In modern macroeconomic models (Calvo, 1983; Taylor, 1980), consumer goods and services exhibit heterogeneous pricing frictions:

1. Frequently Changing Prices (Flexible):
   • Items such as vehicle fuels, fresh produce, energy, and airline tickets.
   • Adjust continuously to real-time supply and demand imbalances, exchange rate fluctuations, and commodity market swings.
   • While flexible prices drive sharp headline inflation volatility, their fluctuations are predominantly transitory and exhibit rapid mean-reversion.
2. Sticky Prices (Infrequently Changing):
   • Items such as residential rents, restaurant dining, education, medical care, personal care, and specialized repair services.
   • Exhibit pronounced pricing inertia due to menu costs, explicit multi-period contracts, implicit customer relationships, and high labor cost shares.
   • Once sticky prices begin to accelerate, they reflect deep-seated wage growth and inflation expectations. Disinflating sticky prices requires significant monetary restraint and operates with extended lags.
3. Analytical Value of the Decomposition:
   • Isolating sticky inflation provides central banks and market analysts with a robust, noise-filtered gauge of underlying inflation persistence that is far less susceptible to temporary commodity reversals than standard core inflation (HICP excluding energy & unprocessed food).

Rather than assigning goods into subjective sector categories, this dashboard applies an objective, frequency-driven empirical classification:

1. Price Adjustment Frequency as Volatility:
   • In monthly CPI data, items adjusting prices infrequently exhibit long plateaus followed by rare step-changes, generating low Month-on-Month (MoM) standard deviation.
   • Items that adjust prices continuously exhibit high MoM variation.
2. Country-Specific Interquartile Calibration:
   • Because national market regulations, administered tariffs, and supply chains vary across Europe, price volatility distributions differ between countries.
   • We calculate category-specific volatility \(\sigma_i\) separately for each European economy and the Euro Area aggregate over the full historical sample (2012–present).
   • Categories are dynamically classified into three non-overlapping groups based on the empirical quartiles (\(Q_1\) and \(Q_3\)) of the national distribution:
     • Sticky: Volatilities below the 25th percentile (\(< Q_1\)).
     • Moderately changing (Normal): Volatilities between the 25th and 75th percentiles (\([Q_1, Q_3)\)).
     • Frequently changing (Flexible): Volatilities at or above the 75th percentile (\(\ge Q_3\)).

Let \(P_{i,c,t}\) be the price index for granular COICOP item \(i\) in country \(c\) at month \(t\). The Month-on-Month (MoM) rate \(\pi^M_{i,c,t}\) is:

For each COICOP category \(i\), price volatility \(\sigma_{i,c}\) is measured as the sample standard deviation of its monthly rates over the historical sample \(t = 1, \dots, T\):

where \(\bar{\pi}^M_{i,c} = \frac{1}{T} \sum_{t=1}^T \pi^M_{i,c,t}\).

Given the country-specific empirical quartiles \(Q_1(\boldsymbol{\sigma}_c)\) and \(Q_3(\boldsymbol{\sigma}_c)\):

For each class \(k \in \{\text{sticky}, \text{normal}, \text{flexible}\}\) in year \(y\), the aggregate group weight \(W_{k,c,y}\) is the sum of official Eurostat item weights \(\omega_{i,c,y}\) (in permille, where total basket \(\Omega = 1000\)):

The sub-index inflation rate \(\pi_{k,c,t}\) (for YoY or MoM) is computed by re-weighting item inflation rates within that specific group:

The contribution \(C_{k,c,t}\) of class \(k\) to headline HICP inflation \(\Pi_{c,t}\) (in percentage points) is:

Headline HICP is partitioned additively by the three component contributions: