Intrastate Regional Cost Differences
Posted Date: December 2025
Key Insights
- Regional differences in frequency, severity, and overall costs exist within NCCI’s three largest states by population: Florida, Illinois, and Texas.
- Neither frequency nor severity were identified as consistent drivers of the loss ratio relativities across regions.
- Differences in results were found for cohorts of policies that span single versus multiple regions within a state.
Introduction
NCCI collects workers compensation (WC) data from 38 jurisdictions and conducts numerous analyses at the state level, our mantra being that every state has a story.
Differences in the WC system manifest across jurisdictions for many reasons: population, employment, industry mix, injury mix, compensability and benefit structures, treatment guidelines, medical fee schedules, and attorney involvement, just to name a few. The volume of data collected also varies across jurisdictions, with larger jurisdictions typically collecting significantly more data than smaller ones. Prior NCCI research has provided insight on many of these differences between jurisdictions.
This report provides a collection of actuarial metrics to compare differences across geographic regions within NCCI’s three largest jurisdictions by population—Florida, Illinois, and Texas. These metrics provide insight into the extent of regional differences in frequency, severity, and overall costs across these jurisdictions. In addition to the report, a downloadable file is available for a deeper dive in the data. By examining these metrics, we expand on the individual story for each state.
Background
Stakeholder interest in understanding regional cost differences within NCCI jurisdictions prompted this research. A robust analysis of regional cost differences requires a considerable amount of data at the regional level, which varies significantly across NCCI jurisdictions. Florida, Illinois, and Texas are NCCI’s three largest states both by population and data volume and therefore serve as natural case studies for exploring intrastate regional cost differences.
Key data elements for this analysis—exposure and loss—are not reported for each individual business location and therefore were estimated by NCCI. For the estimation, NCCI relied on third-party data. While aggregate checks for reasonability were performed on the third-party data, verifying the data on a granular, address-by-address level was not feasible.
Despite these limitations, this research demonstrates the viability of evaluating intrastate regional cost differences in large NCCI states.
Data
The three primary data sources underlying this report are Policy Data, the Unit Statistical Plan, and the Medical Data Call. Exposure and losses are not reported for each individual business location in these data sources; therefore, estimation was necessary to allocate total policy experience across business locations.
We licensed a data set containing employee counts from a third party, Dun & Bradstreet (D&B), to facilitate the allocation of total policy exposure across business locations. We used ZIP Codes reported on paid medical transactions to identify the business location to which the loss amounts should be allocated. The details of these allocation steps are provided in the Appendix.
The volume of data included in the analysis is shown at the right, expressed as a percentage of the total standard premium reported to NCCI. While most policy experience was included in Florida, Illinois, and Texas, some experience was excluded. Policy exclusions were due to an inability to link across the relevant data sources, or other data reporting issues.
Actuarial Metrics
Each of the actuarial metrics that follow are based on data from Policy Years 2021–2023. All losses are incurred at first report and are limited to $500K.
In the loss ratio and frequency calculations, premium is derived by extending exposures by the loss costs in effect during the policy effective period. The experience rating modification (mod) for each risk is included in the premium calculation because the mod may already indirectly reflect some regional cost differences.
To control for class mix, the statewide components of the relativities in the following sections are first calculated at an individual class level and then weighted together using each region’s mix of classes. As a final step, the loss ratio, frequency, and severity relativities are balanced to unity.
Metrics are shown on a combined basis and broken out for two cohorts of policies:
- Single-region policies—all business locations are within the same region; therefore geo-location is not necessary
- Multi-region policies—business locations span at least two regions; therefore geo-location is necessary
Single- and multi-region policies have different characteristics that may impact the actuarial metrics (see the Appendix for examples). Therefore, analyzing actuarial metrics for each individual cohort—as well as combined—may enhance the regional comparisons.
Loss Ratio Relativities
The graph below shows a point estimate for the loss ratio relativity of each region on top of a range produced by alternative exposure allocation methodologies (as described in the Appendix). Ranges that lie wholly above (or below) unity may signal confidence in the estimated directional impact for each region, while those that cross unity may signal uncertainty. Ranges that are wide imply that regional differences are sensitive to the exposure allocation procedure.
Single- Versus Multi-Region Policies
The following graph enables a comparison of the regional loss ratio relativities for all included policies to those of the single- or multi-region cohorts.
Frequency and Severity Relativities
The graph below retains the point estimates of regional loss ratio relativities from the previous section and adds point estimates of regional relativities for frequency, indemnity severity, and medical severity.
Comparing the component relativities to unity shows whether frequency (or severity) in the region is higher than the class-mix-adjusted statewide average. In some regions, the component relativities are all above (or below) unity and therefore are influencing the loss ratio relativity in the same direction. In other regions, however, the component relativities fall on opposite sides of unity, suggesting that offsetting effects may exist.
Comparing the component relativities to the loss ratio relativity of the region shows whether frequency, severity, or both are the predominant driver of the regional loss ratio relativity. No component relativity was identified as a consistent driver of the loss ratio relativities across regions.
