August 20, 2024

Euro Area: July 2024 Final HICP

Wait and Hope

A PDF containing all relevant charts for the EA can be downloaded here. A PDF containing all relevant charts for the big 4 countries can be downloaded here.

Evidence from the distributions

The distribution: centered above target. This month, the distribution is very similar to 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 down in July.

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 July the common component increased by 25bps, in line with the average of the previous months, while the idiosyncratic shock is small (5bps). 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 3.0% in July. 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 2.5%+ (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 unrevised. The models forecasts are unrevised compared to the time of the flash release. 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 2.5% (2.7%) in SA (NSA) space. This implies that the risks around the ECB/NCBs staff forecast are to the upside, as there is little (or no) room to revise the forecast down going forward.

(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.

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Disclaimer

Trezzi consulting is a Swiss registered firm that offers independent economic and statistical consulting services. Trezzi consulting does not have access to any classified information of any central bank, including the Federal Reserve. All econometric and statistical models included in the packages are either developed in-house or they are based on publicly available documents such as papers and notes.