Customs Seemed to Disappear at U.S. Airports. Here’s What Happened
Customs Seemed to Disappear at U.S. Airports. Here’s What Happened
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https://www.fodors.com/news/news/whatever-happened-to-customs-agents-why-airport-customs-checks-look-different-today
Many international travelers have noticed that customs inspections seem less visible at U.S. airports.
For international travelers entering the United States, there used to be a two-step process at the border. The first stop would be an Immigration agent, who would verify your documents and your eligibility to enter the country. Once you were admitted, you’d have a second stop, where a Customs agent would ask questions about what you were bringing into the country with you.
Travelers still get the first step, but many may notice that the second step has largely disappeared. So, what happened?
The Types of Screening at the U.S. Border
The United States is a big country, and many parts of the border lack barriers or staffing, such as most of the northern land border with Canada and most of the country’s ocean coasts. Crossing the border wherever you like, however, is against the law. To enter the United States, travelers must enter at designated Ports of Entry (POE). These can be land checkpoints, seaports, or airports—all told, there are 328 of these in the United States.
Federal officials screen three things at a POE. First, they screen travelers, verifying citizenship status, and for non-U.S. citizens and permanent residents, verifying their eligibility to enter the country. Second, they screen commodities—either those shipped as cargo or personal effects carried by travelers. Third, they screen for potential threats to U.S. agriculture.
These three screening types were once carried out by three different agencies. The U.S. Immigration and Naturalization Service (INS), part of the Department of Justice, was once responsible for the first type of screening. The U.S. Customs Service, part of the Department of the Treasury, was responsible for the second, and the U.S. Department of Agriculture (USDA) was responsible for the third.
Enter the Department of Homeland Security
When the Department of Homeland Security (DHS) was created in 2003 in response to the 9/11 attacks, the screening roles were merged and assigned to a single agency, U.S. Customs and Border Protection (CBP). CBP is one of the largest law enforcement agencies in the United States, with over 69,000 employees—45,000 of whom are officers inspecting passengers and cargo at POEs.
A CBP spokesperson explained to Fodor’s, “CBP’s Office of Field Operations integrates these functions, so OFO personnel conduct all customs, immigration, and agriculture inspections at ports of entry in a unified process. This streamlined approach, supported by modern technology such as biometrics and automated systems, enhances security and efficiency, though procedures may vary by airport based on size, layout, and available programs like Trusted Traveler Programs lanes or preclearance.”
It’s worth noting that two decades ago, before the creation of CBP, border crossing processes in the U.S. (and most other countries) relied heavily on interviews with travelers and written declarations. Much of that process is now digital, so there’s less reliance on interviewing passengers and going through the details individually.
Noted the CBP spokesperson, “While individual officer roles are less visible, CBP continues to coordinate border security and facilitate lawful travel and trade.”
The functions that were once handled by separate agencies are now all handled by CBP, and processes can vary slightly from airport to airport. I recently declared goods over my duty-free allowance on arrival at San Francisco International Airport. The CBP officer at the first screening station locked my passport in an RFID-equipped plastic case, instructing me to visit the secondary screening station in baggage claim after I had collected my checked bag.
After talking with me about what I was importing, the officer at the secondary station unlocked my passport and sent me on my way (the duty amount would have been relatively small, and officers don’t always elect to collect duties in smaller amounts—the important thing is that travelers declare the goods). Here, the CBP officers were performing the functions previously assigned to INS and the U.S. Customs Service.
In Atlanta, the process was different. I didn’t have anything to declare there, but an officer approached me in baggage claim and asked questions about what I had purchased on my trip to Peru. He seemed particularly interested in whether I had food items or plants. I suspect that CBP pays closer attention to arrivals from Peru, where unprocessed coca leaves and teas made from the leaves are sold in plastic bags in markets throughout the country.
Importing coca leaves to the United States is illegal (and so is exporting them from Peru), because they’re used to make cocaine. I did have some tea, but it was Muña (Andean Mint), and some packaged snacks, which are ok, so he waved me through. In Atlanta, the CBP officers were performing the functions previously assigned to INS and the USDA.
