The “True” Unemployment Rate Is the One BLS Releases Every Month*, But It’s Not the One “True” Measure of Labor Market Slack
Yesterday we released a new monthly labor market indicator, an estimate of the number of “missing workers” (potential workers who are not working or looking for work because the job market is currently so weak). We also generated another new measure—what the unemployment rate would be if these missing workers were classified by the Bureau of Labor Statistics as actively looking for work (see below figure). As of the latest data available, August 2013, there were nearly 5 million missing workers. If these workers were actively looking for work, the unemployment rate would be 10.1 percent, not 7.3 percent.
Many have asked me if I think this augmented unemployment rate is the “true” or “real” unemployment rate, so I thought it’d be useful to clarify: The unemployment rate that BLS puts out is the true unemployment rate, and there are good reasons for the BLS to use the definitions it does. But the official unemployment rate is not currently the best measure of changes in the health of the labor market.
In other words, no, I don’t think my new measure is the “true” unemployment rate, but in today’s economy, I do think it’s a better measure than the unemployment rate for gauging trends in job opportunities and the overall health of the labor market
Technically speaking, my measure is the unemployment rate plus the “participation gap” (the participation gap is the cyclical decline in the labor force participation rate, i.e. the decline in participation that is due to the weak labor market, not other trends like retiring baby boomers). In other words, unlike the unemployment rate, this measure accounts for a key component of slack in today’s labor market—the fact that many workers have dropped out of, or never entered, the labor force primarily because job opportunities are so weak. The unemployment rate misses this piece entirely because jobless workers are only counted as unemployed if they are actively seeking work. If policymakers or commentators want the best gauge of trends in the health of today’s labor market and how much productive slack exists in the economy, they should not be looking at the unemployment rate, they should be looking at this (or some other measure uninfected by cyclical changes in participation, like the employment to population ratio of prime-aged workers).
* Potential workers who, due to weak job opportunities, are neither employed nor actively seeking work Source: EPI analysis of Mitra Toossi, “Labor Force Projections to 2016: More Workers in Their Golden Years,” Bureau of Labor Statistics Monthly Labor Review, November 2007; and Current Population Survey public data seriesThe unemployment rate is vastly understating weakness in today's labor market: Unemployment rate, actual and if missing workers* were looking for work, January 2006–July 2014
Date
Actual
If missing workers were looking for work
2006-01-01
4.7%
5.0%
2006-02-01
4.8%
4.8%
2006-03-01
4.7%
4.8%
2006-04-01
4.7%
4.9%
2006-05-01
4.6%
4.8%
2006-06-01
4.6%
4.7%
2006-07-01
4.7%
4.8%
2006-08-01
4.7%
4.6%
2006-09-01
4.5%
4.6%
2006-10-01
4.4%
4.4%
2006-11-01
4.5%
4.4%
2006-12-01
4.4%
4.1%
2007-01-01
4.6%
4.4%
2007-02-01
4.5%
4.4%
2007-03-01
4.4%
4.3%
2007-04-01
4.5%
4.9%
2007-05-01
4.4%
4.8%
2007-06-01
4.6%
4.8%
2007-07-01
4.7%
4.9%
2007-08-01
4.6%
5.1%
2007-09-01
4.7%
4.9%
2007-10-01
4.7%
5.2%
2007-11-01
4.7%
4.9%
2007-12-01
5.0%
5.1%
2008-01-01
5.0%
4.8%
2008-02-01
4.9%
5.0%
2008-03-01
5.1%
5.1%
2008-04-01
5.0%
5.2%
2008-05-01
5.4%
5.4%
2008-06-01
5.6%
5.6%
2008-07-01
5.8%
5.7%
2008-08-01
6.1%
6.0%
2008-09-01
