“Right-to-Work” States Still Have Lower Wages (2023)

Introduction and executive summary

Under federal law, no one can be forced to join a union as a condition of employment, andthe Supreme Court hasmade clear that workers cannot be forced to pay dues used for political purposes. So-called right-to-work (RTW) legislation goes one step further and entitles employees to the benefits of a union contract—including the right to have the union take up their grievance if their employer abuses them—without paying any of the cost.

This means that if an employer mistreats a worker who does not pay a union representation fee, the union must prosecute that worker’s grievance just as it would a dues-paying member’s, even if it costs tens of thousands of dollars. Non-dues-paying workers would also receive the higher wages and benefits their dues-paying coworkers enjoy. RTW laws have nothing to do with whether people can be forced to join a union or contribute to a political cause they do not support; that is already illegal. Nor do RTW laws have anything to do with the right to have a job or be provided employment.

At their core, RTW laws seek to hamstring unions’ ability to help employees bargain with theiremployers for better wages, benefits, and working conditions. Given that unionization raises wages both for individual union members as well as for nonunion workers in unionized sectors, it is not surprising that research shows that both union and nonunion workers in RTW states have lower wages and fewer benefits, on average, than comparable workers in other states.

Indeed, in a 2011 EPI paper, Elise Gould and Heidi Shierholz estimate that wages in RTW states are 3.2 percent lower on average than wages in non-RTW states, even after controlling for a full set of worker characteristics and state labor market conditions. Gould and Shierholz (2011) also find that workers in RTW states are less likely to have employer-sponsored health insurance and pension coverage.

In this paper, we update that research and subject the results to a series of robustness tests. We utilize more recent data from the Current Population Survey, and employ a cost-of-living indicator from the Bureau of Economic Analysis that was only made available in the years following the release of Gould and Shierholz (2011). Last, we subject our results to various robustness tests as suggested by Sherk (2015) regarding choice of specific explanatory variables. We find that the main results hold under any reasonable alternative specifications. Only extensive data-mining and non-standard specifications of wage equations can move the estimated RTW penalty to statistical insignificance. Our central findings are:

  • Wages in RTW states are 3.1 percent lower than those in non-RTW states, after controlling for a full complement of individual demographic and socioeconomic factors as well as state macroeconomic indicators. This translates into RTW being associated with $1,558 lower annual wages for a typical full-time, full-year worker.
  • The relationship between RTW status and wages remains economically and statistically significant under alternative specifications of our econometric model.


The 1947 Taft–Hartley amendments to the National Labor Relations Act (1935) sanctioned a state’s right to pass laws that prohibit unions from requiring a worker to pay dues, even when the worker is covered by a union-negotiated collective bargaining agreement. Within a couple of years of the amendment’s passage, 12 states had passed RTW laws. Today, RTW laws are in place in 25 states, predominantly in the Midwest, South, and Southwest.1

Although there has been an extensive amount of research on the effect of RTW laws on union density, organizing efforts, and industrial development (see Moore 1998 and Moore and Newman 1985 for literature overviews), there has been surprisingly little examination of the perhaps more important issue of RTW laws’ effect on wages and employer-sponsored benefits. Part of the reason that there has been little research done on these latter relationships is that it is hard to identify or isolate the RTW effect. For example, there is little variation in the timing of when many states adopted RTW laws—10 states adopted or amended such laws in a two-year window in the late 1940s, right before a recession hit. In addition, it’s hard to adequately control for the decision of a state to become RTW or isolate that effect from other legislative changes. Further, there are many factors that influence state labor market conditions over time, making it hard to identify the RTW effect amid other economic, social, or technological phenomena.

These limitations make clear why causal impacts of RTW laws are hard to estimate, but one can legitimately take a cross-sectional approach and look at the correlation of RTW status and wages after controlling for a range of other influences that could impact state-level wages. Gould and Shierholz (2011) use this approach and overcome one obvious shortcoming of previous research by controlling for differences in cost of living throughout the United States, thereby making inflation-adjusted wages in various parts of the country as comparable as possible.

First and foremost, this paper is an update to Gould and Shierholz (2011), using data through 2012. Unfortunately, since three states have passed RTW legislation in the last three years, any analysis must still be restricted to data from 2012 and prior so as not to contaminate (that is, bias) the results with data from states switching their regime during the period of study.2Most researchers think that whatever the effect of RTW on states’ economies, it takes a relatively long time to manifest. Thus, it is difficult to know how to classify states that have very recently passed RTW laws. Once the full effects of changes in legislation have been felt in these states, which could take several years, these states can be further evaluated. In this paper we also employ a different cost-of-living adjustment based on a new measure from the Bureau of Economic Analysis (BEA).

And, finally, this paper responds to concerns raised about the robustness of the Gould and Shierholz (2011) findings on RTW and wages. Specifically, Sherk (2015) argues that his preferred regression specification yields the result that a wage differential does not exist between RTW and non-RTW states. After extensive investigation, we do not find his conclusion compelling. The previous Gould and Shierholz (2011) finding is robust to reasonable changes in model specification, and the regression specification Sherk (2015) uses that yields no wage differential is idiosyncratic, excluding variables that belong and including variables that do not belong in a wage regression.

An update: Wages are lower in RTW states, 2010–2012

To determine the relationship between RTW laws and wages, we update the findings in Shierholz and Gould (2011) by estimating log wage equations using Bureau of Labor Statistics Current Population Survey Outgoing Rotation Group (CPS-ORG) data for 2010–2012. The results of the three-year pooled data are very consistent with single-year analyses, but we pool three years of data in this paper to minimize any spurious year-specific economic relationships, thereby helping us achieve more precise estimates. The total sample consists of 304,157 workers, age 18–64, who earn wages and salaries.3About 38 percent of the sample lives in states with RTW laws.4

Table 1 displays the characteristics of workers in both RTW and non-RTW states. On many levels, these two sets of workers are similar. Some demographic characteristics between the two groups are very similar, such as the gender breakdown and the shares of the workforce that are married. Educational attainment is similar, with workers in non-RTW states having slightly higher levels of schooling. The racial/ethnic composition varies, with more white workers in non-RTW states, and more African American and Hispanic workers in RTW states.

