Combining Survey and Administrative Data to Develop Statistics for Monitoring Climate Change UNECE Experts Forum on Climate Change Related Statistics Geneva, 2-3 September 2015 Gerry Brady (Central Statistics Office, Ireland)

Overview This paper briefly looks at how the role of the Environment Division in the Central Statistics Office Ireland has developed through co- operation with national agencies for environment protection and sustainable energy. The CSO has worked with the national agencies to combine administrative data from the agencies with CSO survey data. The co- operation has been supported by a Memorandum of Understanding. 2

Energy and Waste Statistics in Ireland Sustainable Energy Authority of Ireland (SEAI) was established in 2002 and has responsibility for compiling energy balances and is the main body for reporting energy statistics for Ireland Environmental Protection Agency (EPA) was established in The EPA compiles national inventory emissions and is the main body for reporting waste statistics for Ireland Central Statistics Office (CSO) has traditionally had a minor involvement in compiling environment statistics but the Division has grown since 2011 in response to increased legal reporting responsibilities to Eurostat 3

CSO Role in Environment Statistics & Accounts As downstream user only? -> Using data from other existing CSO surveys and National Accounts -> Use administrative data from other agencies As primary data collector? -> Undertaking new surveys -> Avoiding overlaps with existing data collection For data integration and validation? -> Add value by integrating and validating existing data -> Undertake primary data collection only when necessary 4

As downstream user only? Advantages -> Focus on reusing existing data to complete Eurostat environment accounts modules Disadvantages -> Environment statistics frequently requires use of quantity data and relatively low unit value data (e.g. sand and gravel, coal, roundwood) which may not be of same quality -> No involvement of Environment statisticians in the compilation or validation of basic statistics used to compile environment accounts -> Data owners may not have the resources to undertake additional scrutiny of environment-relevant data 5

As primary data collector? Advantages -> Questionnaire customised to environment topics and classifications -> Environment relevant sample of enterprises -> Direct data quality management Disadvantages -> Response burden issues make it difficult to undertake a new survey -> New survey may have overlap with existing data collections -> Requires management and clerical staff 6

For data integration and validation? Advantages -> Focus on adding value to existing survey and administrative data through applying an environment-focused data validation -> Data collected as part of licensing and enforcement mechanisms should be of good quality -> Agency reporting systems can provide a free data collection resource for a statistical office Disadvantages -> Difficult to integrate different data sources at enterprise level -> Administrative data may not fully meet statistical data needs -> Administrative data may not have same classifications as statistical 7

Energy Statistics Example The main data sources for compiling energy balances were a mixture of administrative data and the CSO Census of Industrial Production (structural business statistics) which only collected information on the cost of fuel purchases There was a need to collect data on quantities of fuels purchased across all NACE sectors and the existing data mainly had cost of fuel purchases This requires a business register and the capacity to conduct a survey of 3,000 plus enterprises - the CSO has both 8

CSO Energy Statistics Data Sources Structural business survey (CIP only has cost of fuel purchases) -> Inconsistent fuel breakdown and cost of purchases only -> Large sample of industry enterprises (around 5,000) Annual services inquiry (cost of fuel purchases) -> Typically no fuel breakdown and cost of purchases only -> Large sample of services enterprises (around 12,000) 9

New CSO Business Energy Use Survey Launched by CSO business area in 2009 in conjunction with SEAI Expansion to collect quantities of fuels used as well as purchase costs Fuel questions in structural business statistics reduced to total cost of fuel purchases only (no fuel breakdown) Sample was restructured in 2013 by CSO Environment to get broader NACE coverage and collect data on transport fuel purchases Around 3,000 industry and services enterprises returns in

Administrative Energy Statistics Data Sources SEAI large industry energy network (LIEN) -> Fuel breakdown in quantity and cost -> Annual data source of 130 enterprises SEAI public sector energy programme (PSEP) -> Fuel breakdown in quantity -> Annual data for 100 enterprises with electricity/gas consumption readings EPA emissions trading scheme (ETS) -> Fuel breakdown in quantity -> Annual data source of 130 enterprises 11

Putting it all Together Involves register matching work to get NACE codes and employment data for weighting the sample Estimation of fuel breakdown for SBS and ASI surveys Estimation of quantities for all fuels and a breakdown of costs by fuel Requires more statistician input than using the returns from one survey especially when a country does not have one unique business identifier that is used in all data collections 12

The Integrated File Coverage across most NACE Divisions Quantity of fuel used and purchase cost for each fuel Annual data All data sources matched with CSO business register 13

Benefits Avoids duplicate data collection Environment agencies and statistical offices working closely together and using the same aggregated data Statistical office can create anonymised files for further analysis by research community Improved energy statistics and balances for emissions inventory and energy use classified by NACE sector as required by National Accounts Supply Use Tables 14

Waste Statistics Example The EPA conducted the 2006, 2008, and 2010 Waste Generation Surveys (WGS) In 2010 the CSO Statistical Methods area assisted by selecting a sample and weighting the results EPA and CSO discussed options for the 2012 survey and it was agreed that CSO environment would conduct the survey with assistance from EPA staff for technical queries from enterprises -> CSO business register and surveying capacity were key considerations 15

Waste Statistics Data Integration EPA Pollutant Release and Transfer Register (PRTR) register was integrated with CSO business register before 2012 sample was selected Integrated approach avoids surveying enterprises that EPA have administrative data for 2012 PRTR data were integrated with CSO survey returns to assist in validation of survey data 16

Waste Collectors Data CSO Environment recently agreed to validate local authorities annual administrative data on waste collected from non-domestic sector -> Data are submitted by waste collectors to the local authorities using list of waste codes but data are not classified by the NACE sector where waste was generated -> CSO validated annual administrative waste collectors data will be used to validate biennial CSO Waste Generation Survey data both at overall level and by 6-digit waste stream code -> Identify any errors in reporting units (kg, litres, etc.) -> Identify any specialised waste streams not covered by WGS sample 17

Foreign Trade Statistics Example In many countries, national statistical offices compile foreign trade goods statistics The NSI can examine the data in more detail to assist inventory compilers with specific queries e.g. CN, month, individual trader, NACE sector, unit values, etc. to identify net mass or supplementary units data that may need correction before use in environment statistics -> such scrutiny may assist inventory compilers to gather data on sectors such as fluorinated gases, mercury, etc. 18

Working Together to create Synergy Memorandum of Understanding can be used to clarify how the statistical office and the administrative agency will work together Clarify at the outset that the data are for statistical purposes only and that no confidential data can be made available to the agency Combine subject-matter expertise with statistical experience NSI may have more sophisticated statistical IT validation software Agencies may have access to funding for targeted research 19

Conclusions Environment Divisions in statistical offices are typically understaffed as it is a relatively new domain There are high quality administrative data in environment-related agencies Statistical offices may have legal authority under a Statistics Act to obtain access to confidential administrative microdata and to match it with business registers and survey data If all data sources are used then overall quality should be improved, better NACE representativeness, and reduced respondent burden 20