How Can You Measure Welfare Program Success?

Part 2

By Erik Randolph

My last blog explained dependency metrics and how they measure the success of welfare programs. However, these metrics are not the complete answer.

By also following people after they leave the system, we can gain a fuller picture of success.

This technique is common for job training programs. In fact, it is a requirement for state and local agencies receiving federal funding per the Workforce Innovation and Opportunity Act, where agencies routinely measure the status and income of persons up to a year after  exiting the job training program. 

Follow-the-person metrics can be used for welfare programs as well, as Kansas and Maine already  demonstrate. 


Background on Food Stamp Work Requirements

 When the U.S. economy was recovering from the Great Recession, the states of Kansas and Maine led the nation in reinstating the federal work requirement for “Able-Bodied Adults Without Dependents” (ABAWDs).   

The news media generally criticized the governments of Kansas and Maine for reinstating the rule, claiming it was cruel to push ABAWDs off food assistance. Kansas and Maine responded with follow-the-person data. 

Shortly thereafter in 2015—while Barack Obama was still president—the federal Food and Nutrition Service urged all other states to follow the federal law by reinstating the ABAWD rule. However, most states were hesitant to do so, and they continued seeking waivers and exemptions from enforcing it.

Federal law has two work requirements for the food stamp program. There is the general work requirement for persons ages 19 through 59 with notable exceptions, such as being in school half-time, physically or mentally unfit for employment, or caring for a child under six years of age or an incapacitated person. Under the general work requirement, the recipient must register for work or otherwise have good cause if they are not working at least 30 hours per week or enrolled in a job-training or workfare program. 

The second work requirement is specific to ABAWDs. This rule applies to persons ages 18 through 49, unless they are already exempt from the general work requirement or if they are responsible for a child under 18 years of age, or pregnant. Non-exempt ABAWDs cannot receive benefits for more than three months in a 36-month period unless they work for an average of 20 hours per week on a monthly basis or they participate in an approved “employment and training” program. 

States may, and routinely do, waive the ABAWD rule in areas within their state with unemployment over 10 percent, and they have the discretion to exempt up to 15% of persons from the requirement. 

During the Great Recession, Congress suspended the ABAWD rule until September 20, 2010, but many states continued waiving the requirement well into 2017. 


Kansas and Maine Break New Ground 

Under the administration of Governor Sam Brownback, Kansas restored the ABAWD rule in October 2013. The Kansas Department for Children and Families, with the help of the state’s Department of Labor, followed the wages of individuals exiting the food stamp program. Departments of labor typically administer unemployment insurance programs that collect wage data. 

According to a report by the Foundation for Government Accountability, Kansas had 28,144 ABAWDs on food stamps in October 2013. One year later, in October 2014, there were 9,193. The following October, the number dropped to 7,601.

The drop in enrollment among this population may be alarming if one assumes these individuals were worse off, as many in the news media did. However, the follow-the-person data showed otherwise. On average, the annual wages of these individuals rose above the poverty line, from $6,703 in December 2013 to $13,304 in the fourth quarter of 2014. 


Maine had a similar experience.

No longer requesting an ABAWD waiver in 2014, the Maine Departments of Labor and Health & Human Services cooperated in following the wages of the 6,866 who did not comply with the reinstatement of the work requirement and exited the program. The Governor’s Office of Policy and Management under the political leadership of Governor Paul LePage analyzed the wage data. Its report showed total wages for this group more than doubled from the third quarter of 2014 to the fourth quarter in 2015. On average, quarterly wages increased from $1,984 to $3,514, also raising the wages of many ABAWDs above the poverty level. 



What Follow-the-Person Metrics Could Mean for Georgia and Other States

Unfortunately, both Kansas and Maine abandoned the follow-the-person data collection—not for policy reasons related to the effectiveness of the metrics but because of changes in political leadership.

Nevertheless, the states demonstrated that follow-the-person metrics can be applied to welfare programs in addition to job training programs. There is no good reason why Georgia and other states could not also implement follow-the-person metrics for welfare programs by having their welfare agencies cooperate with their departments of labor.

Additionally, states are not limited to using department of labor wage data. They could also initiate surveys to collect more detailed data on the well-being of individuals after exiting a program. 

Do you think it would be good for Georgia to begin using dependency and follow-the-person metrics to measure the success of welfare programs? Let us know in the comments below.


Erik Randolph is Director of Research at the Georgia Center for Opportunity. This blog reflects his opinion and not necessarily that of the Georgia Center for Opportunity.


Based on the most recent 2015 data, this report provides an in-depth look at the welfare cliffs across the state of Georgia. A computer model was created to demonstrate how welfare programs, alone or in combination with other programs, create multiple welfare cliffs for recipients that punish work. In addition to covering a dozen programs – more than any previous model – the tool used to produce the following report allows users to see how the welfare cliff affects individuals and families with very specific characteristics, including the age and sex of the parent, number of children, age of children, income, and other variables. Welfare reform conversations often lack a complete understanding of just how means-tested programs actually inflict harm on some of the neediest within our state’s communities.

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