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Does Norm Selection Matter in Iterative SUR Estimation?
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AI
DOI：10.24818/18423264/60.1.26.11.png)
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Abstract
En 中文
This study explores how two alternative norms perform within the Iterative Seemingly Unrelated Regression (ISUR) framework, focusing on their efficiency and accuracy across diverse scenarios-such as varying time spans and country samples. By putting these norms to the test, the research offers hands-on guidance for researchers and practitioners seeking the most effective balance between computational speed and statistical precision. The Euclidean findings reveal which norm delivers the best trade-off, serving as a practical roadmap for optimising ISUR models in real-world applications. Ultimately, this comparison not only sharpens methodological decision-making but also enhances the reliability and efficiency of empirical workflows in econometric analysis.
Keywords:
statistical modelling
ISUR framework
comparative performance
computational optimisation
accuracy
precision
Journal
E
IF:
1
Papers:
18
Citations:
617