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Robust inference in models identified via heteroskedasticity

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Abstract
Identification via heteroskedasticity exploits differences in variances across regimes to identify parameters in simultaneous equations. I study weak identification in such models, which arises when variances change very little or the variances of multiple shocks change close to proportionally. I show that this causes standard inference to become unreliable, outline two tests to detect weak identification, and establish conditions for the validity of nonconservative methods for robust inference on an empirically relevant subset of the parameter vector. I apply these tools to monetary policy shocks, identified using heteroskedasticity in high frequency data. I detect weak identification in daily data, causing standard inference methods to be invalid. However, using intraday data instead allows the shocks to be strongly identified.

Suggested Citation

  • Daniel J. Lewis, 2018. "Robust inference in models identified via heteroskedasticity," Staff Reports 876, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:876
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    Cited by:

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    2. Ruben Hipp, 2020. "On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity," Staff Working Papers 20-42, Bank of Canada.
    3. Jarociński, Marek, 2024. "Estimating the Fed’s unconventional policy shocks," Journal of Monetary Economics, Elsevier, vol. 144(C).
    4. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2024. "Blended identification in structural VARs," Journal of Monetary Economics, Elsevier, vol. 146(C).
    5. Marc Burri & Daniel Kaufmann, 2024. "Multi-dimensional monetary policy shocks based on heteroscedasticity," IRENE Working Papers 24-03, IRENE Institute of Economic Research.
    6. Yang, Yang & Tang, Yanling & Cheng, Kai, 2023. "Spillback effects of US unconventional monetary policy," Finance Research Letters, Elsevier, vol. 53(C).
    7. Emiliano A. Carlevaro & Leandro M. Magnusson, 2020. "The (in)stability of stock returns and monetary policy interdependence in the US," Economics Discussion / Working Papers 20-27, The University of Western Australia, Department of Economics.

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    More about this item

    Keywords

    heteroskedasticity; pretesting; weak identification; monetary policy; robust inference; impulse response functions;
    All these keywords.

    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
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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