Abstract
This paper (re-)evaluates the effectiveness of central bank asset purchases in the euro area given their prominent role in the ECB’s response to the pandemic as well as the evidence from the US suggesting diminishing returns of this policy measure over time. We analyse their macroeconomic impact in the euro area using a time-varying parameter structural vector autoregression with stochastic volatility and perform identification via sign and zero restrictions of Arias et al. (Econometrica 86:658–720, 2018), their fusion with high-frequency information approach akin to Jarociński and Karadi (Am Econ Macroecon 12:1–43, 2020) and a novel method which merges high-frequency identification with narrative sign restrictions of Antonlin-Diaz and Rubio-Ramirez (Am Econ Rev 108:2802–2829, 2018). We find that the potency of the ECB’s asset purchases to lift inflation has indeed considerably declined over time with several factors contributing to a more muted response of prices to central bank asset purchases. Our results show that the reanchoring channel is no longer active while the counterproductive effects via the mechanism outlined in Boehl et al. (Working Paper No. 691, 2020), which we dub the capacity utilization channel, have emerged lately and are further complemented with disinflationary effects stemming from the cost channel. Also, the effects passed through more standard transmission channels of central bank asset purchases like portfolio rebalancing and signalling, while still significant, appear to be less persistent recently. Overall, our findings point to a diminishing return of the ECB’s asset purchases to stabilize inflation and its expectations in the euro area.
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Notes
In this paper, the term asset purchases is used interchangeably with quantitative easing in reference to the APP and the PEPP used by the ECB since 2015.
Although a growing list of literature questions the empirical relevance of the ZLB (see Altavilla et al. 2019; Debortoli et al. 2020; Zlobins 2020b), suggesting that standard monetary policy tools are still effective beyond zero, Zlobins (2020b) also shows that their ability to lift inflation is significantly weakened, thus requiring additional unconventional tools to ensure price stability.
Figure A6 in the Online Appendix shows that the estimates are not too sensitive with respect to the specific values of these hyperparameters. In particular, setting \(\chi _0\)=\(\psi _0\)=\(\alpha _0\)=\(\delta _0\)=0.01 gives similar estimates of the ECB’s QE over time.
Monthly real GDP series are obtained by performing the Litterman (1983) temporal disaggregation procedure using the industrial production index as indicator series.
Figure A2 in the Online Appendix shows that the results remain robust also when using two lags.
Fig. A3 in the Online Appendix contains an additional assuming that the standard monetary policy cannot contemporaneously impact output and inflation either. The results remain broadly in line with the baseline results.
Excluding one observation which includes 0.
We set the AR coefficient of the prior to 0, overall tightness \(\lambda _1\)=0.1, cross-variable weighting \(\lambda _2=0.5\), lag decay \(\lambda _3=1\) and block exogeneity shrinkage \(\lambda _5\)=0.001.
Note that the TVP-SVAR-SV is still estimated over the sample from January 2009 to June 2020 so that the parameters are consistent across both identification approaches. The shock series obtained via the HFI approach for the period before June 2014 is set to zero.
We use codes from the website of Refet Gürkaynak: http://refet.bilkent.edu.tr/research.html
Figure A7 in the Online Appendix shows that our results remain robust also when interest rate and stock market surprises are used as endogenous variables in the TVP-SVAR-SV and asset purchase shock is isolated from the information shock using the same restrictions as in Table 2, effectively replicating the approach of Jarociński and Karadi (2020) within the TVP-SVAR-SV.
See also impulse responses at selected horizons along with 68% credible sets in Fig. A8 in the Online Appendix.
Since our data sample ends in June 2020, we cannot fully estimate the macroeconomic effects of the PEPP, thus our results should be interpreted with caution about the PEPP effectiveness in the future.
See also impulse responses at selected horizons along with 68% credible sets in Fig. A9 in the Online Appendix.
When using the HFI approach, we also include the shock series in the model, increasing the total variable count to six.
A caveat of their study though is that they only consider transmission of the ECB’s asset purchases to the German Bunds while (Geiger and Schupp 2018) look at the euro area OIS curve.
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The author would like to thank the participants of an internal seminar held at Latvijas Banka, the 4th Workshop on Macroeconomic Research, the 4th ERMEES Macroeconomics Workshop 2021, the 25th Conference “Theories and Methods in Macroeconomics” and the 4th Baltic Economic Conference for useful suggestions. I am also grateful to the associate editor, three anonymous reviewers, Laura Galdikiene (Bank of Lithuania and Vilnius University), Sara D’Andrea (Sapienza University of Rome), Viktors Ajevskis, Gunārs Bērziņš, Mārtiņš Bitāns, Anete Kravinska, Erlands Krongorns, Uldis Rutkaste, Kārlis Vilerts and Klāvs Zutis (all Latvijas Banka) for valuable comments and their help with data gathering. The views expressed in this paper are those of the author and do not necessarily reflect the views of Latvijas Banka.
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Zlobins, A. On the time-varying effects of the ECB’s asset purchases. Empir Econ 66, 2593–2623 (2024). https://doi.org/10.1007/s00181-023-02529-0
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DOI: https://doi.org/10.1007/s00181-023-02529-0