What to Watch on Jobs Day: What’s at Stake at the Upcoming FOMC Meeting and the Outlook for Young Workers
In tomorrow’s release of the Employment Report, I’m primarily looking for evidence confirming that the Federal Reserve should continue to stay the course through its June (and most likely September) meetings. I’ll also be looking more closely at the labor market for young people: specifically, youth entering the labor market in the summer and prospects for recent high school grads.
When the Federal Open Market Committee meets in two weeks, they will almost surely continue their current agenda and resist pressure to raise interest rates. Raising interest rates prematurely would slow the recovery, which is still in much need of oxygen. Job growth sputtered in March, but picked up again in April. If the economy continues to grow at an average of 191,000 jobs a month (as it has for the past three months), it will return to pre-Great Recession labor market health by August 2017. If you want to downplay the very weak March data, then the average job growth over the past six months (255,000 jobs per month) moving forward gets us back to prerecession health by October 2016.
All measures point to a slowly recovering economy, but an economy that is still far from the health of 2007, let alone the health of the far-stronger economy of 2000. The employment-to-population ratio remains seriously depressed, and there are still over 3 million potential workers sidelined by the weak labor market. Further, wage growth has continued to fall flat—nominal hourly wage growth has remained at around 2 percent over the last five years, far below any reasonable target.
Now that the college graduating class of 2015 has begun to try their luck in the labor market, it’s time to consider how 2015’s high school graduates are expected to do as they graduate this month. Extensive details on the specifics of the high school graduates—including underemployment and wages—are available here. Below is a chart of the unemployment rates of everyone in the labor force versus those under 25 years old and the youngest potential workers, those between 16 and 19 years old. While the unemployment rates for all groups have declined precipitously during the recovery, two other facts are readily apparent. First, the unemployment rates for any of them have not fully recovered (and it’s important to remember that this measure of unemployment fails to include those working part-time that want full time jobs or those who may have just recently given up looking for work). Second, the younger the potential labor mark entrant, the higher the unemployment rate—and the farther those younger cohorts are from a healthy unemployment rate. Unfortunately, this does not bode well for young workers looking for summer employment or their first job out of high school or college.
Note: Shaded areas denote recessions. Data are seasonally adjusted. Source: Economic Policy Institute analysis of Bureau of Labor Statistics Current Population Survey public data seriesUnemployment rate of workers by age group, 1969–2015
Date
All
16–24
16–19
1969-01-01
3.4%
8.2%
12.0%
1969-02-01
3.4%
8.1%
11.9%
1969-03-01
3.4%
8.3%
12.3%
1969-04-01
3.4%
8.2%
12.0%
1969-05-01
3.4%
8.3%
12.4%
1969-06-01
3.5%
8.3%
12.2%
1969-07-01
3.5%
8.7%
12.8%
1969-08-01
3.5%
8.2%
12.2%
1969-09-01
3.7%
8.9%
12.6%
1969-10-01
3.7%
8.8%
12.6%
1969-11-01
3.5%
8.2%
11.6%
1969-12-01
3.5%
8.4%
11.8%
1970-01-01
3.9%
9.3%
13.5%
1970-02-01
4.2%
9.8%
13.3%
1970-03-01
4.4%
9.6%
13.4%
1970-04-01
4.6%
10.4%
14.7%