6.1%
6.3%
2008-10-01
6.5%
6.5%
2008-11-01
6.8%
7.1%
2008-12-01
7.3%
7.5%
2009-01-01
7.8%
8.2%
2009-02-01
8.3%
8.7%
2009-03-01
8.7%
9.3%
2009-04-01
9.0%
9.4%
2009-05-01
9.4%
9.7%
2009-06-01
9.5%
9.9%
2009-07-01
9.5%
10.1%
2009-08-01
9.6%
10.4%
2009-09-01
9.8%
10.9%
2009-10-01
10.0%
11.3%
2009-11-01
9.9%
11.2%
2009-12-01
9.9%
11.7%
2010-01-01
9.7%
11.3%
2010-02-01
9.8%
11.4%
2010-03-01
9.9%
11.3%
2010-04-01
9.9%
11.0%
2010-05-01
9.6%
11.1%
2010-06-01
9.4%
11.1%
2010-07-01
9.5%
11.3%
2010-08-01
9.5%
11.1%
2010-09-01
9.5%
11.3%
2010-10-01
9.5%
11.5%
2010-11-01
9.8%
11.7%
2010-12-01
9.4%
11.6%
2011-01-01
9.1%
11.4%
2011-02-01
9.0%
11.4%
2011-03-01
9.0%
11.3%
2011-04-01
9.1%
11.4%
2011-05-01
9.0%
11.4%
2011-06-01
9.1%
11.5%
2011-07-11
9.0%
11.7%
2011-08-20
9.0%
11.4%
2011-09-01
9.0%
11.3%
2011-10-11
8.8%
11.2%
2011-11-20
8.6%
11.0%
2011-12-30
8.5%
11.0%
2012-01-12
8.2%
10.8%
2012-02-12
8.3%
10.7%
2012-03-12
8.2%
10.7%
2012-04-12
8.2%
10.9%
2012-05-12
8.2%
10.6%
2012-06-12
8.2%
10.5%
2012-07-12
8.2%
10.8%
2012-08-12
8.1%
10.8%
2012-09-12
7.8%
10.4%
2012-10-12
7.8%
10.0%
2012-11-12
7.8%
10.3%
2012-12-12
7.9%
10.3%
2013-01-12
7.9%
10.4%
2013-02-12
7.7%
10.5%
2013-03-12
7.5%
10.6%
2013-04-12
7.5%
10.5%
2013-05-12
7.5%
10.3%
2013-06-12
7.5%
10.3%
2013-07-12
7.3%
10.2%
2013-08-12
7.2%
10.3%
2013-09-12
7.2%
10.3%
2013-10-12
7.2%
10.7%
2013-11-12
7.0%
10.3%
2013-12-12
6.7%
10.2%
2014-01-12
6.6%
10.0%
2014-02-12
6.7%
10.0
2014-03-12
6.7%
9.8%
2014-04-12
6.3%
9.9%
2014-05-12
6.3%
9.7%
2014-06-12
6.1%
9.6%
2014-07-12
6.2%
9.6%
*That is, every month the federal government is not shut down.
New EPI Economic Indicator: Monthly Updates of the Number of “Missing Workers” and What the Unemployment Rate Would Be If They Were Looking for Work
More than four years since the Great Recession officially ended in June 2009, the unemployment rate stands at 7.3 percent. This is still a percentage point above the highest unemployment rate of the early 2000s downturn, 6.3 percent. However, 7.3 percent is a big improvement from the high of 10.0 percent in the fall of 2009. Unfortunately, most of that improvement was for all the wrong reasons.
In today’s labor market, the unemployment rate drastically understates the weakness of job opportunities. This is because in the weak labor market of the aftermath of the Great Recession, there are a huge number of “missing workers”—potential workers who are neither employed nor actively seeking work simply because job opportunities remain so scarce. Because jobless workers are only counted as unemployed if they are actively seeking work, these missing workers are not reflected in the unemployment rate.
As part of its ongoing effort to create the metrics needed to assess how well the economy is working for America’s broad middle class, EPI is introducing its “missing workers” estimate. Our estimate shows there are currently nearly 5 million missing workers. These are workers who would be in the labor force if job opportunities were significantly expanded but, given the state of the labor market, are sidelined.
Exactly how many missing workers macroeconomic policymakers believe there are has enormous implications for their assessment of the strength of the job market, and therefore for their policy decisions. For example, if they underestimate the number of missing workers, they will overstate the strength of the labor market, and be less likely to provide the economy with the support it needs. As shown in the figure below, if the nearly 5 million missing workers were looking for work and thus counted as unemployed, the unemployment rate in August would have been 10.1 percent instead of 7.3 percent.
