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A Python Package to Assist Macroframework Forecasting : Concepts and Examples / Sakai Ando, Shuvam Das, Sultan Orazbayev.
- Format:
- Book
- Government document
- Author/Creator:
- Ando, Sakai.
- Series:
- IMF Working Papers; Working Paper ; No. 2025/172
- IMF Working Papers
- Language:
- English
- Physical Description:
- 1 online resource (20 pages)
- Place of Publication:
- Washington, D.C. : International Monetary Fund, 2025.
- Summary:
- In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining smoothness are important but challenging. Ando (2024) proposes a systematic approach, but a user-friendly package to implement it has not been developed. This paper addresses this gap by introducing a Python package, macroframe-forecast, that allows users to generate forecasts that are both smooth over time and consistent with user-specified constraints. We demonstrate the package’s functionality with two examples about forecasting US GDP and fiscal variables.
- Notes:
- Description based on print version record.
- ISBN:
- 979-82-290-2356-6
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