1970-05-01
4.8%
10.4%
14.2%
1970-06-01
4.9%
11.2%
16.3%
1970-07-01
5.0%
11.0%
14.7%
1970-08-01
5.1%
11.4%
15.7%
1970-09-01
5.4%
12.1%
16.2%
1970-10-01
5.5%
12.2%
16.7%
1970-11-01
5.9%
12.9%
17.4%
1970-12-01
6.1%
12.8%
17.1%
1971-01-01
5.9%
12.6%
16.8%
1971-02-01
5.9%
12.5%
16.3%
1971-03-01
6.0%
12.8%
16.9%
1971-04-01
5.9%
12.5%
16.3%
1971-05-01
5.9%
13.0%
16.8%
1971-06-01
5.9%
13.2%
17.7%
1971-07-01
6.0%
12.9%
17.7%
1971-08-01
6.1%
12.8%
16.8%
1971-09-01
6.0%
12.4%
16.7%
1971-10-01
5.8%
12.4%
16.9%
1971-11-01
6.0%
13.0%
16.9%
1971-12-01
6.0%
12.7%
16.9%
1972-01-01
5.8%
12.7%
16.9%
1972-02-01
5.7%
12.8%
18.0%
1972-03-01
5.8%
12.8%
17.2%
1972-04-01
5.7%
12.4%
16.5%
1972-05-01
5.7%
11.8%
15.3%
1972-06-01
5.7%
11.8%
15.9%
1972-07-01
5.6%
12.0%
15.6%
1972-08-01
5.6%
12.1%
16.5%
1972-09-01
5.5%
12.0%
16.3%
1972-10-01
5.6%
12.0%
15.8%
1972-11-01
5.3%
11.5%
15.7%
1972-12-01
5.2%
11.3%
15.6%
1973-01-01
4.9%
10.2%
13.7%
1973-02-01
5.0%
10.9%
15.3%
1973-03-01
4.9%
10.4%
14.3%
1973-04-01
5.0%
11.0%
15.5%
1973-05-01
4.9%
10.7%
14.9%
1973-06-01
4.9%
10.4%
13.8%
1973-07-01
4.8%
10.6%
14.3%
1973-08-01
4.8%
10.3%
14.0%
1973-09-01
4.8%
10.7%
14.7%
1973-10-01
4.6%
10.0%
14.4%
1973-11-01
4.8%
10.4%
15.0%
1973-12-01
4.9%
10.5%
14.6%
1974-01-01
5.1%
10.8%
14.6%
1974-02-01
5.2%
11.0%
14.9%
1974-03-01
5.1%
10.7%
14.9%
1974-04-01
5.1%
10.5%
14.3%
1974-05-01
5.1%
11.3%
15.4%
1974-06-01
5.4%
11.8%
16.3%
1974-07-01
5.5%
12.1%
16.8%
1974-08-01
5.5%
11.7%
14.9%
1974-09-01
5.9%
12.6%
17.0%
1974-10-01
6.0%
12.5%
17.2%
1974-11-01
6.6%
13.4%
17.8%
1974-12-01
7.2%
14.2%
18.2%
1975-01-01
8.1%
15.1%
19.5%
1975-02-01
8.1%
15.6%
19.4%
1975-03-01
8.6%
16.2%
19.9%
1975-04-01
8.8%
16.5%
19.9%
1975-05-01
9.0%
16.9%
20.4%
1975-06-01
8.8%
16.3%
20.9%
1975-07-01
8.6%
16.6%
20.7%
1975-08-01
8.4%
16.3%
20.7%
1975-09-01
8.4%
16.1%
19.5%
1975-10-01
8.4%
16.1%
19.8%
1975-11-01
8.3%
15.7%
19.0%
1975-12-01
8.2%
15.6%
19.8%
1976-01-01
7.9%
15.4%
19.6%
1976-02-01
7.7%
14.7%
19.0%
1976-03-01
7.6%
14.6%
18.9%
1976-04-01
7.7%
14.9%
19.5%
1976-05-01
7.4%
14.3%
18.6%
1976-06-01
7.6%
14.5%
18.5%
1976-07-01
7.8%
14.2%
18.3%
1976-08-01
7.8%
15.0%
19.6%
1976-09-01
7.6%
14.4%
18.6%
1976-10-01
7.7%
14.9%
19.0%
1976-11-01
7.8%
14.9%
19.2%
1976-12-01
7.8%
14.8%
19.1%
1977-01-01
7.5%
14.3%
18.9%
1977-02-01
7.6%
14.5%
18.4%
1977-03-01
7.4%
14.2%
18.6%
1977-04-01
7.2%
13.7%
18.0%
1977-05-01
7.0%
13.7%
17.8%
1977-06-01
7.2%
14.0%
18.8%
1977-07-01
6.9%
13.3%
17.5%
1977-08-01
7.0%
13.7%
17.4%
1977-09-01
6.8%
13.5%
18.0%
1977-10-01
6.8%
13.0%
17.2%
1977-11-01
6.8%
13.1%
17.2%
1977-12-01
6.4%
12.2%
15.5%
1978-01-01
6.4%
12.9%
16.7%
1978-02-01
6.3%
13.0%
17.2%
1978-03-01
6.3%
13.0%
17.3%
1978-04-01
6.1%
12.6%
16.6%
1978-05-01
6.0%
11.8%
16.0%
1978-06-01
5.9%
11.7%
15.4%
1978-07-01
6.2%
12.5%
16.5%
1978-08-01
5.9%
11.7%
15.7%
1978-09-01
6.0%
12.1%
16.4%
1978-10-01
5.8%
11.5%
16.1%
1978-11-01
5.9%
11.9%
16.3%
1978-12-01
6.0%
12.1%
16.7%
1979-01-01
5.9%
11.6%
16.1%
1979-02-01
5.9%
11.7%
16.1%
1979-03-01
5.8%
11.6%
15.9%
1979-04-01
5.8%
11.6%
16.3%
1979-05-01
5.6%
11.6%
16.1%
1979-06-01
5.7%
11.5%
15.7%
1979-07-01
5.7%
11.6%
15.6%
1979-08-01
6.0%
12.2%
16.5%
1979-09-01
5.9%
12.1%
16.5%
1979-10-01
6.0%
12.1%
16.5%
1979-11-01
5.9%
11.6%
15.9%
1979-12-01
6.0%
12.4%
16.2%
1980-01-01
6.3%
12.6%
16.5%
1980-02-01
6.3%
12.5%
16.6%
1980-03-01
6.3%
12.3%
16.3%
1980-04-01
6.9%
13.1%
16.2%
1980-05-01
7.5%
14.7%
18.6%
1980-06-01
7.6%
14.7%
18.9%
1980-07-01
7.8%
14.9%
19.1%
1980-08-01
7.7%
14.7%
18.9%
1980-09-01
7.5%
14.3%
18.0%
1980-10-01
7.5%
14.5%
18.4%
1980-11-01
7.5%
14.4%
18.5%
1980-12-01
