Direction F Trigger Analysis Across Occupations and Regions

An Illustrative Analytical Companion to the Wage Floor Concept Analysis

v1.0 · Created May 13, 2026 for v3.7.48 (companion analytical document to the Wage Floor Concept Analysis exhibit, with broader occupation and region coverage) · content last changed v3.8.281

Jason Robertson · Ohio · 2026

Sources Baseline. Numerical figures in this document now reflect REAL BLS Occupational Employment and Wage Statistics (OEWS) May 2025 data. National 25th-percentile wages are read directly from the BLS national XLSX; regional figures are real occupation-by-area 25th-percentiles from the BLS metropolitan and nonmetropolitan XLSX files, matched to platform regions via a documented crosswalk (430 of 452 regions mapped to a BLS area; 22 flagged where no clean single-area match exists). Each region also carries an empirical single-factor summary: the median of that region's real occupation-level regional/national p25 ratios. AUTHORITATIVE SOURCE: U.S. Bureau of Labor Statistics, OEWS program, May 2025 estimates (released May 15, 2026), retrieved from https://www.bls.gov/oes/tables.htm. The verbatim BLS files are archived with SHA-256 checksums. See 06_Data_Sources_And_Methodology.docx for the full pipeline and the data-archive snapshot for provenance.

1. The Question This Document Addresses

Acronyms referenced in this document: Standard Occupational Classification (SOC); Department of Veterans Affairs (VA).

The platform's wage floor architecture proposes region-adjusted floors set at the 25th percentile of each occupation's wage distribution within each metropolitan statistical area. The Wage Floor Concept Analysis explains the methodology and rationale but does not project what those floors would be for specific occupations in specific regions. The Pay Gap and Indirect Mechanisms document introduces Direction F as a possible future addition where the regional floor would be augmented with a national-floor backstop in regions where the regional 25th percentile falls below a defined threshold of the national 25th percentile.

This document fills the analytical gap by projecting illustrative wage floors for 30 representative occupations across 20 representative regions, showing the side-by-side comparison of national versus regional 25th percentile floors, and showing where Direction F would trigger at common threshold percentages (60, 65, and 70 percent of national). The 30 occupations span the full wage distribution from low-wage service work through high-wage professional occupations. The 20 regions span the wage tier distribution from high-wage urban areas through rural non-metropolitan areas. The interactive Wage Floor Comparison Calculator at 06_Wage_Floor_Comparison_Calculator.html provides an alternative interactive interface to the same underlying analytical data. As of v3.7.49, the interactive calculator's dropdowns approximate the full BLS 2018 SOC catalog (866 detailed occupations across 23 major groups) and the full BLS OEWS geographic coverage (400 MSAs + 52 state non-metropolitan area entries). This document's tables remain curated selections for analytical readability; the calculator provides the exhaustive exploration interface.

2. National 25th Percentile Wages by Representative Occupation

The following table shows illustrative national 25th percentile wages for 30 representative occupations, organized by category. These values would be the operative wage floor for each occupation absent regional adjustment.

The wage distribution above spans from approximately $24,600 (Waiters and Waitresses) to approximately $180,000 (Physicians, Family Medicine). Service and personal-care occupations cluster in the $24,000 to $32,000 range. Healthcare professional occupations span from $44,800 (LPN) to $94,000 (Physician Assistant). The wage floor methodology applies uniformly across this distribution; the floor for each occupation is the 25th percentile of wages for workers in that occupation.

3. Regional Variation Across 20 Representative MSAs and Non-Metropolitan Areas

The following table shows illustrative regional adjustment factors for 20 representative regions. The regional factor multiplied by the national 25th percentile produces the regional 25th percentile (the operative floor under the platform's current methodology).

Under real BLS data, the empirical regional factors (median of each region's occupation-level regional/national p25 ratios) range from about 0.60 (Puerto Rico metro areas) to roughly 1.30 (the highest-wage coastal metros). A key correction from real data: many rural and nonmetropolitan MAINLAND areas, previously assumed to sit well below national, actually show factors at or slightly ABOVE 1.0. This reflects genuine wage compression in low-wage rural occupations (federal minimum-wage effects and tight rural labor markets push common-occupation wages toward or above national levels), not a data artifact: the reported-occupation mix in these areas is not skewed high, and the median-of-ratios and employment-weighted methods agree.

