In June, the Supreme Court rescued the Fair Housing Act from a claim that it prohibited only overt discrimination—where a government body announces that it is enacting a housing policy for racially discriminatory reasons. Instead, Justice Anthony Kennedy’s opinion concluded that housing policies that have the effect of reinforcing segregation must be avoided, regardless of policymakers’ provable intent, unless an agency enacting such a policy can show that there was no reasonable alternative to segregation as a way to accomplish legitimate housing objectives.1

These days, when few public officials are so incautious as to announce they are racists, a different Court decision would have hamstrung efforts to desegregate housing nationwide.

Justice Kennedy based his ruling, in part, on a brief submitted by “Housing Scholars” organized by the Haas Institute and the Economic Policy Institute.2 The brief recounted the long history of government sponsorship of racial segregation that had established the nation’s racial housing patterns. The Housing Scholars argued that, because of entrenched patterns attributable to government policy, seemingly race-neutral policies could have the effect of reinforcing the segregation that government had helped put in place.

Now, a federal appeals court based in California, again relying in part on the Housing Scholars brief, has developed Justice Kennedy’s theory further. The case arose from the refusal of the City of Yuma, Arizona to permit construction of moderate-cost single family homes adjacent to a neighborhood where homes were more expensive.3 Although opponents of the development never said openly that their objection was based on race, they attacked the proposal using code words alleging that the development would bring crime into the neighborhood, that some of the homes might be purchased by single-parent families, and that “unattended children would roam the streets.” (The appeals court observed that where whites are involved, it is called “letting children play in the neighborhood.”) The court said that a reasonable jury could interpret such objections as racially motivated.

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The White House released a report this morning that illuminates another part of the complex problem of stagnating wages—the rise of non-compete agreements and their spread to low-wage employment. Non-compete agreements, or “non-competes,” are contracts that ban workers at one company from going to work for a competing employer within a certain period of time after leaving a job. They can make sense when a worker has trade secrets or intellectual property in which the employer has invested. But they make no sense when applied to health care workers, retail and restaurant employees, and other low wage employees. All they do is limit opportunity and shackle people to an employer who will have less incentive to give a raise to retain them.

Employers are imposing non-competes in occupations with no possible trade secret justification—even doggy day care providers! The Treasury Department has found that one in seven Americans earning less than $40,000 a year is subject to a non-compete. This is astonishing, and shows how easily businesses abuse their power over employees and restrict their rights, as they increasingly do with forced arbitration clauses that take away the right of workers to seek justice in the courts. In both cases, workers often accept jobs without ever knowing that they have signed their rights away.

The Treasury Department has done groundbreaking work to show that non-competes have a measurable, negative effect on wages, as one would expect from a practice that limits employee mobility. The report also provides evidence that non-competes can reduce entrepreneurship and innovation.

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(This blog post is an update to a post from March 30, 2015).

When the U.S.-Korea Free Trade Agreement (KORUS) was passed just over four years ago, President Obama said that the agreement would support 70,000 U.S. jobs. This claim was supported by a White House fact sheet that claimed that the KORUS agreement would “increase exports of American goods by $10 to $11 billion…” and that they would “support 70,000 American jobs from increased goods exports alone.” Things are not turning out as predicted. Far from supporting jobs, growing goods trade deficits with Korea have eliminated more than 95,000 jobs between 2011 and 2015.

Expanding exports alone is not enough to ensure that trade adds jobs to the economy. Increases in U.S. exports tend to create jobs in the United States, but increases in imports lead to job loss—by destroying existing jobs and preventing new job creation—as imports displace goods that otherwise would have been made in the United States by domestic workers. Thus, it is changes in trade balances—the net of exports and imports—that determine the number of jobs created or displaced by trade and investment deals like KORUS.

In the first four years after KORUS took effect, there was absolutely no growth in total U.S. exports to Korea, as shown in the figure below. Imports from Korea increased $15.2 billion, an increase of 26.8 percent. As a result, the U.S. trade deficit with Korea increased $15.1 billion between 2011 and 2015, an increase of 114.6 percent, more than doubling in just four years.

