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