Modernizing Employment Data Act

Background

The unemployment insurance (UI) system, established under the Social Security Act of 1935, operates as a federal-state partnership in which federal law mandates the payroll tax while states administer their own programs. As part of this framework, states collect quarterly wage data from employers. Since the reporting structure was designed narrowly, UI captures basic identifiers and total wages to determine employer tax liability and worker benefit eligibility. Each quarter, employers report the business’s federal employer identification number (FEIN), each employee's Social Security number, and each employee’s total quarterly wages. Initially, coverage was relatively limited; however, it has expanded throughout the years. Today, state UI systems cover about 98.5% of civilian wage and salary employment.

In addition to using these data to calculate benefit payments for unemployed workers, states also use quarterly UI wage data to analyze employment and wage information and, when linked to education records through a Statewide Longitudinal Data System (SLDS), to evaluate the employment outcomes for secondary, postsecondary, and workforce training programs. States are continuing to find new uses for UI wage data; however, its principal function continues to be collecting quarterly earnings. Additional fields, like Standard Occupational Classification (SOC) codes, primary work location, hours paid, and worker type, are unevenly collected in about half of the states. When states add additional data elements to their UI systems (like those above), the resulting data is referred to as “enhanced wage records.”

States seeking to assess the effectiveness of investments in education and workforce training, report accurate and timely labor market information, and prevent and detect waste, fraud, and abuse in means-tested programs will need to enhance their UI data systems to collect additional data elements. The following sections address the limitations of using standard UI wage data for these purposes, explain how enhanced wage records can overcome these limitations, and provide a model policy for enhancing wage records.

The Problem

This section briefly describes the limitations of using basic (or partially enhanced) UI wage data when attempting to assess the effectiveness of investments in education and workforce training, report accurate and timely labor market information, and prevent and detect waste, fraud, and abuse in means-tested programs.

The most obvious additional use that states have found for UI wage data is related to workforce education. Increasingly, states are connecting their SLDS to the UI data system to link individual student records to employment outcomes. When these education and employment data are linked, states can report earnings and employment rates for student cohorts at the program level. According to one 50-state review of SLDSs, at least 35 states have already connected their education data to UI systems for this purpose.

While these data help track basic employment outcomes, states using standard UI data cannot report and track more meaningful labor market outcomes that matter to policymakers, students, families, educators, and businesses.[1] Using standard UI data inhibits states from reporting important program-level outcomes, such as whether graduates are employed in careers related to their programs of study, are working full- or part-time, or are earning a competitive salary in their local areas. Given that workforce education programs, such as career and technical education (CTE) programs supported by the Perkins Grant, are intended to lead to gainful employment in high-skill, high-wage, or in-demand occupations, it is important for states to track whether investments in these programs are fulfilling the intended purposes.

States also need better methods for monitoring state and local labor market conditions. With standard UI wage data, state policymakers possess information limited to whether individuals are employed and what they earned—not what job an employee performs, the number of hours they worked, or where the job was performed. For this reason, states generally use other methods to estimate labor market needs, including unmet needs for specific occupations, by surveying employers. This is a laborious process that requires both time and resources to collect, analyze, and validate data. Even the best surveys, such as the Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS), use lagged data to estimate employment and wage conditions and support projections of future labor market conditions. Even when states build parallel systems to OEWS, their data is similarly lagged, thereby relying on past rather than current labor market conditions to estimate future labor needs.

Given rapidly changing labor market needs, particularly due to widespread adoption of artificial intelligence (AI) and reshoring industries, states need better data to assess how best to deploy critical resources. For example, reporting the specific jobs employees have and where they work can help states to more efficiently deploy resources to reskill and upskill workers during changing economic conditions. Unfortunately, standard UI wage data fails to provide the granularity of information needed to be useful to states in this regard.

Lastly, incomplete wage records may result in large entitlement programs continuing to be riddled with waste, fraud, and abuse. Standard UI wage data lacks key data elements that policymakers could use to save American taxpayers billions annually if strategically used to verify eligibility in public assistance programs and to identify potential fraud.[2] Many of these programs require recipients to self-report employment status and earnings; however, many fail to do so accurately. While not all missing or inaccurate data implicates waste, fraud, or abuse, using self-attested data undoubtedly conceals improper use of these programs that would be more easily detected in a more comprehensive dataset. Enhanced wage records could help states strengthen verification processes with real, accurate data from employers, thereby likely reducing many of the opportunities for fraudsters to submit fraudulent claims or receive improper payments based on inaccurate self-reported data.[3]

These concerns are well documented, especially in annual reports by federal agencies tasked with monitoring benefits programs. For example, in fiscal year 2024, the Department of Agriculture reported a nearly 11% national payment error rate for SNAP. In fiscal year 2025, the Department of Health and Human Services (HHS) reported a Medicaid improper payment rate of 6.12%, of which 77.1% was attributable to insufficient documentation. The risk of improper benefit payments is especially severe in the case of Temporary Assistance for Needy Families (TANF; also known as “welfare”). Due to “statutory limitations [that] preclude HHS from requiring states to participate in a TANF improper payment measurement,” the agency has produced only a single national error rate estimate—9.3% in FY 2008—for the program over the three decades of its existence.

