Revenue Forecasting and Analysis
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- Revenue Forecasting and Analysis
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Bibliographic details
- Session: OL 23.235
- Location: Course conducted online
- Dates: September 1, 2023 - April 15, 2024 (32 weeks)
- Delivery method: Online Training
- Primary language: Spanish
- Status: Deadline passed
Training program overview
- Session No.: OL 23.235
- Location: Course conducted online
- Date: September 1, 2023 - April 15, 2024 (32 weeks)
- Delivery Method: Online Training
- Primary Language: Spanish
- Presented by: Fiscal Affairs Department, International Monetary Fund
Target audience and qualifications
- Target audience:
- Government officials working in ministries of finance or in revenue administrations who are charged with conducting revenue forecasts and/or assessing the revenue or distributional impact of tax policy changes.
- Qualifications:
- Basic to intermediate understanding of tax policy.
- Expected to have a degree in economics or tax accountancy (ideally with some background in econometrics).
- Proficiency in Microsoft Excel.
- Access to a computer with a reliable Internet connection and a Google Chrome web browser is essential.
Course description
- Focus:
- Technical and institutional aspects of revenue forecasting and tax policy analysis.
- Overview of quantitative methods required to forecast and evaluate revenue implications of changes in major taxes.
- Taxes covered:
- Personal income taxes
- Corporate income taxes
- Value added taxes
- Excise taxes
- International trade taxes
- Emphasis:
- Necessity of establishing a strong institutional framework to support the revenue forecasting process.
- Approach:
- Builds on both conceptual and practical approaches.
- Employs hands-on activities, including quizzes and quantitative exercises with real fiscal data.
Learning objectives
Upon completion of the course, participants should be able to:
- Describe the role of revenue forecasting in the budget-making process.
- Identify good practices relating to the institutional framework that supports the revenue forecasting process.
- Identify data requirements for each method of revenue forecasting.
- Apply macro-based models to forecast tax revenue.
- Apply input-output models and micro-simulation techniques to analyze the revenue and distributional implications from indirect and direct taxes.
- Recognize the strengths and limitations of different models.