Where's my tariff refund? 3 WA companies share their experiences 34%

By Joshua McNichols0%

5/21/2026, 12:19:29 AM

BS Summary: This article contains 28 faulty reasoning types, including Ambiguity (Equivocation), Post Hoc (False Cause), and Appeal to Emotion, with Negativity Bias as the most egregious example at 16.3% saturation with 172 hits. Analysis detected 1,214 faulty-reasoning hits from 1,056 analyzed words, generating a BS Score of 42% and a BS Rank of 34% (14,520 of 21,887 articles). This article is better (less manipulative) than 66.30% of the article peer group.

Courts have struck down some of President Donald Trump’s tariffs. 
Now companies are owed refunds. 
But who gets to pocket that money, and how hard is it to get? 
KUOW spoke with three local companies with three very different perspectives. 
You may have heard about the Nike lawsuit. 
Retail customers want the clothing company to pay them back for tariffs, which made the clothes they bought more expensive. 
Courts have struck down many of Trump’s tariffs. 
Companies are now required to pay them back. 
But how that happens can get messy. 
Layoffs, layoffs, layoffs 
When Barry Barr last spoke with KUOW in early 2025, he described the significant risks tariffs posed to his outdoor clothing company, KAVU. 
After all, the company imports custom clothes from many countries, including China. 
Even the clothes made in West Seattle depend heavily on Chinese-made buckles and fabrics. 
At that time, Barr worried that tariffs would force him to raise prices, lose customers, and lay people off. 
That all came true. 
Barr tried to keep most of his retail prices stable, but had to raise some. 
KAVU’s business dropped by 15%. 
He’s $500,000 in the hole and he’s laid off dozens of workers. 
There are other factors that have increased the pain. 
Anti-American consumer sentiment in other countries has pushed down demand for KAVU’s gear, especially in Canada. 
On a recent tour of the office, there were still people working in their cubicles. 
It’s not a ghost town, but the damage has been widespread. 
“The team has gotten smaller,” Barr said. 
“We’ve had to reduce in the internal office two people, in our retail stores eight people, and our warehouse: 20 people. 
We have a sew shop out in West Seattle and they were 25 people, now they’re down to 12 because the tariffs of all the components that we have to bring in to assemble here." 
"So the tariffs have really affected us," he continued, "and it’s terrible because some of the staff has worked here 20 years. 
You know, to see that part of a family that’s put so much work in, has been horrible.” 
As a clothing manufacturer, Barr is used to paying tariffs. 
But the new tariffs he’s paid have pushed his business to the brink. 
There’s light at the end of the tunnel, though. 
If the tariff refunds come through, Barr says they’ll put KAVU back in the black. 
They won’t build back the business and employees he lost, but it’s a start. 
A massive spreadsheet 
However, just because you’re eligible for refunds, doesn’t mean it’s easy to get them. 
Allison Budvarson runs Out of the Box Manufacturing in Renton. 
They import parts, like printed circuit boards, and produce rapid prototypes for customers: An airline inflight entertainment system. 
A closure mechanism for a naval submarine door. 
Her company paid tariffs on the materials they imported, but they didn’t pay the U.S. government, they paid them to their shipping companies, like FedEx or UPS. 
Those companies are technically the “importer of record.” 
So, even though Budvarson paid the tariffs, “we're not actually eligible to apply for the refund,” she explained. 
“So we're in a waiting game to see if, when, or how we would be eventually receiving that refund from the importer of record, and then in turn, how to pass it down to our customers as well.” 
To complicate matters further, she doesn’t even know how much money she’s owed. 
The invoices from her suppliers have a line item that just says “tariff surcharge.” 
But that surcharge is the sum cost of all tariffs, some of which have been overturned, and some of which haven’t. 
