1. Maurine A Haver Haver Analytics Hong Kong 30 August 2013
The Challenge of Supplying Comparable International Statistics to Professional Users
Maurine A Haver
Haver Analytics
Hong Kong
30 August 2013

2. High Quality & Timely Data for Global Strategy & Research
Haver Analytics
High Quality & Timely Data for Global Strategy & Research
Financial Institutions & Money Managers
Central Banks & Other Government Entities
Corporates
Consulting & Nonprofit Research

3. What do users need?
Comparability
Timeliness
History
Transparency

4. Data Comparability Data Users… Often do not investigate differences
Ignore differences even when informed
Risk flawed analyses that can lead to bad decisions

5. Data Comparability International Standardization
National Accounts (SNA 2008)
Balance of Payments (BPM6)
Monetary & Financial
Central Bank Surveys on lending
Private Surveys (PMI)

6. Not necessary to give up tables presented in familiar formats
US National Accounts now presented in an “ international style” as well
Bank of Italy presents balance sheets according to their original format and the format adopted by the Eurosystem

7. Standardization can create problems
History has been lost with the moves to SNA 2008 and BPM6
Standard needs to be fully adopted
Transition period

8. Big Problems/Frustrations
Industry classification systems
NACE, NAICS, etc.
Public sector financial statistics
Central, General, ?
Cash or Accrual
Debt statistics very country specific

9. Other problematic areas
Where are the inventories?
Profits?
House Prices
Repeat-valuation approach rarely used
Treatment of housing in the CPI

10. HICP Comparison v2 US Euro Area Harmonized Index of Consumer Prices
% Change - Year to Year NSA, 2005=100
Year over Year % Change -
HICP Comparison v2.EMF (EUDATA) P025H / USH

11. US CPI vs US HICP HICP CPI-U US CPI VS HICP - Year over Year % Change
US CPI vs US HICP.EMF (CPIDATA) UIN / USH

12. Final Thoughts
Standardization of our statistics can help us understand the true country differences
Transparency is important for users who need to make adjustments to the data
History is necessary for most models. The best organization to estimate that history when a methodological change causes a break is the one that produces the data in the first place.

13. Thank you!
Users greatly appreciate those data suppliers who provide easily accessible and free data via their web sites.