The Solution

Enhancing UI wage records with additional employer-provided information will add valuable data that states can use to meet important goals. By enhancing wage records, states can improve longitudinal data systems to assess the effectiveness of investments in education and workforce training; collect more accurate and timely labor market information, reducing reliance on estimates derived from lagged labor market data; and mitigate and investigate fraud in means-tested programs. This legislative text accomplishes these goals by requiring the collection of four additional data elements: 1) SOC code, 2) ZIP code of primary work location, 3) hours paid, and 4) worker type (full-time, part-time, or seasonal).[4]

Proposed State Legislative Text

SECTION 1. SHORT TITLE.

This Act shall be known and may be cited as the Modernizing Employment Data Act.

SECTION 2: DEFINITIONS

For purposes of this Act:

• (a) “Occupation” shall mean the Standard Occupational Classification (SOC) code that best describes the employee’s primary occupation during the reporting quarter, as prescribed by the United States Bureau of Labor Statistics.
• (b) “Primary work location” shall mean the ZIP code of the physical location where an employee performs the majority of the employee's work during the reporting quarter.
• (c) "Hours paid" shall mean the total number of hours for which an employee received compensation during the reporting quarter, including hours worked, paid leave, vacation leave, sick leave, holiday leave, overtime hours, and other compensated time. For salaried employees whose hours are not tracked by the employer, "hours paid" shall be reported as eight (8) hours for each day for which the employee received compensation during the reporting quarter.
• (d) “Worker type” shall mean whether the employee is classified as a full-time, part-time, or seasonal worker in accordance with regulations promulgated by the [DEPARTMENT].

SECTION 3. PURPOSE.

The purpose of this Act is to enhance quarterly wage records submitted to the state as required under __________ by requiring the collection of additional job-specific data elements.

SECTION 4. AMENDING QUARTERLY WAGE RECORD REPORTING REQUIREMENTS.

• (1) Amend __________, related to employer reporting requirements, to include the following information for employees:
  • (A) Occupation.
  • (B) Primary work location.
  • (C) Hours paid.
  • (D) Worker type.
• (2) In __________, insert the following:
  • (A) The [DEPARTMENT] shall promulgate regulations to implement and enforce the requirements of this section, including establishing validation procedures and providing technical assistance to employers.

SECTION 5. SEVERABILITY.

If any provision of this Act or its application to any person or circumstance is held invalid, the remaining provisions shall not be affected and shall remain in full force and effect.

SECTION 6. EFFECTIVE DATE.

This Act takes effect on __________.

[1] For the purposes of the model policy, basic employment outcomes refer to whether program completers are employed and their earnings following completion, without regard to their occupation, field of study, or local labor market conditions. Labor market outcomes refer to whether program completers are employed in occupations related to their field of study and whether their earnings are competitive within the local labor market.

[2] States that collect all four data elements and integrate them into eligibility verification systems could create additional business rules to automatically flag suspicious cases for review. For example, states could flag suspicious submissions from claimants who self-report low earnings while employed in high-wage occupations (e.g., engineer, nurse, or computer programmer), or whose reported weekly hours paid and earnings imply an implausibly low hourly wage for their occupation in their local labor market. These flags would not definitively indicate fraud but could help identify discrepancies that warrant further investigation.

[3] States that invest in interoperable employment-data exchanges and other data modernization efforts across government programs could use enhanced wage records as part of efforts to improve eligibility verification systems. While enhanced UI wage records are generally reported quarterly and can be used to identify discrepancies for further review, interoperable employment-data systems may enable states to access employer-reported employment and earnings information more frequently through automated data exchanges. As a result, states could potentially assess eligibility using more current employer-reported information while also reducing reliance on self-attested data.

[4] Through 646 IAC 5-2-1, Indiana has accomplished most of these additions except for hours paid. Even with three of the four data elements, Indiana could address many of the education transparency and accountability and labor market limitations addressed in the section above—the sole apparent exception being the ability to determine whether workers are earning competitive hourly wages in local labor markets (derived by dividing total gross wages by hours paid). As it relates to exposing waste, fraud, and abuse, Indiana’s enhanced wage record system holds great promise. Indiana can avail itself of opportunities to flag potential fraud and investigate these instances more fully.