So Budvarson can’t tell how big any potential refunds will be. 
It's not for lack of trying. 
She’s produced a 400-row spreadsheet of items, attempting to calculate what she’s owed. 
“I’ve got tariffs on this spreadsheet anywhere from three cents to almost $8,200 for a single item,” Budvarson said. 
Allison Budvarson contacts her suppliers every two weeks with follow-up requests asking, Is there any news on this? 
“It's really uncomfortable because I’m already receiving requests from my customers asking me to tell them when they’re going to be getting their refunds,” Budvarson said. 
“And I can’t give them a good answer.” 
Tariffs for the win 
Not everyone is struggling. 
Some companies are doing well, especially those getting a lot more orders because of tariffs. 
Britt LaChance runs Premier Manufacturing just outside of Spokane, a metal fabrication company. 
One of their hottest-selling products right now are server racks for data centers. 
LaChance says that before tariffs, big tech companies would often order their server racks from China because they were cheaper. 
But under tariffs on steel and aluminum, that changed. 
“So now you implement a tariff on that rack, and you can't procure that and land it here in the U.S. for less than $280,” LaChance said. 
“Well, if the U.S. manufacturer was at $210 all along, we saw that uptick come back to the U.S. just because it became competitive for the U.S. to actually build that here.” 
Even though LaChance’s supply costs have gone up, he’s selling more goods and coming out ahead. 
His overall demand and production have doubled. 
He’s grown from 100 employees to around 140. 
He wants to open a second plant. 
But he’s holding off, in case changing politics make the metal tariffs go away. 
That could drive his customers back to Chinese products. 
The big picture 
Dave Reich works on economic predictions for Washington State. 
He pointed to something called the “Economic Uncertainty Policy Index.” 
That’s economist-speak for how unpredictable the economy is. 
“The levels for 2025 were pretty much equal to what they were during Covid," Reich said. 
"When you face an uncertain world, a natural response is to pull back and say, ‘I’m not gonna do anything until I see how things work out.’ 
And that’s really bad for an economy.” 
Adding to that uncertainty: A war, high fuel prices, and the president's promise to bring in new tariffs this summer. 
These three companies tell very different parts of the tariffs story. 
But they have one thing in common: They’re all stuck. 
Barr can’t rebuild what he lost, Budvarson can’t collect what she’s owed, and LaChance won’t break ground on his second plant. 
Article reasoning-pattern comparisonThis article: 5.6%Joshua McNichols: 1.8%KUOW: 2.6%Confirmation Bias5.6%This article: 0.0%Joshua McNichols: 1.7%KUOW: 1.3%Anchoring Bias0.0%This article: 6.8%Joshua McNichols: 2.6%KUOW: 3.4%Availability Heuristic6.8%This article: 2.6%Joshua McNichols: 0.8%KUOW: 1.2%Representativeness Heuristic2.6%This article: 0.4%Joshua McNichols: 0.3%KUOW: 0.7%Hindsight Bias0.4%This article: 2.6%Joshua McNichols: 2.0%KUOW: 1.4%Overconfidence Bias2.6%This article: 3.5%Joshua McNichols: 7.5%KUOW: 7.4%Framing Effect3.5%This article: 5.0%Joshua McNichols: 2.2%KUOW: 1.0%Loss Aversion5.0%This article: 0.9%Joshua McNichols: 1.2%KUOW: 1.0%Status Quo Bias0.9%This article: 1.4%Joshua McNichols: 0.5%KUOW: 0.2%Sunk Cost Effect1.4%This article: 3.8%Joshua McNichols: 5.4%KUOW: 3.8%Optimism Bias3.8%This article: 5.4%Joshua McNichols: 2.8%KUOW: 1.8%Pessimism Bias5.4%This article: 16.3%Joshua McNichols: 6.2%KUOW: 8.0%Negativity Bias16.3%This article: 0.6%Joshua McNichols: 1.7%KUOW: 2.0%Self-Serving Bias0.6%This article: 1.5%Joshua McNichols: 0.5%KUOW: 0.9%Fundamental Attribution Error1.5%This article: 0.0%Joshua McNichols: 0.1%KUOW: 0.2%Actor-Observer Bias0.0%This article: 0.0%Joshua McNichols: 0.8%KUOW: 2.0%In-Group Bias0.0%This article: 1.9%Joshua McNichols: 0.2%KUOW: 0.5%Out-Group Homogeneity Bias1.9%This article: 0.0%Joshua McNichols: 2.1%KUOW: 2.7%Halo