The Fed’s Interest Rate Decisions, Census Data on Income and Poverty… and Occupy Wall Street
It’s been a busy week already for people who think about the economy. On Tuesday, the Census Bureau released its estimates of household income, poverty, and health insurance coverage for 2013. And on Wednesday, the Federal Reserve released its statement on monetary policy, projections of economic growth, and activity for the next year, and Federal Reserve Chair Janet Yellen held a press conference. Wednesday also marked the informal three-year anniversary of Occupy Wall Street (OWS). To incorrectly paraphrase Neil DeGrasse Tyson: it’s all connected, man.
First, the Fed. The debate swirling around the Fed these days is how soon they should start raising short-term interest rates to slow economic growth and forestall excessively high wage and price inflation. The answer to this should be simple: not soon at all. Wage and price inflation remain extraordinarily low, with no evidence that they’re accelerating. In fact, wage growth could effectively double from its current pace before really becoming inconsistent with even the Fed’s too-conservative 2 percent overall price inflation target.
So if this is what the evidence says, why is there a growing chorus arguing for the Fed to tighten?
Here’s where Occupy Wall Street comes in. Tightening now would keep unemployment higher than it would be under genuinely full employment, and stopping job growth short of full employment is a powerful tool to shift bargaining power away from low- and middle-wage workers and keep them from realizing inflation-adjusted wage increases. This tolerance of sub-full employment is a big reason why inflation-adjusted wages for the vast majority have failed to rise at all for most of the time since 1979, and have certainly not risen anywhere near the pace of overall productivity growth. This wasn’t always the case, but starting in the late 1970s a number of policy decisions made on behalf of corporate managers and owners of capital helped tilt the playing field away from low- and middle-wage workers, and this has been a prime source of the rise in income inequality since. A key part of this inequality by design was having macroeconomic policymakers—particularly the Fed—slow the economy down before full employment could spur across-the-board wage growth. The one time the Fed did not slow the economy “in time”—the late 1990s—led to the first across-the-board wage growth in a generation. If OWS had a grand organizing theme, it was certainly along the lines of the idea that economic policy has helped generate the rising inequality we’ve seen over the past generation. They’re right, and macroeconomic policy that has privileged very low rates of inflation over very low rates of unemployment is part of how policy did it.
Poverty Reduction Stalled by Policy, Once Again: Unemployment Insurance Edition
As EPI’s Elise Gould pointed out back in January, a key barrier to translating overall economic growth in recent decades into rapid poverty reduction has been the rise in income inequality. Were economic growth more broadly shared, the poverty rate would be much lower. Here we make the case that this rise in inequality has large policy fingerprints all over it. Today’s data on income and poverty from the Census Bureau shows how a recent policy choice—specifically cutting back on unemployment insurance (UI) in recent years—has stalled poverty reduction.
Unemployment insurance is a key plank of the American social insurance system. During the ferocious period of job loss and historically high unemployment during and immediately after the Great Recession, policymakers responded by significantly expanding the duration of benefits, and the American Recovery and Reinvestment Act (ARRA) included boosts to the generosity of benefits as well. The result was that in 2009, UI benefits kept 3.3 million people out of poverty.
However, since 2010, this poverty-fighting impact has eroded, and the share of unemployed workers receiving UI benefits has fallen: Both of these trends are shown in the figure below. This is due to both the extended duration of unemployment for some workers outstripping the UI eligibility period as well as intentional policy changes that reduced UI recipiency. The federal government reduced total weeks available in 2012 and then all long-term benefits (those lasting longer than 27 weeks) were cut off at the end of 2013. (The impact of the long-term benefits cut won’t be seen until next year’s poverty figures are released.) Further, several states have also restricted eligibility. The result is that by 2013 only 1.2 million Americans were kept out of poverty by UI benefits.
