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Min Woo KIM National Income Statistics & Coordination Team National Accounts Office Economic Statistics Department The Bank of Korea OECD Working Party.

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Presentation on theme: "Min Woo KIM National Income Statistics & Coordination Team National Accounts Office Economic Statistics Department The Bank of Korea OECD Working Party."— Presentation transcript:

1 Min Woo KIM National Income Statistics & Coordination Team National Accounts Office Economic Statistics Department The Bank of Korea OECD Working Party on National Accounts 1 ~ 3 December 2010, Paris, France

2 1957 : Compilation of ANA by the Bank of Korea 1968 : Compilation of QNA 1999 : Inflation-targeting monetary policy regime 2000 : Requests on rapid GDP estimate from the policymakers, academic circles, and journals 2001 : Development of one-step ahead forecasting model of GDP growth 2005 : Compilation of Advance estimate(D+28) 2008 : Compilation of Flash estimate(D+5)

3 1st Flash Estimate D+5 days 2nd Advance Estimate D+28 days 3rd Preliminary Estimate D+70 days Preemptive Economic Policy Decision Monetary Policy Committee Ministry of Strategy and Finance

4 Compilation completed within 5 days of the end of the reference quarter Monthly data of first two-month and various daily collected data Judgemental extrapolation based on many streams of official and unofficial source data and models Production/Expenditure approaches and balancing procedure Provided only to Monetary Policy Committee Not disclosed to the public

5 Advance Advance Compilation completed and announced within 28 days of the end of the reference quarter Provisional corporate financial statements Published to the public Preliminary Preliminary Compilation completed and released within 70 days of the end of the reference quarter Final corporate financial statements and various quarterly statistics(Statistics Korea) Published to the public

6 Provided Tables FAP Gross Domestic Product by Kind of Economic Activity and Gross National Income Expenditure on Gross Domestic Product Gross Capital Formation by Sector and Type of Capital Goods Composition of Final Consumption Expenditure of Households by Purpose Composition of Final Consumption Expenditure of Households by Type Gross Saving and Gross Investment

7 Estimates(%) Difference(%p) Percent change from previous quarter Percent change over previous year Percent change from previous quarter Percent change over previous year FAP FAP A-FP-AP-F A-FP-AP-F 2008 1q0.7 0.85.7 5.80.00.1 0.00.1 2q0.90.8 4.94.8 -0.10.0-0.1 0.0-0.1 3q0.6 0.53.9 3.80.0-0.1 0.0-0.1 4q-5.5-5.6--3.3-3.4--0.1-- -- 2009 1q0.20.1 -4.2-4.3-4.2 -0.10.0-0.1 -0.10.10.0 2q2.3 2.6-2.5 -2.20.00.3 0.00.3 3q2.82.93.20.50.60.90.10.30.40.10.30.4 4q0.2 - 6.0 - 0.0-- 0.0-- 2010 1q1.8 2.17.8 8.10.00.3 0.00.3 2q1.41.51.4 7.2 0.1-0.10.0 0.0 Revisions Revisions: incorporation of more complete or better source data

8 Statistics vs. Forecasts Statistics vs. Forecasts Flash and Advance estimate are just forecasts, not statistics. They are statistics: They still depend on the source data and a reasonable inference of the current economic situation based on various quantitative and qualitative information. Accuracy vs. Rapidity Accuracy vs. Rapidity The Flash or Advance estimate is premised on the sacrifice of statistical accuracy. Rapidity is more important: A rapid but a slightly inaccurate estimate is much better than the acc urate statistics after a long time lag in a new era. Transparency vs. Policy priority Transparency vs. Policy priority It is problematic that why is the Flash estimate provided only to monetary policy committee Policy priority should be emphasized: Its public release should be put off until its statistical stabil ity is clearly proven. It is desirable for the public good to provide it to policymaker. Extra burden vs. User friendly Extra burden vs. User friendly The compilation of the Flash or Advance estimate is certainly an additional burden to compilers, which might cause a lack of precision in statistics. Users are the reason why we are: User satisfaction is also one of the elements in evaluating the qu ality of statistics.

9 Increasing importance of more up to date macroeconomic statistics (especially in inflation- targeting monetary policy regime) One-step ahead policy considerations Reducing the time lag between turning point in the business cycle and policy measures Making strong meat counter-cyclical policy near reference date digestible Improvement in the effectiveness of preemptive economic policy measures and confidence in them

10 Less model Less judgement More source data Statistical infrastructure and capacity still be primary priority Development of monthly GDP


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