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External trade statistics

External trade statistics. Reconciliation of External Trade Statistics. Eurostat. External trade statistics. Introduction to the project …. Producing a general reconciliation methodology Developing an application for the reconciliation of external trade data

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External trade statistics

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  1. External trade statistics Reconciliation of External Trade Statistics Eurostat

  2. External trade statistics Introduction to the project …. • Producing a general reconciliation methodology • Developing an application for the reconciliation of external trade data • Testing the application with real trade data between EU-Canada and EU-USA

  3. From discrepancies to reconciliation …. • Imports (exports) reported by partner A is significantly different from mirror-exports (imports) reported by its trading partner B. imports exports A B

  4. From discrepancies to reconciliation …. • The situation is examined at detailed level, and possible reasons for discrepancies are identified. imports Cif-Fob time lag misclassification methodology triangular trade ... exports ? A B

  5. From discrepancies to reconciliation …. • Adjustment procedures are applied to the compared flows. imports Cif-Fob time lag misclassification methodology triangular trade ... exports A B

  6. Main objectives of the project • Solution: to develop a common and general methodology with a unique computerised application. • Main problem: for each reconciliation exercise, a specific and different method (and tool) was used. • How: based on exercises in the past, to elaborate a handbook of reconciliation methodology, and its computer application.

  7. Main objectives of the project Production of a general reconciliation methodology and computerised application. Expected results: • An economy of scale avoiding the development of methodologies and specific instruments for each reconciliation project. • Increasing expertise in the field of reconciliation around the same working tool. • Link with Edicom II (Action 2 – Quality): to improve the quality of trade statistics by reducing asymmetries.

  8. Main objectives of the project • The tool will be tested by reconciling trade statistics between the EU and Canada and the USA. Next steps: • The common methodology and the new tool for reconciling external trade data might be set-up in the framework of the European Commission’s statistical cooperation projects.

  9. Input data files PC2_PC1_M_2001 PC2_PC1_X_2001 PC1_PC2_M_2001 PC1_PC2_X_2001 Parameter files Parameter files MIRROR REPORT RECONCILIATION REPORT The EU Reconciliation application (ERA) HARMONISATION TOOL Adds and harmonises input data, and aggregates data into 4 harmonised files MIRRORTOOL Creates and displays the mirror report Export of harmonised input data RECONCILIATION TOOL Selection of adjustment modules Creates the reconciliation report Reporting on remaining discrepancies Export of reconciled data

  10. ERA’s modular structure • To be applicable in all cases: the application will be on a modular basis. For a given case, only those relevant and needing reconciliation adjustments will be applied. D C B  cif-fob     Reconciliation of country “A” with partner : time lag  misclassification   methodology  triangular trade

  11. ERA’s flexible structure - 1 • To be easily maintained: a given module can be improved or completed without a need for re-writing the application. D C B  cif-fob cif-fob (updated)     Reconciliation of country “A” with partner : time lag  misclassification   methodology  triangular trade

  12. ERA’s flexible structure - 2 • To develop: a new module can be added without a need for re-writing the application. E D C B   cif-fob (updated)     Reconciliation of country “A” with partner : time lag   misclassification   methodology  triangular trade  exchange rate

  13. Parameters, conversion factors Adjustment values  Adjustment Module ##   Data: Imports – Exports (after Adjustment) Data: Imports – Exports (before Adjustment)             ERA: How adjustment modules operate or

  14. M PC1 X PC2 Discrepancies (X-M) Discrepancies(X-M) / M Discrepancies (X-M) / [(X + M) / 2] HS Published data Published data Discrepanciesin value Discrepancies in % Discrepancies in % 01 … … … … … 02 … … … … … … … … … … … 97 … … … … … 99 … … … … … ERA – Mirror report, at HS2 level

  15. M EU Adjustments M EU Discrepancies (X-M) X P1 Adjustments X P1 HS Published data M1-b M1-c Adjusted data Before ajust. After ajust. Adjusted data M2-c M2-b M1-a Published data 01 02 03 … … 97 99 ERA – Reconciliation report, at HS2 level

  16. Figure 4 Adjusted data Discrepancy indicators Graphic visualisation of the divergences Positions HS where: M (EU ) X (P1) (X-M) (X-M)/ M Low Medium High X P1 = 0 and M EU > 0 ..... ..... ..... X P1 > 0 and M EU = 0 ..... ..... X P1 ≈ M EU (± at 5%) ..... ..... X P1 ≠ M EU ..... ..... ..... ..... ERA – Presentation of Remaining discrepancies

  17. Further information Monica Cerutti - Romesh Paul European Commission, Eurostat Unit C0 - External Trade BECH building, Room A2/011 5, rue Alphonse Weicker, L-2721 Luxembourg Phone: +352 4301 32814 Fax: +352 4301 34339

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