7.2%
13.7%
17.6%
1981-01-01
7.5%
14.5%
19.1%
1981-02-01
7.4%
14.6%
19.3%
1981-03-01
7.4%
14.5%
19.2%
1981-04-01
7.2%
14.5%
18.8%
1981-05-01
7.5%
15.1%
19.1%
1981-06-01
7.5%
14.9%
19.8%
1981-07-01
7.2%
14.1%
18.6%
1981-08-01
7.4%
14.5%
18.8%
1981-09-01
7.6%
14.9%
19.7%
1981-10-01
7.9%
15.3%
20.3%
1981-11-01
8.3%
15.9%
21.3%
1981-12-01
8.5%
16.1%
21.1%
1982-01-01
8.6%
16.5%
22.0%
1982-02-01
8.9%
17.0%
22.6%
1982-03-01
9.0%
16.9%
21.8%
1982-04-01
9.3%
17.4%
22.8%
1982-05-01
9.4%
17.3%
22.8%
1982-06-01
9.6%
17.5%
22.9%
1982-07-01
9.8%
18.0%
24.0%
1982-08-01
9.8%
18.1%
23.7%
1982-09-01
10.1%
18.2%
23.6%
1982-10-01
10.4%
18.5%
23.7%
1982-11-01
10.8%
19.0%
24.1%
1982-12-01
10.8%
18.9%
24.1%
1983-01-01
10.4%
18.5%
23.1%
1983-02-01
10.4%
18.4%
22.8%
1983-03-01
10.3%
18.2%
23.5%
1983-04-01
10.2%
18.0%
23.4%
1983-05-01
10.1%
17.7%
22.8%
1983-06-01
10.1%
17.8%
24.0%
1983-07-01
9.4%
16.8%
22.8%
1983-08-01
9.5%
17.3%
22.9%
1983-09-01
9.2%
16.4%
21.7%
1983-10-01
8.8%
16.2%
21.4%
1983-11-01
8.5%
15.4%
20.2%
1983-12-01
8.3%
14.9%
19.9%
1984-01-01
8.0%
14.8%
19.5%
1984-02-01
7.8%
14.3%
19.4%
1984-03-01
7.8%
14.4%
19.8%
1984-04-01
7.7%
14.5%
19.2%
1984-05-01
7.4%
13.6%
18.7%
1984-06-01
7.2%
13.2%
18.2%
1984-07-01
7.5%
13.7%
18.8%
1984-08-01
7.5%
14.1%
18.7%
1984-09-01
7.3%
14.0%
19.2%
1984-10-01
7.4%
13.6%
18.6%
1984-11-01
7.2%
13.2%
17.7%
1984-12-01
7.3%
13.7%
18.8%
1985-01-01
7.3%
13.6%
18.8%
1985-02-01
7.2%
13.6%
18.3%
1985-03-01
7.2%
13.6%
18.2%
1985-04-01
7.3%
13.2%
17.5%
1985-05-01
7.2%
13.6%
18.5%
1985-06-01
7.4%
13.5%
18.5%
1985-07-01
7.4%
14.2%
20.2%
1985-08-01
7.1%
13.3%
17.9%
1985-09-01
7.1%
13.3%
17.9%
1985-10-01
7.1%
14.1%
20.0%
1985-11-01
7.0%
13.5%
18.3%
1985-12-01
7.0%
13.5%
19.1%
1986-01-01
6.7%
13.0%
18.1%
1986-02-01
7.2%
13.6%
18.8%
1986-03-01
7.2%
13.2%
18.2%
1986-04-01
7.1%
13.7%
19.2%
1986-05-01
7.2%
13.7%
18.6%
1986-06-01
7.2%
13.5%
19.2%
1986-07-01
7.0%
13.3%
18.4%
1986-08-01
6.9%
13.1%
18.0%
1986-09-01
7.0%
13.6%
18.4%
1986-10-01
7.0%
13.0%
17.7%
1986-11-01
6.9%
12.8%
18.1%
1986-12-01
6.6%
13.0%
17.5%
1987-01-01
6.6%
13.0%
17.7%
1987-02-01
6.6%
13.1%
18.0%
1987-03-01
6.6%
12.8%
17.9%
1987-04-01
6.3%
12.6%
17.3%
1987-05-01
6.3%
12.5%
17.4%
1987-06-01
6.2%
12.3%
16.5%
1987-07-01
6.1%
11.8%
15.8%
1987-08-01
6.0%
11.7%
15.9%
1987-09-01
5.9%
11.8%
16.2%
1987-10-01
6.0%
11.8%
17.3%
1987-11-01
5.8%
11.5%
16.6%
1987-12-01
5.7%
11.2%
16.0%
1988-01-01
5.7%
11.5%
16.1%
1988-02-01
5.7%
11.3%
15.6%
1988-03-01
5.7%
11.8%
16.6%
1988-04-01
5.4%
11.2%
16.0%
1988-05-01
5.6%
11.3%
15.3%
1988-06-01
5.4%
10.5%
14.2%
1988-07-01
5.4%
10.8%
14.8%
1988-08-01
5.6%
11.0%
15.4%
1988-09-01
5.4%
10.8%
15.5%
1988-10-01
5.4%
10.8%
15.1%
1988-11-01
5.3%
10.5%
13.9%
1988-12-01
5.3%
10.8%
14.8%
1989-01-01
5.4%
11.8%
16.4%
1989-02-01
5.2%
10.6%
15.0%
1989-03-01
5.0%
10.1%
13.9%
1989-04-01
5.2%
10.6%
14.6%
1989-05-01
5.2%
10.4%
14.8%
1989-06-01
5.3%
11.2%
15.7%
1989-07-01
5.2%
10.6%
14.2%
1989-08-01
5.2%
10.9%
14.6%
1989-09-01
5.3%
11.1%
15.2%
1989-10-01
5.3%
11.0%
15.0%
1989-11-01
5.4%
11.3%
15.5%
1989-12-01
5.4%
11.2%
15.3%
1990-01-01
5.4%
10.8%
14.8%
1990-02-01
5.3%
10.7%
15.0%
1990-03-01
5.2%
10.6%
14.3%
1990-04-01
5.4%
11.1%
14.7%
1990-05-01
5.4%
10.8%
15.0%
1990-06-01
5.2%
10.4%
14.3%
1990-07-01
5.5%
10.7%
15.0%
1990-08-01
5.7%
11.5%
16.3%
1990-09-01
5.9%
11.7%
16.4%
1990-10-01
5.9%
11.8%
16.5%
1990-11-01
6.2%
12.0%
17.1%
1990-12-01
6.3%
12.0%
17.4%
1991-01-01
6.4%
12.6%
18.6%
1991-02-01
6.6%
12.8%
17.4%
1991-03-01
6.8%
13.1%
18.3%
1991-04-01
6.7%
12.7%
17.8%
1991-05-01
6.9%
13.6%
18.8%
1991-06-01
6.9%
13.6%
18.5%
1991-07-01