How CBP Screens Passengers
CBP doesn’t widely discuss details about investigations and screening procedures, but some of them are pretty common-sense. During my time working in airport operations, I spent a good amount of time in various airport Federal Inspection Stations (FIS – the specific name for a CBP screening area at a POE) and observed much of the process. I remember one instance in Anchorage, where an officer was inspecting the baggage of a passenger who had just arrived from an Asian country (at the time, Anchorage still had a handful of nonstop flights from Asia). The passenger was bound for Utgiaqvik, Alaska, and had brought with him a large supply of DVDs, which he claimed were for personal use.
“But why do you have multiple copies of the same title?” The officer asked. “Do you like those movies that much?” In the end, he had his DVDs seized and was warned not to try it again, or he could face stiffer penalties.
On another occasion, in Las Vegas, I watched as officers interviewed a lady arriving from South Asia. There was a question about her visa, and they’d similarly had her open her bags so they could be examined. The officers found that she’d packed many more clothes and household items than they considered typical for the tourist visa she’d planned to enter the country on, and they also noted she brought a lot of credentials and certifications—as though she were seeking work instead of sightseeing. They ultimately decided to revoke her visa and deny her entry, and she returned home on the next available flight.
Nowadays, much of what CBP officers do has been digitized. There are no more paper declaration forms to fill out, and in many cases, U.S. citizens briefly stop for a facial recognition scan before being welcomed home. The work of the officers is lower-touch, but that simply means a lot of the screening now simply happens faster, digitally, and behind-the-scenes, meaning that citizens can largely cross the U.S. border faster and with fewer speed bumps.
Catalyzing competitiveness: Where investment happens and why
https://www.mckinsey.com/mgi/our-research/catalyzing-competitiveness-where-investment-happens-and-why
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Competitiveness has moved to the top of the global agenda, and investment is its indicator and its outcome. In the context of dramatically diverging investment patterns globally, companies and regions can pull seven levers to level up.
Chapter 2
The bottom-up case for investment
What drives the divergence in investment trajectories, and what could be done to establish a new balance? Many macroeconomic factors underpin differing investment patterns across regions, including structural trends like the rapid growth of China’s urban middle class, aging populations in East Asia and Europe, varied monetary and fiscal responses to the 2008 financial crisis and the 2009-10 eurozone debt crisis, and the impact of the tech industry in the United States.
This report, however, focuses on micro-level decisions that shape business investments across geographies, particularly levelized costs. A large share of investment, especially outside China, is made by global companies that commit capital at scale only in places where expected returns are attractive relative to risk. In global markets, this often requires competitive costs. In this chapter, we examine ten examples to understand what makes or breaks each investment case and what could be done to improve it.
Business cases must add up to unlock private investment
A range of factors influences investment decisions. Many strategic considerations come into play, including which markets and technologies to expand into or enter, what types and levels of risk are acceptable, where projects proceed quickly and efficiently, and what is needed to build resilience. Industrial policy also impacts investment, encouraging investments in some technologies and steps of the value chain that support nascent industries and bolster strategic autonomy or avoid creating chokeholds, among other considerations. At bottom, a positive business case is a prerequisite for large-scale investments. Typically, a company will require that the expected net present value, or the risk-adjusted value of a project’s expected cash flow, be positive and better than other options to proceed with any investment.
What will shape investment decisions?
The decisions vary by type of industry. “Anchored” industries providing goods or services that aren’t traded on global markets need to decide whether local market structures and prices are attractive relative to the cost of, say, building energy substations or laying fiber optic cables. “Footloose” industries that trade their products far and wide will choose where it is most cost-effective and profitable to make an investment relative to other geographies. To companies in industries that feature rapid innovation and an escalatory investment race to the top—industries we call new “arenas” of competition—being able to move fast and to find partners and investors in local ecosystems matters most.
This research examines line items in business cases in ten industries in order to understand what shapes investment decisions and competitiveness. While these cases don’t represent the entire economy by any means, we selected them because they illustrate relevant and strategically important themes as well as a variety of factor intensities of production, such as capital, energy, and labor.
