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Macroeconomic Statistics

Business Survey Questionnaire Design for National Accounting


Session No.: SA 19.58

Location: New Delhi, India

Date: August 5-9, 2019 (1 week)

Primary Language: English

    Target Audience

    The workshop is intended for government officials who would benefit from the knowledge of the concepts, principles, and methods used design to business surveys which are subsequently used to compile national accounts statistics.
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    Participants are expected to possess a degree in accounting, the social sciences, or a related field, and have proficiency in Microsoft EXCEL and WORD.
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    Course Description

    This one-week course will be presented by experts from the International Monetary Fund's Statistics Department. The course will cover the following topics: national accounts concepts, methods, and framework; estimating Gross Domestic Product using the production approach; best practices on survey design; designing business surveys to enable national accounts compilation; sampling strategies; best practices on edit and imputation; examining specific business surveys and offering suggestions on improvements. The course will feature interactive lectures and hands-on exercises that enable participants to operationalize what they learn. The main lectures and workshops include: 1. Production accounts: measurement of output; intermediate consumption, and value added (gross domestic product (GDP)).2. Survey design and development.3. Business questionnaire design to facilitate estimation of the production accounts and value added.3. Sampling. 4. Edit and Imputation. 5. Case studies of questionnaire design for selected India business surveys.
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    Course Objectives

    At the end of the course participants should understand the data needs of national accounts compilers. As well, they should be able to describe optimal business questionnaire design that supports the needs of national accounting. Participants will also gain knowledge on the basics of survey design, and best practices of sampling and edit and imputation
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