Table 1

Characteristics of workers, RTW states versus non-RTW states (2010–2012)

Non-right-to-work stateRight-to-work state
Sex (male)51.0%51.8%
Less than high school7.9%9.8%
High school26.0%27.7%
Some college19.4%20.4%
Associate degree10.6%10.7%
College degree23.2%21.1%
Marital status
Never married31.1%28.2%
Metropolitan area86.7%82.3%
Worker characteristics
Hourly worker57.7%55.9%
Union/union contract17.5%7.3%
Average hourly wage (2014 dollars)$23.93$20.66
Median hourly wage(2014 dollars)$18.40$15.79
State characteristics
Unemployment rate9.1%8.4%
Cost of living (PERI)1.030.95
Cost of living (MERIC)112.0994.74
Cost of living (BEA RPP)103.0994.64
Number of observations189,412114,745

Source: EPI analysis of Current Population Survey Outoing Rotation Group microdata (various years)

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The biggest difference between workers in RTW and non-RTW states is the fact that workers in non-RTW states are more than twice as likely (2.4 times) to be in a union or protected by a union contract. Average hourly wages, the primary variable of interest, are 15.8 percent higher in non-RTW states ($23.93 in non-RTW states versus $20.66 in RTW states).5 Median wages are 16.6 percent higher in non-RTW states ($18.40 vs. $15.79).

These are the unadjusted differences between wages in RTW and non-RTW states. Because there are differences between workers’ characteristics in RTW and non-RTW states, and since some of these characteristics will directly impact workers’ expected wages, it is important to control for these factors in a multivariate regression model. This helps us factor in these differences, which allows us to come closer to identifying the pure relationship between RTW legislation and wages.

In Table 2, we construct a regression model, starting with the most general and building up to a model that controls for the full range of explanatory variables. The dependent variable is always the natural log of hourly wages, and the variable of interest is an indicator variable taking on the value one when the worker lives in a RTW state and zero otherwise. (Full regression results are reported in Appendix Table A1.)

Table 2

Log wage regression results (2010–2012)

VariableModel with no controlsModel adds demographic and individual-level labor market controlsModel adds state-level labor market controls and cost-of-living measuresFinal model, updates cost-of-living indicator
RTW indicator-0.136***-0.0936***-0.0329***-0.0318***

Note: Robust standard errors in parentheses. Three asterisks (***) indicate significance at the 1 percent level, two indicate significance at the 5 percent level, and one indicates significance at the 10 percent level.

All models include year indicators.Demographic controls include variables for gender, experience (age and age squared), marital status (four category), race/ethnicity, and education, which are specified as dummy variables for less than high school, some college, associate degree, college, and advanced degree. Log of hourly wage is the dependent variable. Allocated wages are excluded.Individual-level labor market controls include variables for full-time status, hourly status, union status, occupations, and industries.State-level labor market controls include the unemployment rate.For cost-of-living controls, model 3 includes the PERI and MERIC measures (as used by Gould and Shierholz 2011) while model 4 utilizes the log of BEA's RPP-all items measure.

Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata, Political Economy Research Institute (PERI) data, Missouri Economic Research and Information Center (MERIC) data, and Bureau of Economic Analysis Regional Price Parities

(Video) Do Right-to-Work Laws Really Reduce Wages? Examining the Evidence

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The results of the simple model (which only controls for year fixed-effects) mimic the differences in wages found in the descriptive statistics and are displayed in the first column. The coefficient of -0.136 on the RTW indicator variable means that wages in RTW states are estimated to be 12.7 percent lower than in non-RTW states.6 This result almost perfectly matches the corresponding results in Gould and Shierholz (2011), which found a coefficient estimate of -0.137, or a 12.8 percent wage differential.

In the second model, we add in a basic set of controls, which include the demographic variables included in Table 1—age, age squared, race/ethnicity, education indicators, sex, marital status, urbanicity, an indicator for being an hourly worker, and an indicator for being a full-time worker—in addition to a worker’s major industry and occupation. As with worker characteristics, the industry and occupation mix in the state could affect the average wage. Again, controlling for these differences allows us to better isolate the relationship between RTW status and wages. As expected, the coefficient on the RTW indicator moves closer to zero (as shown in the second column of Table 2), and wages in RTW states are found to be 8.9 percent lower, on average, after controlling for these worker differences. Again, these results are in line with previous research.

Following Gould and Shierholz (2011), the third column of Table 2 includes additional state-level variables pertaining to the economic conditions—measured by the state unemployment rate—and differences in the cost of living across states. Averages for these continuous variables are found at the bottom of Table 1. State unemployment rate data come from the Bureau of Labor Statistics Local Area Unemployment Statistics (BLS LAUS). In this third regression, cost-of-living differences are measured by two separate research entities and methodologies: the Political Economy Research Institute (PERI) and the Missouri Economic Research and Information Center (MERIC).7Controlling for these price differences captures the extent to which higher costs and therefore higher wages may be found in non-RTW states for reasons other than their lack of RTW legislation, letting us better isolate the relationship between wages and RTW status. In addition to the cost-of-living variables, the wage regressions reported are quite standard, using controls (race, gender, five education categories, industry, occupation, experience, union status, hourly status, part-time status, marriage status, and unemployment rate) that are very common in labor economic research examining the determinants of wages (Blanchflower and Oswald 1996).

Using the same full set of controls used in Gould and Shierholz (2011), we find a similar result where wages in RTW states are significantly lower, in both statistical and economic terms, than in non-RTW states. On average, RTW laws are associated with wages that are 3.2 percent lower than in states without such laws. As with the earlier regressions, this result is consistent with the findings of Gould and Shierholz (2011), which, using 2009 data, also found a wage differential of 3.2 percent.

Since the Gould and Shierholz (2011) paper was released, the Bureau of Economic Analysis has released measures of Regional Price Parities (BEA RPP), which offer an alternative method of capturing inter-area differences in prices. The fourth model in Table 2 replaces the previously discussed cost-of-living measures with the BEA’s logged RPP-all items index. As compared with model three, this change leaves the RTW penalty essentially unchanged (it falls from 3.2 percent to 3.1 percent).

Using this final model, we can estimate how much less, on average, workers earn in RTW states versus non-RTW states. Taking the average wage in non-RTW states and inferring a full-time, full-year salary, we find that workers in RTW states earn $1,558 less a year than similar workers in non-RTW states.