Investment cases
Analysis of ten industries that represent a cross-section of the global economy forms the foundation of this research
The ten cases span the three archetypes—anchored, footloose, and arena industries—with an emphasis on footloose industries, which are most exposed to global competition. Two cases, nuclear reactors and solar photovoltaic production with battery energy storage systems (PV and BESS), look at anchored industries. Both are capital expenditure intensive, and construction and equipment costs are key determinants of their business cases. Because anchored industries are not traded much, the main investment decision for them is about competitiveness in a local market rather than across global production locations. For instance, is there enough domestic demand, and are the costs of the electricity generated acceptable to the government or private offtakers?
Five other cases—steelmaking in direct reduced iron–electric arc furnace (DRI–EAF plants, polyethylene crackers that manufacture commonly used petrochemicals, battery gigafactories, advanced semiconductor fabs, and production sites for pharmaceuticals—focus on footloose industries. These industries’ products are traded around the planet, and so their products are priced in relation to world markets. A business case for a footloose industry is most likely to be positive if its costs after transportation and tariffs are at least as competitive as in other locations where it could produce the same good or service. For instance, could a steel mill in one country compete against a steel mill in another country that has lower energy costs?
Colocation data centers, automotive R&D that underpins a new electric vehicle (EV) platform, and biotech R&D that leads to new molecular therapies are three examples of projects in arena industries. Investment decisions in these industries are heavily influenced by an ongoing need to improve capabilities and an ability to move fast, from permitting to hiring to fundraising, and so on. They often concentrate in geographic clusters where talent, investors, infrastructure, and partners are in close proximity, such as San Francisco–San Jose (“Silicon Valley”) or Beijing, Shanghai, and Shenzhen in the case of AI.
We compare investment cases using a levelized-cost framework, as well as other factors that influence investment decisions
To compare investment competitiveness in different industries and geographies, we use a levelized cost framework. Levelized cost is the sum of all operating expenses, repayment of debt, and accrued interest on initial project expenses, and an acceptable return to investors over the life cycle of a project, based on the typical weighted average cost of capital (WACC). It is equal to the unit price that would make a project’s net present value equal to zero over its entire life cycle, rendering that project viable, and it corresponds to the established macroeconomic concept of long-run marginal costs.
This method allows us to compare the cost competitiveness of different industries in different geographies. For each investment case, we analyze a standard set of cost drivers including capital expenditures for construction and equipment, labor costs, inputs such as materials and energy, and performance drivers such as time to market, scaling effects, and financing conditions. Comparing levelized costs across geographies and investment cases can explain which cost drivers contribute to differences in competitiveness and to what degree (see sidebar “About the levelized cost methodology”). The set of economies we analyze always includes Mainland China, the United States, and the leading European country by investment in an industry, plus any other countries worldwide among the top three for global investment in that industry.
Final investment decisions will consider factors beyond levelized cost. Chief among them are revenues, but also factors such as regulatory stability, domestic market dynamics, local industrial ecosystems, geopolitical shifts and trade impediments, and industrial policy. We take all of these as given. This is an important constraint, especially for anchored industries in which strategic considerations such as supply chain sovereignty, employment, and energy security often weigh as heavily as economics, and for arena industries, where ecosystem and dynamism effects dominate. A government may opt to support a domestic steel plant or refinery to maintain industrial capacity and reduce import dependence, regardless of whether it is the lowest-cost option globally, and technology companies continue to flock to Silicon Valley, even though wages and energy costs are higher than elsewhere. Nevertheless, levelized cost provides a solid quantitative assessment of the financial differences that need to be bridged by other factors, such as revenues, quality of talent, or abundance of financing. Levelized cost ends up providing a fairly solid explanation for where investment actually goes in many industries, which we turn to at this chapter’s end.
European and US levelized costs are 50 to 300 percent higher in many industries than in best-in-class countries
We analyzed cost differences by region by examining the top five investment locations for each industry.