6.8%
13.8%
19.4%
1991-08-01
6.9%
13.5%
18.9%
1991-09-01
6.9%
13.4%
18.8%
1991-10-01
7.0%
13.9%
19.1%
1991-11-01
7.0%
13.8%
19.0%
1991-12-01
7.3%
14.6%
20.3%
1992-01-01
7.3%
13.9%
19.2%
1992-02-01
7.4%
14.2%
20.1%
1992-03-01
7.4%
14.1%
20.3%
1992-04-01
7.4%
13.6%
18.5%
1992-05-01
7.6%
14.4%
20.1%
1992-06-01
7.8%
15.2%
23.0%
1992-07-01
7.7%
14.5%
20.8%
1992-08-01
7.6%
14.2%
19.9%
1992-09-01
7.6%
14.5%
21.0%
1992-10-01
7.3%
13.5%
18.3%
1992-11-01
7.4%
14.3%
20.5%
1992-12-01
7.4%
14.2%
19.8%
1993-01-01
7.3%
14.0%
19.9%
1993-02-01
7.1%
14.1%
19.7%
1993-03-01
7.0%
13.6%
19.7%
1993-04-01
7.1%
13.8%
19.5%
1993-05-01
7.1%
14.2%
19.8%
1993-06-01
7.0%
13.7%
19.9%
1993-07-01
6.9%
13.1%
18.4%
1993-08-01
6.8%
13.0%
18.4%
1993-09-01
6.7%
12.6%
18.2%
1993-10-01
6.8%
13.0%
18.7%
1993-11-01
6.6%
12.9%
18.5%
1993-12-01
6.5%
12.5%
17.9%
1994-01-01
6.6%
13.4%
18.3%
1994-02-01
6.6%
12.9%
18.0%
1994-03-01
6.5%
13.1%
18.0%
1994-04-01
6.4%
13.3%
19.1%
1994-05-01
6.1%
12.5%
18.0%
1994-06-01
6.1%
12.4%
17.6%
1994-07-01
6.1%
12.4%
17.6%
1994-08-01
6.0%
12.5%
17.3%
1994-09-01
5.9%
12.1%
17.5%
1994-10-01
5.8%
12.0%
17.5%
1994-11-01
5.6%
11.4%
15.6%
1994-12-01
5.5%
11.5%
17.0%
1995-01-01
5.6%
11.4%
16.5%
1995-02-01
5.4%
11.7%
17.4%
1995-03-01
5.4%
11.6%
16.1%
1995-04-01
5.8%
12.0%
17.5%
1995-05-01
5.6%
11.9%
17.5%
1995-06-01
5.6%
12.0%
17.1%
1995-07-01
5.7%
12.5%
18.2%
1995-08-01
5.7%
12.5%
17.3%
1995-09-01
5.6%
12.7%
17.6%
1995-10-01
5.5%
12.4%
17.4%
1995-11-01
5.6%
12.0%
17.5%
1995-12-01
5.6%
12.4%
18.0%
1996-01-01
5.6%
12.8%
17.7%
1996-02-01
5.5%
12.2%
16.8%
1996-03-01
5.5%
12.2%
17.1%
1996-04-01
5.6%
12.0%
17.1%
1996-05-01
5.6%
12.2%
16.8%
1996-06-01
5.3%
11.8%
16.2%
1996-07-01
5.5%
12.4%
17.1%
1996-08-01
5.1%
11.6%
16.8%
1996-09-01
5.2%
11.4%
15.6%
1996-10-01
5.2%
11.6%
16.3%
1996-11-01
5.4%
11.9%
16.8%
1996-12-01
5.4%
11.8%
16.6%
1997-01-01
5.3%
12.2%
16.8%
1997-02-01
5.2%
11.8%
17.1%
1997-03-01
5.2%
11.7%
16.4%
1997-04-01
5.1%
11.6%
15.9%
1997-05-01
4.9%
11.1%
16.0%
1997-06-01
5.0%
11.4%
16.8%
1997-07-01
4.9%
11.2%
17.1%
1997-08-01
4.8%
11.1%
16.1%
1997-09-01
4.9%
11.2%
16.1%
1997-10-01
4.7%
11.0%
15.1%
1997-11-01
4.6%
10.8%
14.8%
1997-12-01
4.7%
10.5%
14.0%
1998-01-01
4.6%
10.9%
13.9%
1998-02-01
4.6%
10.6%
14.5%
1998-03-01
4.7%
10.5%
14.8%
1998-04-01
4.3%
9.7%
13.5%
1998-05-01
4.4%
10.3%
14.8%
1998-06-01
4.5%
10.6%
14.9%
1998-07-01
4.5%
10.6%
14.6%
1998-08-01
4.5%
10.8%
14.7%
1998-09-01
4.6%
11.0%
15.0%
1998-10-01
4.5%
10.5%
15.7%
1998-11-01
4.4%
9.8%
14.7%
1998-12-01
4.4%
9.6%
13.5%
1999-01-01
4.3%
10.2%
15.2%
1999-02-01
4.4%
10.1%
13.9%
1999-03-01
4.2%
9.9%
14.2%
1999-04-01
4.3%
10.0%
14.2%
1999-05-01
4.2%
9.6%
13.3%
1999-06-01
4.3%
10.0%
13.9%
1999-07-01
4.3%
9.9%
13.4%
1999-08-01
4.2%
9.6%
13.3%
1999-09-01
4.2%
10.2%
14.8%
1999-10-01
4.1%
10.0%
13.8%
1999-11-01
4.1%
9.9%
13.9%
1999-12-01
4.0%
9.6%
13.4%
2000-01-01
4.0%
9.4%
12.7%
2000-02-01
4.1%
9.9%
13.8%
2000-03-01
4.0%
9.6%
13.3%
2000-04-01
3.8%
9.2%
12.6%
2000-05-01
4.0%
9.8%
12.8%
2000-06-01
4.0%
9.3%
12.3%
2000-07-01
4.0%
9.3%
13.4%
2000-08-01
4.1%
9.3%
14.0%
2000-09-01
3.9%
8.9%
13.0%
2000-10-01
3.9%
8.9%
12.8%
2000-11-01
3.9%
9.1%
13.0%
2000-12-01
3.9%
9.2%
13.2%
2001-01-01
4.2%
9.6%
13.8%
2001-02-01
4.2%
9.6%
13.7%
2001-03-01
4.3%
9.8%
13.8%
2001-04-01
4.4%
10.2%
13.9%
2001-05-01
4.3%
9.9%
13.4%
2001-06-01
4.5%
10.4%
14.2%
2001-07-01
4.6%
10.2%
14.4%
2001-08-01
4.9%
11.2%
15.6%
2001-09-01
5.0%
10.8%
15.2%
2001-10-01
5.3%
11.5%
16.0%
2001-11-01
5.5%
11.6%
15.9%
2001-12-01
5.7%
12.2%
17.0%
2002-01-01
5.7%
12.1%
16.5%
2002-02-01
5.7%
11.8%
16.0%
2002-03-01
5.7%