Chart 1

U.S.-Korea trade, 2011–2015 (billions of dollars)

	Exports	Imports	Trade balance
2011	$43.5	56.7	-13.2
2012	42.3	58.9	-16.6
2013	41.7	62.4	-20.7
2014	44.5	69.5	-25.0
2015	43.5	71.8	-28.3

ChartData Download data

The data below can be saved or copied directly into Excel.

The data underlying the figure.

Change, billions of dollars, and percent from 2011-2015
Imports: +$15.2 (26.8%)
Exports: $0 (0.0%)
Trade Bal.: -$15.1 (114.6%)

Source: Author's analysis of U.S. International Trade Commission Trade DataWeb

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Last week, the Federal Open Market Committee rightfully decided against another interest rate increase. Raising rates serves to slow the economy down and, at this point in the recovery, the economy still needs all the help it can get to keep growing. Gross domestic product (GDP) showed a slow rate of growth of 0.5 percent annualized in the first quarter of 2016, following just 1.4 percent growth in the last quarter of 2015. As my colleague Josh Bivens wrote, “if such slow growth continues into 2016, there will be significant upward pressure on unemployment and recent gains in labor force participation will likely fade away.” While we all hope that GDP growth for the first quarter gets revised significantly upwards, and that the last 6 months are more of a blip than a new trend, it is certainly the case that the Fed’s decision to not raise rates looks justified by the data.

Private sector nominal wage growth is one of the top indicators to watch on Friday, and one of the indicators the Fed tracks most closely in making their decisions. Last week, however, we got another useful measure of labor compensation growth. The Bureau of Labor Statistics (BLS) released its latest compensation data from the Employment Cost Index (ECI) for March 2016. The data on wages and salaries from the ECI very much confirm the monthly nominal wage growth numbers that appear every month in the Employment Report (with data from the Current Employment Statistics (CES)). Over the year, private industry wages and salaries as measured by the ECI increased 2.0 percent, while overall compensation costs increased 1.8 percent. Turning to the monthly CES data, wages grew 2.3 percent for the year ending in March 2016.

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The Department of Labor (DOL) is about to release a final rule that will require overtime pay for millions of salaried employees who currently can be required to work long hours for no more pay than they receive for a 40-hour week. This will give them either more money or more time with their families or for themselves.

But the overtime rule naturally makes some employers unhappy, since they can currently get 60 hours of work from many employees for only 40 hours of pay. Even some non-profit human service providers, many of which are not even covered by the Fair Labor Standards Act (FLSA), oppose DOL’s updated rule.

An association of community providers serving people with intellectual and developmental disabilities (the American Network of Community Options and Resources, or ANCOR) commissioned a “Cost Impact Scoring Memo” by a company called Avalere to estimate the impact of the proposed overtime rule on its member agencies. Neither the survey questions, the actual responses, nor the response rate were included in Avalere’s report. But it is clear that the cost estimates are deeply flawed.

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Our recent report on the class of 2016 showed that young high school and college graduates still face high levels of unemployment and stagnant wages, even though the labor market has improved since the Great Recession. Between these two groups, however, young high school graduates face a far less forgiving economic reality: the unemployment rate for young high school graduates is over three times higher than their college-educated peers (17.9 percent versus 5.6 percent), nearly one in seven is stuck in a part-time job when they really want full-time work, and the wages of entry-level jobs have barely budged since 2000.

Figure B

Despite improvement in recent years, young high school graduates' unemployment rate remains high: Unemployment rate of young high school graduates, by gender, 1989–2016*

