Processes and Policy for Revising Monthly Production Statistics (GDP) at Statistics Canada Prepared by: Michel Girard & Erika Young Presented by: Michel Girard, Statistics Canada OECD Short-Term Economic Statistics Working Party 25 – 27 June 2007 Paris, France

Overview  Revision policies  Source data and monthly GDP  Integrated revision process  Frequency  Reasons  Computer system  Clients

Revision policies Source data  Raw and seasonally adjusted data are normally revised over a 3-month period  Respondent errors/availability of data  Annual revision process for monthly data  Coding on central registry  Processing  Accumulation of micro data corrections  Data corrections in other programs (exports/imports, prices, administrative data)  Annual surveys: previous year is normally subject to revision  Discrepancy between monthly and annual estimates becoming a concern  Historical process for monthly data  X12, NAICS, Profiling

Revision policies Source data Issues  Carrying back seasonal adjustments further back in time  Micro vs macro adjustments  Reconciling/benchmarking monthly to annual results  Will require modifying processes and systems  Calendarization  Aligning source data and SNA revision policies

Revision policies Source data  Project on revision policy  Description of policies by surveys  Looking at revision policies in other NSO  Extent to which policies fits the needs of clients including SNA  Recommendations  Notably reconciliation and benchmarking issues

Revisions to Monthly GDP  According to frequency  Monthly, quarterly, annual, historical  Classification of revisions  Source data  Seasonality (including trading-day factors)  Reconciliation  Changes to methodologies  Benchmarking including rebasing  Classifications  SNA conceptual revisions

Process of revision Monthly Jan to Dec Quarterly Feb, May, Aug, Nov AnnualSeptemberHistorical 10 years In August, revision back to January of previous year In September, revisions are carried back 5 years Tend to go back to 1961 Source data Seasonal Reconciling with quarterly GDP Incorporating quarterly source data Weights-pricesTrading-dayMethodologiesRebasingBenchmarking Central frame SNA 1993 Classifications

Computer System  Menu driven, accessible by many users  Charts/Reports  Methodologies compiled for specific period of time  Database can be decomposed into 4 categories:  Current version  Revised version  Published version  Test/historical version  Feeder system vs published results  Avoiding building seasonality

Revisions and dissemination  Qualitative information  Source data  Explained in the context of IO and IE Accounts  Methodology  Quantitative information  Always: growth rates and levels  Sometime: mean and standard deviations  Occasionally: bias, dispersion, concordance of movements

Clients Survey in 2004 Survey in 2004  Satisfaction vis-à-vis aggregates – 77%  Concern about detail – 33%  +/- 0.2%: good trade-off on average for aggregates  Accuracy more important than timeliness – Data released 60 days after reference month  Appreciate qualitative information, especially when special events take place  Demand to incorporate revisions sooner than later – for modelling and forecasting purposes  Necessity to revise back when story do not change being questioned