The unemployment rate is vastly understating weakness in today's labor market: Unemployment rate, actual and if missing workers* were looking for work, January 2006–July 2014
| Date | Actual | If missing workers were looking for work |
|---|---|---|
| 2006-01-01 | 4.7% | 5.0% |
| 2006-02-01 | 4.8% | 4.8% |
| 2006-03-01 | 4.7% | 4.8% |
| 2006-04-01 | 4.7% | 4.9% |
| 2006-05-01 | 4.6% | 4.8% |
| 2006-06-01 | 4.6% | 4.7% |
| 2006-07-01 | 4.7% | 4.8% |
| 2006-08-01 | 4.7% | 4.6% |
| 2006-09-01 | 4.5% | 4.6% |
| 2006-10-01 | 4.4% | 4.4% |
| 2006-11-01 | 4.5% | 4.4% |
| 2006-12-01 | 4.4% | 4.1% |
| 2007-01-01 | 4.6% | 4.4% |
| 2007-02-01 | 4.5% | 4.4% |
| 2007-03-01 | 4.4% | 4.3% |
| 2007-04-01 | 4.5% | 4.9% |
| 2007-05-01 | 4.4% | 4.8% |
| 2007-06-01 | 4.6% | 4.8% |
| 2007-07-01 | 4.7% | 4.9% |
| 2007-08-01 | 4.6% | 5.1% |
| 2007-09-01 | 4.7% | 4.9% |
| 2007-10-01 | 4.7% | 5.2% |
| 2007-11-01 | 4.7% | 4.9% |
| 2007-12-01 | 5.0% | 5.1% |
| 2008-01-01 | 5.0% | 4.8% |
| 2008-02-01 | 4.9% | 5.0% |
| 2008-03-01 | 5.1% | 5.1% |
| 2008-04-01 | 5.0% | 5.2% |
| 2008-05-01 | 5.4% | 5.4% |
| 2008-06-01 | 5.6% | 5.6% |
| 2008-07-01 | 5.8% | 5.7% |
| 2008-08-01 | 6.1% | 6.0% |
| 2008-09-01 | 6.1% | 6.3% |
| 2008-10-01 | 6.5% | 6.5% |
| 2008-11-01 | 6.8% | 7.1% |
| 2008-12-01 | 7.3% | 7.5% |
| 2009-01-01 | 7.8% | 8.2% |
| 2009-02-01 | 8.3% | 8.7% |
| 2009-03-01 | 8.7% | 9.3% |
| 2009-04-01 | 9.0% | 9.4% |
| 2009-05-01 | 9.4% | 9.7% |
| 2009-06-01 | 9.5% | 9.9% |
| 2009-07-01 | 9.5% | 10.1% |
| 2009-08-01 | 9.6% | 10.4% |
| 2009-09-01 | 9.8% | 10.9% |
| 2009-10-01 | 10.0% | 11.3% |
| 2009-11-01 | 9.9% | 11.2% |
| 2009-12-01 | 9.9% | 11.7% |
| 2010-01-01 | 9.7% | 11.3% |
| 2010-02-01 | 9.8% | 11.4% |
| 2010-03-01 | 9.9% | 11.3% |
| 2010-04-01 | 9.9% | 11.0% |
| 2010-05-01 | 9.6% | 11.1% |
| 2010-06-01 | 9.4% | 11.1% |
| 2010-07-01 | 9.5% | 11.3% |
| 2010-08-01 | 9.5% | 11.1% |
| 2010-09-01 | 9.5% | 11.3% |
| 2010-10-01 | 9.5% | 11.5% |
| 2010-11-01 | 9.8% | 11.7% |
| 2010-12-01 | 9.4% | 11.6% |
| 2011-01-01 | 9.1% | 11.4% |
| 2011-02-01 | 9.0% | 11.4% |
| 2011-03-01 | 9.0% | 11.3% |
| 2011-04-01 | 9.1% | 11.4% |
| 2011-05-01 | 9.0% | 11.4% |
| 2011-06-01 | 9.1% | 11.5% |
| 2011-07-11 | 9.0% | 11.7% |
| 2011-08-20 | 9.0% | 11.4% |
| 2011-09-01 | 9.0% | 11.3% |
| 2011-10-11 | 8.8% | 11.2% |
| 2011-11-20 | 8.6% | 11.0% |
| 2011-12-30 | 8.5% | 11.0% |
| 2012-01-12 | 8.2% | 10.8% |
| 2012-02-12 | 8.3% | 10.7% |
| 2012-03-12 | 8.2% | 10.7% |
| 2012-04-12 | 8.2% | 10.9% |
| 2012-05-12 | 8.2% | 10.6% |
| 2012-06-12 | 8.2% | 10.5% |
| 2012-07-12 | 8.2% | 10.8% |
| 2012-08-12 | 8.1% | 10.8% |
| 2012-09-12 | 7.8% | 10.4% |
| 2012-10-12 | 7.8% | 10.0% |
| 2012-11-12 | 7.8% | 10.3% |
| 2012-12-12 | 7.9% | 10.3% |
| 2013-01-12 | 7.9% | 10.4% |
| 2013-02-12 | 7.7% | 10.5% |
| 2013-03-12 | 7.5% | 10.6% |
| 2013-04-12 | 7.5% | 10.5% |
| 2013-05-12 | 7.5% | 10.3% |
| 2013-06-12 | 7.5% | 10.3% |
| 2013-07-12 | 7.3% | 10.2% |
| 2013-08-12 | 7.2% | 10.3% |
| 2013-09-12 | 7.2% | 10.3% |
| 2013-10-12 | 7.2% | 10.7% |
| 2013-11-12 | 7.0% | 10.3% |
| 2013-12-12 | 6.7% | 10.2% |
| 2014-01-12 | 6.6% | 10.0% |
| 2014-02-12 | 6.7% | 10.0 |
| 2014-03-12 | 6.7% | 9.8% |
| 2014-04-12 | 6.3% | 9.9% |
| 2014-05-12 | 6.3% | 9.7% |
| 2014-06-12 | 6.1% | 9.6% |
| 2014-07-12 | 6.2% | 9.6% |
* Potential workers who, due to weak job opportunities, are neither employed nor actively seeking work