The variation in levelized costs is biggest in nuclear power and, perhaps somewhat surprisingly, automotive R&D. When it comes to nuclear power, France’s costs per megawatt for a newly built, third-generation fission reactor are roughly three times the costs in Mainland China and South Korea, which are virtually equal as the lowest-cost locations globally. Although electricity generated by a nuclear power plant isn’t traded over long distances, such differences still determine where a build-out is economical and thus whether it proceeds. It’s no surprise that over the past decade, three in four new nuclear plants built globally were in Asia, more than half in Mainland China.
Similarly, the cost of developing a new EV platform for a German or US incumbent car company is about three to four times as much as for a Chinese EV manufacturer. From 2021 to 2024, Mainland China’s share of global EV sales grew from 50 to 65 percent, and as of the end of 2025, one in two new car models globally was launched by a Chinese manufacturer.
Cost differences are much narrower in industries such as advanced semiconductor and battery manufacturing, in large part because costs in these industries are driven by globally tradable input materials. Nonetheless, producing advanced semiconductor chips in Germany or the United States costs about 40 to 50 percent more than in Taiwan or Mainland China, and a similar cost gap holds for producing batteries in Europe and the United States compared to Mainland China. Such gaps can be prohibitive, given that both industries produce easily tradable goods and manufacturing capacity is abundant, especially in the case of batteries. This explains why more than 65 percent of advanced semiconductor foundry capacity and approximately 85 percent of battery cell production capacity are in Taiwan and Mainland China, respectively.
Capital expenditures, labor, materials, and energy all contribute to the cost gap
Examining the line items in the levelized cost calculation between countries clarifies the sources of competitive advantage or disadvantage and points to levers that could be used to restore a balance. Exhibit 14 details the cost gap between the base-case location, a country with high investment and low levelized cost, and the highest-cost location in our sample, always including China, a European country, the United States, and any other countries home to major investment in an industry globally. The rest of this chapter discusses each driver of variation in more detail.
Capital expenditures for construction and equipment vary across geographies—but not for the same reasons. Construction costs are determined by input costs as well as by time and efficiency. Costs of steel, concrete, and construction labor are approximately twice as high in Europe and the United States as in East Asia, and construction times can differ by as much as three times in the case of nuclear. Equipment, on the other hand, is generally sourced on the world market, although differences in plant designs and tariffs or trade restrictions can affect prices. For example, shipping costs and import tariffs on Chinese-made solar and battery equipment make levelized costs for a solar PV project with 95 percent reliability in Texas, in the United States, about twice as expensive as in Inner Mongolia in China, despite comparable irradiation in these regions.
Labor is the biggest source of variation, even in many capital-intensive manufacturing industries. Labor accounts for two-thirds of the cost gap in pharma manufacturing between the United States and China and for nearly half of the gap in semiconductor fabs between Germany and Taiwan. This is because engineering wages differ by three to five times, while productivity is practically the same in state-of-the-art plants around the world.
Materials, being globally tradable, should theoretically be the great equalizer in investment cases, but there are important exceptions. For example, natural gas and gas-derived products are important feedstocks that are not easily tradable where no pipelines exist. That makes the cost of making polyethylene, which is produced using natural gas byproducts, much less expensive in Saudi Arabia and the United States, which produce natural gas. Europe and East Asia must import naphtha to produce polyethylene, increasing their costs.
Each region has pockets of competitively priced energy, and those places have traditionally been home to industry. Yet energy is a significant factor in cost variation around the world. Electricity prices explain two-thirds of the levelized cost gap of a colocation data center built in China compared to the United Kingdom. In steelmaking using the DRI–EAF process, natural gas and electricity account for more than 90 percent of the cost differential between steel production in Oman and Sweden.
Speed affects project economics in several ways. First, it increases project costs directly by increasing overhead costs, such as in nuclear projects. Second, it reduces the useful life of projects in industries with rapid technological progress, such as biotech or automotive R&D. Third, it reduces the market value of a product in industries with rapid technical progress or cyclical capacity constraints. As this is not part of levelized costs, the real-world impact of speed is even more important than shown here.