Date	All	Men	Women
1989-12-01	13.0%	12.6%	13.5%
1990-01-01	12.8%	12.3%	13.4%
1990-02-01	12.8%	12.2%	13.5%
1990-03-01	12.7%	12.1%	13.4%
1990-04-01	12.7%	12.4%	13.2%
1990-05-01	12.7%	12.4%	13.0%
1990-06-01	12.3%	12.2%	12.4%
1990-07-01	12.4%	12.5%	12.3%
1990-08-01	12.4%	12.6%	12.1%
1990-09-01	12.4%	12.8%	12.1%
1990-10-01	12.7%	13.0%	12.3%
1990-11-01	12.8%	13.0%	12.5%
1990-12-01	13.0%	13.2%	12.9%
1991-01-01	13.4%	13.5%	13.2%
1991-02-01	13.9%	14.0%	13.8%
1991-03-01	14.2%	14.3%	14.0%
1991-04-01	14.4%	14.6%	14.3%
1991-05-01	14.8%	14.9%	14.6%
1991-06-01	15.4%	15.5%	15.2%
1991-07-01	15.6%	15.8%	15.5%
1991-08-01	15.9%	16.0%	15.8%
1991-09-01	16.1%	16.2%	16.0%
1991-10-01	16.2%	16.4%	16.1%
1991-11-01	16.3%	16.6%	16.1%
1991-12-01	16.5%	16.9%	16.1%
1992-01-01	16.4%	17.0%	15.8%
1992-02-01	16.5%	17.2%	15.7%
1992-03-01	16.7%	17.5%	15.8%
1992-04-01	16.8%	17.6%	15.8%
1992-05-01	17.0%	17.8%	16.1%
1992-06-01	17.1%	18.0%	16.2%
1992-07-01	17.2%	17.9%	16.5%
1992-08-01	17.2%	18.1%	16.2%
1992-09-01	17.3%	18.2%	16.2%
1992-10-01	17.3%	18.2%	16.2%
1992-11-01	17.4%	18.3%	16.3%
1992-12-01	17.4%	18.3%	16.4%
1993-01-01	17.4%	18.2%	16.5%
1993-02-01	17.2%	17.8%	16.5%
1993-03-01	17.2%	17.7%	16.7%
1993-04-01	17.3%	17.7%	16.9%
1993-05-01	17.2%	17.4%	16.9%
1993-06-01	16.9%	17.1%	16.7%
1993-07-01	16.7%	17.2%	16.1%
1993-08-01	16.6%	17.0%	16.1%
1993-09-01	16.4%	16.6%	16.1%
1993-10-01	16.4%	16.7%	16.0%
1993-11-01	16.3%	16.6%	15.9%
1993-12-01	16.2%	16.6%	15.7%
1994-01-01	16.1%	16.5%	15.5%
1994-02-01	16.0%	16.6%	15.4%
1994-03-01	16.1%	16.8%	15.2%
1994-04-01	15.8%	16.5%	14.9%
1994-05-01	15.6%	16.3%	14.7%
1994-06-01	15.4%	16.0%	14.8%
1994-07-01	15.4%	15.8%	14.9%
1994-08-01	15.2%	15.5%	14.9%
1994-09-01	15.2%	15.6%	14.8%
1994-10-01	15.0%	15.2%	14.8%
1994-11-01	14.8%	14.9%	14.7%
1994-12-01	14.6%	14.6%	14.6%
1995-01-01	14.5%	14.4%	14.7%
1995-02-01	14.1%	13.8%	14.5%
1995-03-01	13.9%	13.3%	14.5%
1995-04-01	14.0%	13.4%	14.6%
1995-05-01	14.0%	13.8%	14.3%
1995-06-01	14.2%	14.3%	14.1%
1995-07-01	14.3%	14.2%	14.3%
1995-08-01	14.4%	14.4%	14.3%
1995-09-01	14.6%	14.5%	14.9%
1995-10-01	14.7%	14.6%	14.8%
1995-11-01	14.9%	14.9%	14.8%
1995-12-01	15.0%	15.2%	14.8%
1996-01-01	15.4%	15.7%	15.0%
1996-02-01	15.5%	15.8%	15.1%
1996-03-01	15.6%	16.0%	15.1%
1996-04-01	15.5%	15.8%	15.0%
1996-05-01	15.5%	15.6%	15.4%
