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Estimation of Impulse Response Functions When Shocks are Observed at a Higher Frequency than Outcome Variables

Author

Listed:
  • Alexander Chudik
  • Georgios Georgiadis
Abstract
This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable), (iii) the data-generating process (DGP) is given by a VAR model at the frequency of the shock, and (iv) the full set of relevant endogenous variables entering the DGP is unknown or unobserved. Consistency and asymptotic normality of the proposed MFDL estimators is established, and their small-sample performance is documented by a set of Monte Carlo experiments. The proposed approach is then applied to estimate the daily pass-through of changes in crude oil prices observed at a daily frequency to U.S. gasoline consumer prices observed at a weekly frequency. We find that the pass-through is fast, with about 28% of the crude oil price changes passed through to retail gasoline prices within five working days, and that the speed of the pass-through has increased over time.

Suggested Citation

  • Alexander Chudik & Georgios Georgiadis, 2019. "Estimation of Impulse Response Functions When Shocks are Observed at a Higher Frequency than Outcome Variables," Globalization Institute Working Papers 356, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddgw:356
    DOI: 10.24149/gwp356
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    References listed on IDEAS

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    2. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    3. Christina D. Romer & David H. Romer, 2010. "The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks," American Economic Review, American Economic Association, vol. 100(3), pages 763-801, June.
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    6. Choi, Chi-Young & Chudik, Alexander, 2019. "Estimating impulse response functions when the shock series is observed," Economics Letters, Elsevier, vol. 180(C), pages 71-75.
    7. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    8. Claudia Foroni & Massimiliano Marcellino, 2016. "Mixed frequency structural vector auto-regressive models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 403-425, February.
    9. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2016. "Structural analysis with mixed frequencies: monetary policy, uncertainty and gross capital flows," JRC Working Papers in Economics and Finance 2016-04, Joint Research Centre, European Commission.
    10. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
    11. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
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    Cited by:

    1. Kilian, Lutz & Zhou, Xiaoqing, 2023. "Oil Price Shocks and Inflation," CEPR Discussion Papers 18416, C.E.P.R. Discussion Papers.
    2. Andrea Gazzani & Alejandro Vicondoa, 2020. "Bridge Proxy-SVAR: estimating the macroeconomic effects of shocks identified at high-frequency," Temi di discussione (Economic working papers) 1274, Bank of Italy, Economic Research and International Relations Area.
    3. Gareth Anderson & Ambrogio Cesa-Bianchi, 2020. "Crossing the Credit Channel: Credit Spreads and Firm Heterogeneity," Discussion Papers 2005, Centre for Macroeconomics (CFM).
    4. Lutz Kilian & Xiaoqing Zhou, 2023. "The Econometrics of Oil Market VAR Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 65-95, Emerald Group Publishing Limited.
    5. Alessandri, Piergiorgio & Gazzani, Andrea & Vicondoa, Alejandro, 2023. "Are the effects of uncertainty shocks big or small?," European Economic Review, Elsevier, vol. 158(C).
    6. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2021. "The real effects of financial uncertainty shocks: A daily identification approach," Working Papers 61, Red Nacional de Investigadores en Economía (RedNIE).
    7. Patozi, A., 2023. "Green Transmission: Monetary Policy in the Age of ESG," Cambridge Working Papers in Economics 2311, Faculty of Economics, University of Cambridge.
    8. Shioji, Etsuro, 2021. "Pass-through of oil supply shocks to domestic gasoline prices: evidence from daily data," Energy Economics, Elsevier, vol. 98(C).

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    More about this item

    Keywords

    Mixed frequencies; temporal aggregation; impulse response functions; estimation and inference; VAR models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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