The U.S. economy grew at just 0.7% annualized in Q4 2025, according to the Bureau of Economic Analysis revised estimate, down from the 1.4% advance estimate and sharply below Q3's 4.4% pace. Meanwhile, core PCE inflation hit 3.1% annualized in January 2026, with the Federal Reserve holding rates steady at 3.5% to 3.75% and signaling no cuts until inflation cooperates. Full-year 2025 GDP growth came in at 2.1%, a respectable headline number that masks the deceleration underneath.
This is the environment where compensation decisions get hardest. Your employees see prices rising and expect their pay to keep up. Your budget reflects slowing revenue and tighter margins. Both sides have legitimate positions, and the gap between them is growing. The companies that navigate this well will be the ones making decisions from verified data, not instinct, not last year's survey, and not whatever a candidate claims they were earning somewhere else.
Slow growth and persistent inflation create a specific kind of pressure on compensation budgets. In a normal expansion, raising wages is straightforward because revenue supports it. In a recession, employees generally accept that raises are limited because the pain is visible and shared. But in a slow-growth, high-inflation environment, neither narrative holds. Revenue is not cratering, but it is not growing fast enough to absorb across-the-board increases. At the same time, your employees' rent, groceries, childcare, and insurance premiums have not slowed down.
The result is a compression trap. According to the Bureau of Labor Statistics, median wages vary by 30% to 50% between the highest- and lowest-paying states for the same role. If your budget only allows a 3% merit pool and inflation is running above 3%, you are effectively giving your workforce a real pay cut. The employees who notice first are the ones with the most market options, which tends to be your highest performers and hardest-to-replace roles.
Takeaway: If your merit budget is at or below the inflation rate, you are not holding the line on costs. You are creating retention risk in your most critical positions. Targeted adjustments based on market data outperform flat percentage increases in this environment.
From the employee perspective, a 3% raise against 3.1% core inflation is not a raise at all. It is a rounding error that does not cover the increase in their monthly expenses. Workers do not experience inflation as a macroeconomic statistic. They experience it at the gas pump, in their mortgage rate, and in their healthcare premiums. When their compensation does not keep pace, they start looking.
The Work Institute's 2025 Retention Report found that compensation and benefits remain among the top three reasons employees leave voluntarily. In an environment where real wages are flat or declining, the threshold for triggering a job search drops. Employees do not need to be dramatically underpaid to start exploring. They just need to feel like they are falling behind.
This is where location-specific data matters most. An HR coordinator in Florida earning $63,960 and an HR coordinator in New York earning $81,140 are both underpaid if their comp ratio falls below 0.95 relative to their state median. The absolute number is less important than the relationship to market. Employees may not know their exact comp ratio, but they can feel it when recruiters start offering more than what they currently earn.
Takeaway: Employees evaluate their compensation relative to what they could earn elsewhere, not relative to your budget constraints. If you do not know what the market is paying for each role in each location, you cannot have a credible conversation about pay.
When budgets are tight, the temptation is to rely on what you already know. What did we pay for this role last time? What did the candidate say their last salary was? What does the hiring manager think is fair? These inputs feel sufficient in stable times because the margin for error is wider. In a slow-growth, high-inflation environment, the margin disappears.
Anecdotal benchmarking fails for three reasons. First, it anchors to outdated data. The salary you paid for a software developer in Texas 18 months ago may be $10,000 below today's market. Second, it anchors to individual data points rather than distributions. One candidate's reported salary does not tell you where the 25th, 50th, and 75th percentiles actually sit. Third, it does not account for geographic variation. A national average is functionally useless when the same role pays $170,910 in California and $130,500 in Texas.
Self-reported salary data from aggregator platforms introduces additional noise. BLS OEWS data is collected from employer-reported surveys covering more than 1.1 million establishments. It is not crowdsourced, not self-reported, and not estimated from job postings. When economic conditions create pressure from both directions simultaneously, the quality of your data source determines whether your compensation decisions hold up under scrutiny.
Takeaway: Economic pressure amplifies the cost of bad data. A 5% benchmarking error on a critical role can mean the difference between retaining a high performer and funding a replacement search that costs 1.5x their annual salary.
The core tension in a stagflation-adjacent economy is that both sides are right. Employees deserve to maintain purchasing power. Employers cannot raise every salary above inflation without financial consequences. The resolution is precision. Instead of across-the-board increases that spread a thin budget even thinner, use role-specific, location-adjusted data to direct limited dollars where they matter most.
