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Subsequent estimates of GDP growth

Using results from revisions analysis to improve compilation methods: a case study on revisions of Dutch estimates of GDP volume growth. Contribution to the joint OECD/Eurostat Task Force on “Performing Revisions Analysis for Sub-Annual Economic Statistics” Leendert Hoven Statistics Netherlands.

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Subsequent estimates of GDP growth

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  1. Using results from revisions analysis to improve compilation methods: a case study on revisions of Dutch estimates of GDP volume growth Contribution to the joint OECD/Eurostat Task Force on “Performing Revisions Analysis for Sub-Annual Economic Statistics” Leendert Hoven Statistics Netherlands

  2. Subsequent estimates of GDP growth • Quarterly Accounts, flash after 45 days • Quarterly Accounts, regular after 90 days • Yearly estimate, based on QA April t+1 • National Accounts, provisional July t+1 • National Accounts, revised provisional July t+2 • National Accounts, final July t+3

  3. Summary statistics

  4. Graph 3. Mean revision and mean absolute revision between consecutive estimates of GDP volume growth, 1990 – 2003

  5. Average contribution of components to revision of GDP growth between QA regular and NA final, 1990-1998

  6. Average contribution of components to revision of GDP growth between QA regular and NA final, 1990-1998

  7. Two important findings • biggest mean revision between revised provisional estimate and final estimate. Quite large differences between short-term statistics and structural business statistics. Methodological shortcomings (matched pairs approach sts insufficiently allows for effects of population dynamics). • within production approach, commercial services and trade have contributed most to the revisions of GDP growth; short-term source situation particularly bad.

  8. How can we improve early estimates? • improve methodology short-term statistics • improve short-term source situation for commercial services and trade • more research needed on: • validity different assumptions; • effects of balancing process; • ……………….. • ........................

  9. Bias correction at the aggregate level? • no guarantee that average bias of past period will also hold in the future • ignores the underlying data and subaggregates • impact of introduction mew methodologies, changes in data collection, sampling or data processing difficult to capture in the short term

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