Wage differences remain after a series of robustness tests

In his recent paper, Sherk (2015) critiques the Gould and Shierholz (2011) methods. Since this paper serves as an update to their methods, we use the most recent data presented here to test some of his criticisms. Primarily, we defend our methods against the idiosyncratic empirical model choices Sherk (2015) uses. Secondarily, we explore some suggestions Sherk (2015) makes regarding the cost-of-living methodology to control for possible measurement error. As shown in Table 3, and as will be discussed in detail below, in all cases we find that his suggestions do not change, in a statistically or economically significant way, the estimated RTW wage differential. (All of the models in Table 3 should be compared against the final model in Table 2. Full regression results are reported in Appendix Table A2.)

Table 3

Results of robustness tests

VariableTwo-stage least squares(second-stage results)Less occupationsLess industriesLess unemployment rateLess full-time statusLess union
RTW indicator-0.0315***-0.0308***-0.0322***-0.0319***-0.0271***-0.0407***

Note: Robust standard errors in parentheses. Three asterisks (***) indicate significance at the 1 percent level, two indicate significance at the 5 percent level, and one indicates significance at the 10 percent level.

Demographic controls include variables for gender, experience (age and age squared), marital status (four category), race/ethnicity, and education, which are specified as dummy variables for less than high school, some college, associate degree, college, and advanced degree. Log of hourly wage is the dependent variable. Allocated wages areexcluded.Labor market controls include variables for full-time status, hourly status, union status, state unemployment rate, occupations, and industries. In model 1, BEA’s RPP-rents (1 and 2 years lagged) are included in the first-stage regression to predict log RPP-all items, but excluded from the log wage regression. Second-stage results are displayed; first-stage results are available upon request. All other models in the table use BEA's RPP-all items index as the cost-of-living control.

(Video) Right to Work Laws: Lions, Tigers and Unions. Oh My!

Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata, Bureau of Labor Statistics Local Area Unemployment Statistics, and Bureau of Economic Analysis Regional Price Parities

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Here, we address the question of possible measurement error first before moving on to concerns over our model specification. Sherk (2015) suggests that simply putting cost-of-living variables on the right-hand side of a regression may produce inaccurate estimates. Following Winters (2009), he uses an instrumental variable two-stage least squares model to instrument the primary cost-of-living indicator (log RPP-all items) on the two previous years’ worth of the instrumental variable (log RPP-rents).8We use a very similar method on the fourth model from Table 2, and the results of the second-stage least squares can be seen in the first model of Table 3. It is clear that our earlier findings are robust to using the instrumental variable regression, and we therefore find that extra step unnecessary.

More broadly, Sherk (2015) makes several claims in justifying his idiosyncratic regression specification that finds no RTW wage penalty. We find most of these claims unconvincing. In the remainder of this section, we address these model specification issues. Sherk (2015) suggests that Gould and Shierholz (2011) over-control for labor market features that could have been impacted over time by states being either a RTW state or not. Specifically, he asserts that labor market controls used in Gould and Shierholz (2011)—occupations, industry, unemployment, full-time status—bias results downward for RTW states because when controlling for these variables, Gould and Shierholz eliminate some of the positive effects of RTW laws on wages through indirect economic benefits. Among these, only the exclusion of occupations has any reasonable rationale in standard wage equations, though even that is questionable in this context.

Some labor economists have argued that occupations do not belong in wage equations because they are too co-determined (and statistically collinear) with educational attainment to provide useful information (i.e., one’s education is what qualifies one to enter a particular occupation). But others have noted that including them in wage equations “works” (i.e., they return economically and statistically significant coefficients) and therefore they should be included (see Lemieux 2011 for a review of the literature). Furthermore, the objective here is to compare similar workers, not examine the returns to education, a common use of a log wage model. We exclude occupation from our regression as a reasonable robustness test. The exclusion very slightly reduces the estimated RTW wage differential, as shown in the second column of Table 3.

While we maintain that occupation should be included, it is also important and relevant to include control variables such as industry, unionization, and full-time status in our regressions because we are trying to compare wages between RTW and non-RTW states for similar workers with similar types of jobs. Ideally, we would have two workers with exactly the same set of characteristics, except for one—the fact that one lives in a RTW state and the other does not. Then, when we compare their wages, we are isolating the RTW effect. Controlling for job and economic conditions is the best way we can estimate the relationship between wages and RTW status. It is also standard practice in the analysis of wages using individual workers as observations (Blanchflower and Oswald 1996). While we think it is important to include these labor market controls, we explore whether or not removing any one of these variables dramatically reduces the RTW coefficient, which could indicate that our results are not robust.

Sherk (2015) relies on a theory that RTW laws affect the industry composition of states. He claims, for example, that RTW laws may have attracted manufacturing jobs that pay higher wages, but that this wage-boosting impact of RTW would not show up in a regression model that controls for the state’s industry composition among its other labor market variables. Empirically, these are mostly moot arguments. There has been no research showing a clear causal relationship between RTW status and attracting manufacturing jobs, and when we examined the relationship between the manufacturing share of employment in a state and RTW status we found no evidence to support his claim.9 Furthermore, recent statistical studies show no basis for assuming that RTW affects manufacturing share of employment. The annual Area Development Magazine (2014) survey, a survey of manufacturers, has never reported RTW ranking anywhere in the top 10 factors shaping manufacturers’ location decisions. Additionally, the annual State New Economy Index, which ranks states according to their favorability for higher-wage, higher-tech manufacturers, shows that these firms are drawn to states with strong education systems, strong research universities, good digital infrastructure, and other features that are predominantly found in fair-share, not RTW, states (Atkinson and Nager 2014). Sherk (2015) relies on anecdotal evidence, but even in his examples, it’s not clear that RTW status has led to company location decisions.10 In contrast, there are plenty of statistically rigorous studies that find little effect of RTW on manufacturing or overall employment growth (Stevans 2009;11 Eren and Ozbeklik 2015;12Lafer and Allegretto 2011;13Belman, Block, and Roberts 2009;14Hicks 201215).

The policy question at hand concerns precisely what RTW status does to similar workers. For example, do autoworkers in, say, Alabama earn lower wages than autoworkers in, say, Ohio in part because of RTW status? Still, we explore what happens to our wage equation when we remove industry controls, and we actually see the wage differential increase, albeit slightly (see the third model in Table 3).

