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This guide outlines the rigorous standards for establishing causal claims in development economics and social sciences. It covers robust quantitative methods (like DID, IV, RDD, RCT) and structured qualitative/mixed-methods approaches. The core principle is that the logical route from evidence to claim must be explicitly defensible and matched to the strength of the assertion, avoiding over-claiming.

Polars is a lightning-fast DataFrame library designed for efficient, memory-efficient data processing in Python and Rust. Built upon Apache Arrow, it supports lazy evaluation and parallel execution, making it ideal for ETL pipelines, large-scale data transformations, and scenarios where standard Pandas performance is insufficient. It excels at handling datasets up to 100GB that fit within available RAM.