Cross-Language Replication

Cross-language replication uses AI tools to translate research code between programming languages — enabling researchers to replicate results across different platforms and modernize legacy codebases.

Context & Background

Economics researchers often need to work across multiple languages: legacy code in MATLAB or Stata, new projects in Python or R, and collaborators who prefer different tools. AI excels at code translation because it understands the semantics of operations across languages.

Common translation tasks:

• MATLAB to Python: Modernizing research codebases (NumPy/pandas equivalents)
• Stata to R or Python: Translating econometric workflows
• R to Python: Consolidating across the data science stack
• Any language to documented pseudocode: Creating language-agnostic documentation

Practical Implications

• Translate incrementally: Convert one function or module at a time, testing as you go
• Verify numerical results: Ensure translated code produces identical results (within floating-point tolerance)
• Don't assume 1:1 mapping: Different languages have different idioms; AI should translate concepts, not just syntax
• Use this for replication: Translate published code to verify results in an independent implementation

Related Concepts

• Coding With Llms
• Reproducibility Transparency
• Ai Research Tools