Beyond industries, Sherk (2015) also suggests that unemployment rates and full-time status are two channels through which RTW can boost wages. But again, the empirical evidence finds that neither one changes our results. The removal of the unemployment rate control variable (the fourth model in Table 3) leaves the wage differential unchanged. When we remove full-time status, we do find that the wage differential moves closer to zero but remains statistically significant at -2.7 percent. Of the three mediums through which Sherk claims RTW can boost wages, we found that only one of them (full-time status) moved the wage differential closer to zero, but even this reduction was minimal, with the differential remaining economically and statistically significant.

Sherk also removes union status in his preferred model because it eliminates a likely channel through which RTW laws reduce wages. This would actually suggest that by including the union status variable, our regression results understate any wage penalty associated with RTW laws.16But again, the policy question is the effect of RTW status on similar workers. A key question is precisely whether working in a RTW state lowers the wages of even similar nonunion workers when compared with other states. We do in fact see that when we remove union status controls, the wage differential increases to 4.0 percent.

Standard practice in empirical labor economics when modeling the determinants of wages is to account for a full complement of factors that affect wages outside of the policy measure of interest (RTW status). Sherk’s (2015) arguments for the removal of several labor market control variables because those variables either directly or indirectly affect wages miss the point of this type of wage regression model: to control for things that affect wages. Clearly the unemployment rate where one lives, the industry one works in, whether one is full-time or part-time, and union status may all affect one’s wages and therefore should be included in the model. The goal of the analysis is to isolate the effect of RTW legislation, and removing labor market controls confounds these effects.

In his full model, Sherk (2015) also adds in several other variables without much justification. And these additions are quite idiosyncratic. For instance, he adds in 15 variables for educational attainment, includingseven different ones for workers without a high school degree or GED (a group that is less than 10 percent of the workforce). He also employs specific variables such as “married man,” “parent with a child at home,” and “single parent,” after already controlling for sex and marital status. His justification for the addition—or, alternatively, removal—of variables appears weak, at best.

Sherk also adds his own set of controls for state-level amenities. In theory, workers would be willing to accept a lower wage if they are able to enjoy more amenities (e.g., preferential weather, proximity to schools and shops, etc.). Winters (2009) worked with city-level data and was therefore able to use measures of amenities that were specific to the local level and could plausibly affect the value of one wage versus another between cities. It is difficult to conceive of appropriate measures for amenities that are uniform at the state level while not also oversimplifying preferences of workers and their families. Sherk’s choices of amenity control variables—whether or not a state borders an ocean (Los Angeles, California, does, for example, but Bakersfield, California, does not) and the average temperatures and precipitation by season—are fraught with those problems.

Since our results are very robust to model specification, only the accumulated weight of nonstandard model specification by Sherk resulted in an insignificant relationship between RTW status and workers’ wages. In the end, between the removal of relevant and standard labor market controls and the inclusion of nonstandard and irrelevant worker characteristics and state-level amenities, the regression specification that Sherk (2015) constructs to find no RTW wage differential looks deeply data-mined. In other words, his idiosyncratic choices may simply be the result of extensive searching for the model that produces the result he wants. On the other hand, our specification adheres to the industry standard for empirical labor economics and should clearly be preferred over his. And our results hold after reasonable robustness tests.


This paper updates and confirms the findings of Gould and Shierholz (2011). No matter how you slice the data, wages in RTW states are lower, on average, than wages in non-RTW states.

As shown in great detail in Gould and Shierholz (2011), these results do not just apply to union members, but to all employees in a state. Where unions are strong, compensation increases even for workers not covered by any union contract, as nonunion employers face competitive pressure to match union standards. Likewise, when unions are weakened by RTW laws, all of a state’s workers feel the impact.

About the authors

Elise Gould, senior economist, joined EPI in 2003 and is the institute’s director of health policy research.Her research areas include wages, poverty, economic mobility, and health care.She is a co-author ofThe State of Working America, 12thEdition. In the past, she has authored a chapter on health inThe State of Working America 2008/09;co-authored a book on health insurance coverage in retirement; published in venues such as The Chronicle of Higher Education,Challenge Magazine, and Tax Notes;and written for academic journals includingHealth Economics,Health Affairs,Journal of Aging and Social Policy,Risk Management & Insurance Review, Environmental Health Perspectives, and International Journal of Health Services.She holds a master’s in public affairs from the University of Texas at Austin and a Ph.D. in economics from the University of Wisconsin at Madison.

Will Kimball joined EPI in 2013. As a research assistant, he supports the research of EPI’s economists on topics such as wages, labor markets, macroeconomics, international trade, and health insurance. Prior to joining EPI, Will worked at the Center on Budget and Policy Priorities and the Center for Economic and Policy Research. He holds a B.A. in economics and political science from the University of Connecticut.

Appendix Table A1

Full log wage regression results from Table 2 regressions

VariablesModel with no controlsModel adds demographic and individual-level labor market controlsModel adds state-level labormarket controls and cost-of-living measuresFinal model, updates cost-of-living indicator
RTW indicator-0.136***-0.0936***-0.0329***-0.0318***
Union indicator0.129***0.118***0.117***
Other race/ethnicity0.0496***0.0463***0.0480***
Some high school-0.119***-0.120***-0.119***
Some college0.0692***0.0668***0.0678***
Associate degree0.151***0.149***0.150***
College degree0.264***0.259***0.261***
Advanced degree0.461***0.455***0.457***
Age squared-0.000332***-0.000333***-0.000334***
Divorced or widowed0.0366***0.0456***0.0453***
Hourly worker-0.178***-0.171***-0.170***
Full-time worker0.148***0.151***0.150***
Metro area0.124***0.0944***0.0957***
State unemployment rate-0.00325***0.000247
Cost-of-living (PERI)0.606***
Cost-of-living (MERIC)0.000772***
Cost-of-living (BEA RPPI)0.771***
Industry and occupation indicatorsNoYesYesYes

Note: Robust standard errors in parentheses. Three asterisks (***) indicate significance at the 1 percent level, two indicate significance at the 5 percent level, one indicates significance at the 10 percent level.

(Video) Robert Reich: Why "Right to Work" is Wrong for Workers

All models include year indicators.

Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata, Political Economy Research Institute (PERI) data, Missouri Economic Research and Information Center (MERIC) data, and Bureau of Economic Analysis Regional Price Parities

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Appendix Table A2

Full log wage regression results from Table 3 regressions

VariablesTwo-stage least squares (second-stage results)Less occupationsLess industriesLess unemployment rateLess full-time statusLess union
RTW indicator-0.0315***-0.0308***-0.0322***-0.0319***-0.0271***-0.0407***
Union indicator0.117***0.101***0.133***0.117***0.127***
Other race/ethnicity0.0480***0.0647***0.0420***0.0479***0.0445***0.0449***
Some high school-0.119***-0.143***-0.130***-0.119***-0.125***-0.123***
Some college0.0678***0.0961***0.0752***0.0678***0.0596***0.0688***
Associate degree0.150***0.202***0.158***0.150***0.148***0.150***
College degree0.261***0.364***0.277***0.261***0.259***0.262***
Advanced degree0.457***0.595***0.457***0.457***0.453***0.463***
Age squared-0.000334***-0.000344***-0.000375***-0.000334***-0.000395***-0.000339***
Divorced or widowed0.0453***0.0494***0.0546***0.0453***0.0503***0.0461***
Hourly worker-0.170***-0.220***-0.180***-0.170***-0.191***-0.167***
Full-time worker0.150***0.171***0.185***0.150***0.157***
Metro area0.0955***0.103***0.0932***0.0958***0.0950***0.0965***
State unemployment rate0.0002130.000508-0.00125**0.000010.000429
Cost-of-living (BEA RPP)0.775***0.796***0.779***0.772***0.763***0.808***

Note: Robust standard errors in parentheses. Three asterisks (***) indicate significance at the 1 percent level, two indicate significance at the 5 percent level, one indicates significance at the 10 percent level.

Unless otherwise indicated, the regression models include variables in Model IV from Appendix Table A1.

Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata, Political Economy Research Institute (PERI) data, Missouri Economic Research and Information Center (MERIC) data, and Bureau of Economic Analysis Regional Price Parities


1. RTW states include Alabama, Arizona, Arkansas, Florida, Georgia, Idaho, Indiana, Iowa, Kansas, Louisiana, Michigan, Mississippi, Nebraska, Nevada, North Carolina, North Dakota, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Wisconsin, and Wyoming.

2. Although Indiana’s RTW legislation took effect in March 2012, we include Indiana as a non-RTW state in our analysis. Any economic changes due to RTW status would likely operate with a lag. We did run sensitivity analysis on this decision by re-running our regressions without Indiana, and found that the wage differential was essentially unchanged.

3. We exclude all observations for which earnings are allocated. Information is “allocated,” or “imputed,” to a respondent in the CPS when they either refuse to report their earnings or a proxy respondent is unable to report earnings. The method of imputing earnings to workers for whom earnings are not reported does not take account of their union status, thus reducing the estimates of the union wage premium and potentially biasing the relationship between RTW and wages.

4. For the purpose of this analysis, which contains pooled data from 2010 to 2012, three states (Indiana, Michigan, and Wisconsin) that have recently enacted RTW legislation are considered non-RTW.

5. All wages are adjusted to 2014 dollars using the CPI-U-RS.

6. Interpreting the results from these semilogarithmic functions requires utilizing the exponential function on the coefficient. Specific to the binary variable coefficient (β1) for RTW, the percent change in workers’ wages resulting from a state being RTW can be calculated by the formula: 100*[exp(β1)-1]. Typically, the result of this equation will be very close to the coefficient itself, but will differ more as the coefficient becomes larger.

7. See Gould and Shierholz (2011) for a more extensive discussion of these cost-of-living measures.

8. Sherk (2015) also includes an indicator for whether a state borders the ocean, but since there is little justification for its inclusion, we do not include it. Additional discussion of state-level amenities follows.

9. We examined the relationship between the share of manufacturing jobs and RTW status in a simplified regression model with only demographic controls. The result was not consistent with Sherk’s (2015) proposition. Results are available upon request.

(Video) At-Will Employment Explained by a Lawyer

10. In the very industry that Sherk raises as his hypothetical—the auto industry—the effect of RTW status on site location decisions is ambiguous at best. In fact, the North American vice president for site location for Toyota reported that RTW had no effect one way or the other on Toyota’s choice to build a plant in Mississippi and another in Texas (Sloan 2011). Furthermore, in the first year after adopting RTW, the state of Indiana was not able to identify a single company that stated it had moved to Indiana because of RTW and would not have done so without the law (Lafer, Wolfson, and Guyott 2012).

11. A 2009 study conducted by Hofstra University economics professor Lonnie Stevans controlled for a broad array of economic and business climate variables, and concluded that RTW is associated with lower wages and higher proprietors’ income but has “no influence on employment” and “no effect on economic growth.”

12. An econometric study conducted by a pair of economics faculty at Louisiana State University and the Claremont McKenna Colleges and slated for publication in 2015 examined the impact of Oklahoma’s adoption of RTW, concluding that the law resulted in a decrease in unionization but no significant impact on employment either overall or specifically in the manufacturing sector.

13. In 2011, an economist at the University of California at Berkeley, together with a political scientist at the University of Oregon, examined Oklahoma’s experience after adopting RTW in 2001. Conducting multiple forms of regression analysis, the authors found that RTW had no impact whatsoever on overall job growth, manufacturing job growth, or the state’s unemployment rate.

14. A 2009 analysis by a team of faculty at Michigan State University’s School of Labor and Industrial Relations likewise found that after controlling for the impact of other state economic policies and industrial dynamics, “right to work laws … seem to have no effect on economic activity.”

15. A 2012 study by the director of the Center for Business and Economic Research at Ball State University in Indiana concluded that RTW had no discernible effect on manufacturing employment.

16. Sherk (2015) is correct here that excluding the union indicator would increase the wage differential between RTW and non-RTW states, but we argue that it should still be included for all the reasons already mentioned.


Area Development Magazine. 2014. “28th Annual Survey of Corporate Executives: Availability of Skilled Labor New Top Priority.” http://www.areadevelopment.com/Corporate-Consultants-Survey-Results/Q1-2014/28th-Corporate-Executive-RE-survey-results-6574981.shtml?Page=2.

Atkinson, Robert, and Adams Nager. 2014. The 2014 State New Economy Index: Benchmarking Economic Transformation in the States. Information Technology and Innovation Foundation. http://www2.itif.org/2014-state-new-economy-index.pdf

Belman, Dale, Richard Block, and Karen Roberts. 2009. “Economic Impact of State Differences in Labor Standards in the United States, 1998-2000.” Employment Policy Research Network blog, February.

Blanchflower, David G., and Andrew J. Oswald. 1996. The Wage Curve. Cambridge, Mass.: MIT Press.

