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Macroeconomic Statistics

Virtual : Balance Sheet Approach (BSA)

Deadline passed

Session No.: CT 22.22V

Location: Beijing, China

Date: November 7-11, 2022 (1 week)

Delivery Method: Virtual Training

Primary Language: English

Interpretation Language: Chinese

    Target Audience

    Officials at central banks, ministries of finance and other agencies in charge of compiling monetary and financial statistics, government finance/debt statistics, and external sector statistics; and/or overseeing macro-financial analysis.
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    Qualifications

    Participants are expected to have a degree in economics or statistics, or equivalent experience.
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    Course Description

    This course, conducted by the IMF Statistics Department, presents a user-friendly tool developed by the department to automatically combine monetary, government, and balance of payment data reported to the Statistics Department to create a distribution of claims and liabilities on a from-whom-to-whom basis—an extremely useful tool for macro-financial analysis. Once the matrix is generated, country officials should be able to use the Balance Sheet Approach (BSA) analysis to focus on overall balance sheet linkages and identify specific exposures and vulnerabilities, such as excessive reliance on external funding, leverage buildup in the corporate sector, and overreliance on the banking sector for sovereign debt placement. This course is an abbreviated version of the longer, BSA course traditionally offered by STA in-person.
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    Course Objectives

    Upon completion of this course, participants should be able to:  Use the BSA matrix information for the identification of balance sheet imbalances, exposures, and risks to shocks such as sudden capital outflows or sharp exchange rate depreciation.   Summarize the source data used for preparing the BSA matrix and identify critical data gaps for their respective countries.  Prepare work plans for addressing these data gaps over the medium-term, in order to provide national policy makers with an analytically useful BSA matrix.
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