1996-06-01	15.2%	15.0%	15.5%
1996-07-01	15.1%	15.1%	15.2%
1996-08-01	15.1%	15.0%	15.1%
1996-09-01	15.1%	15.3%	14.8%
1996-10-01	15.4%	15.6%	15.2%
1996-11-01	15.4%	15.5%	15.3%
1996-12-01	15.4%	15.5%	15.4%
1997-01-01	15.4%	15.3%	15.6%
1997-02-01	15.5%	15.2%	15.8%
1997-03-01	15.3%	15.0%	15.7%
1997-04-01	15.4%	14.8%	16.0%
1997-05-01	15.1%	14.4%	15.9%
1997-06-01	15.2%	14.7%	15.8%
1997-07-01	15.0%	14.2%	15.9%
1997-08-01	15.0%	14.3%	15.8%
1997-09-01	14.7%	13.9%	15.7%
1997-10-01	14.4%	13.6%	15.4%
1997-11-01	14.3%	13.4%	15.4%
1997-12-01	14.0%	13.0%	15.2%
1998-01-01	13.7%	12.9%	14.7%
1998-02-01	13.6%	12.9%	14.4%
1998-03-01	13.5%	13.0%	14.1%
1998-04-01	13.2%	13.1%	13.4%
1998-05-01	13.3%	13.5%	13.0%
1998-06-01	13.1%	13.2%	12.9%
1998-07-01	12.9%	13.3%	12.5%
1998-08-01	12.9%	13.3%	12.5%
1998-09-01	13.0%	13.4%	12.6%
1998-10-01	12.9%	13.4%	12.4%
1998-11-01	12.8%	13.2%	12.2%
1998-12-01	12.6%	13.1%	12.1%
1999-01-01	12.6%	13.3%	11.9%
1999-02-01	12.6%	13.1%	12.0%
1999-03-01	12.5%	12.7%	12.2%
1999-04-01	12.6%	12.5%	12.6%
1999-05-01	12.4%	12.2%	12.7%
1999-06-01	12.2%	12.1%	12.4%
1999-07-01	12.2%	12.0%	12.4%
1999-08-01	12.1%	11.8%	12.6%
1999-09-01	12.0%	11.6%	12.5%
1999-10-01	12.0%	11.5%	12.7%
1999-11-01	12.1%	11.6%	12.7%
1999-12-01	12.3%	11.9%	12.7%
2000-01-01	12.2%	11.7%	12.8%
2000-02-01	12.1%	11.8%	12.5%
2000-03-01	12.3%	12.0%	12.6%
2000-04-01	12.3%	12.0%	12.7%
2000-05-01	12.3%	12.0%	12.7%
2000-06-01	12.4%	12.2%	12.6%
2000-07-01	12.3%	12.1%	12.6%
2000-08-01	12.4%	12.5%	12.4%
2000-09-01	12.2%	12.4%	11.9%
2000-10-01	12.0%	12.4%	11.7%
2000-11-01	12.1%	12.4%	11.7%
2000-12-01	12.1%	12.4%	11.8%
2001-01-01	12.2%	12.3%	11.9%
2001-02-01	12.2%	12.5%	11.8%
2001-03-01	12.1%	12.6%	11.5%
2001-04-01	12.2%	12.8%	11.4%
2001-05-01	11.9%	12.6%	11.1%
2001-06-01	12.0%	12.6%	11.3%
2001-07-01	12.3%	12.9%	11.5%
2001-08-01	12.5%	12.9%	11.9%
2001-09-01	12.9%	13.4%	12.5%
2001-10-01	13.3%	13.7%	12.9%
2001-11-01	13.6%	13.9%	13.2%
2001-12-01	13.9%	14.2%	13.5%
2002-01-01	14.2%	14.5%	13.7%
2002-02-01	14.5%	15.0%	13.9%
2002-03-01	14.9%	15.4%	14.3%
2002-04-01	15.2%	15.8%	14.5%
2002-05-01	15.6%	16.1%	15.1%
2002-06-01	16.0%	16.4%	15.4%
2002-07-01	16.3%	16.7%	15.8%
2002-08-01	16.6%	17.1%	16.0%
2002-09-01	16.5%	17.1%	15.9%
2002-10-01	16.5%	16.9%	16.0%
2002-11-01	16.6%	17.0%	16.0%
2002-12-01	16.4%	16.9%	15.8%
