On June 6, the U.S. Bureau of Labor Statistics (BLS) announced the economy added 217,000 jobs in May compared to an adjusted 282,000 jobs for April. The BLS original numbers for April were 288,000 jobs created with unemployment having fallen by .4% from 6.7% to 6.3%.
The April decline in unemployment may sound good. But, that’s not necessarily so because the April drop was caused primarily by 800,000 people leaving the workforce
At the end of May, the U.S. Bureau of Economic Analysis (BEA) restated GDP growth for the first quarter of this year from a meager 0.1% to a miserly -1.0%. But, that may not be so bad because many economists stated that that poor performance was caused by the bad weather in the first three months of the year and projected strong GDP growth for the remainder of the year.
This causes us to raise two questions about these and other government metrics: are the measures being used accurate and are the right things being measured?
The answer in both cases is somewhat and sometimes. That’s not an appropriate answer when government policy and decision-making and private sector investments and actions are frequently based on this data — or lack of it.
Zachary Karabell examines the fundamental flaws in our current “leading indicators” — the term economists give to the statistics in areas such as GDP, unemployment and the consumer price index (CPI) — in his new book, The Leading Indicators: A Short History of the Numbers that Rule Our World. In an essay for Foreign Affairs adapted from that book, Karabell highlights some of those deficiencies.
He notes that GDP does a relatively good job of measuring output and consumption. But, it: does not include “domestic work — cooking, cleaning, child rearing, and so on — counts all output or production and consumption as positive regardless of its nature (e.g., steel mills that pollute or industries that contribute to the carbon footprint); and, does nothing to measure social or economic well-being.
Karabell points out that in 1977 because the measures that were being used appeared to be overstating inflation, “government statisticians introduced the ‘core CPI’ which measures inflation without taking into account goods such as gasoline and food, whose prices change frequently.” If that seems like a faulty approach, consider what is not taken into account in the official unemployment rate as reported by the BLS.
The widely reported BLS unemployment rate in April of 6.3% is known formally as U-3. The U-3 for May stayed at 6.3%. That number does not include those who have given up looking for work or who are working in part-time jobs but would prefer to have full time employment.
The BLS captures and reports that number as U-6. That U-6 rate in April was 12.4%. The U-6 rate in May was 12.2%.
Paul Solman, PBS correspondent and economist, has developed his Solman Scale U-7 for tracking unemployment. According to his scale, the unemployment rate in April was 14.38%. His rate for May was actually higher at 14.46%.
Regardless of whether it’s U-6 or U-7, the fact is that these higher numbers, in conjunction with an imperfect CPI, and a GDP that was never meant to be a metric for economic well-being, help to explain that while government data in the aggregate indicates a slow but sluggish recovery over the past five years or so, it doesn’t feel that way to many Americans. The reason for this is simple.
These indicators do not measure factors that matter to them. Yet, these statistics dominate and control much of our national dialogue and debate about the state of the economy.
Today, GDP, CPI, and the U-3 unemployment rate among others are what are on the nation’s economic score card. They are insufficient measures to give us a holistic and accurate picture of what is really going on in the economy.
We need an enhanced and expanded score card that reflects the interests and concerns of the average citizen and our society in general. We need “a balanced score card” that incorporates the concepts of Individual Economic Well Being (IEW) and National Economic Welfare (NEW).
GDP was never intended to function as an indicator of well-being and GDP is insensitive to the distribution of income within a country. As Nobel Prize winning economist Joseph Stiglitz puts it, “No single measure can capture what is going on in a modern society, but the GDP measure fails in critical ways. We need measures that focus on how the typical individual is doing (measures of median income do lot better than measures of average income…”
We agree with Stiglitz, median income would be an important metric to incorporate into a construct to measure IEW. So, too would wage growth.
In a recent paper, David Blanchflower, an economics professor from Dartmouth and Adam S. Posen, president of the Peterson Institute for International Economics, posit that wage growth is the best measure for determining the health of the economy. Given this perspective, their viewpoint is that our economic recovery here in the United States will not take place until wages start to rise more quickly.
Wage growth over the past 12 months has been only 1.9%. When adjusted for inflation, that growth is a mere 0.5%. We’ve obviously got a very long way to go to achieve a full recovery.
While IEW would focus on dollars, NEW would provide a more comprehensive assessment of the economic and social health of the United States. There are a variety of approaches being employed to provide this sort of measurement today.
For example, the Organization for Economic Cooperation and Development employs the Better Life Index, the World Economic Forum uses a Global Competitiveness Index, and the Sustainable Development Solutions Network issues a World Happiness Report ranking countries around the globe using Gallup World Poll data. The measurement approach that we find most interesting, however, because it is being employed here in the United States by the state of Maryland is the Genuine Progress Indicator (GPI).
Maryland’s GPI consists of 26 indicators clustered in three broad categories: Economic Indicators, Environmental Indicators, and Social Indicators. It was constructed adhering to three underlying principles: account for income inequality; include non-market benefits not measured by GDP; and deduct “bads” such as environmental degradation and loss of leisure time.
We are not proposing using Maryland’s GPI or any of these other approaches in developing the NEW for the United States. We are advocating that economists from the public and private sectors come together to create better metrics that more fully tell the story of NEW and IEW so they can be used to flesh out the nation’s economic score card.
One might think we are tilting at windmills in making this proposal. We are pleased to say that we are not and that activity is already underway to improve our economic measurement system.
In an extended conversation on PBS’ Making Sen$e segment on April 29, Steve Landefeld, head of the Bureau of Economic Analysis, stated that the BEA is working with the Census Bureau to put out annual measures of median income and income distribution to supplement the GDP and hopes to have something in place by the end of this year.
Landefeld also indicated that the BEA was investigating other multiple indicator measures such as Maryland’s GPI. He was not as optimistic, however, regarding developing a measurement approach of this type because of the “subjectivity”, “self-reported” nature of some of the data, and “how to weight each indicator.
Nonetheless, Landefeld opined that “that research should continue.”
In our opinion, indeed it should. More importantly, it should be brought to a successful conclusion with the development and implementation of a NEW that the BEA or some other official government agency publishes for use in shaping public discourse and for policy-making purposes.
In conclusion, we must emphasize that an expanded and enhanced economic scorecard is just a beginning. That’s because data in the aggregate conceals as much as it reveals.
As Zachary Karabell observes in his Foreign Affairs article, “Employment trends vary dramatically by race, geography, gender and level of education. But none of that is reflected in the all encompassing unemployment rate…”
Because of this, although he is highly critical of the current system, Karabell does not recommend replacing it with a new framework or a set of new indicators. Rather, he advocates moving away from looking at a single number and employing a more tailored and micro-approach to data analysis, policy-making and solution development.
We concur with Karabell on the need for approaches of this type. But, in our nation where politicians and pundits will continue to be fixated on “big numbers” and single measures, that does not obviate the need to bring other numbers and measures into the line of sight so that they are discussed regularly and eventually become top of mind.
Years ago, Albert Einstein — someone who was pretty good with numbers — sagely advised, “Not everything that can be counted counts, and not everything that counts can be counted.” Einstein was correct.
We currently have a national system of leading indicators that does not include or count important things that can be counted. We need one that does.
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