12.5%
16.6%
2002-04-01
5.9%
12.3%
16.7%
2002-05-01
5.8%
11.6%
16.6%
2002-06-01
5.8%
11.8%
16.7%
2002-07-01
5.8%
12.1%
16.8%
2002-08-01
5.7%
12.0%
17.0%
2002-09-01
5.7%
11.7%
16.3%
2002-10-01
5.7%
11.8%
15.1%
2002-11-01
5.9%
12.1%
17.1%
2002-12-01
6.0%
12.1%
16.9%
2003-01-01
5.8%
12.0%
17.2%
2003-02-01
5.9%
12.1%
17.2%
2003-03-01
5.9%
12.0%
17.8%
2003-04-01
6.0%
12.6%
17.7%
2003-05-01
6.1%
12.9%
17.9%
2003-06-01
6.3%
13.2%
19.0%
2003-07-01
6.2%
13.0%
18.2%
2003-08-01
6.1%
12.3%
16.6%
2003-09-01
6.1%
12.8%
17.6%
2003-10-01
6.0%
12.2%
17.2%
2003-11-01
5.8%
12.1%
15.7%
2003-12-01
5.7%
11.7%
16.2%
2004-01-01
5.7%
12.0%
17.0%
2004-02-01
5.6%
11.7%
16.5%
2004-03-01
5.8%
12.0%
16.8%
2004-04-01
5.6%
11.6%
16.6%
2004-05-01
5.6%
12.1%
17.1%
2004-06-01
5.6%
12.0%
17.0%
2004-07-01
5.5%
12.1%
17.8%
2004-08-01
5.4%
11.5%
16.7%
2004-09-01
5.4%
11.7%
16.6%
2004-10-01
5.5%
12.1%
17.4%
2004-11-01
5.4%
11.5%
16.4%
2004-12-01
5.4%
11.7%
17.6%
2005-01-01
5.3%
11.6%
16.2%
2005-02-01
5.4%
12.4%
17.5%
2005-03-01
5.2%
11.8%
17.1%
2005-04-01
5.2%
11.8%
17.8%
2005-05-01
5.1%
11.7%
17.8%
2005-06-01
5.0%
11.1%
16.3%
2005-07-01
5.0%
10.7%
16.1%
2005-08-01
4.9%
11.1%
16.1%
2005-09-01
5.0%
10.8%
15.5%
2005-10-01
5.0%
10.8%
16.1%
2005-11-01
5.0%
11.1%
17.0%
2005-12-01
4.9%
10.5%
14.9%
2006-01-01
4.7%
10.4%
15.1%
2006-02-01
4.8%
10.8%
15.3%
2006-03-01
4.7%
10.5%
16.1%
2006-04-01
4.7%
10.3%
14.6%
2006-05-01
4.6%
10.0%
14.0%
2006-06-01
4.6%
10.4%
15.8%
2006-07-01
4.7%
10.9%
15.9%
2006-08-01
4.7%
10.7%
16.0%
2006-09-01
4.5%
10.6%
16.3%
2006-10-01
4.4%
10.6%
15.2%
2006-11-01
4.5%
10.6%
14.8%
2006-12-01
4.4%
10.0%
14.6%
2007-01-01
4.6%
10.3%
14.8%
2007-02-01
4.5%
9.9%
14.9%
2007-03-01
4.4%
10.0%
14.9%
2007-04-01
4.5%
10.3%
15.9%
2007-05-01
4.4%
9.9%
15.9%
2007-06-01
4.6%
10.6%
16.3%
2007-07-01
4.7%
10.5%
15.3%
2007-08-01
4.6%
10.7%
15.9%
2007-09-01
4.7%
11.2%
15.9%
2007-10-01
4.7%
10.7%
15.4%
2007-11-01
4.7%
10.8%
16.2%
2007-12-01
5.0%
11.7%
16.8%
2008-01-01
5.0%
11.7%
17.8%
2008-02-01
4.9%
11.4%
16.6%
2008-03-01
5.1%
11.4%
16.1%
2008-04-01
5.0%
11.0%
15.9%
2008-05-01
5.4%
13.0%
19.0%
2008-06-01
5.6%
12.9%
19.2%
2008-07-01
5.8%
13.5%
20.7%
2008-08-01
6.1%
13.1%
18.6%
2008-09-01
6.1%
13.5%
19.1%
2008-10-01
6.5%
13.6%
20.0%
2008-11-01
6.8%
14.0%
20.3%
2008-12-01
7.3%
14.8%
20.5%
2009-01-01
7.8%
15.0%
20.7%
2009-02-01
8.3%
16.0%
22.3%
2009-03-01
8.7%
16.5%
22.2%
2009-04-01
9.0%
16.7%
22.2%
2009-05-01
9.4%
17.6%
23.4%
2009-06-01
9.5%
18.0%
24.7%
2009-07-01
9.5%
17.9%
24.3%
2009-08-01
9.6%
18.1%
25.0%
2009-09-01
9.8%
18.4%
25.9%
2009-10-01
10.0%
19.1%
27.2%
2009-11-01
9.9%
19.2%
26.9%
2009-12-01
9.9%
18.8%
26.7%
2010-01-01
9.8%
18.8%
26.1%
2010-02-01
9.8%
18.7%
25.6%
2010-03-01
9.9%
18.8%
26.2%
2010-04-01
9.9%
19.5%
25.4%
2010-05-01
9.6%
18.1%
26.5%
2010-06-01
9.4%
18.2%
25.9%
2010-07-01
9.4%
18.4%
25.9%
2010-08-01
9.5%
17.7%
25.5%
2010-09-01
9.5%
17.9%
25.8%
2010-10-01
9.4%
18.7%
27.2%
2010-11-01
9.8%
18.5%
24.8%
2010-12-01
9.3%
17.9%
25.3%
2011-01-01
9.2%
18.1%
25.7%
2011-02-01
9.0%
17.7%
24.1%
2011-03-01
9.0%
17.6%
24.4%
2011-04-01
9.1%
17.6%
24.6%
2011-05-01
9.0%
17.3%
23.9%
2011-06-01
9.1%
17.1%
24.6%
2011-07-11
9.0%
17.3%
24.7%
2011-08-20
9.0%
17.4%
25.0%
2011-09-01
9.0%
17.3%
24.4%
2011-10-11
8.8%
16.7%
24.2%
2011-11-20
8.6%
17.1%
24.2%
2011-12-30
8.5%
16.7%
23.3%
2012-01-12
8.3%
16.1%
23.7%
2012-02-12
8.3%
16.5%
23.8%
2012-03-12
8.2%
16.3%
25.0%
2012-04-12
8.2%
16.5%
24.8%
2012-05-12
8.2%
16.1%
24.3%
2012-06-12
8.2%
16.3%
23.4%
2012-07-12
8.2%
16.3%
23.6%
2012-08-12
8.0%
16.7%
24.3%
2012-09-12
7.8%
15.4%
23.7%
2012-10-12
7.8%
16.1%