2003-01-01	16.6%	17.0%	16.0%
2003-02-01	16.6%	17.1%	16.0%
2003-03-01	16.6%	17.0%	16.0%
2003-04-01	16.6%	17.1%	15.8%
2003-05-01	16.8%	17.4%	16.0%
2003-06-01	17.0%	17.4%	16.5%
2003-07-01	17.1%	17.6%	16.5%
2003-08-01	17.1%	17.3%	16.7%
2003-09-01	17.2%	17.5%	16.8%
2003-10-01	17.4%	17.8%	16.8%
2003-11-01	17.6%	18.2%	16.7%
2003-12-01	17.6%	18.5%	16.4%
2004-01-01	17.5%	18.4%	16.2%
2004-02-01	17.3%	18.1%	16.3%
2004-03-01	17.4%	18.3%	16.4%
2004-04-01	17.4%	18.1%	16.5%
2004-05-01	17.3%	18.0%	16.4%
2004-06-01	17.0%	17.9%	15.9%
2004-07-01	16.8%	17.5%	15.9%
2004-08-01	16.6%	17.5%	15.5%
2004-09-01	16.6%	17.4%	15.5%
2004-10-01	16.4%	17.1%	15.5%
2004-11-01	16.1%	16.6%	15.5%
2004-12-01	16.0%	16.3%	15.6%
2005-01-01	16.0%	16.3%	15.6%
2005-02-01	16.2%	16.7%	15.5%
2005-03-01	16.1%	16.7%	15.3%
2005-04-01	16.1%	16.8%	15.2%
2005-05-01	16.1%	16.8%	15.2%
2005-06-01	16.2%	17.1%	15.1%
2005-07-01	16.1%	17.2%	14.8%
2005-08-01	16.4%	17.4%	15.2%
2005-09-01	16.4%	17.3%	15.2%
2005-10-01	16.3%	17.3%	15.0%
2005-11-01	16.2%	17.2%	14.8%
2005-12-01	15.9%	16.8%	14.7%
2006-01-01	16.0%	16.7%	15.1%
2006-02-01	15.9%	16.3%	15.3%
2006-03-01	15.7%	16.0%	15.3%
2006-04-01	15.8%	16.0%	15.5%
2006-05-01	15.7%	16.1%	15.2%
2006-06-01	15.4%	15.8%	15.0%
2006-07-01	15.5%	15.8%	15.1%
2006-08-01	15.4%	15.9%	14.8%
2006-09-01	15.5%	16.0%	14.7%
2006-10-01	15.5%	16.1%	14.8%
2006-11-01	15.5%	16.0%	14.9%
2006-12-01	15.8%	16.2%	15.1%
2007-01-01	15.6%	16.3%	14.7%
2007-02-01	15.4%	16.1%	14.4%
2007-03-01	15.3%	16.0%	14.3%
2007-04-01	15.2%	15.9%	14.3%
2007-05-01	15.2%	15.8%	14.3%
2007-06-01	15.5%	16.3%	14.4%
2007-07-01	15.5%	16.5%	14.1%
2007-08-01	15.6%	16.4%	14.6%
2007-09-01	15.5%	16.3%	14.4%
2007-10-01	15.5%	16.5%	14.1%
2007-11-01	15.5%	16.6%	14.0%
2007-12-01	15.9%	17.1%	14.2%
2008-01-01	16.1%	17.2%	14.6%
2008-02-01	16.4%	17.5%	14.8%
2008-03-01	16.9%	17.8%	15.5%
2008-04-01	16.9%	17.9%	15.5%
2008-05-01	17.2%	18.3%	15.7%
2008-06-01	17.4%	18.6%	15.8%
2008-07-01	18.0%	19.1%	16.5%
2008-08-01	18.2%	19.5%	16.4%
2008-09-01	18.6%	19.9%	16.7%
2008-10-01	19.0%	20.4%	17.0%
2008-11-01	19.5%	21.0%	17.4%
2008-12-01	19.7%	21.3%	17.5%
2009-01-01	20.2%	22.0%	17.5%
2009-02-01	20.9%	22.9%	18.0%
2009-03-01	21.3%	23.5%	18.1%
2009-04-01	21.9%	24.2%	18.6%
2009-05-01	22.4%	24.8%	19.1%
2009-06-01	22.9%	24.9%	20.1%
2009-07-01	23.5%	25.5%	20.6%
