New Fact Sheet: Forced Unionism Correlated With Higher Poverty Rates
Hispanic Americans Are 20% More Likely to Be Poor in States That Don’t Protect Employees’ Right to Work
By Stan Greer
The share of a state’s population that is poor, commonly referred to as its poverty rate, is undoubtedly an important (negative) indicator of economic vitality. Other things being equal, states with better job and business climates will have poverty rates below the national average.
Consequently, poverty rates are a potentially useful gauge to look at when one is seeking to compare the relative economic success of states with laws on the books protecting employees from termination for refusal to pay dues or fees to an unwanted union with that of states that lack Right to Work protections.
However, the U.S. Census Bureau’s Official Poverty Measure (OPM) is an altogether inadequate tool for comparing state poverty rates, and has long been widely recognized as such.
There Is No Plausible Reason to Use the OPM When Comparing State Poverty Levels
Policy analyst Chuck DeVore, a former California assemblyman and now a vice president at the Austin-based Texas Public Policy Foundation, bluntly summarized the problems with the OPM in a commentary published by Forbes magazine last month:
Census’ Official Poverty Measure is largely bunk for two reasons: it ignores regional cost of living differences and it doesn’t include the value of all benefits to the poor, such as food stamps (now called Supplemental Nutritional Assistance Program or SNAP), housing assistance or Medicaid and Medicare. As a result, the official poverty measure undercounts poverty in high cost states such as California and New York, while over-counting poverty in the low-cost Midwest and South.
Fortunately, since the fall of 2011 the Census Bureau has been releasing alternative poverty-rate estimates that correct several of the defects of the OPM.
Most important for our purposes here, the Census Bureau’s new Supplemental Poverty Measure (SPM) accounts for state-to-state variances in taxes and the cost of housing, though it does not factor in differences in the cost of other necessities like food, energy, and health care.
As David Johnson, chief of the Census Bureau’s Social, Economic, and Housing Statistics Dvision, and University of Wisconsin-Madison professor Timothy Smeeding explained in a May 2012 analysis they coauthored, the SPM “is designed to provide a more modern, comprehensive, and meaningful measure of national poverty.”
While the SPM is certainly not perfect, there is no plausible reason to use the OPM rather than it when comparing state and local poverty rates.
Another potential pitfall for analysts using poverty rates as a gauge of states’ comparative economic dynamism is that the demographic makeup of a state heavily influences the overall share of its population that is below the poverty level, regardless of how well the state is doing otherwise.
In 2014, for example, the nationwide aggregate SPM poverty rate for whites of all ethnicities nationwide was 13.6%. Meanwhile, the national SPM poverty rate for Asian Americans was 16.8%. The respective aggregate poverty rates for blacks and Hispanics (of all races) were 23.4% and 25.4%, respectively. These disparities are found nationwide and cannot reasonably be attributed to the policies or other special characteristics of particular states.
One-Fourth of Asians in Forced-Unionism New York State Live in Poverty
The simplest way to control for disparities in states’ demographic makeups when examining their respective poverty rates is to examine the data for the principal racial and ethnic groups separately. The Census Bureau does not publish such data at the state level. However, the agency’s unpublished data are available for review through the Integrated Public-Use Microdata Series (IPUMS) project from the University of Minnesota.
Last month, Mr. DeVore, who has access to the IPUMS database, kindly offered to forward to me state-by-state SPM poverty data for whites, Asians, blacks and Hispanics.
The data show that, adjusting for demographics, states that do not protect employees from being forced to pay union dues or fees as a condition of employment have higher average SPM poverty rates than do Right to Work states.
The Right to Work advantage is widest among Hispanic Americans.
Over the years 2009 to 2012, the average SPM poverty rate for Hispanics (of all races) nationwide was 27.7%.
But in the 27 states that lacked any Right to Work statute or constitutional amendment throughout this four-year period, an average of 29.7% of Hispanics were living in poverty according to the SPM. Meanwhile, in the 22 states that had Right to Work laws on the books for the entire time, SPM poverty was 24.8%. In short, from 2009 to 2012 Hispanic poverty was nearly 20% higher in forced-unionism states as a group than in Right to Work states as a group.
(Since Indiana’s Right to Work law was adopted and took effect in early 2012, it is excluded from this analysis and those that follow, except when otherwise noted. Since the two most recent states to pass Right to Work measures, Michigan and Wisconsin, still allowed compulsory unionism in 2012, they are regarded as non-Right to Work here.)
While poverty rates among Asian Americans are generally far lower than they are for Hispanics, the analogous data for U.S. residents of Asian descent show a similar advantage for Right to Work states.
The average 2009-2012 SPM poverty rate for Asian Americans nationwide was 17.1%. But in forced-unionism states, where roughly three-quarters of this racial group lives, the Asian SPM poverty rate was 17.8%, compared to an average of 14.6% in Right to Work states. The two states with the highest share of their Asian populations living in poverty are forced-unionism New York (25.4%) and forced-unionism Pennsylvania (24.6%).
