Realizar el Control Integrado de Cambios

In order to shed more light to the results, we re-estimate results as follows: we employ alternative country groups and estimate their variance decomposition during the full sample period, as follows: “core and peripheral” or “Eurozone” (Germany, Austria, Belgium, France, Greece, Ireland, Italy, the Netherlands, Portugal, and Spain), “core” (Germany, Austria, Belgium, France and the Netherlands) and “peripheral” (Ireland, Italy, Portugal, Spain and Greece). The results are presented in Table 10: Panel A presents the results for the Core and Peripheral countries (Full Sample), Panel B for the Core countries (Full Sample), Panel C for the Peripheral countries (Full Sample), Panel D for the Core and Peripheral countries (1st period), Panel E for the Core and Peripheral countries (2nd period), Panel F for the Core and Peripheral countries (3rd period).

As can be seen in Table 10 (Panel A) the main contributor for the “core and peripheral” countries’ sovereign CDS variance decomposition for the full sample period (except for the own effect, 58.83%), is the iTraxx European index, with 18.68% of the total sovereign CDS variance. The termspread and the VIX are also important contributors contributing to 7.7% and 9.03% of the total variance respectively, while the other factors appear to be less important. For the core countries (Panel B), the results remain approximately the same, with the contribution of VIX and termspread slightly reduced and the CDS own effect slightly increased. For the peripheral countries (Panel C) the effect of the termspread is significantly increased (13.34%) and the CDS own variance significantly reduced (46.53%). VIX seems to be an important contributor with almost

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17% of the total variance. For the “core and peripheral” country group during the three sub-periods (Panels D, E, F) the main result that emerges is that investor sentiment (ESI) during the first sub-period contributes 7.07% to the total CDS variance, market sentiment (NOC) contributes 12.42% to the total CDS variance. Also, during the third sub-period the Eur-Eon variable becomes significantly important (22.02% from 2%-7.95%), that the iTraxx contribution is significantly reduced but still remains important (10.08% from 19.06%-21.82%), and that the CDS own contribution is increased during the third sub- period.

These results strongly indicate that the determinants of CDS variance are neither uniform nor stable during different sample periods and different sample countries. For instance, the CDS own effect for the “core and peripheral” group differs during the three periods, contributing 29.94%, 44.57% and 54.93% for the first, second and third period respectively. The iTraxx (a proxy for market-wide credit risk) is almost the same for the three different country groups, while it is more important as contributor for the “core and peripheral” group during the first and the second period; the CDS trading volume (NOC) is important during the first sub-period for the “core and peripheral” countries (around 12.42%), but not as important in the second sub-period and with no effect in the third sub-period. The ESI appears important for the first sub-period (7.07%) while it has no important effect during the other two sub-periods. The Euribor-Eonia spread (a proxy for banking stress in Europe) seems to be gaining importance during the third period for the “core and peripheral” group (22.02%) and is less importance during rest sub-periods.

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Table 10

Robustness tests - Forecast Error Variance Decomposition

Response Variable

Impulse Variables Panel A

Core and Peripheral countries (Full Sample)

Vix Eur-Eon iTraxx Termspread ESI Noc Cds

Cds 9.03 2.59 18.68 7.7 0.54 2.6 58.83

Panel B

Core countries (Full Sample)

Vix Eur-Eon iTraxx Termspread ESI Noc Cds

Cds 6.53 2.52 19.21 4.99 0.92 2.69 63.1

Panel C

Peripheral countries (Full Sample)

Vix Eur-Eon iTraxx Termspread ESI Noc Cds

Cds 16.92 3.13 17.24 13.34 0.35 2.46 46.53

Panel D

Core and Peripheral countries (1st sub-period)

Vix Eur-Eon iTraxx Termspread ESI Noc Cds

Cds 10.85 7.95 21.82 9.91 7.07 12.42 29.94

Panel E

Core and Peripheral countries (2nd period)

Vix Eur-Eon iTraxx Termspread ESI Noc Cds

Cds 16.03 2.2 19.06 10.04 1.16 6.91 44.57

Panel F

Core and Peripheral countries (3rd period)

Vix Eur-Eon iTraxx Termspread ESI Noc Cds

Cds 2.71 22.02 10.08 5.29 4.62 0.32 54.93

Notes to Table 10

The Table reports the fraction (in percentage points) of the 10 months ahead forecast error variance of the sovereign CDS variance decomposition that is attributable to VIX, Euribor –Eonia, iTraxx, Termspread, ESI, NOC, Sovereign CDS, for different periods and sample country groups. We employ three country groups as follows and estimate their variance decomposition during the full sample period: “core and peripheral” or “Eurozone” (Germany, Austria, Belgium, France, Greece, Ireland, Italy, the Netherlands, Portugal, and Spain), “core” (Germany, Austria, Belgium, France and the Netherlands) and “peripheral” (Ireland, Italy, Portugal, Spain and Greece). Next, we re-estimate results for the “core and peripheral”

countries for the three sub-periods. In “core and peripheral” full sample, “peripheral countries” full sample

and “core and peripheral” 3rd period we exclude Greece and Ireland due to lack of data. In “core and peripheral” 2nd period we exclude Greece due to lack of data.

When the ZEW Eurozone Index is used instead of the ESI index (Table 11) the results are qualitatively similar with one exception: the sentiment proxy seems to be a very important spread determinant for all countries during the second period, since it

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contributes approximately 8.5% to CDS variance. This finding, further supports the notion that sentiment may be an important spread determinant during crisis periods.

