Advisory Expert Group Backcasting

1. Advisory Expert GroupBackcasting Statistics Canada

2. For discussion • The need for National Account time series • Considerations and constraints • Possible approaches • The need for guidance Statistics Canada • Statistique Canada

3. Main functions of the National Accounts • The National Accounts allow users to examine the structure of the economy and the evolution of the economy. • Users require a time-series of economic data in order to undertake: • monetary and fiscal policy and monitoring; • structural analysis (productivity, input-output or GE modelling); • forecasting and business cycle analysis • administrative uses; • environment-economy linkages; and • research uses. Statistics Canada • Statistique Canada

4. How long is long enough? • The National Accounts (NA) record the macroeconomic history of a nation. The data along, with associated contextual and analytical information, is a national asset that needs to be both preserved and invested in. • The greater the coverage of an NA time series, the greater the benefit, since one of the uses is to compare recent events to similar economic developments of the past. • The greater the number of economic developments covered by the time series the greater the use to policy makers. Statistics Canada • Statistique Canada

5. Why it should be done by the NSO • An argument can be made that backcasting should be left to the users—the NSO need only supply the metadata required to backcast the data. • This is countered (mainly by users) that: • The NSO is in the best position to backcast the data given their intimate knowledge of the data and accounting rules. • This would avoid multiple ‘official’ measures due to differences in approaches. • NSO compilation lends credibility to the data. Statistics Canada • Statistique Canada

6. Considerations and constraints to backcasting • An NSO can take a number of different approaches to backcasting. These include: • Publishing breaks in the time series • Backcasting a portion of the time series with partial detail • Backcasting a portion of the time series with full detail • Backcasting the full time series with partial detail • Backcasting the full time series with full detail Statistics Canada • Statistique Canada

7. Considerations and constraints to backcasting • There are some important considerations and constraints national accountants face when backcasting National Account time series. These include: • Time • Human capacity • Legislative / administrative uses of the data • Coordination (e.g., integrated accounts, decentralized accounts) • Availability of source data and quality of source data • Significance of the changes to be backcasted • The approach taken in large part is determined by the above factors. Statistics Canada • Statistique Canada

8. Considerations and constraints to backcasting • In order to properly backcast data, the NA compiler needs to have an important understanding of the economic history of the country including: • Business cycles • Major economic events • Structural Changes • Changes in government policy • Knowledge of government programs • Demographic trends • Etc... • A lack of understanding in these areas could result in more damage than good. Statistics Canada • Statistique Canada

9. Example – Provincial and Territorial Accounts of Canada Statistics Canada • Statistique Canada

10. Considerations and constraints to backcasting • Revising an integrated set of accounts is an additional challenge in terms of: • Project management • Time constraints • Quality assurance • Scope • For example, in Canada the benchmark estimates for GDP are established when compiling the supply-use tables. When conducting a historical revision it is not realistic to backcast detailed supply-use tables given the source data and time constraints. At the same time there is a desire to preserve the integrated nature of the accounts—it may not always be possible to preserve the same level of integration when backcasting NA data. Statistics Canada • Statistique Canada

11. Backcasting techniques • There are many different ways to backcast NA data. Some possible approaches include: • Linking • Recompilation • Estimation / modelling • Metadata approach • Most likely backcasting will involve a combination of the above techniques—the challenge is to understand when a particular approach is appropriate. Statistics Canada • Statistique Canada

12. Possible techniques – linking • Approach • Linking datasets requires that the new NA dataset and the old NA dataset overlap for at least a single period. • The level associated with the new NA dataset is backcast using the movements of the vintage NA dataset. • Implications • The advantage of this approach is that it is straightforward to implement and does not require any vintage base statistics. • There are major drawbacks to this approach in that it assumes that the impact of the changes in the overlap period are the same for the entire period being backcast. In addition, it could result in changing the amplitude of the business-cycle and the weight of certain series in an aggregate. Statistics Canada • Statistique Canada

13. Possible techniques – linking Statistics Canada • Statistique Canada

14. Possible techniques – recompilation • Approach • This requires re-compiling the entire NA database (or parts of it) from it’s elemental level using source data or proxy information. • Implications • The advantage of this approach is the high quality estimates it produces. • The drawback of this approach is the time and cost, as well as the requirement for detailed source data,which, if available, may not always exist in a consistent time series. Statistics Canada • Statistique Canada

15. Possible techniques – recompilation Statistics Canada • Statistique Canada

16. Possible techniques – estimation/modelling • Approach(es) • Using auxiliary information: for example, using balance sheet data and assumptions about rates of return to estimate income flows • Balancing techniques / residual calculations: for example, calculating net operating surplus of corporations using the expenditure side as the benchmark measure of GDP • Instrumental variable technique: for example, using employment and wage relationships to back-cast industry production or productivity • Triangulation: using two or more of the methods above in order to do quality assurance   • Implication • The advantage of this approach is that it is not data intensive or labour intensive and does not assume the relationship in the link year holds for the backcasted portion of the time series. • The disadvantage of this approach is that this can usually only be done for selected variables. Also, the new estimates do not benefit from being constructed within a framework as it assumes the relationships between the NA variables and instrumental variables hold for the entire time period. Statistics Canada • Statistique Canada

17. Possible techniques – estimation Modelling (example) Statistics Canada • Statistique Canada

18. Possible techniques – metadata approach • Approach • The NSO does not attempt to link the NA databases, but rather provides metadata explaining the differences between the databases. • Implications • The advantages of this approach are its limited use of resources and time • The disadvantage of this approach includes difficulty for users in compiling NA time series and the potential for multiple versions of NA time series. Statistics Canada • Statistique Canada

19. Possible techniques – metadata approach Statistics Canada • Statistique Canada

20. Possible techniques – metadata approach Statistics Canada • Statistique Canada

21. Possible techniques – metadata approach (example) • Changes between CSNA 2008 and CSNA 1993 • Classifications systems • Household Final Consumption Expenditure • North American Product Classification System • North American Industrial Classification System • Asset and Liabilities • Sectors • -Persons and unincorporated businesses, -corporations +household, +NPISH, +financial corporations + non-financial corporations, + Aboriginal general government • Asset boundary • Research and development, weapons systems • Major presentational changes Statistics Canada • Statistique Canada

22. Lessons learned at Statistics Canada • You need to be an economic historian • Information management is important • Saving for later is a bad idea: • It is difficult to “get back to it’ • Fatigue prevents it • Key staff departures • Memory fades... • The classification system of today is not the right classification system for yesterday and will not be the right classification system for tomorrow. • Scale the project to avaliable Communicate, Communicate, Communicate... Statistics Canada • Statistique Canada

23. Lessons learned at Statistics Canada “I made the following chart to illustrate one of the great frustrations that journalists, economists and academics have with StatsCan. One minute, the agency, tasked with measuring the tick tock of the economy and society, tracks seemingly vital data (such as detailed breakdowns of public sector employment and wages by all levels of government, or the total value of government transfer payments to persons by province and type of transfer), the next, *poof*, they’re terminated. Good thing StatsCan still tracks the square footage of fungi production.” By Jason Kirby http://www.macleans.ca/economy/economicanalysis/the-case-of-the-disappearing-statistics-canada-data/ August 13, 2014 Statistics Canada • Statistique Canada

24. Questions for the AEG to consider • Does the NA community need to work together to establish best practices and general approaches to backcasting? • If so what should be included in such a guide? Statistics Canada • Statistique Canada