Start with a clear picture of where your workforce sits relative to market. Calculate the comp ratio for each employee: their current salary divided by the market median for their role and location. Employees below 0.95 are at the highest retention risk and should be prioritized for adjustment. Employees between 0.95 and 1.05 are within a defensible range. Employees above 1.10 may not need an increase this cycle, and that reallocation funds the adjustments where they matter.
This approach gives you a defensible, data-backed narrative for every conversation. When an employee asks why their raise was 2% instead of 5%, you can show them exactly where their salary sits relative to the BLS median for their role in their state. When a hiring manager insists a new role needs to pay $120,000, you can show them the 75th percentile for that role in that location and have a grounded discussion about where to target.
In pay transparency states like California, Colorado, New York, Illinois, and Washington, this is not optional. Salary ranges in job postings need to reflect actual market data, not internal guesswork. Using BLS OEWS data as the foundation gives your posted ranges the credibility to withstand both candidate scrutiny and regulatory review.
Takeaway: Precision beats generosity when budgets are constrained. Verified, role-specific, location-adjusted data lets you allocate limited compensation dollars where they generate the most retention value.
What It Pays™ is built on government-verified data including BLS and OEWS data as the foundation, covering over 800 occupations across all 50 states. The platform layers in compensation analytics, comp ratio calculations, and retention risk indicators so employers can move from raw data to informed action. As the platform grows, anonymized employer-reported salary data will be layered on top of the BLS foundation to provide real-time compensation signals alongside the government-verified benchmarks.
Run a free salary lookup to see where your roles sit relative to market. Explore the platform at whatitpays.com.
What is stagflation and how does it affect employee compensation?
Stagflation refers to an economic environment where growth slows while inflation remains elevated. For compensation, this creates pressure from both sides: employees push for raises to keep up with rising costs, while employers face tighter budgets due to slowing revenue. The result is a narrower margin for error in compensation decisions, making accurate market data essential.
How does inflation affect real wages even when employees receive raises?
If an employee receives a 3% raise but inflation is running at 3.1%, their purchasing power has effectively declined. Real wages are calculated by subtracting the inflation rate from the nominal wage increase. When inflation outpaces raises, employees experience a pay cut in practical terms even though their paycheck shows a higher number.
What is a comp ratio and why does it matter during economic downturns?
A comp ratio is an employee's current salary divided by the market median (or your target percentile) for their role and location. A comp ratio of 1.00 means the employee is at market. Below 0.95 signals retention risk. During economic pressure, comp ratios help employers identify which positions are most at risk so limited budget can be directed where it has the greatest impact.
Why is BLS data more reliable than salary data from job posting aggregators?
BLS Occupational Employment and Wage Statistics (OEWS) data comes from employer-reported surveys covering more than 1.1 million business establishments. It is not crowdsourced, not self-reported by employees, and not estimated from job postings. This makes it the most reliable public benchmark for setting defensible compensation ranges, especially in pay transparency states.
How should employers allocate merit budgets when inflation exceeds the budget percentage?
Rather than distributing flat percentage increases across all roles, employers should use comp ratio analysis to prioritize. Employees with comp ratios below 0.95 in critical roles should receive above-average adjustments. Employees already above market (comp ratios above 1.10) may not need increases this cycle. This targeted approach maximizes retention value from a constrained budget.
What is the current GDP growth rate and how does it affect hiring decisions?
Q4 2025 GDP was revised to 0.7% annualized growth, down from 4.4% in Q3. Full-year 2025 came in at 2.1%. Slowing GDP typically leads employers to tighten hiring budgets and delay backfills, which increases workload on remaining staff and can accelerate turnover if compensation does not keep pace with market.
Do pay transparency laws require employers to use specific salary data sources?
Pay transparency laws in states like California, Colorado, New York, Illinois, and Washington require salary ranges in job postings but do not mandate a specific data source. However, using government-verified BLS data provides a defensible, auditable foundation for posted ranges. Employers who base ranges on outdated surveys or anecdotal data risk both regulatory scrutiny and candidate skepticism.
Dr. Bruce Brown is the founder of CompRatio LLC and the creator of What It Pays™. He holds a PhD in Human Resources and the SHRM-SCP certification, and works as a practicing HR professional.
Ready to see where your compensation stands relative to market? Explore the platform at whatitpays.com.
This article is intended for educational and informational purposes only and does not constitute legal advice. Compensation practices vary by organization, jurisdiction, and circumstance. Nothing in this article should be relied upon as a substitute for consultation with a qualified HR professional or employment attorney regarding your specific situation. What It Pays™ and CompRatio LLC are not law firms and do not provide legal services.