Exhibit 14
A waterfall-style bar chart decomposing the cost gap between the lowest- and highest-cost production locations for various products, before taxes and direct subsidies. Each panel covers a different primary driver category. The rows show cost components: Capex (construction, equipment), Opex (labor, materials, energy, other), and Performance drivers (time to market, country risk premium, interaction effect). Bars indicate how much each component contributes to the gap in $/unit, with primary and secondary drivers highlighted in blue. Each product column identifies the lowest-cost location (top), the highest-cost location (bottom), and the total range multiplier. The first panel focuses on Capital. Nuclear power (Gen III+ fission): South Korea is the lowest at $65/MWh; France is the highest at $190/MWh (2.9×); construction is the primary driver (75 percent of the gap). Solar power (PV + BESS): China is the lowest at $52/MWh; the United States is the highest at $110/MWh (2.1×); equipment is the primary driver (85 percent).
The second panel of the waterfall-style bar chart focuses on Labor. Pharmaceuticals (mAb): China is the lowest at $85k/kg, the United States is the highest at $135k/kg (1.6×); labor is the primary driver (65 percent). Automotive R&D (EV platform): China is the lowest at $445/vehicle, Germany is the highest at $1,600/vehicle (3.6×); labor is the primary driver (55 percent), and time to market is also significant (40 percent). Semiconductors (advanced-node fab): Taiwan is the lowest at $2,800/wafer, Germany is the highest at $4,000/wafer (1.4×); labor is the primary driver (50 percent), and construction is the secondary driver (30 percent).
The third panel of the waterfall-style bar chart focuses on Inputs. Batteries (LFP assembly): China is the lowest at $48/kWh; the United States is the highest at $67/kWh (1.4×); materials (40 percent) and labor (30 percent) are co-primary drivers. Polyethylene (HDPE): Saudi Arabia is the lowest at $660/metric ton; Germany is the highest at $1,305/metric ton (2×); energy (30 percent) and materials (30 percent) are co-primary drivers.
The fourth panel of the waterfall-style bar chart focuses on Energy. Colocation data centers (AI, excluding chips): China is the lowest at $198/MWh; the UK is the highest at $378/MWh (1.9×); energy is the primary driver (55 percent). EAF steel (DRI-EAF-HRC): Oman is the lowest at $495/metric ton; Sweden is the highest at $750/metric ton (1.5×); energy is the dominant driver (90 percent).
The fifth panel of the waterfall-style bar chart focuses on Time. Biopharma R&D (fast-follower mAb, indexed to China = 100): China is the lowest at 100; the global highest is 266 (2.7×); labor (45 percent) and time to market (40 percent) are co-primary drivers.
Construction: Differences in costs and timelines explain up to one-third of the cost gap in manufacturing industries and 60 to 80 percent in nuclear energy
Nuclear power is one of the most capital expenditure-heavy and complex industries in the world, and levelized costs of nuclear power generation differ by a factor of three between France and South Korea. Differences in construction costs explain almost 60 percent of that gap.
Construction costs are determined by input costs as well as by time and efficiency. Lower costs of inputs such as cement, steel, and construction labor in some regions change the calculus. Costs of steel, concrete, and construction labor are approximately twice as high in Europe and the United States as in South Korea, and the gap with China is even more pronounced.
Higher levels of standardization and delivery discipline and lower build times, also have an impact on construction costs, further widening the gap. Benchmark programs in China average roughly 70 months, or a little less than six years, from the time concrete is first poured to completion of a unit; that figure is close to 100 months, or a little more than eight years, in South Korea and the United Arab Emirates. By contrast, recent projects in Europe and the United States have taken as long as two decades to complete.
While nuclear power is an extreme case, similar trends are visible in other industries. The construction of a new semiconductor fab in Germany or the United States, for example, costs twice as much as building a fab in Taiwan, whereas equipment costs are the same globally.42 In more standardized industries such as AI data centers, which are secure buildings with power and cooling systems to house racks of chips, the difference in construction time and costs is much narrower, with timelines for permits and licenses being the differentiator.