Source: EPI analysis of Mitra Toossi, “Labor Force Projections to 2016: More Workers in Their Golden Years,” Bureau of Labor Statistics Monthly Labor Review, November 2007; and Current Population Survey public data series
Estimating the number of missing workers is not straightforward because some changes in labor force participation over the last five years have nothing at all to do with the weak labor market (for example, baby boomers beginning to reach retirement age). Our estimate of the number of missing workers isolates the cyclical component of the decline in the labor force participation rate since the start of the Great Recession. In other words, it counts just those missing workers who would be in the labor force if job opportunities were strong. It doesn’t count, for example, those retiring baby boomers who would have left the labor force whether or not the Great Recession happened.1
We will update these estimates on the first Friday of every month immediately after the Bureau of Labor Statistics releases the monthly jobs numbers. In particular, we will update the following three figures each month at EPI’s Missing Workers page:
1. The trend in the total number of missing workers, currently nearly 5 million:
Millions of potential workers sidelined: Missing workers,* January 2006–July 2014
| Date | Missing workers |
|---|---|
| Jan-2006 | 530,000 |
| Feb-2006 | 110,000 |
| Mar-2006 | 110,000 |
| Apr-2006 | 250,000 |
| May-2006 | 210,000 |
| Jun-2006 | 110,000 |
| Jul-2006 | 60,000 |
| Aug-2006 | -120,000 |
| Sep-2006 | 120,000 |
| Oct-2006 | -50,000 |
| Nov-2006 | -220,000 |
| Dec-2006 | -500,000 |
| Jan-2007 | -460,000 |
| Feb-2007 | -210,000 |
| Mar-2007 | -150,000 |
| Apr-2007 | 650,000 |
| May-2007 | 560,000 |
| Jun-2007 | 360,000 |
| Jul-2007 | 370,000 |
| Aug-2007 | 840,000 |
| Sep-2007 | 410,000 |
| Oct-2007 | 800,000 |
| Nov-2007 | 280,000 |
| Dec-2007 | 250,000 |
| Jan-2008 | -320,000 |
| Feb-2008 | 220,000 |
| Mar-2008 | 50,000 |
| Apr-2008 | 340,000 |
| May-2008 | -60,000 |
| Jun-2008 | 20,000 |
| Jul-2008 | -70,000 |
| Aug-2008 | -90,000 |
| Sep-2008 | 180,000 |
| Oct-2008 | 60,000 |
| Nov-2008 | 420,000 |
| Dec-2008 | 420,000 |
| Jan-2009 | 710,000 |
| Feb-2009 | 620,000 |
| Mar-2009 | 1,050,000 |
| Apr-2009 | 750,000 |
| May-2009 | 650,000 |
| Jun-2009 | 650,000 |
| Jul-2009 | 1,040,000 |
| Aug-2009 | 1,320,000 |
| Sep-2009 | 2,050,000 |
| Oct-2009 | 2,270,000 |
| Nov-2009 | 2,300,000 |
| Dec-2009 | 3,120,000 |
| Jan-2010 | 2,770,000 |
| Feb-2010 | 2,680,000 |
| Mar-2010 | 2,460,000 |
| Apr-2010 | 1,940,000 |
| May-2010 | 2,510,000 |
| Jun-2010 | 2,960,000 |
| Jul-2010 | 3,210,000 |
| Aug-2010 | 2,830,000 |
| Sep-2010 | 3,200,000 |
| Oct-2010 | 3,570,000 |
| Nov-2010 | 3,340,000 |
| Dec-2010 | 3,830,000 |
| Jan-2011 | 3,950,000 |
| Feb-2011 | 4,080,000 |
| Mar-2011 | 3,960,000 |
| Apr-2011 | 4,020,000 |
| May-2011 | 4,070,000 |
| Jun-2011 | 4,220,000 |
| Jul-2011 | 4,650,000 |
| Aug-2011 | 4,130,000 |
| Sep-2011 | 3,970,000 |
| Oct-2011 | 4,010,000 |
| Nov-2011 | 4,150,000 |
| Dec-2011 | 4,230,000 |
| Jan-2012 | 4,490,000 |
| Feb-2012 | 4,120,000 |
| Mar-2012 | 4,220,000 |
| Apr-2012 | 4,690,000 |
| May-2012 | 4,190,000 |
| Jun-2012 | 4,070,000 |
| Jul-2012 | 4,540,000 |
| Aug-2012 | 4,690,000 |
| Sep-2012 | 4,480,000 |
| Oct-2012 | 3,840,000 |
| Nov-2012 | 4,400,000 |
| Dec-2012 | 4,180,000 |
| Jan-2013 | 4,370,000 |
| Feb-2013 | 4,700,000 |
| Mar-2013 | 5,240,000 |
| Apr-2013 | 5,130,000 |
| May-2013 | 4,780,000 |
| Jun-2013 | 4,710,000 |
| Jul-2013 | 5,050,000 |
