1. Economic Monitoring in an Uncertain Global Environment Processes and Tools from the World Bank Soong Sup Lee Hans Timmer Gauresh Rajadhyaksha The World Bank Group Washington, DC Presentation at the International Seminar on Early Warning and Business Cycle Indicators, Scheveningen, The Netherlands

2. Monitoring and High Frequency data Who we are – Team of macro-economists – Provide “data-driven, forward looking analyses” Produce Bank global forecasts Provide planning, investment, and policy-advice to Senior and Executive Management – Monitor real and financial indicators Trade, financial flows, commodity prices, remittances flows – Maintain Datasystems for high-frequency data Service internal and external clients with a daily-updating high frequency data-set

3. Outline of the presentation Examples from some of our analytical work during the onset of the financial crisis Details of our data infrastructure Conclusions and “lessons for the future”

4. 1. “Revealed Vulnerability Index” Identifying risk during the financial crisis Index Exchange Rate Depreciation (Daily) Change in Equity Mkts (Daily) Change in Spreads (Daily) Change in Current Account Balances, %GDP (Quarterly) Change in Capital Flows, %GDP (Monthly)

5. 2. “Credit Risk Monitoring” Inputs to briefing for the Bank’s Risk Committee Monthly briefing to Sr. Management on the Credit Risks of client countries We provide “global overview” that supplements the “country details” We “aggregate” country data to provide a broader implication of the existing climate

6. Source: Thomson/Datastream, DECPG. “Credit Risk Monitoring” Example of input provided in Dec ‘ 08 All Developing East Asia Latin America Europe and Central Asia IP now in decline across all regions industrial production, ch% (3m/3m saar)

7. 3. Industrial Production Forecasting” 3 month IP index forecast Forecast created using OECD leading indicators and ARIMA models Example of input provided in Dec ‘ 08 Forecast

8. Supporting our diverse data needs “ World Bank’s High Frequency Data system“ Sourcing DataStream/Thomson Reuters, Bloomberg World Bank, UN, IMF, OECD databases Country Statistical Office websites “Value Added” Organize and classify Process: gap-fill, extend, seasonally adjust, rebase Dissemination Share on internal and external websites (“Global Economic Monitor” http://www.worldbank.org/gem) Create web-portals, integrate with our “forecasting tools” and produce Excel files for download

9. Data Coverage “World Bank’s High Frequency Data system“ Exchange Rates (145 countries, Daily) Spreads (44 countries, Daily) Policy rates (55 countries, Daily) Stock Market Indices (70 countries, Daily) Bond Indices (20 countries, Daily) Trade: Imports, Exports (160 countries Monthly) Industrial Production (85 countries, Monthly) Commodity Prices (40 Daily, 87 Monthly) Effective Exchange Rates (140 countries, Monthly)

10. Regional Aggregation “World Bank’s High Frequency Data system“ “Aggregation” of country data to provide global picture is core to our analysis We create regional estimates based on weight of reporting countries for that time period (> 2/3 rd reporters) New data releases change estimates but weighting criteria prevent rapid changes on a day-to-day basis

11. Visualization and Dissemination “World Bank’s High Frequency Data system“ Data feeds to numerous websites, web-portals and publications – World Bank’s Global Economic Monitor website http://www.worldbank.org/gem – World Bank’s Prospects for Global Economy website http://www.worldbank.org/prospects – iSimulate @ World Bank (forecast system) http://isimulate.worldbank.org – Internal World Bank data portal Will soon be available “programmatically” (using an API ) within the Bank

12. Interactive Data Portal “World Bank’s High Frequency Data system“ Interactive Charts to compare “Aggregate” with “country” data Heat Maps to visualize global trends

13. Conclusions We rely heavily on high frequency data (and estimates) for our analyses We have learnt that “aggregating” high-frequency data provides a unique flavor to any economic analyses Modern-day graphing and visualization tools make it very easy to compare country data with larger groups and aid in information dissemination And yes, our appetite for high frequency data is only increasing!

14. Some Road-blocks … Our biggest challenge to-date has been in “harmonizing” diverse reporting practices across the world – Same indicator is often reported with different assumptions across countries – Any harmonization efforts would be very much welcomed by us! We source our data from commercial providers and there is a limit to our “sharing” of this data with our external customers

15. Lessons Learnt Keys to Success At the onset of the financial crisis, our analysts could respond in large part due to our robust Datasystems that update information on a Daily basis – Includes retrieving data, processing and harmonizing, and creating aggregates High Frequency data is seen to be playing an increasingly important role in various economic modeling exercises Successful dissemination must cater to the needs of both the novice and advanced users – For eg: we provide data in Excel format to our novice user and will soon provide programmatic access (via an API) to our advanced users