Unemployment insurance (UI) recipiency rate* and the number of persons UI lifted out of poverty, 1987–2014
| UI recipiency rate* (right axis) | Persons lifted above poverty (left axis) | |
|---|---|---|
| 1987 | 31.2% | 0.684 |
| 1988 | 31.8% | 0.518 |
| 1989 | 34.0% | 0.481 |
| 1990 | 36.5% | 0.668 |
| 1991 | 41.2% | 1.006 |
| 1992 | 51.3% | 1.468 |
| 1993 | 47.7% | 1.208 |
| 1994 | 37.2% | 0.905 |
| 1995 | 36.3% | 0.716 |
| 1996 | 36.8% | 0.633 |
| 1997 | 35.4% | 0.601 |
| 1998 | 36.7% | 0.572 |
| 1999 | 38.1% | 0.602 |
| 2000 | 38.0% | 0.563 |
| 2001 | 44.3% | 0.726 |
| 2002 | 53.1% | 1.177 |
| 2003 | 50.3% | 1.257 |
| 2004 | 38.1% | 0.7 |
| 2005 | 35.9% | 0.656 |
| 2006 | 36.0% | 0.573 |
| 2007 | 36.7% | 0.488 |
| 2008 | 43.7% | 0.905 |
| 2009 | 64.3% | 3.322 |
| 2010 | 66.5% | 3.21 |
| 2011 | 56.4% | 2.306 |
| 2012 | 48.5% | 1.7 |
| 2013 | 40.8% | 1.2 |
| 2014** | 28.9% |
* Recipiency rate is defined as the number of people receiving any form of unemployment insurance (regular program and extended benefits) as a share of the total number of unemployed.
** 2014 UI recipiency rate value is based off of January–August data.
Source: EPI analysis of Current Population Survey basic monthly microdata; U.S. Department of Labor, "Persons Claiming UI Benefits in State and Federal UI Programs [Excel spreadsheet],” updated August 2014; Thomas Gabe and Julie M. Whittaker, Antipoverty Effects of Unemployment Insurance, Congressional Research Service, October 16, 2012; and Carmen DeNavas-Walt and Bernadette D. Proctor, "Income and Poverty in the United States: 2013," U.S. Census Bureau Current Population Reports, September 2014.
Real Median Household Incomes for all Racial Groups Remain Well Below Their 2007 Levels
Today’s Census Bureau report on income, poverty and health insurance coverage in 2013 shows that real median household income increased more among Latino (+$1,391) and African American (+$793) households than white households (+$433), but declined for Asian households (-$2,568). Between 2012 and 2013, the black-white income gap has narrowed from 58.4 cents for every dollar of white median household income to 59.4 cents for every dollar of white median household income. The Hispanic-white income gap has also narrowed from 68.4 to 70.3 cents on the dollar. This is fairly consistent with the modest labor market gains made by African Americans and Latinos in 2013. According to the Bureau of Labor Statistics, between 2012 and 2013, the share of employed adults increased for each of these populations while the share for whites remained unchanged. Despite these relative improvements, real median household incomes for all groups remain well below their 2007 levels. Between 2007 and 2013, median household incomes declined by 9.2 percent (-$3,506) for African Americans, 5.7 percent (-$2,492) for Latinos, 5.6 percent (-$3,432) for whites and 9.7 percent (-$7,201) for Asians. Asian households continue to have the highest median income in spite of large income losses in the wake of the recession.
Real median household income, by race and ethnicity, 1972–2013
| Year | White | Black | Hispanic | Asian |
|---|---|---|---|---|
| Jan-1972 | $51,380 | $29,569 | $38,229 | |
| Jan-1973 | $52,084 | $30,391 | $38,165 | |
| Jan-1974 | $50,314 | $29,669 | $37,942 | |
| Jan-1975 | $48,945 | $29,163 | $34,899 | |
| Jan-1976 | $50,477 | $29,415 | $35,621 | |
| Jan-1977 | $50,965 | $29,490 | $37,281 | |
| Jan-1978 | $52,282 | $30,838 | $38,676 | |
| Jan-1979 | $52,338 | $30,302 | $39,001 | |
| Jan-1980 | $51,180 | $28,972 | $36,743 | |
| Jan-1981 | $50,243 | $27,793 | $37,602 | |
| Jan-1982 | $49,764 | $27,739 | $35,179 | |
| Jan-1983 | (NA) | $27,628 | $35,357 | |
| Jan-1984 | $51,546 | $28,767 | $36,286 | |
| Jan-1985 | $52,581 | $30,595 | $36,058 | |
| Jan-1986 | $54,286 | $30,580 | $37,215 | |
| Jan-1987 | $55,342 | $30,742 | $37,929 | |
| Jan-1988 | $55,958 | $31,044 | $38,522 | |
| Jan-1989 | $56,339 | $32,801 | $39,762 | |
| Jan-1990 | $55,194 | $32,268 | $38,581 | |
| Jan-1991 | $53,914 | $31,369 | $37,848 | |
| Jan-1992 | $54,154 | $30,509 | $36,759 | |
| Jan-1993 | $54,249 | $31,008 | $36,331 | |
| Jan-1994 | $54,596 | $32,682 | $36,403 | |
| Jan-1995 | $56,427 | $33,987 | $34,696 | |
| Jan-1996 | $57,342 | $34,716 | $36,821 | |
