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An identification and testing strategy for proxy-SVARs with weak proxies

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  • Giovanni Angelini
  • Giuseppe Cavaliere
  • Luca Fanelli

Abstract

When proxies (external instruments) used to identify target structural shocks are weak, inference in proxy-SVARs (SVAR-IVs) is nonstandard and the construction of asymptotically valid confidence sets for the impulse responses of interest requires weak-instrument robust methods. In the presence of multiple target shocks, test inversion techniques require extra restrictions on the proxy-SVAR parameters other those implied by the proxies that may be difficult to interpret and test. We show that frequentist asymptotic inference in these situations can be conducted through Minimum Distance estimation and standard asymptotic methods if the proxy-SVAR can be identified by using `strong' instruments for the non-target shocks; i.e. the shocks which are not of primary interest in the analysis. The suggested identification strategy hinges on a novel pre-test for the null of instrument relevance based on bootstrap resampling which is not subject to pre-testing issues, in the sense that the validity of post-test asymptotic inferences is not affected by the outcomes of the test. The test is robust to conditionally heteroskedasticity and/or zero-censored proxies, is computationally straightforward and applicable regardless of the number of shocks being instrumented. Some illustrative examples show the empirical usefulness of the suggested identification and testing strategy.

Suggested Citation

  • Giovanni Angelini & Giuseppe Cavaliere & Luca Fanelli, 2022. "An identification and testing strategy for proxy-SVARs with weak proxies," Papers 2210.04523, arXiv.org, revised Oct 2023.
  • Handle: RePEc:arx:papers:2210.04523
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    Cited by:

    1. Giovanni Angelini & Luca Fanelli & Luca Neri, 2024. "Invalid proxies and volatility changes," Papers 2403.08753, arXiv.org.
    2. Bertille Antoine & Otilia Boldea & Niccolo Zaccaria, 2024. "Efficient two-sample instrumental variable estimators with change points and near-weak identification," Papers 2406.17056, arXiv.org.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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