Bureau of Economic Analysis (U.S. Department of Commerce) Regional Data: GDP and Personal Income. Various years. Regional Data: GDP and Personal Income Tables [data tables]. http://www.bea.gov/itable/iTable.cfm?ReqID=70&step=1#reqid=70&step=1&isuri=1

Bureau of Labor Statistics (U.S. Department of Labor) Consumer Price Indexes program. Various years. All Urban Consumers: Consumer Price Index (CPI) [database]. http://www.bls.gov/cpi/data.htm

Bureau of Labor Statistics (U.S. Department of Labor) Local Area Unemployment Statistics program. Various years. Local Area Unemployment Statistics (LAUS) [database]. http://www.bls.gov/lau/data.htm

Current Population Survey Outgoing Rotation Group microdata. Various years. Survey con­ducted by the Bureau of the Census for the Bureau of Labor Statistics [machine-readable microdata file]. Washington, D.C.: U.S. Census Bureau. http://thedataweb.rm.census.gov/ftp/cps_ftp.html#cpsbasic

Gould, Elise, and Heidi Shierholz. 2011. The Compensation Penalty of “Right-to-Work” Laws. Economic Policy Institute, Briefing Paper No. 299. http://www.epi.org/publication/bp299/

Heintz, James, Jeannette Wicks-Lim, and Robert Pollin. 2005. The Work Environment Index: Technical Background Paper. Political Economy Research Institute (PERI) Working Paper No. 107. http://www.peri.umass.edu/fileadmin/pdf/resources/WEItechappendix.pdf

Hicks, Michael J. 2012. Right-to-Work Legislation and the Manufacturing Sector. Center for Business and Economic Research (Ball State University) report. https://cms.bsu.edu/-/media/WWW/DepartmentalContent/MillerCollegeofBusiness/BBR/Publications/RightToWork/RightToWork.pdf

Lafer, Gordon, and Sylvia Allegretto. 2011. Does Right-to-Work Create Jobs? Answers from Oklahoma. Economic Policy Institute Briefing Paper No. 300. http://www.epi.org/publication/bp300/

Lafer, Gordon, Marty Wolfson, and Nancy Guyott. 2012. Indiana Experience Offers Little Hope for Michigan ‘Right-to-Work’ Law. Economic Policy Institute Policy Memorandum #199. http://www.epi.org/publication/pm199-indiana-experience-offers-little-hope-michigan-right-to-work/

Lemieux, Thomas. 2011. “Wages and Occupations.” Albert Rees’ Lecture presented April 30. http://www.sole-jole.org/2011LemieuxReesLecture.pdf

Missouri Economic Research and Information Center (MERIC). 2010. “Cost of Living Data Series: 2010 Annual Average.” Economic Indicators, Missouri Economic Research and Information Center website. http://www.missourieconomy.org/indicators/cost_of_living/index.stm

Moore, W.J. 1998. “The Determinants and Effects of Right-To-Work Laws: A Review of the Recent Literature.” Journal of Labor Research, vol. 19, no. 3, 449–469.

Moore, W.J., and R.J. Newman. 1985. “The Effects of Right-to-Work Laws: A Review of the Literature. Industrial and Labor Relations Review, vol. 38, no. 4, 571–585.

Ozkan, Eren, and Serkan Ozbeklik. 2015, forthcoming. “What Do Right-to-Work Laws Do? A Case Study Analysis Using Synthetic Control Method.” Journal of Policy Analysis and Management.

Sherk, James. 2015. “How Unions and Right-to-Work Laws Affect the Economy.” Testimony before the Wisconsin Senate Committee on Labor and Government Reform, February 24. http://www.heritage.org/research/testimony/2015/how-unions-and-right-to-work-laws-affect-the-economy

Sloan, Scott. 2011. “Kentucky Got Toyota in 1986, but Why Have None Come Since?” Herald-Leader, May 2. http://www.kentucky.com/2011/05/01/1725979/kentucky-got-toyota-in-1986-but.html

Stevans, Lonnie K. 2009. “The Effect of Endogenous Right-to-Work Laws on Business and Economic Conditions in the United States: A Multivariate Approach.” Review of Law and Economics, 2009, vol. 5, no. 1, 595–614.

Winters, John V. 2009. “Wages and Prices: Are Workers Fully Compensated for Cost of Living Differences?” Regional Science and Urban Economics, 2009, vol. 39, 632–643.


Which state has the best worker rights? ›

The data published is based on laws and policies in effect as recent as July 2022. Oregon took the top spot as the best state to work in the U.S for the second straight year. The state received high marks for its policies to improve workplace conditions and ensure workers the right to form unions.

What does right-to-work state mean in Florida? ›

Florida is also a “right to work” state. This term has nothing to do with an employer's hiring or firing you. Instead, it simply means that unionization is not compulsory, and your employer is not able to force you to participate in a union or to pay union dues.

What state has the most union workers? ›

Union affiliation by U.S. state
RankStatePercent union members
2New York22.2
48 more rows

Is Ohio a right-to-work 2022? ›

When Can Your Employer Terminate You? You have a lot of rights as an Ohio worker, but you may be surprised by some of the things to which you are not entitled. Ohio is an at-will employment state, meaning unless you have a contract stating otherwise, your employer can terminate you at any time, without notice.

What are the cons of a right-to-work state? ›

Opponents counter that workers in right-to-work states earn lower wages, thereby decreasing consumer demand, resulting in fewer jobs. Right-to-work states tend to have much lower rates of union membership.

Are the 10 poorest states all right-to-work states? ›

In order, these states are New Hampshire, Minnesota, Vermont, Utah and Massachusetts. "Right to work" states account for eight of the 10 worst states, and all five of the five worst states (in order, from 46th–50th: Alabama, Tennessee, Arkansas, Louisiana, Mississippi).

Are right-to-work states better? ›

National Study Says So-called “Right to Work” States Have Worse Economic, Health, Social, and Civic Outcomes – The Illinois Update.

Who Benefits From right-to-work laws? ›

Right-to-work proponents believe that these laws improve economic growth and allow workplaces to remain competitive in a global economy. Both companies and workers benefit from a better economy, as wages and corporate earnings increase.

Which states do not allow unions? ›

The states that have laws against union membership as a condition of employment are Alabama, Arizona, Arkansas, Florida, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Michigan, Mississippi, Nebraska, Nevada, North Carolina, North Dakota, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, ...

