GDP 2.0: Measuring who prospers when the U.S. economy grows
Gross Domestic Product, or GDP, is the one-number economic indicator that news anchors and senators alike love to dissect. Reading quarterly reports from the U.S. Department of Commerce’s Bureau of Economic Analysis on GDP growth is a form of divination that, in popular imagination, tells us whether the economic fortunes of the United States are trending up or down. Strong GDP growth is considered evidence of good fortune for all Americans under the presumption that “a rising tide lifts all boats.”
This presumption is mistaken. GDP growth may once have indicated good fortune for the vast majority of Americans, but over the past several decades, many Americans have been left behind amid long-term economic expansion. This reality makes GDP a misleading statistic for the opinion leaders and politicians who rely on it. The consequence is that policymakers’ diagnoses of the U.S. economy, and their prescriptions for what ails it, are based on the wrong metric.
The good news is that the data and the statistical know-how are now available to fix the problem. To reflect the true range of how people experience the economy, the Bureau of Economic Analysis, or BEA, can and should produce statistics that show income growth for Americans in different income brackets. These statistics will allow policymakers to evaluate how the economy is performing for the working class, the middle class, and the affluent.
GDP 2.0 is a policy proposal that will extend existing GDP reports, adding a distributional component, so we know not just how much the economy grew overall, but also how much incomes grew for those at the bottom, middle, and top of the income distribution. This column does not propose that policymakers toss out the U.S. National Income and Product Accounts, of which GDP is just one part, but rather that they modernize them to better reflect the realities of our 21st century economy. Each BEA report on GDP should come with measures of growth for each quintile of income earners, as well as measures of income growth at the very top of the income distribution, where the largest gains of the past several decades have been seen.
GDP 2.0 will have a significant impact on how economic policy is discussed and what economic policy is implemented. Specifically, it will:
- Connect the idea of aggregate economic data with the real-life circumstances of families in the economy
- Focus the attention of the nation on improvements in the economic well-being of families, which is what growth is supposed to deliver
- Guide policymakers in designing policies that produce broad-based growth
- Allow citizens to hold their elected representatives accountable to delivering an economy that works for all
This column explains why GDP has become less valuable since 1980, why measurement is an important first step for better policy, and the current status of progress toward GDP 2.0.
Who benefits from economic growth?
The National Income and Product Accounts were devised in the 1930s, the result of a concerted effort by many economists to better quantify economic output. Simon Kuznets was primarily responsible for their development in the United States and later won a Nobel Prize in economics for his work. Gross Domestic Product, a part of those accounts, was a tool well-adapted to the economic problems of mid-20th century America. It allowed economic policymakers to understand the vast depth of the Depression and highlighted the need for bold action. Similarly, it served as a guide in World War II, providing some indication of how many planes and boats and tanks we might plausibly manufacture if the full resources of the nation were focused on the task.
These are no longer the economic questions the nation needs answered. In an era where inequality has swelled to levels approaching the Roaring Twenties, elected officials need to know who is prospering from economic progress so they can manage the economy for broad-based growth that benefits all Americans. This need is acute now, because headline GDP growth has become unmoored from the economic fortunes of many Americans.
Growth was equitably distributed between 1963 and 1979. Americans at all levels of income saw annual growth that was at or above the level of total GDP growth, unless they were among the very richest. But starting around 1980, this relationship began to change. In the decades since 1980, the vast majority of Americans have seen growth in their own incomes that is below GDP growth. This is possible thanks to the extremely high growth enjoyed by the most affluent Americans over this time period. (See Figure 1.)
This divergence between the average and the actual fortunes of families is a problem Kuznets warned about in one of his very first publications on the subject of national accounts. In a section of his report to Congress titled “Uses and Abuses of National Income Measurements,” he noted that, “The welfare of a nation can, therefore, scarcely be inferred from a measurement of national income.”
This divergence makes GDP increasingly misleading as a guide to public policy: It does little good to target GDP as an outcome if the majority of GDP growth flows to a small group of families, leaving the rest with scraps. Despite this, politicians continue to fetishize GDP growth, and pundits encourage them. The Trump administration made a campaign issue out of targeting 3 percent growth and sometimes promised to achieve much higher growth.
Figure 2 shows how growth has been split in recent recessions and expansions. In recent expansions, the top 10 percent of income earners have taken around 50 percent of all economic growth.
The pattern of growth shown in both Figure 1 and Figure 2 has serious downstream consequences. To take just one significant example, Harvard University economist Raj Chetty and his colleagues have demonstrated that absolute intergenerational income mobility has declined precipitously in the United States, and that two-thirds of this decline can be attributed to unequal patterns of growth.
