Domestic airfares

Why this view matters: The time-series view supports two different questions: monthly data are better for short-run movements and seasonality, while annual data are better for long-run trends.

How to read the chart: In monthly mode, follow the sequence month by month. Use the 6- or 12-month moving average to emphasize the underlying trend. In annual mode, compare year-level changes and note any partial-year label.

Calculation and caveats: Moving averages use the trailing 6 or 12 monthly observations. The current-price series uses the reported fare values; the inflation-adjusted series restates each month in the purchasing power of the selected IPCA base month. An active geographic filter restricts the full time series to the selected geography and trip endpoint.

Why this view matters: The airline time series shows whether carriers’ average fares move together or diverge over time and helps identify changes in relative fare positioning.

How to read the chart: Follow each airline using the legend and end labels. A moving average is useful when the objective is to compare underlying trends rather than monthly volatility.

Calculation and caveats: Airline names are displayed with their source code when a reliable mapping is available. ANAC’s ASSENTOS field is used only as the internal weighting variable for the average-fare calculation.

Why this view matters: An average fare does not show how reported fares are distributed. Fare bands reveal whether the weighted fare observations are concentrated at lower, middle or higher price points and how that pattern changes across years.

How to read the chart: Each series shows the weighted share of reported fare observations in each fare band. Compare shifts in the distribution toward higher or lower bands across the selected years.

Calculation and caveats: The same fare bands are used for every period so distributions are comparable. Shares refer only to the processed ANAC fare dataset and are not estimates of the universe of tickets sold.

Why this view matters: Plotting current-price and inflation-adjusted fares together separates changes in the amount actually reported at the time from changes in purchasing-power terms.

How to read the chart: The current-price line reflects the fare values of each month. The inflation-adjusted line expresses every observation in the purchasing power of the stated base month. A wider gap between the two lines reflects a larger cumulative price-level adjustment.

Calculation and caveats: The current-price series is unchanged. The inflation-adjusted series multiplies each monthly fare by the ratio of the IPCA in the base month to the IPCA in the observation month.

Why this view matters: This view isolates the size of the inflation adjustment required to restate a historical airfare in base-month purchasing power.

How to read the chart: Higher values mean that a larger inflation adjustment is required to convert the historical current-price fare into constant-price terms. This is not the monthly inflation rate.

Calculation and caveats: The indicator is calculated as (inflation-adjusted fare ÷ current-price fare − 1) × 100.

Why this view matters: An index with base 100 removes differences in currency levels and focuses on the relative path of airfares from a common starting point.

How to read the chart: The selected base month equals 100. A value of 120 means the series is 20% above its base-month level; a value of 80 means it is 20% below. Compare both slope and divergence between the series.

Calculation and caveats: Each observation is divided by the value of the same series in the selected base month and multiplied by 100.

Why this view matters: Rolling volatility highlights periods when month-to-month fare changes became unusually unstable, even when the average fare level itself did not move dramatically.

How to read the chart: Higher values mean recent monthly percentage changes were more dispersed; lower values indicate a more stable path. This is a descriptive volatility measure, not a measure of financial risk.

Calculation and caveats: The chart shows the standard deviation of monthly percentage changes in the inflation-adjusted average fare over a trailing 12-month window.

Why this view matters: Quartiles complement the average fare by showing the center and middle spread of the weighted fare distribution.

How to read the chart: The median is the 50th percentile. The 1st and 3rd quartiles bound the middle 50% of the weighted distribution. A wider interquartile range indicates greater dispersion in the central part of the distribution.

Calculation and caveats: Quartiles are estimated from the fare distribution using ANAC’s ASSENTOS field as the internal weighting variable. They describe the processed fare dataset only.

Why this view matters: The gap between the weighted mean and median shows whether higher or lower fare observations are pulling the average away from the center of the distribution.

How to read the chart: Positive values mean the mean is above the median, consistent with relatively greater influence from higher fare observations. Negative values indicate the opposite.

Calculation and caveats: The measure is (mean − median) ÷ median × 100. It is a descriptive mean–median gap, not the formal statistical coefficient of skewness.

Why this view matters: This measure tracks how widely airline-level average fares differ from one another over time. It can reveal periods of greater or smaller dispersion in fare levels across carriers.

How to read the chart: Higher values indicate greater relative dispersion across airline average fares; lower values indicate that airline averages are closer together. It does not measure market concentration or competition directly.

Calculation and caveats: The indicator is the weighted coefficient of variation across airline average fares. ANAC’s ASSENTOS field is used only as the internal weighting variable.