23.9%
2012-11-12
7.7%
15.9%
24.0%
2012-12-12
7.9%
16.6%
24.1%
2013-01-12
8.0%
16.8%
23.9%
2013-02-12
7.7%
16.2%
25.2%
2013-03-12
7.5%
16.1%
24.1%
2013-04-12
7.6%
16.1%
24.1%
2013-05-12
7.5%
16.2%
24.2%
2013-06-12
7.5%
16.1%
23.3%
2013-07-12
7.3%
15.5%
23.2%
2013-08-12
7.2%
15.5%
22.5%
2013-09-12
7.2%
15.0%
21.1%
2013-10-12
7.2%
15.0%
22.2%
2013-11-12
7.0%
14.2%
20.9%
2013-12-12
6.7%
13.5%
20.4%
2014-01-12
6.6%
14.3%
20.8%
2014-02-12
6.7%
14.3%
21.3%
2014-03-12
6.6%
14.5%
20.9%
2014-04-12
6.2%
12.8%
19.1%
2014-05-12
6.3%
13.2%
19.2%
2014-06-12
6.1%
13.3%
20.7%
2014-07-12
6.2%
13.6%
20.0%
2014-08-12
6.1%
13.0%
19.4%
2014-09-12
5.9%
13.7%
19.8%
2014-10-12
5.7%
12.7%
18.7%
2014-11-12
5.8%
12.7%
17.5%
2014-12-12
5.6%
12.4%
16.8%
2015-01-12
5.7%
12.2%
18.8%
2015-02-12
5.5%
11.9%
17.1%
2015-03-12
5.5%
12.3%
17.5%
2015-04-12
5.4%
11.6%
17.1%
New Research Does Not Provide Any Reason to Doubt that CEO Pay Fueled Top 1% Income Growth
A new paper, Firming up Inequality, has been receiving substantial attention in the media for its claim that wage inequality is not occurring within firms but only occurs between firms. The authors claim that their results disprove the claim made by me and others, such as Thomas Piketty and Emmanuel Saez, that the growth of top 1 percent incomes was driven by the pay of executives and those in the financial sector. Though the authors present valuable new data, which offers the possibility of great insights, their current analysis does not disprove that executive pay has fueled top 1 percent income growth. In fact, the study neither examines nor rebuts claims about executive pay.
The authors also offer a “we live in the best possible world” interpretation of their findings—inequality is due to high productivity growth of “superfirms.” This is pure speculation and is completely disconnected from their actual empirical work. A similar study examined productivity trends and contradicts their narrative about superfirms.
Last, there are reasons to be skeptical of their findings because they imply huge wage disparities have opened up between median workers across firms within an industry that are implausible.
1. The paper neither examines nor rebuts the claim that executive pay was a major factor in the doubling of the income share of the top 1 percent.
The paper characterizes itself as a critique of the findings that executive pay (and financial sector pay) has fueled the growth of top 1 percent incomes, citing my work with Natalie Sabadish, as well as Piketty’s:
In the absence of comprehensive evidence on wages paid by firms, it is frequently asserted that inequality within the firm is a driving force leading to an increase in overall inequality. For example, according to Mishel and Sabadish (2014), “a key driver of wage inequality is the growth of chief executive officer earnings and compensation.” Piketty (2013) (p. 315) agrees, noting that “the primary reason for increased income inequality in recent decades is the rise of the supermanager.”
Strong Wage Growth Would Complement the Safety Net in Reducing Poverty
Last week, we published Broad-Based Wage Growth Is a Key Tool in the Fight Against Poverty, which argued that our fight against poverty over the last few decades has been missing a key element: strong wage growth for the majority of workers. To substantiate this claim, we simulated the impacts on poverty rates in a few scenarios in which wages grew across the board according to different benchmarks (e.g., average wage growth, productivity, and productivity and full employment).
