Last Friday, the first round of recipient reported Recovery Act grant and loan data was made available on the Recovery.gov website. Much like the previously released federal contract data, this wave of data lacks the comprehensive information needed to truly determine how the funds are being spent and from what source. The data are both difficult to decipher and include several instances of human error.
While working with the data we discovered several issues that make the data difficult to understand. For example, less than half of all education-related data are tagged with the funding agency name "Department of Education." Other possible funding agencies include "Federal Student Aid," "Impact Aid Programs," "Office of Elementary and Secondary Education," "Office of Higher Education Programs," "Office of Special Education and Rehabilitative Services," "Office of Postsecondary Education," and "Office of Vocational and Adult Education."
Additionally, data that should be education-related are tagged with TAS codes that are not for education programs. As we've discussed before, the Treasury Accounting Symbol (TAS) is used to identify funding sources in each record. Of the 15 TAS codes in the education-related data, only nine of those codes pertain to education programs. The remaining six appear to be the result of erroneously entered codes. These erroneous codes account for 17 education-related records.
While helpful to a certain extent, the TAS code does not always identify specific programs. For example, the TAS code for the State Fiscal Stabilization Fund does not distinguish between Education Stabilization and Government Services Funds. Similarly, the School Improvement TAS code does not distinguish between McKinney Vento Homeless Education and Education Technology grant funds. This further information is included in the qualitative variables in the data which are impossible to categorize systematically, making it difficult to determine exactly what funding sources each record is referring to.
Significant information is missing in the sub recipient data as well (in this case, school districts or institutions of higher education are considered sub recipients). None of the sub recipient data contain information on funding agency or TAS codes, making it impossible to determine the funding sources or programs referenced in any of the sub recipient data. (We hope to receive this data with all the proper information in the near future.)
However, using the prime recipient data, we were able to extrapolate data on jobs created or saved and funds awarded, received, and expended by TAS code and by state. For example, the data we have show that a total of $58.8 billion in education related stimulus funds have been awarded. Of that amount, $14.2 billion has been received and $14.0 billion has been expended. Nearly 398,000 jobs were created or saved by the stimulus.
The amount of received funds that have been expended varies widely by state, as does the number of jobs saved. For example, Alaska has expended only 2.2 percent of its received funds, while Connecticut has expended 188.0 percent of its received funds. It is possible for a state to expend funds before they have received them because some states receive federal funds on a reimbursement basis after the expenditures have been made. It is very likely that Connecticut, and the 16 other states that have expended more than 100 percent of their received funds are on reimbursement plans for the education funds. Wyoming reported that it saved 15 jobs through the education stimulus funds, while California claims to have saved nearly 81,000.
The percent of funds expended also varies widely by program. For example, the data suggests that 108.7 percent of the received School Improvement funds have been expended while only 38.2 percent of the received Impact Aid funds have been expended. More than 100 percent of received Higher Education Program, Special Education, Title I, and School Improvement funds have been expended. The data also suggest that State Fiscal Stabilization Funds were used to save more than 316,000 jobs and special education funds were used to save more than 35,500.
It is clear that stimulus fund recipient reported data, while valuable for understanding how funds effect education and the economy, are being collected in a flawed manner. The data lack comprehensive information on funding sources, and problems with sub recipient data make it impossible to determine what is happening with the funds in school districts and institutions of higher education. Further, human error in data reporting is skewing findings. Hopefully, the Department of Education will work out these kinks as reporting continues. If not, state and local efforts to report this information may be fruitless in the end.
Complete data on recipient reported data by state and by TAS code are available here and here.