| Jan-1997 | $58,720 | $36,250 | $38,534 | |
| Jan-1998 | $60,569 | $36,181 | $40,433 | |
| Jan-1999 | $61,733 | $39,019 | $42,984 | |
| Jan-2000 | $61,715 | $40,131 | $44,867 | |
| Jan-2001 | $60,927 | $38,776 | $44,164 | |
| Jan-2002 | $60,729 | $37,584 | $42,863 | $68,143 |
| Jan-2003 | $60,513 | $37,547 | $41,793 | $70,547 |
| Jan-2004 | $60,318 | $37,114 | $42,264 | $70,916 |
| Jan-2005 | $60,597 | $36,821 | $42,917 | $72,899 |
| Jan-2006 | $60,567 | $36,936 | $43,650 | $74,218 |
| Jan-2007 | $61,702 | $38,104 | $43,455 | $74,266 |
| Jan-2008 | $60,079 | $37,021 | $41,018 | $71,013 |
| Jan-2009 | $59,146 | $35,387 | $41,312 | $71,101 |
| Jan-2010 | $58,185 | $34,321 | $40,205 | $68,654 |
| Jan-2011 | $57,392 | $33,380 | $40,004 | $67,456 |
| Jan-2012 | $57,837 | $33,805 | $39,572 | $69,633 |
| Jan-2013 | $58,270 | $34,598 | $40,963 | $67,065 |
Note: White refers to non-Hispanic whites, black refers to blacks alone, Asian refers to Asians alone, and Hispanic refers to Hispanics of any race. Comparable data are not available prior to 2002 for Asians. Data for non-Hispanic whites are unavailable for the year 1983. Shaded areas denote recessions.
Source: EPI analysis of Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables (Table H-5 and H-9)
The Generation-Long Trend Towards Ever-Greater Income Inequality Continues
Today’s release of data on family income from the Census Bureau reinforces the fact that the generation-long trend towards ever-greater income inequality seems to be firmly underway again, after only the briefest interruption caused by the Great Recession.
Several economic commentators noted the decline in income inequality (mostly driven by steep but temporary falls in income at the very top of the distribution) that accompanied the aftermath of both the early 2000s recession and the Great Recession, some even going so far as to suggest that the recessions had somehow solved the problem of rising income inequality. Yet the evidence is clear that this isn’t the case—recessions seem to only suspend the growth of inequality temporarily. This, of course, should not be a shock—declines at the top of the income distribution are driven largely by stock market movements, and the steep stock market declines of the early 2000s and 2008 bottomed out quickly, and stock prices rose relatively quickly thereafter.
Figure 1 below shows the long-run rise in family income inequality. It tracks growth in average family income by various income groupings since 1947. A key feature of this figure is the extraordinarily tight distribution of income growth from 1947 to 1979 (all lines move upward in a tight bunch), and the rapid pulling apart of income growth thereafter (the lines start pulling apart from each other).
Modest Income Growth in 2013 Puts Slight Dent in More than a Decade of Income Losses
Wage trends greatly determine how fast incomes at the middle and bottom grow, as well as the overall path of income inequality, as we argued in Raising America’s Pay. This is for the simple reason that most households, including those with low incomes, rely on labor earnings for the vast majority of their income. That is why my initial look at the data from the newly released Census Bureau report on income and, poverty in 2013 will look at wages and the incomes of working age households.
The Census data show that from 2012 to 2013, median household income for non-elderly households (those with a head of household younger than 65 years old) increased 0.4 percent from $58,186 to $58,448. However, that modest growth barely begins to offset the losses incurred during the Great Recession or the losses that prevailed in the prior business cycle from 2000 to 2007. Between 2007 and 2013, median household income for non-elderly households dropped from $63,527 to $58,448, a decline of $5,079, or 8.0 percent. Furthermore, the disappointing trends of the Great Recession and its aftermath come on the heels of the weak labor market from 2000-2007, where the median income of non-elderly households fell significantly, from $65,785 to $63,527, the first time in the post-war period that incomes failed to grow over a business cycle. Altogether, from 2000 to 2013, median income for non-elderly households fell from $65,785 to $58,448, a decline of $7,337, or 11.2 percent.
