water; but not covering construction; with a base year 2015=100. Data ia reported by all industrial local units with 20 or more persons engaged. Details are provided on the quantity of production or on the value of production (which is deflated by relevant industrial producer sub-indices of the wholesale price index). Indices are published in both the original and seasonally adjusted form.

The monthly industrial production index
monitors current trends in the volume of production of industrial local units with three or more persons engaged. The primary purpose of the index is to measure change in value added at constant prices.
Production Concept
Indicator of the monthly change in the volume of industrial production.
Production Definition
The index measures the change in gross value added at constant prices.
The monthly index of turnover
measures the change in the level of sales each month of industrial products, whether manufactured in the month in question or in previous periods (excluding non industrial activity where practicable). The turnover indices outlined in this release are exclusive of VAT.
Turnover Concept
Indicator of the monthly change of sales of industrial products.
Turnover Definition
The index measures the change in the level of sales each month of industrial products.


Industrial classification: NACE Rev. 2 of The European Communities.

Scope of the Data

  • Industrial coverage: All local units with three or more persons engaged in the mining and quarrying, manufacturing, electricity, gas and water supply sectors.
  • Product coverage: All products by 8-digit Prodcom code manufactured in Ireland are used in calculating the production indices based on production or net sales value.

Source data collection programs

  • Nature of indicators used: Production volume data for all sectors valued at base year prices or where appropriate net selling value deflated by associated earnings, or wholesale price deflators. Turnover measures the change in the level of sales each month of industrial products, whether manufactured in the month in question or in previous periods (including non industrial activity where practicable).
  • Nature of weights: The weights for the Production Index are gross value added at factor cost in the base year.The weights for the Turnover Index are turnover in the base year.
  • Source of weights: Census of Industrial Production (CIP) for the production industries.
  • Period of current weights: 2015.
  • Frequency of weight update: Every five years.
  • Unit selection: Businesses are selected according to their main activity and include all businesses with employment greater than 20. There is an exception to this threshold criterion. For a few sectors a threshold of 12 rather than 20 per employees is used.
  • Sample sizes: Around 1400 businesses every month.
  • Data collection methods: The source of information for the index is the Monthly Industrial Production Inquiry (MIP) which is conducted by post. The survey sample is drawn from CSO Business Register. Non-responding units are followed up on telephone.

Source data timeliness

Timing of production observations: Questionnaires are despatched on the first working day following the end of the reference month.

Source data statistical techniques

  • Computation of lowest level indices: Where data are supplied in physical quantities the average daily production (in physical units) of all sample units (including estimates for non-respondents) for each commodity is aggregated. The resulting aggregate is valued at base year prices using the base year price for that commodity (the base year price is derived from the 2015 PRODCOM value and quantity data for the sample units).
  • Alignment of value of weights and base period: Where data are supplied in value terms a suitable deflator is used to convert the daily value to a value at base-year prices. In most cases a suitable component of the Wholesale Price Index is used.
  • Linking of reweighted index to historical index: The total daily production valuations at base year prices are aggregated over all commodities in a 4-digit NACE sector and annualised by multiplying by the number of working days in the year. This annualised value is then divided by the corresponding value of gross output for the sample firms in that sector for 2015 The result is then multiplied by 100 to give an index number (to base 2015=100) of production for the sector.
  • Aggregation: the indices compiled for the 4-digit NACE sectors are combined to provide the published sectoral indices at 2-digit or 3-digit level and the broader sectoral groupings and overall indices for manufacturing, transportable goods and all industries. They are combined using as weights for each 4-digit sector the gross value added for all local units in that sector covered in the 2000 Census of Industrial Production.
  • Reference period: 2015 = 100.
  • Procedures for non-response: There is telephone follow-up of non-responding units, but if the problem persists, the data from the previous period are carried forward, or they are imputed using the movement in the aggregate index within the 4 digit NACE class.

Other statistical techniques

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:

  • Calendar effects, e.g. the timing of Easter
  • Outliers, temporary changes and level shifts in the series