A Big Drop of the Median
Big drop of the median, took a little signal. The distribution is more friendly than last month and the median dropped notably. Partially, this movement is driven by non-market prices which carry no signal for future readings of core PCE price inflation itself (see Figure 0). The CI model suggests that the common component is also lower. Finally, the medium-term forecast is little changed.
In general, we take no signal from one month of data. In this case, we took a little signal, given the drop of the median, and lower our near-term forecast. We now expect core PCE price inflation to expand at an average of 17bps MoM in H2 and we expect the YoY at 2.7% in December. Our forecast for 2024 is now slightly lower than the latest SEP.
We remind the reader that we currently estimate pi* at 2.6% in core PCE space. For the time being, the Fed can wait.
A PPT containing all relevant CPI/PCE charts can be downloaded here.
Figure 0. MoM of core PCE prices, market-based vs non-market prices.
Evidence from the distributions
Big drop of the median. This month, the distribution is more friendly than last month (Figure 1) but in this highly volatile environment we have learned to take little signal from a single month. Zooming out, in the last 3 months (Figure 2) there are little signs of progress. Having said that, the big news in today’s data is that the median of the distribution dropped notably in May (Figure 3). While the median remains volatile and part of the drop is due to non-market prices (Figure 0), it is hard to dismiss entirely such movement.
To sum up: considering that we are about to enter H2 (residual seasonality), it is reasonable to expect, on average, lower MoM than in H1. We are now expecting core PCE prices to grow at an average of 17bps in H2 and the YoY at 2.7% in December 2024.
Figure 1. Distribution of PCE excluding food and energy items changes (%, a.r.)
Note: The Figure shows the fitted Kernel (Epanechnikov) distribution of MoM percent changes at annual rate of PCE prices excluding food and energy items. The colors indicate the percentiles: 0-10pct, 10-25pct, etc. The dashed line shows the median of the distribution.
Figure 2. Kernel of PCE excluding food and energy items changes (%, a.r.)
Note: The Figure shows the fitted Kernel (Epanechnikov) distribution of MoM percent changes at annual rate of PCE prices excluding food and energy items.
Figure 3. Median PCE price increase
Note: The Figure shows the median (MoM %, a.r.) of the distribution of PCE prices changes excluding food and energy items (left panel) and the YoY (right panel).
Evidence from our Common-Idiosyncratic (CI) model
Our CI model estimates a drop in the common component. Figure 4 shows the decomposition of the MoM of core PCE in the “common” component (blue bars) and the “idiosyncratic” component (yellow bars). The model estimates that in May the common component increased by 4bps, while the idiosyncratic shock is a small positive (4bp). Overall, the common component (Figure 5) seems to have bottomed and it has gone sideways in recent months above target. The signal of the CI model is roughly in line with the one of the distributions.
Figure 4. Contributions to MoM changes of PCE excluding food and energy items (CI-C model)
Note: The Figure shows the decomposition of the MoM percent changes of PCE prices excluding food and energy items. The contributions are estimated using our CI-C model, a 2-stage OLS-LASSO regression model. The “Covid” effect is identified with price variations outside the 10th-90th percentiles of each item pre-Covid price change distribution.
Figure 5. 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-C model.
Implications for the medium-term forecast of core PCE price inflation
The medium-term forecast is unchanged. Today’s data imply no change to the medium-term forecast. The (Q4/Q4) model forecast is: 3.0% in 2024, 2.6% in 2025, and 2.5% in 2026.
Note: The figure shows the latest run of our “main” Phillips curve model. The confidence intervals (C.I.) are estimated using quasi-out-of-sample methods (estimate the model over a sub-sample, forecast, and calculate the root mean squared forecast errors).