‘If There Is No Correlation Between A and B Then We Can Pretty Much Rule Out a Causal Relationship’
The Right to Work advantage for SPM poverty among African Americans (of all ethnicities) is smaller, but still statistically significant.
From 2009 to 2012, an average of 25.1% of blacks across the U.S. were living below the poverty line. But in Right to Work states, the average was just 24.2%, compared to 25.7% in forced-unionism states.
There is only a small difference with regard to SPM poverty for whites (of all ethnicities) in Right to Work states versus forced-unionism states, but all the same Right to Work states retain the advantage. Overall, the SPM poverty rate for whites from 2009-2012 was 14.0%, compared to the 14.2% average for forced-unionism states.
The fact that poverty for the four largest racial/ethnic groups in the U.S. is consistently lower in Right to Work states than in forced-unionism states is just one of many pieces of evidence indicating that protection for the individual employee’s freedom of choice in the workplace fosters economic growth.
Another closely related example concerns Temporary Assistance to Needy Families (TANF), the federal program that provides cash assistance to indigent American families with dependent children through the U.S. Department of Health and Human Services (HHS).
During the 2014 calendar year, an average of just 5.0 per 1000 residents of Right to Work states (then 24 in number, including Indiana and Michigan) relied on TANF assistance to get by. That’s less than half the national average of 10.9 residents per 1000 and less than one-third of the forced-unionism state average of 15.6.
The multiple correlations between Right to Work status, faster growth, and higher incomes for a wide array of citizens make it reasonable to believe there is a causal relationship. As clinical neurologist and Yale professor Steven Novella correctly observed a few years ago, to ignore correlation “entirely, as if it does not imply causation,” means dismissing “a large swath of important scientific evidence.”
At a minimum, the fact that forced unionism is correlated with higher poverty and more welfare dependence almost certainly discredits Big Labor claims that monopoly privileges for union bosses somehow help the economically disadvantaged. Dr. Novella explained why:
In observational studies lack of correlation is easier to interpret than a positive correlations – if there is no correlation between A and B then we can pretty much rule out a causal relationship. The only caveat is that a correlation is being obscured by a factor that was not accounted for.
Unless and until Big Labor apologists can identify one or more “unaccounted-for” factors absent which poverty rates would be higher in Right to Work states than in forced-unionism states, they have no credible grounds for claiming that corralling workers into unwanted unions somehow alleviates poverty.
No Worker Should Be Forced to Join or Pay Dues to a Union
Though the SPM is clearly superior to the traditional Census poverty measure for comparing and contrasting poverty in different states, it undoubtedly fails to adjust sufficiently for higher living costs in forced-unionism states.
Regional cost-of-living indices calculated and published by the Missouri Economic Research and Information Center (MERIC, a state government agency, show that, on average, not just housing, but also food, energy, and other necessities cost significantly more in forced-unionism states than in Right to Work states.
Yet the SPM attempts to account only for interstate differences in housing costs. A more comprehensive adjustment would show poverty rates in forced-unionism states even further above the national and Right to Work averages.
And even if it could be shown that monopolistic unionism had no detrimental economic effects, it would still be indefensible.
The fundamental reason for any state to adopt a Right to Work law is that it’s morally wrong for public policy to force any employee to bankroll a private organization in order to get or keep a job. Accelerated economic growth that occurs as a result of Right to Work is, in other words, a side benefit of implementing a just and necessary labor policy reform.
Stan Greer is the National Institute for Labor Relations Research’s senior research associate. He may reached by e-mail at firstname.lastname@example.org or by phone at 703-321-9606. Nothing here is to be construed as an attempt to aid or hinder the passage of any bill before Congress or any state legislature.
Mr. Greer thanks Chuck DeVore of the Texas Public Policy Foundation for his invaluable assistance in the preparation of this fact sheet. Mr. Greer alone is responsible for the analysis.
 “Cost of Living Matters in the Census Bureau’s New Poverty Report,” Forbes online, September 16, 2015.
 “A Consumer’s Guide to Interpreting Various U.S. Poverty Measures,” Fast Focus, Institute for Research on Poverty, University of Wisconsin, Madison.
 See Chuck DeVore, “Of the Four Majority-Minority States in America, Minorities to Best in Texas,” Forbes online, June 21, 2015, for a short discussion regarding the principal criticism of the SPM.
 Kathleen Short, “The Supplemental Poverty Measure: 2014,” Census Bureau Current Population Report, issued September 2014. See esp. Table 2.
 See “TANF Caseload 2015,” a release issued by HHS’s Office of Family Assistance on May 22, 2015.
 “Evidence in Medicine: Correlation and Causation,” posted on the web site Science-Based Medicine, November 18, 2009.