Use of Statistical and Administrative data for national accounts

1. Use of Statistical and Administrative data for national accounts Clementina Ivan-Ungureanu Training: Essential SNA: Building the basics Addis Ababa, 13-16 February 2012

2. Content of the presentation • Main statistical sources used for national accounts • Administrative sources - need for administrative sources - translation of administrative data into national accounts concepts

4. Statistical sources

7. Statistical sources- Agriculture • Agriculture household survey • crop production • number of livestock • data of major inputs: seeds and fertilizers, expenditure for agriculture services • Survey concerning the crop production • Survey of annual number of livestock • Other specific surveys

8. Statistical sources- other sectors • SBS – main yearly survey • data for the estimation of O, IC: turnover, stocks, taxes, subsides • data about GFCF • data wages and number of employees

9. Statistical sources- other sectors(cont) • Monthly or quarterly • Manufacturing industry • Construction • Transport • Other services • HBS • LFS

12. LFS • Questionnaire for the household • Individual questionnaire for the personas more than 15 years old • Labor status • Characteristics of the main job, secondary job • Working time, hours worked • Education, training

13. Households surveys • HBS, income and expenditure • Main sections: • Household members • Income : from wages, benefits, own production, remittances, etc • Expenditures: durable goods, other goods and services, health, education, transport • Information about the dwelling

14. ADMINISTRATIVE SOURCES

15. Definition The administrative source is the register of units and data associated with an administrative regulation (or group of regulations), viewed as a source of statistical data. Source: Glossary of Statistical Terms, OECD, 2007 http://www.oecd.org/dataoecd/9/20/1963116.pdf

16. Examples of Administrative Sources • Value Added Tax (VAT) data; • Personal income tax data; • Business (including corporate) taxation data; • Social security data; • Business registration and administration records; • Business accounts of corporations; • Records held by Central Banks; • Records (other than VAT) held by Customs and Excise Authorities; • Records of government (central and local);

17. Examples of Administrative Sources (cont) • Records held by associations of employers, of employees and of businesses and professions; • Records held by other private sector bodies, e.g. credit rating agencies, non-profit units, etc. • Identity cards / passports / driving licenses • Electoral register • Register of farms • Local council registers • Building permits • Licensing systems e.g. television, sale of restricted goods, import / export

18. Advantages • They are ‘cheaper’ than other sources and oft en even free. • Provide complete, or almost complete, coverage of the population to which the administrative process applies. • Very high response rates, no survey errors, providing more accurate and detailed estimates of sub-populations. • Timelinessof the statistical variables derived from administrative sources could be improved. • Reduce the response burdenon businesses.

19. Coverage • Administrative sources usually offer better coverage of target populations, and can make statistics more accurate: • No survey errors • No (or low) non-response • Better coverage gives: • Better small-area data • More detailed information

20. Timeliness • Producing statistics from administrative sources can sometimes be quicker than using surveys • No need for: • forms design; • pilot surveys; • sample design etc.

21. Framework to access to administrative data • ACCESS Key barrier to the use of administrative data WAYS – depend of the existing conditions in each country GENERAL DIMENSSION OF THE FRAME: • Legal • Policy • Organizational

22. Legal framework • Legal frameworks are constructed at the national level, and are specific to national sources and circumstances. • In some cases, relevant legislation at the international level : legislation of the European Union • IMPORTANT : STATISTICAL LAW

23. Policy Frameworks • Many countries have general policies on data sharing within government, which will influence the right of access administrative data for statistical purposes • UN Fundamental Principles of Official statistics- principle 5 : Data for statistical purposes may be drawn from all types of sources, be they statistical surveys or administrative records. Statistical agencies are to choose the source with regard to quality, timeliness, costs and the burden on respondents

24. Organizational Frameworks Organizational arrangements to facilitate data flows by written agreements and protocols. Key elements: • Legal basis • Defining the data • Frequency of data supply • Quality standard • Confidentiality rules • Technical standards • Provision of metadata

25. Problem (i) 1.Obtaining access to administrative sources. 2.The information used in administrative sources does not directly correspond to the statistical indicator definitions 3.The classification systems used within administrative sources may be different to those used in the statistical world