| Aug-2013 | 5,230,000 |
| Sep-2013 | 5,380,000 |
| Oct-2013 | 6,060,000 |
| Nov-2013 | 5,710,000 |
| Dec-2013 | 6,100,000 |
| Jan-2014 | 5,850,000 |
| Feb-2014 | 5,660,000 |
| Mar-2014 | 5,290,000 |
| Apr-2014 | 6,220,000 |
| May-2014 | 5,950,000 |
| Jun-2014 | 5,980,000 |
| Jul-2014 | 5,860,000 |
* Potential workers who, due to weak job opportunities, are neither employed nor actively seeking work
Note: Volatility in the number of missing workers in 2006–2008, including cases of negative numbers of missing workers, is simply the result of month-to-month variability in the sample. The Great Recession–induced pool of missing workers began to form and grow starting in late 2008.
Source: EPI analysis of Mitra Toossi, “Labor Force Projections to 2016: More Workers in Their Golden Years,” Bureau of Labor Statistics Monthly Labor Review, November 2007; and Current Population Survey public data series
2. The breakdown of missing workers by gender and age, showing most missing workers are of prime working age:
Roughly half of missing workers are of prime working age: Missing workers,* by age and gender, July 2014
| Missing workers | |
|---|---|
| Men under 25 | 630,000 |
| Women under 25 | 420,000 |
| Men 25–54 | 1,850,000 |
| Women 25–54 | 1,380,000 |
| Men 55+ | 580,000 |
| Women 55+ | 1,000,000 |
* Potential workers who, due to weak job opportunities, are neither employed nor actively seeking work
Source: EPI analysis of Mitra Toossi, “Labor Force Projections to 2016: More Workers in Their Golden Years,” Bureau of Labor Statistics Monthly Labor Review, November 2007; and Current Population Survey public data series
3. The earlier figure depicting what the unemployment rate would be if the missing workers were looking for jobs.
Methodology
1. How do we estimate the number of missing workers? Labor force participation rate projections published by the Bureau of Labor Statistics in November 2007—before the start of the Great Recession—are available in Table 3 of Mitra Toossi, “Labor Force Projections to 2016: More Workers in Their Golden Years,” Bureau of Labor Statistics Monthly Labor Review, November 2007. The projections assumed a healthy labor market over the period in question, 2006–2016, so the participation rate changes it forecasts reflect purely non-cyclical factors (e.g., the impact of retiring baby boomers). The difference between these projections and the actual labor force participation rate is thus a good measure of the cyclical change in the labor force participation rate, i.e., the change that is a direct result of the weak labor market in the Great Recession and its aftermath. Based on this logic, missing workers are estimated in the following way: The labor force participation rate projections for 2016 by gender and age group (age groups 16–19, 20–24, 25–34, 35–44, 45–54, 55+) available in Table 3 of Toossi (2007) are assumed to be structural rates. The current month’s structural rates (by gender and age group) are calculated by linearly interpolating between 2006 and 2016. The size of the potential labor force is calculated by multiplying the current month’s structural rates by actual population numbers (available by gender and age group from the Current Population Survey public data series). The difference between the size of the potential labor force and size of the actual labor force (also available by gender and age group from the Current Population Survey public data series) is the number of missing workers.
