Funding Distribution and the Noveau Poor

During my time as state workforce administrator for Ohio, one of the duties that had become a ritual responsibility with each economic downturn was my journey to the Cleveland/Cuyahoga County Workforce Investment Board to explain why their allocations were smaller than those from the prior year. Not that they were alone in questioning the reductions they experienced, I was also receiving letters from the workforce boards of the Appalachian counties in southeastern Ohio asking the same question.

The board members all knew that the allocation formula was based primarily on poverty and unemployment. Hadn’t we provided WIA training that clearly told them about that? The funding reductions seemed to defy logic. After all, weren’t these areas among the poorest in the State? The economies of each had experienced higher than average unemployment for many years. Lack of transportation, industry change, aging infrastructure, inadequate financial support for schools, and multi-generational poverty presented challenges to these areas on a much larger scale than many areas of the state. They questioned the State’s calculations. Surely the numbers must be wrong. Things had not gotten better, if anything they had gotten worse. Reducing their funding seemed to defy logic.

Each time, I would dutifully explain how funding formulas worked. That poverty was based on decennial census data and would remain unchanged until the next census, effectively taking that factor out of year-to-year funding variations. What remained as the factor driving the calculations was unemployment data. They would listen quietly as I explained the relative nature of the calculations. That the thresholds for ASU unemployment and excess unemployment were fixed and that as the economy declined and more areas experienced employment loss, those areas with historically high unemployment that always exceeded the established thresholds were being joined in that group by additional areas that now qualified due to increased unemployment. They sighed as I explained that without additional resources being added, the same amount of funding was being shared by more areas who met the qualifications for excess and ASU unemployment. Eyes glazed over as I explained that excess unemployment had little impact because it counted only those unemployed in excess of 4.5% of the labor force but ASU unemployment was the real culprit, because it counted all those residing in such an area, giving heavy impact to the densely populated counties surrounding the metro areas. Ultimately,they accepted that the calculations were correct, but never that they were right. It was difficult to accept that the poorest areas of the state with the highest unemployment would experience reductions while suburban areas, with comparably healthier economies were receiving increases. They would shrug and leave the meetings further convinced in the illogic of government regulation and the fundamental unfairness of it all.

While the ability to comprehend the complex and arcane science of government had always been a source of some ego satisfaction for me, I never felt good leaving those meetings. Like a professional spin-doctor, I left feeling empty, aware that I had successfully defended a policy that I could not rationalize in my own mind.

Since my retirement, those duties now fall to someone else. But, as I read about the rollout of the new decennial census, an uneasy thought crossed my mind. Could we see something similar occurring when poverty is recalibrated among the areas of the state? Could the current recession set a new departure point for poverty based upon the impacts of large-scale layoffs and income loss that will remain in place for the coming decade skewing the distribution of resources away from the areas of historical poverty towards areas more likely to recover in the coming years? I’m not sure. But in any event, it will be someone else’s charge to explain that one.