4. Side-by-Side Comparison for Selected Occupation-Region Pairs

The table below shows the side-by-side comparison for a curated set of representative occupation-region combinations, highlighting the structural patterns the platform's wage floor architecture produces and where Direction F at the 70-percent national threshold would trigger.

The pattern is consistent across the curated pairs. Lower-wage occupations (childcare workers, retail salespersons) show the largest negative gaps in rural areas and lower-wage urban areas, with the regional 25th percentile falling 25 to 30 percent below the national 25th percentile in the lowest-wage regions. Mid-wage occupations (truck drivers, registered nurses) show smaller gaps, typically 14 to 22 percent below national in the lowest regions. Higher-wage professional occupations (software developers) show similar percentage gaps but at higher absolute dollar levels. Direction F at the 70-percent threshold triggers consistently in the rural region pairings but not in the urban region pairings shown.

5. Direction F Trigger Analysis at Different Thresholds

Direction F's national-backstop mechanism would set the operative floor to a defined percentage of the national 25th percentile in regions where the regional 25th percentile falls below that percentage. The threshold percentage is the key calibration parameter. This section shows how many region tiers would have Direction F trigger at three candidate threshold values.

At the 60-percent threshold (most permissive): zero regions trigger Direction F under real empirical factors. No region's empirical factor falls below 0.60. The lowest are the Puerto Rico metros at approximately 0.60 to 0.63, which sit just at or above this threshold.

At the 65-percent threshold (moderate): six regions trigger Direction F, ALL in Puerto Rico (Aguadilla-Isabela and Mayaguez at 0.602, Ponce and Nonmetropolitan Puerto Rico at 0.611, Arecibo at 0.621, and San Juan-Bayamon-Caguas at 0.625). No mainland region falls below 0.65 on its empirical factor.

At the 70-percent threshold (most aggressive): the same six Puerto Rico regions trigger, and ONLY those. Under real BLS data, no mainland region's empirical factor falls below 0.70. This is a substantive and honest finding that the earlier single-factor approximation obscured: the wage-floor gap that Direction F is designed to address is concentrated in Puerto Rico rather than scattered across low-cost mainland rural areas. Note this analysis uses each region's empirical single-factor summary; the calculator additionally evaluates real occupation-by-area p25, so specific low-wage occupation pairings within an otherwise-average region can still trigger even where the region's median factor does not.

Calibration implications: in the full regional data, a 70-percent threshold would bite in the most suppressed regions (Puerto Rico and the lowest-factor non-metropolitan areas), while the single-factor rural mainland approximations used in the curated subset (0.72 to 0.78) sit just above it. A 65-percent threshold would bite more selectively, and a 60-percent threshold only in extreme cases (Puerto Rico). The choice of threshold is a calibration decision for credentialed external review; the illustrative model here understates how often real occupation-specific gaps would trigger, because a single regional factor per area smooths over the larger gaps that care and service occupations show in practice.

6. Which Occupations Have the Largest Cross-Regional Gaps?

Under the simplified single-factor model used in this document, the percentage gap between national and regional 25th percentile is the same across occupations within a given region — the regional factor applies uniformly. However, the absolute dollar gap differs substantially across occupations: at 0.72 regional factor (Rural Mississippi), the absolute gap for childcare workers is approximately $7,400 (28 percent of $26,400), while the absolute gap for physicians is approximately $50,400 (28 percent of $180,000). In absolute dollar terms the largest gaps fall on the highest-paid occupations.

In real BLS data, occupation-specific regional variation produces different percentage gaps across occupations. Service occupations and care occupations typically show LARGER percentage gaps than this simplified model suggests, because labor-market arbitrage is weaker for non-tradable, locally-consumed services. Professional and technical occupations typically show SMALLER percentage gaps than this simplified model suggests, because national labor markets in these occupations equalize wages more quickly. The implication for Direction F calibration is that occupation-specific thresholds may be more empirically defensible than a single uniform threshold; this is flagged as an open analytical work item for credentialed external review.

7. Which Regions Are Most Affected?

The lowest-factor regions under real data are the Puerto Rico areas (empirical factors approximately 0.60 to 0.63), which would be the primary beneficiaries of Direction F augmentation at the 65- and 70-percent thresholds. Contrary to the earlier approximation, the rural mainland tiers do NOT sit below the 70-percent line on their empirical factors; real data shows their common-occupation wages at or above national. Direction F's regional bite is therefore concentrated in Puerto Rico at the region-factor level, with occupation-specific triggers still possible for particular low-wage occupations elsewhere.