2009-08-01	24.4%	26.4%	21.6%
2009-09-01	25.1%	27.1%	22.1%
2009-10-01	25.9%	27.9%	23.2%
2009-11-01	26.6%	28.3%	24.1%
2009-12-01	27.1%	28.9%	24.5%
2010-01-01	27.6%	29.6%	24.6%
2010-02-01	27.8%	29.9%	24.8%
2010-03-01	27.8%	29.9%	24.8%
2010-04-01	28.0%	30.2%	25.0%
2010-05-01	28.1%	30.1%	25.3%
2010-06-01	28.1%	30.4%	24.9%
2010-07-01	28.0%	30.2%	24.9%
2010-08-01	27.8%	30.2%	24.4%
2010-09-01	27.7%	30.1%	24.4%
2010-10-01	27.4%	29.7%	24.1%
2010-11-01	27.2%	29.6%	23.8%
2010-12-01	27.1%	29.4%	23.8%
2011-01-01	26.9%	28.8%	24.2%
2011-02-01	26.6%	28.5%	24.0%
2011-03-01	26.8%	28.6%	24.3%
2011-04-01	26.7%	28.5%	24.1%
2011-05-01	26.5%	28.3%	23.9%
2011-06-01	26.4%	28.2%	23.9%
2011-07-01	26.7%	28.3%	24.4%
2011-08-01	26.6%	28.0%	24.6%
2011-09-01	26.4%	27.9%	24.4%
2011-10-01	26.2%	27.9%	23.9%
2011-11-01	26.3%	27.9%	24.0%
2011-12-01	26.2%	28.0%	23.7%
2012-01-01	26.1%	27.9%	23.5%
2012-02-01	26.1%	27.8%	23.5%
2012-03-01	25.8%	27.7%	23.1%
2012-04-01	25.7%	27.5%	23.3%
2012-05-01	26.0%	27.7%	23.6%
2012-06-01	26.2%	27.8%	23.8%
2012-07-01	25.9%	27.6%	23.5%
2012-08-01	25.9%	27.7%	23.3%
2012-09-01	26.0%	27.8%	23.4%
2012-10-01	26.1%	27.6%	24.0%
2012-11-01	25.9%	27.3%	23.8%
2012-12-01	25.7%	26.8%	24.3%
2013-01-01	25.4%	26.3%	24.0%
2013-02-01	25.2%	25.9%	24.2%
2013-03-01	25.2%	25.7%	24.5%
2013-04-01	25.1%	25.4%	24.7%
2013-05-01	24.8%	25.1%	24.5%
2013-06-01	25.0%	25.3%	24.5%
2013-07-01	24.6%	25.2%	23.9%
2013-08-01	24.8%	25.3%	24.2%
2013-09-01	24.6%	25.1%	23.8%
2013-10-01	24.3%	25.1%	23.3%
2013-11-01	24.0%	24.9%	22.8%
2013-12-01	23.4%	24.3%	22.2%
2014-01-01	23.1%	24.0%	22.0%
2014-02-01	23.0%	24.1%	21.4%
2014-03-01	22.9%	24.1%	21.2%
2014-04-01	22.5%	23.9%	20.5%
2014-05-01	22.0%	23.3%	20.2%
2014-06-01	21.4%	22.5%	19.8%
2014-07-01	21.3%	22.4%	19.7%
2014-08-01	20.6%	21.7%	19.0%
2014-09-01	20.3%	21.3%	18.9%
2014-10-01	20.1%	20.8%	19.0%
2014-11-01	20.0%	20.5%	19.2%
2014-12-01	19.9%	20.6%	19.0%
2015-01-01	19.9%	20.5%	19.0%
2015-02-01	19.8%	20.1%	19.3%
2015-03-01	19.5%	19.6%	19.4%
2015-04-01	19.3%	19.3%	19.3%
2015-05-01	19.2%	19.6%	18.5%
2015-06-01	19.0%	19.6%	18.2%
2015-07-01	18.6%	19.1%	17.9%
2015-08-01	18.5%	18.8%	17.9%
2015-09-01	18.2%	18.5%	17.7%
2015-10-01	17.9%	18.1%	17.6%
2015-11-01	17.7%	17.9%	17.4%
2015-12-01	18.0%	18.1%	18.0%
2016-01-01	18.0%	18.1%	18.0%
2016-02-01	17.9%	18.0%	17.8%