There They Go Again: More Political Theater
Just a few weeks ago, budget deliberations centered around a “grand bargain,” in which Democrats would get some loosening of the austere discretionary budget caps (ie, the “sequester”) and an increase in the nation’s statutory debt ceiling in exchange for cuts to mandatory spending programs (such as Social Security and Medicare). While objectionable, this script at least made some logical sense in a debate over budgets. But as the beginning of the new fiscal year approached with no budget and a breach of the debt ceiling not far behind, House Republicans decided to force a government shutdown “to get something out of this,” though as Rep. Marlin Stutzman (R-Ind.) acknowledged, it’s unclear “what that even is.” At first, it appeared they were going to demand mandatory spending cuts as the condition to pass a continuing resolution (CR) and demand some changes to Obamacare as the condition for raising the debt ceiling. In the end, the Tea Party pressured the House Republican leadership to tie defunding Obamacare to passing even a 2-month CR. As a result, the government has been shut down since October 1.
Does “Poverty” Cause Low Achievement?
On her “Bridging Differences” blog, educator Deborah Meier began a discussion with Mike Petrilli of the Thomas B. Fordham Institute, on whether urging disadvantaged women to defer childbearing until they had sufficient income (whether from work or marriage) to adequately support their offspring would result in better outcomes for those children. This, in turn, led to an extended discussion (not on the blog, but widely circulated among some education policy experts and commentators by e-mail) about whether alleviating poverty would raise student achievement, whether alleviating poverty through tax reform or income redistribution might be effective for that purpose, whether poor children in the United States have worse outcomes than poor children in other countries, what the best way might be to calculate poverty levels across countries, and whether school reform in the absence of alleviating poverty can be significantly effective.
The shortcoming of this discussion is that because Americans are averse to acknowledging the concept of social class and hold to a widely shared myth of unrestricted mobility (that is less and less reflective of reality), we tend to use the term “poverty” as a proxy for lower social class status. This shortcut causes great mischief in educational policy. Lower class children are not only characterized by having families with low current money income; they also have a collection of interacting characteristics, each of which affects the ability to learn.
Years ago, the Heritage Foundation published a report called No Excuses, by Samuel Casey Carter. Among others, one school it found enrolled a majority of children who were eligible for subsidized lunches yet who still had high achievement. According to the report, this (along with other, equally flawed examples) proved that poverty is no bar to high achievement. The school in question was in Cambridge, Massachusetts, and it turned out that the students mostly had parents who were graduate students at Harvard or MIT, whose stipends were low enough that their children were eligible for the lunch program.
Who, Exactly, Has Benefited from Mississippi’s Anti-Unionism? Not Its Workers.
In a New York Times article about a drive led by the United Automobile Workers (UAW) to unionize Nissan’s workforce at a factory in Canton, Mississippi, various local businessmen are quoted extolling the value to Mississippi of being a “right-to-work state” and maintaining a “non-union environment.” Given the economic condition of Mississippi, one has to wonder who, exactly, has benefited from Mississippi’s anti-unionism.
Mississippi has been a “right-to-work” state for nearly 60 years, plenty of time to benefit from its non-union environment, but its per capita income in 2012 was the lowest in the United States—not just low, but dead last.
Mississippi has the highest poverty rate in the nation, as well. 1 out of 5 Mississippi households has income beneath the official poverty line. (“Right-to-work” seems to be associated with high poverty since 9 of the 10 highest poverty states are “right-to-work.”)
Does the future look brighter? Not much. In terms of education, Mississippi is at the bottom again, ranking last in test scores on the gold standard National Assessment of Education Progress. Mississippi is the only state in which fewer than 1 out of 5 eight graders is proficient in math and reading.
Mississippi’s low rate of unionization has not led to prosperity. It might be time to try something new.
Are “We” Broke?
In an op-ed in today’s New York Times Stephen King, chief economist for HSBC, writes a deeply confused column that seems designed solely to sound serious and informed while scaring readers into thinking the U.S. economy cannot “afford” decent living standards for most Americans. Dean Baker notes a bunch of problems with the column here, but there are a couple of other things worth pointing out.