Judging by a recent blog post, Matt Bruenig seems unimpressed. He spends a large part of the first part of his post suggesting that efforts to boost market incomes (i.e., wages) will necessarily fall short because the majority of those who are in poverty (namely, the elderly, children, the disabled, and caregivers) do not work. He ends by assessing the result of our simulation as uninspiring largely because the “employable” poor make up only a minority of those in poverty. Given the alleged ineffectiveness of wage-growth, he calls for increased transfers to fight poverty.
We think Bruenig overlooks two key aspects of the role of wages in reducing overall poverty. First, we believe he ignores the extent to which children would benefit from the spillover of increased wages for their parents. Second, he ignores the fact that people move in and out of poverty—by raising the income floor for many families, broad-based wage growth plays an important role in preventing more of them from falling under the poverty line.
Yes, Trade Deficits Do Indeed Matter for Jobs
The issue of currency management by U.S. trading partners that increases U.S. trade deficits has become a front-burner issue in debates over the proposed Trans-Pacific Partnership (TPP). The discussion about whether or not trade deficits can really affect U.S. employment, however, occasionally gets very muddled. Here’s a quick attempt to un-muddle a couple different issues.
Trade deficits and overall employment
Trade deficits occurring when the U.S. economy is stuck below full employment and at the zero lower bound (ZLB) on short-term interest rates are a drag on economic growth and overall employment, period. And this describes the U.S. economy today, so a reduction in the trade deficit in the next couple of years spurred by a reversal of trading partners’ currency management would boost growth and jobs.
The logic is simple—exports boost demand for U.S. output while imports reduce demand for U.S. output. When net exports (exports minus imports) fall, then aggregate demand is reduced. Trade deficits are the mirror image of capital inflows into the U.S. economy, and there are times when these capital inflows can reduce domestic interest rates and boost economic activity, providing an offset to the demand-drag caused by trade flows. Today is not one of those times—further downward pressure on already rock-bottom interest rates (particularly since most of these inflows go into U.S. Treasuries) do very little to boost domestic investment to counteract the demand drag from trade flows.
Millennials Aren’t Lazy: Millennials Aren’t Working Because the Economy Isn’t Either
‘Tis the season to be a graduate and members of the class of 2015 may be wondering: what are my chances in this job market?
The class of 2015 is entering an economy still in recovery from the Great Recession. Job prospects for the class of 2015 are better than for the several classes that graduated before them, but young graduates today still face many economic challenges, including stagnant wages and high levels of unemployment and underemployment. The class of 2015 joins the six classes before it in graduating into an acutely weak labor market and competing with more experienced workers for a limited amount of job opportunities.
Although unemployment rates of young graduates have come down in recent years after skyrocketing during the Great Recession, they still remain elevated compared to where they were before the recession began. Underemployment rates for the class of 2015 also remain high. This means that many young graduates either want a job but have recently given up looking for work, or have a job that does not provide the hours they need.
Among young college graduates who are employed, many are working in a job that does not require a college degree at all. This is another sign of continued slack in the labor market, and a sign that young graduates’ high unemployment is not because they lack the right skills, but because of a continued lack of economy-wide demand for workers.
Head Start’s 50th Anniversary
This week marks the 50th anniversary of Head Start, a Great Society program that despite spotty funding has brightened the lives of millions of preschoolers. My daughter is one of them.
Like three-quarters of the public schools here in Washington DC, my daughter’s school is a Title I school, where 40 percent or more of the students are from low-income families. Her pre-K program is funded in part by Head Start, even though my daughter and some of her classmates don’t qualify as low income. As it happens, my daughter’s school, HD Cooke Elementary, helped pioneer the Head Start program in 1965 (see cute picture below).
DC has a cutting-edge universal pre-K program and also participates in a pilot program where all kids eat free thanks to a U.S. Department of Agriculture grant. So my daughter not only started attending a great public school at age 3, but eats two nutritious meals a day with her buddies, starting with a meet-and-greet breakfast, the social highlight of her day (and often mine).
DC is somewhat atypical in that there has been an influx of upper-income taxpayers, yet the school system still serves a heavily low-income student body. DC public schools were “majority-minority” before this was true for the United States as a whole.
The growing tax base helped pay to retrofit my daughter’s school to add more natural lighting, a beautiful library and gym, and great playgrounds. In 2010, the school, built in 1909 with an extension dating to 1960, became the first school in DC and one of the oldest in the country to be certified green. Projects like these show how infrastructure and human capital investment can combine with job creation and energy efficiency—a win-win-win unless your name is Koch.
Don’t Blame the Poor for the Faults of Our Economy
When assigning blame for our nation’s persistent poverty problem, many policymakers tend to focus on underlying demographics or behavior of the poor—factors like racial background or the rise of single parent households, instead of the stark economic reality the poorest Americans have to contend with. While demographics and individual behavior have a place in the policy discussion, growing inequality is the primary reason the poverty rate has remained elevated over the last several decades.
The chart below breaks down the poverty rate and shows how demographic and economic factors affected the poverty rate between 1979 and 2013. Since 1979, increasing inequality has been the largest poverty-boosting factor, outweighing racial identity and family structure and completely eclipsing the effects of overall economic growth and educational attainment in driving down the poverty rate. Despite our growing economy and the fact that poor workers are now more educated than ever, rising inequality has worked to keep low-income people in poverty. This increase in inequality was driven by stagnating wages for low- and middle-income households (for example, 10th percentile real wages were actually lower in 2013 than they were in 1979).
Source: EPI analysis of Current Population Survey Annual Social and Economic Supplement microdata based on Danziger and Gottschalk (1995)Impact on poverty rate of economic, demographic, and education changes, 1979–2013
Factor
Effect
Inequality
7.1
Growth
-3.4
Education
-2.9
Family structure
1.6
Race
1.1
Interaction
-0.5
More Notes on the Gains From Trade and Who Gets Them
The New York Times’ Binyamin Appelbaum wrote an excellent piece yesterday on the costs and benefits of globalization. But because I’ve thought a lot about this topic, I have some hobby-horse issues concerning how economists characterize how large the gains from trade are and how its gains and losses are distributed. Put simply, the overall net benefits of trade are much smaller than commonly advertised, but the regressive redistribution trade causes is considerable.
