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“Statistics used by the BIS in monitoring and research of the economic and financial crises”

“International Seminar on Timeliness, Methodology and Comparability of Rapid Estimates of Economic Trends” Ottawa, Canada, 27 - 29 May 2009. “Statistics used by the BIS in monitoring and research of the economic and financial crises” Gert Schnabel. 1. BIS as a data user. Natural BIS focus

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“Statistics used by the BIS in monitoring and research of the economic and financial crises”

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  1. “International Seminar on Timeliness, Methodology and Comparability of Rapid Estimates of Economic Trends” Ottawa, Canada, 27 - 29 May 2009 “Statistics used by the BIS in monitoring and research of the economic and financial crises” Gert Schnabel 1

  2. BIS as a data user • Natural BIS focus • aggregated respectively cross-country work • central bank focus (ie focus on monetary and financial stability) • BIS is also a compiler of statistics (international banking, derivatives and security statistics)

  3. Within the Monetary and Economic Department of the BIS, the financial market crises has triggered an adjustment in business direction. The aim is to get a better understanding of the dynamics and the implications of the crisis and the economic slowdown by implementing the following: • Monitoring financial and macroeconomic indicators • Focussing the research on new or revised research fields 3

  4. Monitoring • Financial markets • Standard daily financial market indicators • Central bank balance sheets • Credit market developments • Bank rescue packages • Banks’ performance • Financial market news • Macroeconomic indicators • Standard monthly and quarterly indicators • Surveys • Forecasts

  5. Example for daily monitoring of financial markets

  6. Example for monitoring central bank balance sheets

  7. Example for monitoring macro situations

  8. ResearchGiven the severity of the current financial crisis and the synchronised economic downturn, historical models and data will prove to be a poor reference for the future as future business cycles will certainly be different. The MED has thus partly refocused its research strategy on banking sector related projects and on the economic impact of the crisis.

  9. Example for research (i)“The market reaction to bank rescue packages” • Event study on the announcement of bank rescue packages • Focus on impact on creditors versus impact on shareholders • Data looked at: share prices, CDS spreads, government rescue data; micro data

  10. Rescue database; example for BIS data collection

  11. Example for research (ii) • Some further projects • Banks’ early warning indicators • Banking crisis now and in perspective (eg comparison with Nordic crisis) • Sudden stops and monetary policy in Asia • Needed data • Macroeconomic aggregates • Domestic credit data • Banks’ balance sheets • Asset prices • BIS international banking statistics

  12. Data sources • Central banks • National statistical offices • International organisations (IMF, OECD, Eurostat, World Bank, United Nations) • Thomson Reuters • Bloomberg • Moody’s • Bureau van Dijk Bankscope • Markit • BIS International Financial Statistics

  13. An example of timeliness at the expense of quality • BIS real effective exchange rates (REER) • Timeliness: to what extent is the extrapolation of previous months’ y-o-y changes of CPI still acceptable to gain timeliness?

  14. Selection of BIS activities in international groups and coordination to discuss statistical data issues • Regular exchange with central banks at various levels: meeting of experts (International Financial Statistics, BIS Data bank, Special Task Forces) • Participation at international groups with formal membership (eg Inter-agency Task Force on Finance Statistics, Working Group on Securities databases, SDMX) • Irving Fisher Committee (IFC)

  15. Selection of projects/ initiatives underway in which the BIS is involved: • Review of OTC derivative statistics • Publication of a handbook on securities statistics (IMF, ECB, BIS) • Joint work with the IMF as a follow-up to FSB/G20 recommendations on identifying and addressing possible data gaps

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