King lists globalization as the first influence that allowed rapid living standards growth in the past. He contends, however, that the pace of global integration will begin slowing and will provide less of a spur to growth in the future. I’m not sure what it is about international economics that makes people think they can make wild claims and no evidence must ever be brought to bear, but, there is a deep literature on the gains from international trade, and it’s just not true that they were a first-order driver of (aggregate) American income growth in recent decades. Further, while growing trade has likely (slightly) boosted aggregate U.S. incomes, it has (especially in recent decades) also led to significant changes in the distribution of income, outright lowering wages for most American workers. To put it simply, a reduction in the pace of American integration through trade and investment into the global economy would actually be good for most workers’ living standards (if not good for aggregate U.S. income).
Hitting the Debt Ceiling: An Anti-Stimulus at Least Twice as Large as the Stimulus in the Recovery Act
This blog post has been updated.
Several days ago Paul Krugman made a good point—while it’s really hard to be precise about how much it would hurt to slam into the constraint of the debt ceiling, we do know clearly that it would indeed hurt.
Say that Treasury decided to prioritize debt payments (and even say that interest on the debt doesn’t increase at all, which is unlikely), and cutback on other spending to levels that can be supported by incoming revenues rather than borrowing. This would by itself lead to a shock to GDP of well over 5 percent of GDP (annualized) when accounting for both the decline in spending (about 4 percent of GDP) and a modest multiplier.
Union Membership and the Income Share of the Top Ten Percent
In a previous post and economic snapshot, I and others noted the historical symmetry of the rise and fall of union density across the last century and its uncanny mirror image—the fall and rise of the share of income going to the top ten percent. The juxtaposition of the two lines suggests less a direct causal relationship than an emblematic one—between the trajectory of the workers’ bargaining power on the one hand, and trajectory of rent-padded top incomes on the other.
Updating this data through 2012 only confirms this dismal pattern. Union membership fell to 11.3 percent in 2012, and to a measly 6.6 percent in the private sector. As the last business cycle battered working Americans, the very rich just got richer—hoarding all of the income gains of the recovery, and reaching income shares unseen in the last century (19.3% for the top one percent, 35.8 percent for the top five percent, and 48.2 percent for the top ten percent).
Union membership and share of income going to the top 10%
| Year | Union membership | Share of income going to the top 10 percent |
|---|---|---|
| 1917 | 11.0% | 40.3% |
| 1918 | 12.1% | 39.9% |
| 1919 | 14.3% | 39.5% |
| 1920 | 17.5% | 38.1% |
| 1921 | 17.6% | 42.9% |
| 1922 | 14.0% | 43.0% |
| 1923 | 11.7% | 40.6% |
| 1924 | 11.3% | 43.3% |
| 1925 | 11.0% | 44.2% |
| 1926 | 10.7% | 44.1% |
| 1927 | 10.6% | 44.7% |
| 1928 | 10.4% | 46.1% |
| 1929 | 10.1% | 43.8% |
| 1930 | 10.7% | 43.1% |
| 1931 | 11.2% | 44.4% |
| 1932 | 11.3% | 46.3% |
| 1933 | 9.5% | 45.0% |
| 1934 | 9.8% | 45.2% |
| 1935 | 10.8% | 43.4% |
| 1936 | 11.1% | 44.8% |
| 1937 | 18.6% | 43.4% |
| 1938 | 23.9% | 43.0% |
| 1939 | 24.8% | 44.6% |
| 1940 | 23.5% | 44.4% |
| 1941 | 25.4% | 41.0% |
| 1942 | 24.2% | 35.5% |
| 1943 | 30.1% | 32.7% |
| 1944 | 32.5% | 31.6% |
| 1945 | 33.4% | 32.6% |
| 1946 | 31.9% | 34.6% |
| 1947 | 31.1% | 33.0% |
| 1948 | 30.5% | 33.7% |