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The data underlying the figure.

* Data reflect 12-month moving averages; data for 2016 represent 12-month average from March 2015 to February 2016.

Note: Shaded areas denote recessions. Data are for high school graduates age 17–20 who are not enrolled in further schooling.

Source: EPI analysis of basic monthly Current Population Survey microdata

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There are clear economic advantages for young people with a college degree relative to those who do not pursue and complete a college degree. This often leads pundits to suggest that more education is a solution to the low wages and high unemployment facing non-college educated workers. While this could be good advice at the individual level, encouraging more people to pursue higher education will do little to address the ongoing wage stagnation experienced by both high school and college graduates.

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Neil Irwin wrote a piece on productivity growth in the New York Times that’s making the rounds. It’s a good piece, definitely worth reading. But I think we need to focus a lot more on the portion of the productivity slowdown that is likely fixable quickly with policy: the depressing effect of chronic aggregate demand slack. While economics textbooks tend to shorthand the determinants of productivity growth as slow-moving, supply-side influences like the education of the workforce and the pace of technological advance, plenty of evidence shows that productivity growth is actually positively affected by the rate of demand-growth in the economy. If this is true, then the deceleration of productivity might be just the latest casualty from the too-long slog back to full recovery after the Great Recession. And this would in turn provide yet another reason why the Fed and other macro policymakers should err strongly on side of giving the economy too much rather than too little support going forward.

This theme—that productivity and potential output may be depressed by our failure to generate enough demand-growth to engineer a full recovery—is also a key point of my recent paper on the Congressional Progressive Caucus budget. If passed, this budget would do a lot for boosting productivity growth. People are absolutely right to be concerned about sluggish productivity growth, but we should at least try to pluck the low-hanging fruit in restoring a decent rate of growth by finally locking in full employment.

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For more than two years, the Obama administration has been working on restoring and strengthening working people’s right to receive overtime pay for working more than 40 hours per week. It’s been reported that the salary threshold under which all workers, regardless of their title or responsibilities, will be eligible for overtime will be set at $47,000 a year. While this is slightly lower than DOL’s original proposal, it represents a significant step forward in the effort to boost wages for working people.

If the salary threshold is indeed set at $47,000, it will directly benefit 12.5 million workers. 4.8 million workers will be newly eligible for overtime protections and another 7.6 million will be more easily able to prove their eligibility. All told, about 33 percent of the salaried workforce will be eligible for overtime, regardless of their duties on the job.

By restoring their right to be paid for the hours they work, President Obama and Secretary of Labor Perez are giving a raise to millions of working- and middle-class Americans. They deserve praise for their efforts.

On September 11, 2001, almost 3,000 people died in the attacks on the World Trade Center, the Pentagon, and the airliner crash in Pennsylvania. That tragedy is being compounded by the growing toll of cancer, lung disease and other illnesses related to the attack, particularly in the New York metro area, where first responders were exposed to a sickening mix of chemical and biological toxins. USA Today reported that “more than 9,000 claimants have been determined eligible for compensation of medical bills and other expenses,” and that 2,620 of the approved cases were cancer-related. This second wave of illness and death is taking place out of the public spotlight, but it is real and is causing suffering in thousands of families.

During the years since 9/11, a much larger wave of workplace deaths has been crashing down on American families without drawing much attention from the public or the media. Every year, more people are killed from injuries in the workplace than were killed on September 11, 2001. The number of fatal injuries has been as high as 5,840 but never lower than 4,551—this translates into roughly 65,000 unnecessary deaths resulting from negligence or the reckless indifference of employers who continue to send workers into unshored trenches, onto roofs without fall protection, into confined spaces filled with toxic gas, and into factories and mills with dangerous levels of explosive dust.

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