Unit value indices and Import/Export price surveys : Pros and Cons of collection methods

1. Unit value indices and Import/Export price surveys : Pros and Cons of collection methods • 1. Sources of information • 2. Unit value vs specific price indices • 3. Comparison of indices in the EU • 4. Way forward

2. 1. Data sources • Customs data  Unit Value Indices (UVI) • Enterprise-based price surveys - Survey of transactions  Specific price Indices (SPI) • Partner countries (e.g. USA & Canada) • Special sources for specific products : electricity, water, petroleum, gas … • Proxies: PPI, CPI…

3. 2. Unit values vs. specific prices2.1. Problems with unit values • Heterogeneity of items at the lowest level of the product classification • Misreporting of values (e.g., transfer pricing). • Misreporting of quantities. • Inadequate measures of quantities. • Consignments with mixed products. • Unrecorded transactions (low value transactions, e-commerce …) • [Within the EU: absence of intra-EU customs data]

4. 2. Unit values vs. specific prices2.1. Problems with unit values : lack of harmonisation between countries

5. 2.2. Problems with price surveys • Coverage and representativeness • Products • Traders • Size of sample (traders, items) and sampling errors • Need to adjust for quality change, new products; etc. • Cost

6. 2.3. Summary of Pros and Cons of UVIs and SPIs

7. 3. Comparison UVI/SPI on EU data3.1. The study • Datasets: Monthly data on Imports from 4 EU Member States; SPIs; UVIs; CPA 3 digits (close to CPC) • Methodology: SPIs as reference • Measures: distance, discrepancy, association / correlation, variability / instability

17. Normalised average standard deviation of monthly, quarterly, annual and pluriannual UVI / SPI discrepancies by product

18. Normalised average standard deviation of monthly, quarterly, annual and pluriannual UVI / SPI discrepancies by product

19. 3.2. Results (1) • Stability • SPIs more stable than UVIs • Monthly UVIs often very unstable • Long-term vs. short-term • More discrepancies on the short-term than on the long-term • Little relationship between ST and LT discrepancies

20. 3.2. Results (cont’d) • Aggregation level • less discrepancies at aggregated levels • no SPI data at very disaggregated level • low-discrepancy product groups differ among MS • Technological levels – for high tech products • more short-term discrepancies • long-term systematic upward bias of UVIs

21. 3.3 Methodological issues • Data limitations: • geographical coverage • time coverage • disaggregation • Eurostat vs. national UVI data: • sensitivity to methodology (detail, outliers) • Quality of SPI data: • erratic movements / stability • synchronisation among EU MS

22. 4. The way forward (1) • a. More detailed specification for UVI ? • Narrower specification • Country of origin or destination • Point of export / import • Size of shipment • Individual trader • Experience with consumer goods: bar-code scanner data

23. 4. The way forward (cont’d) • b. Different formulas? • c. Improving data editing? • Lack of benchmark • The risk of discarding all large price changes, even real ones… • d. Hybrid solutions?

24. Thank you