By Paul Schreyer
A long-standing critique of National Accounts is that their high level of aggregation obscures who benefits from economic growth. Measures of consumption growth or comparisons of expenditure per capita across countries are criticised for not reflecting the experience of most people in the economy. Alternative measurements are then presented to which macroeconomic statisticians’ riposte that these are not comparable and do not represent the complete economy due to lacking a comprehensive framework such as the national accounts.
The resulting suite of inconsistent measures purporting to describe the economy reveals the gaps that exist between such indicators and the objective to comprehensively describe the reality of economies. In a move to try and reconcile these differences and close the gap, the latest System of National Accounts introduces distributional accounts for household income, consumption and wealth.
The distributional accounts integrate granular information on the distribution of income, consumption and wealth across households into the framework of the national accounts to give a complete picture on how different households are faring over time as the economy grows. This requires alignment of definitions – for example what counts as income? – as well as alignment of data, for example interest income reported by households can be very different from interest payments to households reported by banks.
With the availability of such data for a range of countries, we decided to look at the question “how much have living standards improved for households with different income levels”?
How do we measure changing living standards?
To answer the question, we defined material well-being as real market consumption plus government-provided Social Transfers in Kind (STiK), corresponding to Actual Individual Consumption (AIC) in the national accounts. We measured this using total expenditure by income quintile across 11 OECD countries, from which we calculated time series of material well-being:
- Deflating current expenditure: The quintile data for market consumption and STiK first needed to be deflated to a common period to get changes in quantity. This utilised the consumption deflators for market consumption while considering several possible deflators for government expenditure.
- Construct indices by quintile: With prices in a common period, quantity indices are calculated for the (weighted) change in the quantity of consumption for each quintile to show the changes in real consumption, accounting for market and STiK goods.
- Calculate each quintile’s annual rate of growth of living standards: Adjusting the index value to an annual growth rate, changes in growth of well-being at the aggregate and quintile level can be compared across countries.
This approach allowed us to construct comparable measures of the growth of market goods and STiK to measure the evolution of material well-being and answer whether growth rates differ across the income distribution. Although methodologies are aligned, a drawback of the available data is that time periods vary significantly across countries.
How have living standards evolved?
We present a number of findings in our ESCoE Discussion Paper, looking at difference in growth rates of well-being within and across countries.
Well-being growth and income
Our key finding is that when all countries are considered simultaneously, changes in material well-being are not related to the income quintile. Levels and patterns of change in material well-being vary across countries, and there is no common trend of well-being being impacted by the income quintile.
Within countries, however, strong patterns do exist. Here, we can see how a single aggregate value for the growth of material well-being of a country may not reveal the full story of where these gains have been made and who has benefited the most, with six of the countries showing greater growth of well-being in the lowest income quintile than in the highest income quintile.
Cost of living across the distribution
Against the backdrop of increasing costs of living, the distributional accounts allow us to look at how increasing prices may be concentrated in certain households. By combining the consumption profiles of income quintiles with price deflators, we derive quintile-specific measures of price growth.
Here the results show a strong negative effect of income quintile on price growth. In almost all countries, lower income households face faster price growth than higher income households. Moreover, the changes are typically monotonic, with the price index consistently declining as household income rises.
At the same time, despite facing faster price growth, lower-income households in many cases do not experience lower growth in real consumption. This indicates increased expenditure at the bottom of the distribution relative to the top, with these higher prices absorbed by faster earnings growth, increased government transfers, or dissaving.
Summary
Our findings highlight the importance of incorporating distributional dimensions into the national accounts. Aggregate indicators alone can hide complex heterogeneity in household outcomes, which may result in more differentiated behaviour by households than headline figures would suggest.
At the same time, the analysis demonstrates the importance of retaining the national accounts framework when assessing material well-being. Incorporating STiK is essential for accurately evaluating the changes in material well-being experienced by households and making meaningful comparisons across countries.
Our estimates show that while material well-being does not exhibit a common relationship with income across all the countries in our sample, prices faced by households do. Poorer households commonly facing larger price increases than richer households, making it relatively more costly to maintain comparable growth in material well-being.
ESCoE blogs are published to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of ESCoE, its partner institutions, the Office for National Statistics, or the UK Endorsement Board.