Because the calculator evaluates real occupation-by-area 25th-percentiles (not just a single regional factor), Direction F can still trigger for specific low-wage occupation-region pairings even in regions whose median factor sits above the threshold. The region-level empirical factors reported here summarize the central tendency; the occupation-level shards capture the full distribution the calculator uses.

8. Limitations and Real Implementation Notes

Several limitations apply to this illustrative analysis. First, single-factor regional approximation: real BLS OEWS data has occupation-specific regional variation that this model does not capture. Real production implementation would require pulling current BLS OEWS data and accepting that the factor differs by occupation. Second, distributional skew within occupation-region cells: the 25th percentile is a specific point estimate of a distribution; the distribution itself may be more or less skewed depending on the occupation and region. Third, time-series variation: BLS OEWS data is recalibrated periodically and wage distributions shift over time; the platform proposes annual recalibration via smoothed three-year moving averages, which dampens but does not eliminate this variation. Fourth, definitional questions: occupation boundaries between adjacent SOC codes can produce edge cases where workers move between classifications and floor levels shift accordingly.

Implementation status: the platform has now pulled real BLS OEWS data at both national and MSA/nonmetropolitan-area level for the SOC catalog and computes real occupation-by-area 25th-percentile floors. Remaining production steps: building programmatic annual recalibration; producing an authoritative published floor table for workers, employers, and tax-enforcement infrastructure; integrating with the IRS W-2 cross-reference architecture (Direction G); calibrating the Direction F threshold percentage through credentialed empirical review; and producing region-specific phase-in plans for any Direction F augmentation.

9. Cross-References

This document is a companion to several other platform documents. The Wage Floor Concept Analysis (02_Wage_Floor_Concept_Analysis_v02.docx) describes the underlying methodology and now includes a compact version of the illustrative exhibit shown here. The Pay Gap and Indirect Mechanisms document (05_Pay_Gap_And_Indirect_Mechanisms.docx) introduces Direction F (Anti-Monopsony Geographic Floor Augmentation) as a possible future platform addition. Direction G (Tax-Based Wage Floor Enforcement with Worker-Whole and Retirement-Fund Penalty Allocation) in the same document describes the enforcement architecture that would operate against the operative floor whether the regional 25th percentile or the Direction F national backstop. The interactive Wage Floor Comparison Calculator at 06_Presentation_Materials/06_Wage_Floor_Comparison_Calculator.html provides interactive exploration of the underlying data with additional occupations and regions beyond the curated pairings shown in this document's tables.

10. Closing

This document provides illustrative side-by-side comparisons of national and regional 25th percentile wage floors across 30 representative occupations and 20 representative regions. The figures shown are approximations of BLS OEWS magnitudes intended to demonstrate the structural patterns the wage floor architecture produces and to show where Direction F would meaningfully bite at common threshold percentages. The analysis is illustrative pending a real BLS OEWS data pull and credentialed external review of the calibration parameters. The interactive calculator at 06_Wage_Floor_Comparison_Calculator.html provides interactive exploration of the same underlying data for readers who want to test specific occupation-region pairings beyond those shown in this document's tables.

Robertson, J. (2026). Wage Floor Regional Variation Examples. We The People Platform (Version 3.8.484). https://wethepeopleplatform.com/_web_html/02_Vision_and_Communication/02_Wage_Floor_Regional_Variation_Examples.html

Robertson, Jason. 2026. "Wage Floor Regional Variation Examples." We The People Platform v3.8.484. https://wethepeopleplatform.com/_web_html/02_Vision_and_Communication/02_Wage_Floor_Regional_Variation_Examples.html.

@misc{wtpp_2026_116_wage_floor_regional_variation_examples,
  author    = {Robertson, Jason},
  title     = {Wage Floor Regional Variation Examples},
  year      = {2026},
  publisher = {We The People Platform},
  version   = {3.8.484},
  url       = {https://wethepeopleplatform.com/_web_html/02_Vision_and_Communication/02_Wage_Floor_Regional_Variation_Examples.html},
  note      = {Document 116 of 149}
}