What is the strongest union in America? ›

The AFL-CIO is the largest union federation in the U.S., made up of 55 national and international unions with 12.5 million members worldwide. Its member unions span from the Actors Equity Association to the Utility Workers Union of America. WHO IS THE AFL-CIO PRESIDENT?

What is the least unionized state? ›

Ten states had union membership rates below 5.0 percent in 2021. South Carolina had the lowest rate (1.7 percent), followed by North Carolina (2.6 percent) and Utah (3.5 percent). Two states had union membership rates over 20.0 percent in 2021: Hawaii (22.4 percent) and New York (22.2 percent).

Which occupations are most heavily unionized? ›

Most Unionized Occupations
  1. Police officers. Union membership rate: 52.8%
  2. Secondary school teachers. Union membership rate: 49.6% ...
  3. Elementary and middle school teachers. Union membership rate: 46.6% ...
  4. Electricians. ...
  5. Teaching assistants. ...
  6. Plumbers, pipefitters, and steamfitters. ...
  7. Social workers, all other. ...
  8. Postsecondary teachers. ...
1 Aug 2022

Does Ohio follow the 7 year rule? ›

How Far Back Can a Background Check for Employment in Ohio Go? The seven-year lookback period under the FCRA applies to Ohio employment background checks.

What is the new minimum wage for 2022 in Ohio? ›

In 2022, Ohio's minimum wage was $9.30 per hour for non-tipped employees, and $4.65 per hour for tipped employees.

Does Ohio pay double time? ›

(A) Except as provided in section 4111.031 of the Revised Code, an employer shall pay an employee for overtime at a wage rate of one and one-half times the employee's wage rate for hours worked in excess of forty hours in one workweek, in the manner and methods provided in and subject to the exemptions of section 7 and ...

Why right to work is wrong for workers? ›

Right to Work Hurts Everyone

Workers in states with right to work laws have a consistently lower quality of life than in other states—lower wages, higher poverty and infant mortality rates, less access to the health care they need and poorer education for their children.

How long does right to work last? ›

You must contact the Home Office Employer Checking Service. If the person has a right to work, the Employer Checking Service will send you a 'Positive Verification Notice'. This provides you with a statutory excuse for 6 months from the date in the notice. It remains an offence to work illegally in the UK.

Why are unions against right to work? ›

These laws are anti-union and anti-worker because they drive down everyone's wages, benefits, and overall living standards. By many measures, the quality of life is worse in states with “right to work” laws. These laws take away working people's freedom to join together and negotiate for a fair return on their work.

Do right-to-work states have higher wages? ›

She pointed to research from the Economic Policy Institute that found wages in right-to-work states were 3.1% lower than non-right-to-work states after accounting for differences in the cost of living.

What is the hardest working state? ›

Alaska has the longest hours worked per week, 41, which is 11 percent longer than in Utah, the state with the shortest at 37. New York has the longest average commute time, 34 minutes, which is two times longer than in South Dakota, the state with the shortest at 17 minutes.

Whats the most hard working state? ›

North Dakota is the hardest working state in America, according to a new report from WalletHub. WalletHub compared the 50 states across 10 key indicators, ranging from average hours worked per week to the number of workers with multiple jobs to identify where the nation's hardest working people live.

How right-to-work laws affect wages? ›

They find a difference of nearly 20 percent in the unionization rate between states with and without right-to-work laws. Right-to-work laws are also associated with 7.5 percent lower wages.

What are the benefits of right-to-work? ›

What are the benefits of right to work?
  • Right to work laws expand workers' rights. The right-to-work law expands workers' rights by giving them the right to decide whether or not they want to join a union.
  • Right to work laws hold unions accountable. ...
  • Right to work laws give workers more financial freedom.
14 Feb 2022

Is right-to-work unconstitutional? ›

Twenty-eight states have right-to-work policies (either by statutes or by constitutional provision). In 2018, the U.S. Supreme Court ruled that agency shop arrangements for public sector employees were unconstitutional in the case Janus v. AFSCME.

What proof is right to work? ›

Birth or adoption certificate

UK, when produced in combination with an official document giving the person's permanent national insurance number and their name issued by a government agency or a previous employer.

Does Right to Work create jobs explain? ›

Research shows that states with right-to-work laws feature higher employment rates but lower average wages and union membership than states without it. At present, there is no federal right-to-work law, but 27 states have one on the books. National Conference of State Legislatures.

Is Las Vegas a right to work state? ›

Nevada is a right-to-work state. Right-to-work laws prohibit agreements between labor unions and employers making membership in a union, or payment of union dues, a condition of employment.

What political party is against unions? ›

Since the 1920s Republicans have generally been opposed to labor unions, which comprise a major component of the Democratic New Deal coalition.

Are unions making a comeback? ›

While Americans are more likely to believe unions have lost rather than gained power over the past 30 years, there is some evidence of a perceived rebound in their influence over the past year (a finding consistent with data on union elections from the National Labor Relations Board): 31% say unions have gotten ...

Can you fire employees for unionizing? ›

Can you be fired for joining a union? Your employer can speak to you about the union, but under the law they are not allowed to threaten, coerce, discriminate, make promises, impose a penalty, or do anything that stops you from making a free decision on union representation.

What state has the best union? ›

1. Washington
  1. Washington. Washington climbed from third place in last year's study to claim the top spot as the state with the strongest unions in 2022. ...
  2. Oregon. Oregon drops one spot this year with a dip in rankings across different metrics. ...
  3. California. ...
  4. New Jersey. ...
  5. Pennsylvania. ...
  6. Massachusetts. ...
  7. New York. ...
  8. Rhode Island.
31 Aug 2022

What is the strongest weapon a labor union has? ›

Union members withholding their labor through a strike is also a one of the Union's strongest weapons. It's one that isn't brandished often, but it's still as powerful today as it was then.

What union makes the most money? ›

The highest-paid union trade is a nuclear power reactor operator. A nuclear power reactor operator has a median salary of $91,730 a year. These workers control and operate nuclear reactors.

Is it better to go union or non-union? ›

Workers in union-represented jobs have a clear advantage over their non-union counterparts. On average, union members have better insurance, better retirement benefits, paid sick leave and higher pay.

