Unemployment Insurance (UI) Worker Misclassification Prevention and Detection Supplemental Supporting Statement

Unemployment Insurance (UI) Supplemental Funding Opportunity for

Worker Misclassification Prevention and Detection

Supplemental Justification

Supplemental Supporting Statement A: Justification

This request seeks OMB approval under the Paperwork Reduction Act for the unique information collection requirements in the Unemployment Insurance (UI) Supplemental Funding Opportunity (FO) for Worker Misclassification Prevention and Detection.

The U.S. Department of Labor (Department), Employment and Training Administration (ETA), is committed to the development of UI tax-related systems and tools focused on the prevention and detection of worker misclassification. The Consolidated and Further Continuing Appropriations Act, 2015, (the Act) provides funds for states to enhance their prevention and detection methods for worker misclassification.

Worker misclassification occurs when an employer incorrectly classifies an employee as a non-employee, such as when the employee is incorrectly classified as an independent contractor. In some cases, when an employer does not report an employee, the employment relationship may be part of the underground economy. Both of these actions reduce UI tax revenue, and adversely affect a worker’s ability to receive UI benefits, worker’s compensation, Social Security benefits, health insurance coverage, retirement coverage, and protection under the Fair Labor Standards Act.

The Act includes $10 million for activities to address the misclassification of workers. The ETA, Office of Unemployment Insurance will make $10 million available, through competitive grants, to States to help states increase their capacity for preventing and detecting worker misclassification and to help states enforce their state UI laws and policies related to worker misclassification.

Applications will include the following information collections: (1) Form SF-424 “Application for Federal Assistance,” separately cleared under OMB control number 4040-0004, (2) Form SF-424A “Budget Information-Non Construction Programs,” separately cleared under OMB control number 4040-0006, and 3) Supplemental Budget Request (SBR) Outline.

Electronic availability:

This Funding Opportunity will be emailed directly to the State Workforce Agencies. Based on past experience, the Department anticipates 100 percent of responses will be submitted electronically by email to DOL.

Small Entities:

This information collection will not have a significant impact on a substantial number of small entities.

Assurances of confidentiality:

This FO does not offer applicants assurances of confidentiality.

Special circumstances:

This FO implicates no special circumstances.

Burden:

Based on past experience, the DOL expects to receive approximately 50 applications from an equal number of respondents. The ETA estimates public reporting burden for the information collection to average 20 hours per response for reviewing instructions, searching existing data sources, gathering and maintaining needed data, and completing and reviewing the collection of information.

50 applications x 20 hours = 1,000 hours.

The DOL has increased the October 2014, average hourly earnings in the professional and business services industry of $29.29 per hour by 40 percent (total $41.01 per hour) to monetize this burden. See The Employment Situation—October 2014, DOL, Bureau of Labor Statistics, http://www.bls.gov/news.release/archives/empsit_11072014.pdf at page 32.

1,000 hours x $41.01 = $41,010.00

The DOL associates no other burden costs with this information collection. In addition to the application, each grantee will be required to submit quarterly financial, performance, and narrative reports to the ETA. Those information collection requirements will be cleared under a separate control number.

Total burden: 50 respondents, 50 responses, 1,000 hours, $0 other cost burden.

Supplemental Supporting Statement B: Statistical Methods

This information collection does not employ statistical methods.

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