Chetty finds that children in American used to have a 90 percent chance of earning more than their parents did, comparing parents at age 30 to children at age 30. But by 1980, the chances had dropped to just 50 percent. This is partially due to lower average growth in the decades since 1980, but Chetty’s research finds that it is primarily caused by most income growth accruing to the high end of the income distribution. (See Figure 3.)
How does measurement mold policy?
The measurements at the center of national policy debates affect both what policies are discussed and what policies are adopted. A central conceit of many recent policy battles is that growth is an unalloyed good, worth targeting without regard for other considerations. The Tax Cuts and Jobs Act of 2017 was sold on exactly these grounds by its biggest proponents.
But claims about economic growth are nearly useless without the relevant context that most growth in our modern economy accrues to the highest income earners in society. With that bit of context, it becomes difficult to understand why policymakers should be targeting growth at all. Surely we should instead look at distributional tables that tell us how people in particular income brackets will be affected by the tax, as Equitable Growth has advocated. As Figure 4 shows (see below), trumpeting the impact of the Tax Cuts and Jobs Act on growth only serves to obscure what the distributional table shows: The 2-year-old law will raise the incomes of the wealthiest Americans over the next 8 years and will do little for those at the bottom.
Targeting a common, available metric without adequate consideration of context can lead people down strange paths. An oft-repeated example is US News & World Report’s annual Best Colleges rankings. These ratings so dominated the public imagination that colleges became obsessed with improving their ratings. Since the ratings were based on a small set of measurable outcomes, such as graduation rate, class size, and admissions selectivity, colleges quickly found ways to improve their ratings by changing their practices.
Baylor University, for example, offered financial incentives to freshmen to retake the SAT, raising their incoming class average and their ranking. Multiple colleges gave falsified data to US News. Some schools hired their own graduates to boost graduate employment metrics. These and other attempts to game the system forced US News to rethink how they compile the statistics, but problems persist.
This college rankings example shows that measurement shapes outcomes. The metrics that are collected shape the policy options that elected officials consider. Terms of public debate over economic policy are likewise shaped by the available indicators. The U.S. economy has changed enormously since Kuznets first devised the National Accounts in the 1930s. Managing our complicated modern economy requires more context. It requires GDP 2.0.
GDP 2.0: Measuring who prospers when the U.S. economy grows
Academic economists have already provided a working prototype of what GDP 2.0 might look like. Thomas Piketty at the Paris School of Economics, and Emmanuel Saez and Gabriel Zucman, both at the University of California, Berkeley, have published a public dataset they call Distributional National Accounts that uses U.S. tax data to measure the distribution of income in the United States from 1962 onward. Most of the charts in this column use their dataset, without which these analyses of inequality in the country would not be possible.
But academic datasets are not a long-term solution for the problem. Government statistics are produced on reliable schedules, using standardized methodologies and the best available data. A distributional measure of growth presented alongside the headline GDP growth number would make the report more meaningful to American families who are not currently well-represented by overall GDP growth.
And GDP 2.0 statistics would help facilitate the diagnosis of a real and concerning phenomenon in the economy—increases in inequality that could presage weakness in future consumer spending, indicate falling income mobility, and indicate that the economy is not working for every American.
GDP 2.0: Coming soon
Creating a distributional component in the National Accounts is well underway at the Bureau of Economic Analysis, thanks to interest from the broader economic community and pressure from Congress. In 2018, Sens. Charles Schumer (D-NY) and Martin Heinrich (D-NM) and Rep. Carolyn Maloney (D-NY) introduced the Measuring Real Income Growth Act of 2018 in both chambers. The Senate bill garnered 24 co-sponsors.
This initial legislative action has been followed by a flurry of further congressional interest. In March 2019, the conference report accompanying the Consolidated Appropriations Act of 2019 included a clause instructing BEA to report income growth within deciles of income starting in 2020. In their appropriations bill for the Department of Commerce for fiscal year 2020, House appropriators instructed the agency to report on its progress toward the FY2019 appropriations language.
Most recently, Senate appropriators allocated $1 million to the effort. Sens. Schumer and Heinrich and Rep. Maloney further wrote to BEA Director Brian Moyer to ask what resources BEA needs to begin producing distributional statistics. In his answer, Commerce Secretary Wilbur Ross indicated that BEA plans to produce prototype statistics and take public comment on them in 2020.
Measure what matters
The metrics that policymakers use to evaluate the U.S. economy are reflective of what type of success we, as a nation, value. If realizing the promise of the American Dream is important, then adopting GDP 2.0 will align our economic policies with our values. Adding this crucial context to our National Income and Product Accounts is not just a bookkeeping exercise. It’s a way to set new economic goals and guideposts. Without these guideposts, we cannot achieve strong, stable, and broad-based economic growth.