| 1949 | 29.6% | 33.8% |
| 1950 | 30.0% | 33.9% |
| 1951 | 32.4% | 32.8% |
| 1952 | 31.5% | 32.1% |
| 1953 | 33.2% | 31.4% |
| 1954 | 32.7% | 32.1% |
| 1955 | 32.9% | 31.8% |
| 1956 | 33.2% | 31.8% |
| 1957 | 32.0% | 31.7% |
| 1958 | 31.1% | 32.1% |
| 1959 | 31.6% | 32.0% |
| 1960 | 30.7% | 31.7% |
| 1961 | 28.7% | 31.9% |
| 1962 | 29.1% | 32.0% |
| 1963 | 28.5% | 32.0% |
| 1964 | 28.5% | 31.6% |
| 1965 | 28.6% | 31.5% |
| 1966 | 28.7% | 32.0% |
| 1967 | 28.6% | 32.1% |
| 1968 | 28.7% | 32.0% |
| 1969 | 28.3% | 31.8% |
| 1970 | 27.9% | 31.5% |
| 1971 | 27.4% | 31.8% |
| 1972 | 27.5% | 31.6% |
| 1973 | 27.1% | 31.9% |
| 1974 | 26.5% | 32.4% |
| 1975 | 25.7% | 32.6% |
| 1976 | 25.7% | 32.4% |
| 1977 | 25.2% | 32.4% |
| 1978 | 24.7% | 32.4% |
| 1979 | 25.4% | 32.4% |
| 1980 | 23.6% | 32.9% |
| 1981 | 22.3% | 32.7% |
| 1982 | 21.6% | 33.2% |
| 1983 | 21.4% | 33.7% |
| 1984 | 20.5% | 34.0% |
| 1985 | 19.0% | 34.3% |
| 1986 | 18.5% | 34.6% |
| 1987 | 17.9% | 36.5% |
| 1988 | 17.6% | 38.6% |
| 1989 | 17.2% | 38.5% |
| 1990 | 16.7% | 38.8% |
| 1991 | 16.2% | 38.4% |
| 1992 | 16.2% | 39.8% |
| 1993 | 16.2% | 39.5% |
| 1994 | 16.1% | 39.6% |
| 1995 | 15.3% | 40.5% |
| 1996 | 14.9% | 41.2% |
| 1997 | 14.7% | 41.7% |
| 1998 | 14.2% | 42.1% |
| 1999 | 14.2% | 42.7% |
| 2000 | 13.6% | 43.1% |
| 2001 | 13.7% | 42.2% |
| 2002 | 13.5% | 42.4% |
| 2003 | 13.0% | 42.8% |
| 2004 | 12.6% | 43.6% |
| 2005 | 12.5% | 44.9% |
| 2006 | 12.0% | 45.5% |
| 2007 | 12.1% | 45.7% |
| 2008 | 12.5% | 46.0% |
| 2009 | 12.4% | 45.5% |
| 2010 | 11.9% | 46.4% |
| 2011 | 11.8% | 46.6% |
| 2012 | 11.3% | 48.2% |
Data on union density follows the composite series found in Historical Statistics of the United States; updated to 2012 from unionstats.com. Income inequality (share of income to top 10%) from Piketty and Saez, “Income Inequality in the United States, 1913-1998, Quarterly Journal of Economics, 118(1), 2003, 1-39. Updated and downloadable data, for this series and other countries, is available at the Top Income Database. Updated September 2013.
What We Read Today
Here’s what we read today. Share what you’re reading in the comments.
- Will work for free: How unpaid internships cheapen workers of all ages (PBS Newshour)
- Looting the Pension Funds (Rolling Stone)
- I worked all week for free?!: The horrifying, true story of $0 paychecks (Salon)
- Why I Miss Pork-Barrel Politics (Slate)
- Government Shutdown Jeopardizes WIC Program (Huffington Post)
- Mr. Zuckerberg Goes to Washington (Dissent)
- Rep. Jeff Denham: U.S. must provide a ‘pathway to citizenship’ (Modesto Bee)
Growing Together, Growing Apart
The September release of the Census Bureau’s income and poverty numbers (and I link to them here only to remind us all that the federal shutdown has made the unavailable) add one more data point to a lost decade punctuated by the recessions of 2001 and 2007, and also to a longer trajectory—stretching back to the 1970s—of starkly unequal income growth.
That growing inequality is underscored by plotting the Census data (reporting average family income by income percentiles) alongside the top incomes estimates of Thomas Piketty and Emmanuel Saez (recently updated through 2012).
There are some bumps in the “crosswalk” between these data sources1 and, for this reason, I include the “top 5 percent” estimate from both. That aside, the big picture is at once familiar and depressing. Over the long postwar era (1947-2012), we see steady and shared income growth running into the 1970s—and then suddenly fanning out as the top incomes (in green) take off. Over that long half-century, incomes (in real, inflation adjusted 2012 dollars) at the 20th percentile do not quite double; those for the top .01 percent of earners grow almost tenfold.