Algorithm-Driven SVARs: Navigating the Wilderness of Big Data

Yucheng Yang and Tao Zha
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Yucheng Yang: University of Zurich; Swiss Finance Institute

No 26-57, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Every SVAR result is conditional on two choices: the restrictions that identify the shock and the variables on which they operate. The literature disciplines the first; the second is chosen by hand. We develop a Bayesian methodology that constructs information sets, uses an out-of-sample criterion, and retains the largest system it admits. Under recursive identification, output rises with housing production rather than household credit alone. For monetary policy, an anchor-free joint Bayesian proxy SVAR with multiple instruments strengthens the credit spread channel. A core system augmented with the selected corporate spread identifies expected default risk as a potent transmission margin.

Keywords: Information set; model construction; out-of-sample selection; external instruments; household credit; housing production; expected default risk; monetary policy transmission (search for similar items in EconPapers)
JEL-codes: C32 C53 C55 E00 E44 E52 (search for similar items in EconPapers)
Pages: 92 pages
Date: 2026-08
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Related works:
Working Paper: Algorithm-Driven SVARs: Navigating the Wilderness of Big Data (2026)
Working Paper: Algorithm-Driven SVARs: Navigating the Wilderness of Big Data (2026)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2657

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