Effect0.0%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.2%Horn Effect0.0%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.0%Dunning-Kruger Effect0.0%This article: 1.3%Joshua McNichols: 0.7%KUOW: 1.1%Recency Bias1.3%This article: 0.9%Joshua McNichols: 0.2%KUOW: 0.4%Primacy Effect0.9%This article: 0.0%Joshua McNichols: 0.1%KUOW: 0.0%Blind-Spot Bias0.0%This article: 0.0%Joshua McNichols: 0.2%KUOW: 0.5%Ad Hominem0.0%This article: 0.0%Joshua McNichols: 0.2%KUOW: 0.3%Straw Man0.0%This article: 3.2%Joshua McNichols: 3.8%KUOW: 4.3%Appeal to Authority3.2%This article: 2.7%Joshua McNichols: 2.0%KUOW: 1.4%False Dilemma2.7%This article: 1.3%Joshua McNichols: 1.9%KUOW: 0.9%Slippery Slope1.3%This article: 0.0%Joshua McNichols: 0.2%KUOW: 0.1%Circular Reasoning0.0%This article: 6.8%Joshua McNichols: 3.6%KUOW: 4.1%Hasty Generalization6.8%This article: 1.9%Joshua McNichols: 0.3%KUOW: 0.3%Red Herring1.9%This article: 0.0%Joshua McNichols: 1.4%KUOW: 0.8%Bandwagon0.0%This article: 9.6%Joshua McNichols: 5.8%KUOW: 6.1%Appeal to Emotion9.6%This article: 0.0%Joshua McNichols: 1.1%KUOW: 0.8%Begging the Question0.0%This article: 12.3%Joshua McNichols: 2.1%KUOW: 2.2%Post Hoc (False Cause)12.3%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.1%Tu Quoque0.0%This article: 0.6%Joshua McNichols: 0.3%KUOW: 0.3%Burden of Proof0.6%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.2%Appeal to Nature0.0%This article: 0.0%Joshua McNichols: 0.2%KUOW: 0.2%Composition/Division0.0%This article: 0.8%Joshua McNichols: 2.8%KUOW: 3.3%Anecdotal0.8%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.1%No True Scotsman0.0%This article: 13.5%Joshua McNichols: 1.2%KUOW: 1.4%Ambiguity (Equivocation)13.5%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Joshua McNichols: 0.2%KUOW: 0.1%Middle Ground0.0%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.1%Personal Incredulity0.0%This article: 0.0%Joshua McNichols: 0.7%KUOW: 0.2%Special Pleading0.0%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.2%Genetic Fallacy0.0%This article: 1.7%Joshua McNichols: 0.4%KUOW: 1.0%Unattributed Quote1.7%This article: 0.0%Joshua McNichols: 0.4%KUOW: 0.8%Quote-first Misdirection0.0%This article: 0.0%Joshua McNichols: 3.2%KUOW: 3.2%Biased Writer Voice0.0%This article: 0.0%Joshua McNichols: 0.4%KUOW: 1.5%Indoctrination0.0%This article: 0.0%Joshua McNichols: 0.1%KUOW: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Joshua McNichols: 0.0%KUOW: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Joshua McNichols: 1.0%KUOW: 1.3%Attempt to Sell a Product or S…0.0%

1056 words analyzed.

Speakers

5speakers39%attributed speech647writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 4 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageKUOW • 11 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageBarry Barr • 23 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageBarry Barr • 19 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageBarry Barr • 7 words • 0.0% coverageBarry Barr • 21 words • 0.0% coverageBarry Barr • 35 words • 0.0% coverageBarry Barr • 22 words • 0.0% coverageBarry Barr • 18 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageBarry Barr • 15 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageAllison Budvarson • 18 words • 100.0% coverageAllison Budvarson • 38 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageAllison Budvarson • 19 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageAllison Budvarson • 26 words • 0.0% coverageAllison Budvarson • 8 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageBritt LaChance • 20 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageBritt LaChance • 27 words • 0.0% coverageBritt LaChance • 32 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageDave Reich • 16 words • 0.0% coverageDave Reich • 27 words • 0.0% coverageDave Reich • 7 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverage
Selected voice

Dave Reich

100%flagged-word coverage
50 attributed words12% of attributed speech68% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

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