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Is employee misclassification a problem in Pennsylvania?

On Behalf of | May 16, 2024 | employment law for employers |

Employee misclassification is a significant issue in Pennsylvania. It is the practice of mislabeling workers as independent contractors rather than employees. Recent data reveals the severity of this problem and its impact on the state’s workforce, economy and social safety nets.

Employers should recognize the extent of employee misclassification

The scope of misclassification

According to data from the Office of Unemployment Compensation Tax Services, employer audits conducted between Q3 of 2021 and Q2 of 2022 revealed an average of 5.3 misclassified employees. An estimated 48,939 employers in Pennsylvania misclassify at least one employee each year. This results in approximately 259,000 misclassified workers in the state.

The impact on workers’ compensation

Misclassification has severe consequences for employees who suffer injuries or illnesses at work. In 2021, an estimated 10,892 misclassified employees in Pennsylvania lost out on Workers’ Compensation benefits, resulting in losses of approximately $153,365,895.20 for these individuals. Additionally, the Uninsured Employers Guarantee Fund experienced estimated losses of $383,414.74 due to misclassification in the same year.

Lost revenue for the state

Employee misclassification also leads to significant lost revenue for Pennsylvania’s social safety net programs and the General Fund. The UC Trust Fund loses an estimated $91,000,000 annually due to misclassification, based on OUCTS data from Q3 2021 to Q2 2022. The Pennsylvania Department of Revenue estimates that the General Fund lost between $6.4 million and $124.5 million in tax year 2019 as a result of misclassification.

The widespread nature of misclassification and its impact on various aspects of the workforce and social safety nets underscore the need for increased awareness. Business owners should be attentive to their worker classification details to minimize these complications.