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Lived Inflation Methodology

Calculating Lived Inflation rates

The following data sources are used to create the historical lived inflation rates 

1. Living Cost and Food Survey (LCFS) for expenditure patterns by various demographic subgroups.

2. ONS Inflation tables for past price indices data and for the average expenditure weighting used in official figures.

For each wave of the LCFS from 2002/03, we match the LCFS expenditure to the ONS categories of expenditure (COICOP). However, we do not include Council Tax expenditure from the LCFS as the ONS indicate that LCFS data alone would likely overstate council tax expenditure. The latest LCFS data available runs to March 2020, to account for this we ran a sensitivity check accounting for changes in expenditure in categories which had changed significantly during 2020. We found that this made no significant difference to our analysis. 

We generate two grouping variables based on household observational data, income quintiles and household composition. These are calculated for each LCFS wave separately.

To create income quintiles, we rank the equivalised household income variable (OCED scale) and take 5 equal proportions. The 1st household income quintile represents those in the lowest 20% of income and the 5th income quintile represents the highest 20% of household incomes. 

For household composition, we use socio-demographic information to create the following groups: single without children, single with children, couple without children, couple with children, 3 adults or more and retired households. From these grouping variables we calculate the total expenditure by demographic group for each COICOP expenditure category e.g. the total expenditure spent by single parent households on tea and coffee. To account for differences in demographic sample sizes over time, a weighting is calculated to ensure consistency over LCFS waves. From these summed expenditure values, we calculate weights that are the proportion of total expenditure spent on each COICOP category for each demographic group.  These demographic specific weights are used to reweight the CPIH price level changes to generate an overall lived inflation rate for each demographic group.

Forecasting future Lived Inflation rates

The following sources are used to make assumptions about the price rises that will occur for different expenditure categories:

1. Cornwall Insight’s energy price forecast for Spring/Summer 2022 from December 2021. They estimate that energy prices will on average increase by around 50%. 

2. For food inflation, evidence points towards continued increases in early 2022. Capital Economics predicts food prices will be pushed to 5%.

3. For all other variables we use the latest inflation figures (December 2021) and carry the same inflation values forward. 

We feed these figures into the modelling: 

  • For electricity and gas prices, we assume the same price level between January and March 2022 then in April 2022 feed in a 50% increase on the October 2021 price level.
  • For food, we assume a 5% inflation rate between January to April 2022.
  • For all other categories, we assume the inflation rate remains constant from December 2021 to April 2022 unless there is an existing pattern for example Education price level is revised again in September 2022.

Sensitivity tests

We ran several sensitivity checks during this estimation process. 

  • Making adjustments for categories where the ONS indicated expenditure had changed significantly between 2019 and 2020. This test made no significant difference on the estimated lived inflation figures so we stuck with the latest LCFS figures.
  • We ran another scenario where all categories increase to 5% inflation from January 2022 apart from energy price rises where we use the latest Cornwall insight forecasts. These assumptions lead to a higher predicted level of inflation c.0.5-1% higher than the main scenario assumptions. However, importantly, the comparisons between demographic groups did not change. We report the more conservative estimates.
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