First, on the gains from trade policy (i.e., how much we should expect national income to rise if we sign trade agreements), Appelbaum refers to a piece from the Peterson Institute of International Economics claiming that trade liberalization added 7.3 percent of GDP to American incomes by 2005—about $9000-10,000 per American household. This is just not true. It’s a wildly inflated number that should not be in the policy debate (and if you need much smarter and better-credentialed people making the some point—here’s Dani Rodrik). This number is an effort to bully people into going along with today’s trade agreements by making them think the stakes are utterly enormous. In fact, even if it was correct (again, it’s not) this study would be irrelevant to today’s trade policy debates because the sum total of economic gains from all post-1982 trade agreements (this includes NAFTA, the completion of the General Agreement on Tariffs and Trade, the formation of the WTO, and the permanent normal trading relations with China) is estimated to be just $9 per household, meaning that 99.9 percent of the gains from trade estimated in the study happened before 1982. So even if trade liberalization really did spur mammoth gains at some point in the (distant) past, the effects were over by the early 1980s.
Second, on the distribution of gains and losses from trade, it is striking to me that so many economists who favor signing every trade agreement that comes down the pike can still feign surprise that expanded trade seems to be bad for most workers’ wages. Put simply, it is completely predicted in textbook trade economics that wages for most workers will fall and inequality will rise when the United States trades more with poorer trading partners. Yes, expanded trade is predicted to lead to higher overall national income, but it is also predicted to redistribute enough income within the United that it can (and is likely to) make most workers worse-off. This should not be a surprise to anyone familiar with the topic.
H-1B Visas Do Not Create Jobs or Improve Conditions for U.S. Workers
The common wisdom on Capitol Hill, carefully nurtured by corporate lobbyists and campaign cash, is that America needs more high-tech guestworkers, requiring a big increase in the number of H-1B guestworker visas made available each year. A number of senators, including Amy Klobuchar and Orrin Hatch, have introduced legislation to double or triple the number of non-immigrant tech workers who can be imported each year, despite evidence from the U.S. Government Accountability Office, independent researchers, and various media reports that the H-1B is used to lower wages and displace U.S. workers.
The senators endlessly proclaim that H-1B employees are good for our economy, that businesses can’t find enough talent here, that the H-1Bs are innovative, the “best and the brightest,” and that importing them leads to more job creation. In support, they cite a paper by Agnes Scott College researcher Madeline Zavodny, which found that hiring H-1Bs creates jobs for Americans: specifically, that “adding 100 H-1B workers results in an additional 183 jobs among U.S. natives.”
The problem is that it isn’t true. Zavodny’s research couldn’t discern whether the H-1Bs were hired because the economy was growing and jobs were being created—for natives and guestworkers alike—or whether the H-1Bs were responsible for the job growth. (The weakness of her results is demonstrated by another, completely implausible finding she reports, that H-2B unskilled guestworkers are associated with two-and-a-half times greater job creation than the college-educated H-1Bs: 464 jobs for every 100 H-2B guestworkers. The notion that hiring low-wage-earning landscapers and groundskeepers, hotel maids and dishwashers—most of whom have little or no college education—spurs spectacular job growth is ludicrous on its face.)
Growing Consensus that Labor Market Slack Remains: The Fed Should Stay the Course and Wait to Increase Rates Until the Weakness Has Lessened Substantially
Nominal wage growth’s failure to significantly increase over the last several months (and years) is evidence enough that there’s sufficient labor market slack to convince the Federal Reserve to keep its foot off the economic brakes and not increase short-term interest rates. Nominal hourly wages have grown at only around 2.0-2.3 percent annually, far below wage growth that would be consistent with the Fed’s own 2 percent inflation target, 1.5 percent trend productivity growth, and a stable labor share of income. It’s clear from the evidence that the Fed should not even consider raising interest rates to forestall inflation until wage growth is consistently above this target.
One of the leading forces (besides the 30+ year trend in workers losing bargaining power ) behind sluggish wage growth is the fact that there’s still much labor market slack left in the economy today. The headline unemployment rate underestimates this slack because some of it shows up as cyclically depressed rates of labor force participation instead of elevated unemployment. Over the last couple of years, we’ve been tracking what we call “missing workers”—potential workers who, because of weak job opportunities, are neither employed nor actively seeking a job. In other words, these are people who would be either working or looking for work if job opportunities were significantly stronger. Because jobless workers are only counted in the labor force if they are actively seeking work, these missing workers are not included in the labor force and hence are not classified as officially unemployed.
While it’s clear that some structural forces (aging of the Baby Boomers, for example) are putting downward pressure on labor force participation rates, it’s clear that some of the depressed participation rate is still reflecting cyclical weakness. New evidence released today backs up our “missing worker” interpretation that the unemployment rate is underestimating the true degree of labor market slack because labor force participation remains cyclically depressed. The Goldman Sachs Global Macro Research US Daily (sorry, no link: paywall) points out that research from the New York Fed implies that the overall “jobs gap” may be 3 million, even while the Fed’s estimates of the ”unemployment gap”—the gap between today’s unemployment rate and the rate consistent with stable inflation— is much lower. In short, the headline unemployment rate does indeed continue to obscure how much labor market slack remains. The Goldman team draws out the policy implications:
“This implies much less urgency to start normalizing monetary policy . . . and it is an important reason why we think it would be better for the FOMC to wait until 2016 before starting the normalization process.”
I couldn’t agree more. Sluggish wage growth and depressed labor force participation continue to show signs of a weak economy and the Fed should continue staying the course until the economy is considerably stronger. Acting too soon, would be a mistake for the economy and the people in it.