Real median household income, all and non-elderly, 1979–2013
| All households | Non-elderly households | |
|---|---|---|
| Jan-1979 | $49,225 | |
| Jan-1980 | $47,668 | |
| Jan-1981 | $46,876 | |
| Jan-1982 | $46,752 | |
| Jan-1983 | $46,425 | |
| Jan-1984 | $47,867 | |
| Jan-1985 | $48,761 | |
| Jan-1986 | $50,487 | |
| Jan-1987 | $51,121 | |
| Jan-1988 | $51,514 | |
| Jan-1989 | $52,432 | |
| Jan-1990 | $51,735 | |
| Jan-1991 | $50,249 | |
| Jan-1992 | $49,836 | |
| Jan-1993 | $49,594 | |
| Jan-1994 | $50,147 | $57,893 |
| Jan-1995 | $51,719 | $59,417 |
| Jan-1996 | $52,472 | $60,527 |
| Jan-1997 | $53,551 | $61,307 |
| Jan-1998 | $55,497 | $63,792 |
| Jan-1999 | $56,895 | $65,435 |
| Jan-2000 | $56,801 | $65,785 |
| Jan-2001 | $55,562 | $64,772 |
| Jan-2002 | $54,914 | $64,108 |
| Jan-2003 | $54,865 | $63,545 |
| Jan-2004 | $54,674 | $62,801 |
| Jan-2005 | $55,278 | $62,391 |
| Jan-2006 | $55,690 | $63,228 |
| Jan-2007 | $56,435 | $63,527 |
| Jan-2008 | $54,424 | $61,443 |
| Jan-2009 | $54,059 | $60,623 |
| Jan-2010 | $52,646 | $59,057 |
| Jan-2011 | $51,843 | $57,627 |
| Jan-2012 | $51,758 | $58,186 |
| Jan-2013 | $51,939 | $58,448 |
Note: Non-elderly households are those in which the head of household is younger than age 65. Data for non-elderly households are not available prior to 1994. Shaded areas denote recessions.
Source: EPI analysis of Current Population Survey Annual Social and Economic Supplement Historical Income Tables (Tables H-5 and HINC-02)
What to Look for in next Week’s Census Income Data: How Long Will It Take to Claw Back Lost Years of Income Growth?
Next week will see the release of Census data on family income (as well as poverty and health insurance coverage) for 2013. Before the data are released, it’s worth reminding ourselves of one thing that last year’s data showed clearly: economic recoveries in recent recessions have been increasingly unequal, largely mirroring the generation-long upwards march of income inequality more generally. And this pattern seems poised to continue in the recovery from the Great Recession.
The figure below shows these unequal recoveries from recessions in a potentially new way. It essentially looks at just how many years of income growth were lost by each income grouping in various recessions. It measures this by simply counting how many years it took after a recession for each group to regain its previous income peak. For example, incomes for the middle fifth saw a peak in 1989 at $62,212. The recession in the following year led average income for these middle-fifth families to fall for a time, and the 1989 peak of $62,212 was not re-gained for these families until 1996, meaning that essentially seven years (from 1989 to 1996) of income growth for this group was stalled by the recession of the early 1990s. The figure below shows this number of lost years of income growth by income grouping across a range of recessions.
NAM’s “Cost of Regulations” Estimate: An Exercise in How Not to Do Convincing Empirics
The latest effort to scaremonger about a rising regulatory burden on U.S. business was released yesterday by the National Association of Manufacturers (NAM). The report, by W. Mark Crain and Nicole V. Crain (C&C, henceforth) purports to (among other things) estimate the total cost of U.S. regulations. The claimed price tag is enormous—$2.1 trillion. The bulk of these costs (75 percent) are estimated using a cross-country regression analysis. This cross-country analysis, however, is completely unconvincing and should be ignored.
An earlier C&C study used a similar methodology as yesterday’s release—that study was shown to be deeply flawed by an EPI analysis. Yet, the methodology of the current study is largely the same. In fact, if anything, the current analysis is less robust and convincing than the previous one.
