Is the Tax Code Causing MASS Tech Layoffs?

The tech job market these days feels more like playing a complicated board game with ever-changing rules than simply coding or developing the next best app. It’s alarming when figures flash before our eyes: 93,000 tech jobs lost in 2022, nearly 191,000 in 2023, and over 95,000 disappearing in 2024.

With such numbers, it’s no surprise the tech community is scrambling for explanations—were we over hiring or is AI to blame? Yet, an intriguing catalyst might actually hinge on something seemingly distant from daily coding: changes in U.S. tax code.

Let’s delve into this notion, turning political and fiscal gears to shine a light on an unexpected corner of the tech industry’s landscape.

This video is from Annie Sexton.

Historically, since 1954, companies in the U.S. could deduct 100% of their qualified research and development (R&D) expenses—a significant incentive that encouraged innovation and lowered the fiscal burden on tech companies. Up until 2017, this setup was straightforward and favorable.

The tax reform passed in 2017 included a critical modification, not implemented until 2022, that altered R&D cost deduction protocols. Instead of allowing companies to write off these expenses fully each year, now they had to amortize them over a span of five years. What does this mean in layman’s terms? Imagine your company spent a million dollars on R&D (and let’s say your revenue also hovered around a million). Pre-2022, you’d write off all that million immediately, neutralizing your profit and, therefore, your tax obligations for that period. Fast forward to the post-reform era, you could only deduct 20% of that million in a given year, substantially increasing your taxable income and your tax bill, even though in reality, your cash reserves have remained unchanged.

Why such a perplexing change? Here’s where the broader legislative picture needs consideration. The change to Section 174 of the tax code was packaged within a larger bill that dramatically slashed corporate tax rates from 35% to 21%, aiming to stimulate economic growth. This huge tax cut naturally posed a risk of ballooning the national deficit beyond the boundary set by the so-called Byrd Rule in the Senate, which prevents any tax law from increasing the national deficit over a ten-year forecast period.

The odd twist? The alteration in R&D tax deductions under Section 174 was supposed to be a temporary lever to balance reductions elsewhere, not a permanent fixture. Yet, due to a combination of legislative inertia and political gridlock, this ‘temporary’ measure remains in effect.

Now lies the conundrum—repeal Section 174, and you potentially unravel a political compromise, hinting at why both parties might be dragging their feet. Consequently, the tech sector finds itself in a precarious position, bearing unintended fiscal burdens that could be influencing hiring and investment decisions.

Anticipated solutions, such as the whimsically named ‘big beautiful bill,’ have floated around, but clarity remains elusive. For those of us in tech, understanding these dynamics is crucial—not just for forecasting our sector’s economic health but also for strategically navigating our businesses and careers through these fiscal shoals.

Moving forward, it’s evident that the interplay between technology, policy, and economics is more intertwined than it might appear at a surface glance. This interconnection suggests a need for a keener awareness and understanding of policy among tech professionals, beyond our usual focus on innovation and development.

Who knows? By the time you read this, regulations may have shifted yet again—such is the pace of change in both technology and policy. But one thing remains certain: staying informed and agile will be key to navigating this complex landscape.

So, as we switch back from taxes to tech in our next discussions, let’s keep one eye on the broader horizon—because in tech, like in life, everything is connected.

Frank

#DataScientist, #DataEngineer, Blogger, Vlogger, Podcaster at http://DataDriven.tv . Back @Microsoft to help customers leverage #AI Opinions mine. #武當派 fan. I blog to help you become a better data scientist/ML engineer Opinions are mine. All mine.