Now we’ve created Inclusive Income, what do we do with it? 

By Richard Heys

Measuring wealth is crucial to get a better idea about the state and progress of an economy. Many people are familiar with Gross Domestic Product (GDP), a commonly used economic measure of national output. However, whilst GDP provides useful insights, it tells only part of our economic story.

Inclusive Income refers to estimates and analysis of economic progress which encompass a broader range of economic activities and assets than GDP does. It includes unpaid household services, ecosystem services, and more.

Today we publish a summary which brings together our historic releases on Inclusive Income and tries to give our single, best articulation of the methods we’ve developed. 

But standing back, for anyone new to the topic, a technical article won’t provide simple answers to some of the entry-level questions: why did we create Inclusive Income and how are users meant to interpret and use these new statistics? 

Why do we need these data?

• ‘Beyond GDP’ literature explains that it makes little sense to use existing headline economic measures, such as GDP, to understand issues which relate to social or environment issues. GDP is deliberately designed to not address these.        
  
  
• It also makes little sense to use GDP to understand issues which relate to many ‘new’ economic issues. GDP is deliberately scoped to omit a range of services received by households or various types of assets, which fundamentally affect decisions which once were of low priority to policy-makers. For instance, accurately assessing the value of human capital, currently excluded from National Accounts, requires a broader set of metrics. This allows for meaningful comparisons with other forms of capital, enabling informed decisions about structural investments within a capital-rich economy.
  
  
• It also makes little sense to use GDP to understand traditional economic issues, when part of the challenge can be the movement of activities between those objects in scope of GDP and those which are not.
  
  For example, many economists have built careers out of trying to understand why UK productivity has been so weak for the past fifteen years, particularly at a time when technological innovation is so obvious and apparent. These data allow us to see that innovation hasn’t stopped leading to productivity improvement. However,this is because innovation has been reducing carbon emissions, which are excluded from GDP, rather than increasing output, which is included in GDP. Once we can include the value of reduced carbon emissions, based on UK carbon prices and published volumes, the productivity puzzle vanishes. We are living through a period of technology transition where innovation is replacing old ‘dirty’ technology with new ‘clean’ technology, but often without any additional output/far less output.
  
  This dataset reveals a critical limitation of using GDP alone to solve the productivity puzzle: if I lose my phone in either the kitchen or the dining room, it doesn’t matter how many times I look in the kitchen, the answer may be in the dining room. Focusing solely on GDP provides an incomplete picture.

How should users understand and use these data?

Very simply, in conjunction with the wider dataset available from ONS. The productivity example above needs a consideration of both GDP and Inclusive Income estimates to give you a full vision of the problem. That’s why we argue these new metrics are complementary to GDP and the traditional headlines. 

For example, Inclusive Income might help you understand what government may wish to spend money on. GDP can then inform you about the taxable base of the economy and therefore budget constraint – how much money does the government have to spend on its priorities and what is the best way to do this?         

We would argue for maintaining and building upon some of the core strengths of GDP; developing coherent, consistent underlying accounts, and using these to derive consistent, long time series. To achieve this, we have brought together the best data we have available in the UK. However, we need your help to interrogate these data, identify key insights and determine the most effective methods for interpreting the evolving metrics.

Understanding trade-offs

We suggest that a core part of economics is the understanding of trade-offs between resources and uses. This requires the resources and uses to be measured in a consistent way. This is as true for cost benefit analysis as it is for macroeconomic modelling. GDP is useful because wages and profits are bought together comparably to tell us whether income as a whole grew. Similarly, Inclusive Income brings together paid and unpaid work so we can understand whether a shift in the nature of economic activity (for example, from households driving cars themselves to using ride-hailing apps) has increased total resources in the UK or just shifted where those resources are created. The underlying accounts of Gross and Net Inclusive Income are equally crucial to the aggregates themselves, as they illuminate the intricate flows of resources throughout the economy, encompassing both paid and unpaid contributions.

Similarly, when considering policy interventions, it is vitally important to understand the associated trade-offs. The Inclusive Income Accounts are useful for understanding how best to ‘reactivate’ the economically inactive, in a way which best increases resources. By incorporating unpaid household work, we can more effectively analyse the trade-offs faced by economically inactive individuals who leave unpaid care or volunteer roles to re-enter the labour market. We can also better understand how a widened understanding of capital and wealth may have impacted on this decision for certain groups.         

Ultimately, data and statistics serve two purposes – answering questions but also helping people ask better questions. As this article and the corresponding statistics from ONS show, we are now at the stage where we are beginning to provide fresh perspectives. This is allowing us tounlock newinsights and, move key debates forward.  

This links with ESCoE work on Beyond GDP and inclusive wealth.

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 the ESCoE, its partner institutions or the Office for National Statistics.