Wait and Hope
The August HICP report raises the same questions of the last few months. Our models continue to suggest disinflation going forward. However, reaching (and staying) at target is still a question mark: the distribution of price changes has not moved in recent months and it is centered above target (if any, it is less dispersed now). The CI model suggests that the common component is very solid and remains well above target. Finally, the medium-term models deliver a forecast higher than the latest macroeconomic projection exercise and higher than target.
The ECB has cut rates and it is now in “wait and hope” mode. So far, the data have remain very solid. The suspect is that without a recession, it will be very difficult to reach and stay at target going forward.
Evidence from the distributions
The distribution: centered above target. This month, the distribution is less dispersed than last month (ridge plot here). Extending the horizon (Figure 1), the distribution shows little changes in recent months and remains centered above target. Finally, the median (Figure 2) has ticked up in August and remains volatile.
Overall, this evidence continues to suggest solid near-term readings above target (MoM saar around 2.5%+).
Figure 1. Kernel of HICP excluding food and energy items changes (%, a.r.)
Figure 2. Median of HICP excluding food and energy items prices increase
Evidence from our CI model
Our CI model estimates that net of idiosyncratic shocks, the common component across items is solid. Figure 3 shows the decomposition of the MoM of core HICP in the “common” component and the “idiosyncratic” component. The model estimates that in August the common component increased by 23bps, in line with the average of the previous months, while the idiosyncratic shock is null (0bps). As we did in previous months, we consider as “true” core the one netting out the idiosyncratic part. Therefore, a rough estimate put the MoM (saar) of “true” core HICP at 2.8% in August. The signal of the CI model in the last few months is in line with the distributions and suggests that core HICP is running around 2¾ (ar) at the moment (see Figure 4 below).
Figure 3. Contributions to MoM changes of HICP excluding food and energy items
Note: the Figure shows the decomposition of the MoM percent changes of HICP prices excluding food and energy items. The contributions are estimated using our CI model, a 2-stage OLS-LASSO regression model.
Figure 4. Estimated “Common” component: YoY, 3m/3m a.r. and 6m/6m a.r.
Note: the Figure shows the 3m/3m at annual rate (green line), the 6m/6m at annual rate (red line), and the YoY (blue line) of the “common component” estimated using our CI model.
Implications for the medium-term forecast of core HICP
Medium-term model-based forecast is unrevised. The models forecasts are unrevised compared to the time of the flash release and the September governing council meeting. Using the unemployment rate as measure of “slack”, the forecast is at 2.9% (average YoY) in 2024, 2.6% in 2025, and 2.4% in 2026. Using the output gap, the forecast is: 2.9% in 2024, 2.5% in 2025, and 2.3% in 2026. The average of these forecasts is above the latest ECB/NCBs staff forecast.
Figure 5. Model-based medium-term forecast of core HICP (YoY)
Using Urate as a measure of “slack”
Using outputp gap as a measure of “slack”
Note: the confidence intervals (C.I.) are calculated using the estimated parameters distributions.
A comparison with the ECB/NCBs staff forecast
Risks around the ECB/NCBs forecasts are to the upside. Table 1 shows a comparison between our latest forecast and the ECB/NCBs staff forecast. Acquired inflation for 2024 is 2.7% (2.8%) in SA (NSA) space. Please, note that the new ECB/NCBs staff forecast is now in line with our model in 2024. We continue to suspect that the ECB/NCBs staff will be forced to revise up the 2025 and 2026 forecast in the coming months.
(For a technical note on the concepts of “acquired inflation” and “carryover effect” see here and here).
Table 1. Comparison of forecasts
Note: the “UnderlyingInflation” forecast refers to the average of the two models shown in Figure 5.