What states are most union friendly? ›

States With the Highest Union Participation Rates
  1. Hawaii. Percentage of workers who are union members: 22.4%
  2. New York. Percentage of workers who are union members: 22.2% ...
  3. Washington. Percentage of workers who are union members: 19.0% ...
  4. Oregon. ...
  5. New Jersey. ...
  6. Minnesota. ...
  7. California. ...
  8. Alaska. ...
13 Jul 2022

Why are there no unions in the South? ›

The Enduring Politics of an Anti-Union Generation

Many Southerners saw industrialization and labor organization as a threat to their agricultural way of life. So, political leaders in the South used their power to ensure that unions couldn't establish themselves in the region.

What union is the best to join? ›

Six best union jobs
  1. School bus driver. National average salary: $16.48 per hour. ...
  2. Carpenter. National average salary: $20.67 per hour. ...
  3. Machinist. National average salary: $21.49 per hour. ...
  4. Electrician. National average salary: $23.58 per hour. ...
  5. Nuclear power reactor operator. ...
  6. Tractor-trailer truck driver.

Are unionized workers happier? ›

In the U.S., the U.K., Europe and elsewhere, union members, particularly younger union members, are now happier, even after controlling for some of the scenarios listed above.

What is the 20 day rule in Ohio? ›

In a situation where an employee begins working remotely (e.g., from home), Ohio ordinarily follows a "20-day rule" under which an employer doesn't need to withhold tax for a municipality if the employee is working in the municipality for 20 or fewer days.

Is Ohio an at will state for firing? ›

Ohio is an employment-at-will state, which means that, in the absence of a written employment agreement or a collective bargaining agreement, either the employer or the employee can terminate employment for any reason that is not contrary to law.

Do warrants show up on background checks? ›

In most cases, standard criminal record checks will not reveal any warrants. Unless your employer conducts an FBI or level 2 background check, warrants are unlikely to appear. If you'd like to learn more about a criminal records background check, you can review Checkr's screenings service.

What is a livable salary in Ohio? ›

Living Wage Calculation for Ohio
0 Children2 Children
Living Wage$15.61$34.83
Poverty Wage$6.19$12.74
Minimum Wage$9.30$9.30

What does Walmart pay in Ohio? ›

How much does Walmart in Ohio pay? Average Walmart hourly pay ranges from approximately $10.00 per hour for Cashier/Clerk to $31.11 per hour for Trailer Mechanic. The average Walmart salary ranges from approximately $18,000 per year for Sales to $101,046 per year for Senior Software Engineer.

What state has the highest minimum wage? ›

The highest minimum wage is in Washington D.C. at $16.10 per hour, followed by Washington at $14.49 and Massachusetts at $14.25. Here is a list of all the states with a minimum wage higher than the federal minimum wage.

Is 32 hours considered full-time in Ohio? ›

A full time employee is defined as an individual employed on a forty hour per week, nine-, ten-, eleven-, or twelve-month basis per fiscal year; or an individual employed an average of not less than thirty hours per week on a twelve month contract shall be considered a full time employee.

Is working 32 hours considered full-time? ›

Definition of Full-Time Employee

For purposes of the employer shared responsibility provisions, a full-time employee is, for a calendar month, an employee employed on average at least 30 hours of service per week, or 130 hours of service per month.

Is mandatory overtime illegal in Ohio? ›

An Ohio employer can legally require that its employees work overtime. There are no federal or Ohio laws that prohibit or otherwise limit the right of an employer to require its employees to work as many hours as an employer sees fit.

What is the most hardworking state? ›

North Dakota is the hardest working state in America, according to a new report from WalletHub. WalletHub compared the 50 states across 10 key indicators, ranging from average hours worked per week to the number of workers with multiple jobs to identify where the nation's hardest working people live.

Who has the best labor laws in the world? ›

The top five countries are explored here, from the point of view of employees, with best worker laws and their labor traditions.
  • Austria: ...
  • Belgium: ...
  • Denmark: ...
  • Finland: ...
  • Germany:
22 Apr 2022

Which states are not employer friendly? ›

Least friendly state governments – California, Rhode Island and Illinois failed, receiving an F. D-rated states include Connecticut, New Jersey and Pennsylvania.

Which state has the best life? ›

2022's top 10 best states to live in
  • New York; Score: 60.64.
  • Idaho; Score: 58.73.
  • Virginia; Score: 58.73.
  • New Hampshire; Score: 58.25.
  • Florida; Score: 58.07.
  • Wyoming; Score: 58.
  • Minnesota; Score: 57.99.
  • Wisconsin; Score: 57.92.
16 Aug 2022

What is the most difficult state to live in? ›

Worst States to Live in 2022
New Hampshire41
43 more rows

What state is hardest to find jobs? ›

Wrapping Up
RankStateRecent Job Growth
3West Virginia-0.72%
37 more rows
21 Jul 2022

Who is the number 1 employer in the world? ›

Walmart is one of the largest companies in the world, generating 523.96 billion U.S. dollars in 2019.
Leading 500 Fortune companies based on number of employees in 2020.
CharacteristicNumber of employees
12 more rows
5 Aug 2022

Who is the best employer in the world? ›

1 best employer in the world: Samsung Group. The Samsung Group was founded in 1938 and is headquartered in Seoul, South Korea. According to Forbes, the tech company was also featured as one of the best employers for new grads.

Why are unions against right-to-work? ›

These laws are anti-union and anti-worker because they drive down everyone's wages, benefits, and overall living standards. By many measures, the quality of life is worse in states with “right to work” laws. These laws take away working people's freedom to join together and negotiate for a fair return on their work.

Which state is the most corporate friendly? ›

America's Top States for Business 2022
Overall RankStateCost of Doing Business
1North Carolina26
26 more rows
13 Jul 2022

Which state is the least business friendly? ›

The 10 lowest-ranked, or worst, states in this year's Index are:
  • Hawaii.
  • Vermont.
  • Minnesota.
  • Maryland.
  • Connecticut.
  • California.
  • New York.
  • New Jersey.
25 Oct 2022


1. Fair Share vs. Right to Work Laws
(Citizen Genius)
2. right to work for less wages
(Robert Gomez)
3. 5 Rights Overlooked by Employees - Employment Law Show: S3 E23
(Samfiru Tumarkin LLP Employment Lawyers)
4. Will Coursey Speaks against Right to Work & Prevailing Wage
(House Dem Caucus)
5. The West Block - The future of unions in Canada
(Global News)
6. Damon Miles on union wages
(Right to Work HURTS Missouri Families)
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