WSG News Blog

Economic convergence in coastal Washington: How COVID-19 changed regional unemployment

October 13, 2025

By Kevin Decker, WSG Coastal Economist

For a long time, Washington’s rural coastal counties – such as Grays Harbor, Pacific, and Wahkiakum counties – had higher unemployment than the state average. This was largely due to their reliance on a few industries and their distance from the I-5 corridor. However, following the COVID-19 pandemic, new data indicate that these counties are now more aligned with state and national economic trends. When this occurs, economists refer to it as convergence.

What the data shows

To evaluate this change, I gathered unemployment data from the Bureau of Labor Statistics for all of Washington’s 15 coastal counties from 2015 to mid-2025. I used the STUMPY Python library to study not only unemployment rates but also patterns, unusual changes, and instances when unemployment settled at a new level. When I first compared Clallam and Jefferson counties with Washington state and the U.S., I quickly noticed the unemployment gaps narrowed after 2020 (see Figure 1). That led me to check every coastal county.

Graph showing unemployment gaps between WA coastal counties and others in the state narrowing after 2020.

Figure 1. Unemployment rates for Clallam and Jefferson counties compared to Washington state and the U.S. (2015–2025).

Figure 2 shows how unemployment gaps changed for each county compared to the state average. Based on this, three groups stand out: counties with strong convergence (i.e. whose unemployment moved closer to the state average), those with moderate changes; and two whose unemployment rates moved further away.

Bar graph showing how employment gaps changed for each county compared to the state average.

Figure 2. Change in county unemployment gaps with Washington state before and after COVID-19. Positive values indicate counties moved closer to the state average (convergence).

Who caught up

The results show a clear pattern: nine out of 15 counties showed significant convergence: a gap reduction of more than half a percentage point.

  • Clallam, Jefferson, Grays Harbor, Mason, Pacific and Wahkiakum: These rural counties on the Olympic Peninsula and Pacific coast have historically had unemployment rates higher than the state average. All reduced their gaps with the state by more than one percentage point.
  • King County: Known for its tech-driven economy, King County also moved closer to the state average.
  • Island and Skagit Counties: These counties joined the list of significant convergence counties as well.

Importantly, the counties that used to be the most separated from the state economy are now following it more closely.

The middle of the pack

Four counties – Snohomish, Whatcom, Kitsap and Thurston – showed moderate convergence. They were already close to state and national trends before COVID, so their changes were smaller. Their mixed economies may also help to protect them from big economic shifts.

The outliers

  • San Juan County moved slightly away from the state average. Its wealthy, tourism-dependent economy, combined with its geographic isolation, makes this county less tied to statewide employment trends. Despite this divergence, San Juan County also has the lowest unemployment rate on the coast at just 3.1%.
  • Pierce County showed a negligible divergence (-0.01%). With its mix of military, manufacturing, and logistics, Pierce County’s labor market is likely to respond differently to state-level forces.

Current unemployment

As of July 2025, unemployment across coastal Washington shows both progress and persistent gaps (see Figure 3):

  • High unemployment: Wahkiakum (7.3%), Grays Harbor (5.7%), Pacific (5.6%), Mason (5.2%).
  • Low unemployment: San Juan (3.1%).
  • Everyone else: between 4.1% and 4.9%, nearly identical to the state average of 4.5% and the national average of 4.2%.

While it is good to see most counties close to the average, the extremes still matter. A community with 7% unemployment faces very different challenges than one with 3%.

Figure showing unemployment rates by coastal county, July 2025.

Figure 3. Unemployment rates by coastal county, July 2025.

Volatility and structural breaks

Looking beyond the averages, the analysis also revealed how unemployment rates changed over time. By checking for significant shifts, I observed that counties like Clallam and Jefferson experienced major changes in 2020 and 2021, which brought their unemployment rates closer to the state level. Others, like San Juan and Pierce, experienced fewer significant changes but more fluctuations each month. Some counties experienced a lasting reset in their job markets, while others continue to undergo significant changes. For policymakers, these differences are just as important as the averages.

Why convergence matters

Convergence is good news for state policy. It means programs like unemployment insurance, job training, and stimulus funding can now help the coast more evenly. This makes statewide efforts more effective than before.

However, a single approach will not work for everyone. Outliers like San Juan and Pierce need their own strategies. Counties with high unemployment, like Wahkiakum and Grays Harbor, need special help to deal with their ongoing problems. Many rural counties still rely on legacy industries, making them more exposed to downturns and slower to recover compared to the state as a whole.

A lasting shift

The main point is that this change is not just a short-term effect from the COVID-19 pandemic. The convergence has persisted through 2025, suggesting a lasting shift in how coastal economies align with the state and national economies. For rural counties that have often been left out of Washington’s growth, this is a significant step toward greater connectivity.

COVID-19 did more than disrupt the economy. It changed how regional economies move together. For coastal Washington, this means less isolation and a new, lasting starting point for local communities.

About the analysis: This analysis used advanced time series pattern recognition (the STUMPY Python library) to detect unemployment patterns, anomalies, and regime changes, revealing shifts traditional approaches might miss. I used AI tools for coding and formatting. All analysis and interpretation are my own.

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Washington Sea Grant, based at the University of Washington, helps people and marine life thrive through research, technical expertise and education supporting the responsible use and conservation of coastal ecosystems. Washington Sea Grant is one of 34 Sea Grant programs supported by the National Oceanic and Atmospheric Administration in coastal and Great Lakes states that encourage the wise stewardship of our marine resources through research, education, outreach and technology transfer.

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