26. Problem (ii) 4. Timeliness. Data may either not be available in time to meet statistical needs or refers to a period that does not coincide with that required for statistical purposes 5. Inconsistency between sources

27. Problem (iii) 6. Administrative sources are generally set up for the purpose of collecting taxes or monitoring government policies. For this reason, they are susceptible to political change. 7. Resistance to change

28. 1.Public Opinion • The level of public concern about government departments sharing data varies from country to country • There is usually some suspicion of the motives for data sharing • Sometimes public opinion favours data sharing

29. Solutions • Adopt and publish a code of practice following international standards • Clearly stated limits and rules may help reduce concerns • The principle of the “one-way flow” of sensitive data must be understood by all • Publish cost-benefit analyses of the use of different sources

30. 2.Definitions of Variables • Administrative data are collected according to administrative concepts and definitions • Administrative and statistical priorities are often different, so definitions are often different

31. Example: Unemployment • Statistical definition (ILO) • Out of work • Available for work • Actively seeking work • Administrative definitions are often based on those claiming unemployment benefits

32. Solutions • Know and document the differences and their impact • Use other variables to derive or estimate the impact of the difference • Statistical adjustments during data processing

33. 3.Classifications • Used for different purposes • May not be a priority variable for the administrative source • Different classification rules for the same classification • Different classifications used

34. Solutions • Understand how administrative data are collected and what classification is used • Collaboration for the use of the same classifications ( help of Government) • Stress the advantages of using a common classification • Provide coding expertise, tools and training to administrative data suppliers to use the same classification

35. Solutions( cont) • Provide coding expertise, tools and training to administrative data suppliers to use the same classification • Use text descriptions to re-code administrative data

36. 4.Timeliness Two Issues • Data arrive too late • Data relate to a different time period

37. a. Data arrive too late • Data from annual tax returns are often only available several months after the end of the tax year, so they are unsuitable for monthly or quarterly statistics • Lags in registering “real world” events

38. Solutions • Understand the length and impact of lags • Adjust data accordingly • Look for ways to reduce lags where possible – collaboration with Ministry of Finance

39. b. Different Time Periods • Administrative reference period (e.g. Financial/tax year) may not be the same as the statistical reference period • Monthly average versus point in time (e.g. employment data)

40. Different Time Periods

41. Solutions • Statistical corrections • Estimations using data from other reference periods

42. 5. Inconsistency between sources • Data from one source may appear to contradict those from another. This may be due to different definitions or classifications, differences in timing, or simply to an error in one source. • Could be between: • Administrative and statistical sources • Two administrative sources

43. Solutions • Establish priority rules • Analysis of the variable evolution and trend

44. 6. Change Management • Risk of changes in: • Government / administrative policy • Thresholds • Definitions • Coverage • Systems Happed: • Immediately after an election • Change of government, of minister

45. Solutions Manage the Risk by: • Legal provisions • Contractual agreements • Regular contact with administrative colleagues • Anticipating changes • Contingency plans

46. 7. Resistance to Change One of the least recognized, can come from within the organization. • Statisticians may resist the use of administrative data because they do not trust data that they have not collected themselves.

47. Solutions • Better education of statisticians • To analyze and determine the real quality of survey and administrative data. • to show that cost savings from using administrative data do not necessarily mean staff reductions

48. TRANSITION FROM ADMINSTRATIVE DATA TO NATIONAL ACCOUNTS INDICATORS

49. How administrative sources are used? • It is a complex process • It is not a standardised process, but specific to each country, according to its specific administrative data sources Two main steps involved: • Constructing transition tables (so-called “bridge ”from administrative data sources to SNA aggregates; • Applying adjustments in order to fulfill the SNA conceptual requirements, when needed

50. How administrative sources are used?(cont) Preparation of “bridge tables”: a) Identification of administrative data sources; b) Analysis of content in respect of national accounting methodological requirements; c) Collection of data source indicators; d) Translation of each indicator from administrative data sources into national accounts concepts; e) Application of adjustments to meet national accounting requirements; f) Estimation of the national accounts indicators.