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Shadow rates and spillovers across the Eurozone: a spatial dynamic panel model

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Abstract

In this paper, we focus on the effect of spillovers in monetary policy in the period 2004–2017. Firstly, we calculate shadow rates that measure the monetary stances for each country analysed. Then, by using the approach of spatial dynamic panel, we account for the presence of potential spillovers in the Eurozone, both in the long and short run, while controlling for the main channels regulating the monetary stances. Results confirm that monetary policy is largely affected by the presence of spillovers due to proximity in the business cycles and this effect should be considered to manage the effects of monetary policy in different European economies.

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Notes

  1. See Peersman (2011), Baumeister and Benati (2013), Altavilla et al. (2014), Gambacorta et al. (2014), Acharya et al. (2016), and Kremer (2016).

  2. We construct the yield curve for euro area with bond maturity of 3 months and 1, 5, 10, and 30 years.

  3. The series are retrieved from Eurostat.

  4. The number of simulations considered for the MCMC for direct, indirect, and total impacts is 500.

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Authors and Affiliations

  1. Department of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico, 1, 00133, Rome, Italy

    Cristiana Fiorelli

  2. Department of Economic Studies, G. d’Annunzio University of Chieti-Pescara, Viale Pindaro, 42, 65122, Pescara, Italy

    Alfredo Cartone & Matteo Foglia

Authors
  1. Cristiana Fiorelli
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  2. Alfredo Cartone
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  3. Matteo Foglia
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Correspondence to Cristiana Fiorelli.

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Appendix

Appendix

See Tables 5, 6 and 7 and Fig. 6.

Table 5 A: Percentage of Variance for each principal component analysis calculated for seven Eurozone Countries. Only the first two principal components are computed to obtain data reduction for each country
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Table 6 Panel estimate results of dySDM. The column (1) report a constrained version of the dySDM not including the spatial lag of \(\Delta {\text{SSR}}_{{{\text{i}},{\text{t}} - 1}}\), while column (2) includes the complete model with only spatial fixed effects
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Table 7 Space–time direct (VOL) and indirect (CA and UN) effect estimates
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Fig. 6
figure 6

Extracted components per countries. First component (PC1) is the Term premium (black line); second component (PC2) is the Expectation component (blue line) (color figure online)

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Fiorelli, C., Cartone, A. & Foglia, M. Shadow rates and spillovers across the Eurozone: a spatial dynamic panel model. Empirica 48, 223–245 (2021). https://doi.org/10.1007/s10663-020-09483-5

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