C&C undertake a cross-country regression analysis across 34 OECD countries for the years 2006–2013. This obviously leads to a first reason for being wary of results—one would expect the economic performance of rich countries during the 2006–2013 period to be utterly dominated by the Great Recession and its aftermath. C&C use dummy variables to control for the years 2008 and 2009, presumably to capture the official years of the Great Recession. But most of the OECD remains operating far below potential even in 2013 due simply to a shortfall of demand. Unless one is making the case that regulations impede recovery from recessions (a claim that they do not make) then it is extraordinarily hard to make large inferences about the effects of regulations on long-run economic performance in this short sample period.
NAM Publishes Bogus Regulatory Cost Estimates
The National Association of Manufacturers (NAM) is a cynical organization. It knows that few journalists will read a lengthy paper on the cost of regulation and realize that it is dressed-up junk economics, so it has published a re-run of the truly meretricious report that Mark Crain and Nicole Crain issued four years ago. The new report is even worse than its predecessor, in the sense that the authors have chosen not to respond to any of the criticism of their earlier work—even though it has been shown to be based on bad research, unreviewable and probably biased data, and faulty assumptions about the relationship between regulation and GDP.
EPI’s Josh Bivens and others will deal with the main methodological problems with the Crains’ analysis. I want to focus just on the Crains’ re-use of the same indefensible research concerning the cost of OSHA regulation, which we first exposed in 2011. The Crains claim that OSHA regulations cost businesses $71 billion a year, even though the cost for new regulations since 2001 is only $733 million. How is it that the previous years’ regulation cost nearly 100 times as much? The Crains don’t have an explanation—they simply rely on someone else’s discredited work.
Joseph M. Johnson published “A Review and Synthesis of the Cost of Workplace Regulations” in 2005. Johnson’s paper makes many serious mistakes, but the biggest is the application of a cost “multiplier” derived from yet another analyst’s work. Harvey S. James, Jr. estimated that the true cost of OSHA rules is not the cost estimated by the agency at the time of rulemaking (which often turns out, in reality, to be too high), but a cost 5.5 times greater because of “fines for violations and the costs of the many non-major regulations for which no cost estimates exist.” This multiplier is ludicrous on its face, both because OSHA fines have never amounted to very much (even today the maximum fine that can be assessed for a willful or repeat violation is only $70,000, and the amount paid is usually far less than what is initially assessed) and because the costs of non-compliance should not be double-counted as compliance costs.
Here’s Why We Need to Legalize the Undocumented Immigrant Workforce
The Tennessean reported yesterday on the miserable work life of a 17-year old migrant worker named Ivan Alvarez, who lost three fingers when a tobacco farmer’s makeshift shearing machine sliced them off. How did the farmer treat him? He gave him a check for $100 and fired him. No worker’s compensation, no disability insurance, and no compassion.
Young Alvarez was one of six migrant teenagers working at Marty Coley Farms in Macon County, Tennessee. He lived with 13 adult men in a vermin-infested three-bedroom house, and was paid less than minimum wage for six days a week of work. Why did Alvarez and the others put up with such mistreatment? As undocumented immigrants, they were trapped.
A recorded conversation between the farm’s owner and one of the employees after the amputation shows how employers use the threat of deportation to oppress their workers and drive labor standards to the bottom. When the worker said he was leaving to take a better-paying job at another farm, the farmer, Marty Coley (one of the largest tobacco growers in the county), threatened him with deportation.
“I’ll tell you what,” Coley said. “You all go there and I’m going to call immigration and clean the whole damn bunch out.”
It adds insult to injury to learn that, as The Tennessean reported, Marty Coley Farms has received more than half a million dollars in federal tobacco price support subsidies over the past ten years.
One often hears that employers hire undocumented migrants because no American wants to do the kind of work they’re hired to do. Clearly, no American wants to live in overcrowded and disgusting quarters, be paid a subminimum wage, and have his fingers cut off. The answer isn’t to let this kind of exploitation continue—it’s to improve pay and working conditions enough that Americans will do the work, and to give immigrants the right to reject a job that degrades rather than rewards their labor. As long as the undocumented workforce is subjected to the threat of deportation, Marty Coley Farms and other low-road employers will continue to abuse and exploit them, to the detriment of every American.