1. Non consolidated data: the role of inter-NFC loans
Taskforce on consolidated vs. non consolidated data – April 17-18, 2013
Felix Geiger, Deutsche Bundesbank

2. Presentation Outline Background: increasing user needs
Consolidation aspects in the German NFC sector
Compilation of inter-NFC loans and trade credits
Data sources and challenges
New quarterisation and forecasting method of inter-NFC loans: preliminary results
Conclusion and outlook
Felix Geiger
Deutsche Bundesbank

3. Background: increasing user needs
Financing and the role of inter-NFC loans
Substitution of MFI loans an important mitigating factor for financial constraints restricting investment
Inter-NFC loans gained relative importance during the last decade, in particular during the financial crisis
Felix Geiger
Deutsche Bundesbank

4. Background: increasing user needs
Debt definitions and intrasectoral liabilities
Debt according to the MIP Scoreboard is non consolidated
significant differences between consolidated and non consolidated debt
implications for Alert Mechanism Report and In- Depth Reviews
Felix Geiger
Deutsche Bundesbank

5. Consolidation aspects in the German NFC sector
Instruments, sources and frequency of primary data
Instruments
Consolidated
Non-consolidated
Source
Frequency of data sources
F.2 (currency and deposits) P
BSI
B.o.P. / I.I.P.
monthly
monthly/quarterly
F.3 (securities other than shares) O
ESA 2010
SEC
SHS
quarterly
F.4 (loans)
CBSS
other sources
annually
F.5 (shares and other equity)
F.6 (insurance technical reserves
NSI
F.7 (other accounts, trade credits)
Felix Geiger
Deutsche Bundesbank

6. Compilation of inter-NFC loans and trade vredits: data sources
Inter-NCF loans in Germany
Make up a significant part of the difference between consolidated and non consolidated debt
Data sources: main aspects
Companies’ balance sheet statistics
annual information on total inter-NFC loans and trade credits (final coverage 100% with grossing-up method based on turnover)
timeliness of primary data: up to t+14 months (March 2013: data for 2011)
I.I.P.
quarterly information on assets and liabilities of enterprises
delineation of NFC counterparts to derive figures of non-domestic inter-NFC loans and trade credits
timeliness of primary data: up to t+3 months
Necessity for quarterisation and forecasting (up to 7 quarters)
Felix Geiger
Deutsche Bundesbank

7. Compilation of inter-NFC loans: method
Current compilation
Quarterly growth rate ≈ annual growth rate / 4 + random factor
Forecast: extrapolation of dynamics according to last year’s developments
Major disadvantages
Compilation purely based on statistical techniques
No consideration of additional (quarterly) information
Danger of over-/underestimation of (recent) quarterly developments
Main aim of new compilation
Compile reliable data of high quality which reflect the development both during the year and during recent quarters according to economic fundamentals
Increasing user needs
Felix Geiger
Deutsche Bundesbank

8. Compilation of inter-NFC loans and trade credits: method
New compilation method: key elements
Approach: related to factor analysis
Idea: replicate annual primary data using quarterly data
Quarterisation and forecasting at once
Requirements for quarterly data:
always available on time
reliable and of high quality
strong and robust correlation from an economic viewpoint
Main challenges
Preferably long time series ( use of commercial data)
Avoid one-way dependency ( consideration of several variables) !
Research based variable selection
Felix Geiger
Deutsche Bundesbank

9. Compilation of inter-NFC loans and trade credits: method
Basic pattern of new compilation:
Δ Annual inter-NFC loans = X% * Var1 + Y% * Var2 + … + Z% * Var3
Set weights (X, Y, Z) accordingly via grid search routine
in order to maximize correlation
Variables considered:
Flows: RoA (group), Δ RoA, sales, EBITDA, gross operating surplus…
Stocks: short / long term debt, Δ debt, liquid / total assets, trade credits...
Overall:
about 15 variables
years covered:
Felix Geiger
Deutsche Bundesbank

10. Compilation of inter-NFC loans and trade credits: quarterisation
Felix Geiger
Deutsche Bundesbank

11. Compilation of inter-NFC loans and trade credits: forecasting
Felix Geiger
Deutsche Bundesbank

12. Conclusion and outlook
Background
User needs increase  need for data of high quality and reliability
Main issue for inter-NFC loans
Insufficient primary sources require quarterisation and forecasting of inter- NFC loans
Solution: the Bundesbank approach
considers economic developments rather than statistical techniques only
idea: replicate annual primary data using related quarterly data
Outlook
Implementation of new method envisaged for April 2013 ( revisions)
Implementation of consolidation aspects for F3 and F5 with ESA 2010
Felix Geiger
Deutsche Bundesbank

13. Thank you for your attention
Taskforce on consolidated vs. non consolidated data – April 17-18, 2013
Felix Geiger, Deutsche Bundesbank