A Drop in Interest Rates Could Boost Renewables

If the Federal Reserve cuts interest rates in the coming weeks, a friendlier borrowing environment could make all the difference for some mothballed renewable-energy projects.

The returns generated by such projects once they are up and running are often predictable and modest, but because they require a large upfront expenditure, frequently funded in part by debt, they are sensitive to interest-rate fluctuations.

With recent economic data suggesting the Fed has plenty of room to cut, some investors say now is the time to get moving on renewable plans.

Thomas Byrne, chief executive at solar investor CleanCapital, said a drop in interest rates would affect a “not inconsequential amount” of solar developments under consideration. “We have had projects on hold that simply don’t make economic sense for us anymore because the borrowing cost was too high. So those projects will immediately unlock,” he said.

Byrne estimates some of these projects could begin construction by the end of the year and start generating energy next summer.

Solar and wind energy in particular stand to gain from lower borrowing costs, said Srinivasan Santhakumar, principal research analyst with the research firm Wood Mackenzie. “Higher interest rates have disproportionately affected the economics of wind and solar projects,” he said.

An interest-rate increase of 2 percentage points could result in a 20% jump in the cost of producing energy for utility-scale solar power over the life cycle of a project, according to a Wood Mackenzie analysis released in April. In comparison, the same increase might boost the cost of producing energy from gas by 10% to 12%.

Some developers may wait to see a steeper drop before making moves. “It’s definitely a phenomenon, particularly for the more sophisticated, more longer-standing developers who’ve had a history of surfing the ups and downs of the interest-rate spectrum and are also aware of the consequences for their own balance sheet of a long-term interest rate rise,” said Katherine Mogg, managing director at the New York Green Bank, a state-sponsored investment fund that focuses on filling gaps in energy transition financing. Mogg said she expects to see a modest uptick in requests for proposals in the coming months.

The Federal Reserve has signalled a rate cut at its next meeting in September, and most futures investors expect a quarter-percentage-point reduction, according to CME FedWatch. More than three quarters of investors expect the Fed to lower its benchmark rate, now in a range between 5.25% and 5.5%, by at least a full percentage point by year-end.

While a cut in interest rates is a positive for renewables financing, a durable boost for green projects may require a Goldilocks economic scenario in which a cut to borrowing costs don’t coincide with rising fears of a global recession, which could in turn drive investors away from the U.S., said Ron Erlichman, partner at the law firm Linklaters.

“There are a lot of different factors, like the old cliché of ‘headwinds,’ that affect transactions,” he said, adding that large-scale projects such as offshore wind, hydrogen and carbon capture frequently rely on foreign investment.

Fears of unchecked inflation and rampant increases in the cost of materials have cooled down somewhat in the past year, he said, but the looming U.S. election brings a fresh element of uncertainty . While many see a low probability of a full rollback of the Inflation Reduction Act, the legislation that provides game-changing tax breaks for renewables, an executive branch hostile to green energy could slow project permitting or otherwise “nibble at the fringes” of the landmark legislation, as Byrne put it.

“Having done this awhile and seen the cycles in the market, I still remain incredibly optimistic about renewables and energy transition in the United States,” Erlichman said.

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.

A Drop in Interest Rates Could Boost Renewables

Long-shelved capital-intensive green-energy projects could be dusted off for construction to begin—if everything goes right

A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.

Playing a different game

Overlooked