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A Python Package to Assist Macroframework Forecasting: Concepts and Examples

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  • Mr. Sakai Ando
  • Shuvam Das
  • Sultan Orazbayev

Abstract

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.

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  • Mr. Sakai Ando & Shuvam Das & Sultan Orazbayev, 2025. "A Python Package to Assist Macroframework Forecasting: Concepts and Examples," IMF Working Papers 2025/172, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2025/172
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