Table 11

Forecast Error Variance Decomposition - ZEW Sentiment (Full period)

Impulse variables

Group / Period Vix Eur-Eon iTraxx ZEW Termspread Noc Cds

Core and Peripheral countries (Full period) 7.57 1.82 17.18 6.55 6.95 3.4 56.51 Core countries (Full period) 5.49 1.87 16.74 6.42 6.16 3.3 59.98 Peripheral countries (Full period) 13.77 2.16 16.71 5.85 12.41 3.73 46.33

Core and Peripheral

countries / 1st period 7.56 1.55 19.52 5.17 28.49 4.22 33.45

Core and Peripheral

countries / 2nd period 14.32 1.42 18.17 8.34 10.6 5.83 41.81

Core and Peripheral

countries / 3rd period 3.2 21.55 17.38 4.49 4.47 0.19 48.68

Notes to Table 11

The Table presents results with the ZEW Economic Sentiment variable instead of the ESI variable; see also notes to Table 8.

As a further robustness test, we also re-estimate the effect of sentiment on spreads, using the proxy index (ESI) in levels (ESI minus 100), rather than log differences, i.e. differences of the index from the optimism-threshold (see for details, Georgoutsos and Migiakis, 2013). We present the results for the three sub-periods for the “core” and the “peripheral” groups in the following Table 12. The results reveal that when the ESI is used in levels the effect of local sentiment has a strong effect during the first and the

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second sub-period in peripheral countries with an important contribution of 13.14% and 12.5%, respectively.

Table 12

Forecast Error Variance Decomposition (ESI in levels-100)

Response Variable

Impulse Variables Panel A Core (1st period)

Vix Eur-Eon iTraxx Termspread ESI NOC Cds

CDS 4.46 4.09 7.14 34.5 6.84 4.21 38.74

_{Peripheral (1st period)} Panel B

Vix Eur-Eon iTraxx Termspread ESI NOC Cds

CDS 9.71 6.35 13.44 29.96 13.14 3.08 24.3

_{Core (2st period)} Panel C

Vix Eur-Eon iTraxx Termspread ESI NOC Cds

CDS 11.51 1.35 34.82 2.93 0.26 8.46 40.65

_{Peripheral (2st period)} Panel D

Vix Eur-Eon iTraxx Termspread ESI NOC Cds

CDS 17.63 12.27 5.0 10.14 12.5 6.87 35.58

_{Core (3st period)} Panel E

Vix Eur-Eon iTraxx Termspread ESI NOC Cds

CDS 2.92 14.22 12.55 0.93 4.84 0.49 64.03

_{Peripheral (3st period)} Panel F

Vix Eur-Eon iTraxx Termspread ESI NOC Cds

CDS 3.25 38.19 14.3 21.22 0.73 3.09 19.2

Notes to Table 12

See Notes to Table 9

To formally test whether changes in excess correlation are also statistically significant between sovereigns (core/peripheral) and Country-of-Interest CDS spreads, for different time periods we make use of the Fisher transformation of (excess) correlation

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coefficients. Fisher’s z transformation converts Pearson’s r correlation to a normally distributed variable z, which is defined as 𝑧 = 0.5[ln(1 + r) − ln(1 − r)]. The standard error of z is given by 𝜎𝑧 = (√𝑁 − 3)

−𝑡

, where N is the number of observations. The test- statistic, Z, for the difference between two measures of excess correlation is given then by: 𝑍 = (𝑧1− 𝑧2) √ 1 √𝑁1− 3 + 1 √𝑁2− 3 , (3)

In (3) 𝑁₁ and 𝑁₂ represent the number of observations of the two samples and Z is normally distributed and hence significance can be assessed with the usual test statistics. .

The results concerning the residual correlation between sovereign and Country-of-Interest CDS spreads (we test for spillover effects steaming from Spain and Italy to the core countries as those two had the larger contribution in the core CDS variance) are available upon request, but are discussed here. First, we note a clear increase in excess correlations over the first two sub-periods and a drop in excess correlations during the third sub- period. To formally test whether the differences in correlations are also statistically significant, we make use of the Fisher transformation of (excess) correlation coefficients. This is interpreted as providing support to the argument that there might have been a transfer of default risk from peripheral countries to core countries during the crisis periods. We apply the same test for the three different periods, grouped pair-wise each time (1st-2nd, 2nd-3rd and 1st-3rd) for potential spillover effects steaming from peripheral to core countries and from peripheral to peripheral countries. In all cases we reject the null

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that the residual correlations are the same for the three different sub-periods. This result offers support to the argument that during the turbulent periods the links between core and peripheral countries have strengthened, while during the third the links decrease substantially. Moreover, even though during the first two sub-periods we detect increased residual correlation, the Fisher Z test shows that these correlations are statistically different between these two periods.

Similar results are obtained for peripheral countries (the spillover effects here steam from Spain, Portugal and Italy, the most contributive at the CDS variance decomposition - we do not test for Ireland due to missing data during the third period), where we test the hypothesis that the residual correlation has remained the same over the three sub- period. The values of the Fisher test statistic reveal that we are unable to accept the null (i.e. that correlations have remained the same), during all periods while the spillover effects steam from Spain and Italy to the peripheral countries. When the spillover effects come from Portugal we are unable to reject the null when we test for differences in correlation between 2nd and 3rd period, and 1st and 3rd period. This again reinforces the conclusion that the debt problems of the core and peripheral sovereigns and peripheral with peripherals, have become inextricably interwoven.