In our ten cases, project timelines are almost always longest in large European countries. In Germany, the average time for obtaining a nonresidential construction permit is roughly 200 days, compared with about 60 days in the United States, 40 days in Mainland China, and 30 days in India.43 Timelines for operating licenses are similarly varied. In France, obtaining an operating license takes about 115 days, compared to about 20 days in the United States and about five days in Mainland China.44 This absorbs management time and attention, with French managers reporting that they spend more than 20 percent of their time dealing with regulatory matters. These examples illustrate how institutional capacity to permit and deliver complex projects quickly can generate a competitive advantage in capital-intensive industries.
Equipment: Barriers to equipment trade drive cost differences between China and the United States in solar PV and data centers
Equipment is generally sourced on the world market and contributes little to cost differences. However, equipment costs become a key contributor to variation when lower-grade natural resources require more equipment to extract the same output, when plant designs differ, and when tariffs or trade restrictions come into play.
In the case of solar power, shipping costs and import tariffs on Chinese-made solar and battery equipment make levelized costs for a 95 percent “firmed” solar PV project, or a project designed to meet demand 95 percent of the time, in Texas in the United States about twice as expensive as in Inner Mongolia in China, despite comparable irradiation in these regions.
As for data centers, trade restrictions on leading-edge semiconductors have a material impact on Mainland China’s data center costs and performance.45 Our case focuses on colocation data centers, or “colos” as the tech industry calls them. In this model, investors fund the building shell and facilities, and the computing equipment is provided by users who rent space in the data center. In this model, energy is the primary cost driver for the data center player. By contrast, in the so-called hyperscaler model, the data center owner also owns the computing equipment, including chips. In this model, equipment costs constitute most of total costs and introduce a wedge between Mainland China and other markets. This is because export controls on leading-edge US graphics processing units require Chinese data centers to rely on less advanced imported or domestic alternatives. These consume significantly more power per rack and deliver lower performance, meaning that Chinese customers need to install more racks for the same amount of compute or accept lower performance, which increases levelized cost per token by 30 to 35 percent at current levels of chip performance.
Labor: Labor costs for comparable roles differ by a factor of three or more, even though productivity in state-of-the-art facilities is the same across the world
Labor costs matter more than labor’s factor intensity, or the extent to which it is used to produce a specific good or service, would suggest. Our research doesn’t include classically labor-intense industries such as textile manufacturing and electronics assembly. Nonetheless, given the equalizing role of equipment and materials sourced on world markets, labor is the biggest source of variation in many capital-intensive manufacturing industries. Labor accounts for two-thirds of the 1.6 times cost gap in pharma manufacturing between the United States and China and for close to 50 percent of the 1.4 times gap in semiconductor fabs between Germany and Taiwan. In battery gigafactories, which require less specialized labor, labor explains more than 30 percent of the cost gap between China and the United States, and that excludes the labor cost differences embedded in construction capital expenditures.
Differences are also large in R&D-intensive investments such as in biopharma and automotive development projects. Labor represents about a third of development costs in automotive platform development R&D in China, compared to over 55 percent in higher-cost European countries and the United States, for biopharma the labor cost rises from a quarter of the total in China to 37 percent of the total for global players located in Europe or the United States. The differences in labor costs and labor productivity drive 50 to 80 percent of the substantial cost gap between China and its global competitors, with time to market and inputs explaining most of the remainder.
Labor costs in the United States and Western Europe are typically two to three times higher than in Mainland China and Taiwan and up to tenfold for blue-collar workers in steel production.
What may be more surprising to some readers is that this difference is no longer offset by higher productivity. Wages are determined by the overall economy of a country, but productivity is determined by the technology deployed at individual offices and factories, which is increasingly state-of-the-art everywhere. For instance, the output of a pharmaceutical plant in China and the United States is virtually identical, given that the same plant designs are used in both locations. But wages at US pharmaceutical companies are about three times higher than for comparable roles in China, creating a substantial structural cost difference despite comparable output. In advanced semiconductor fabs, Taiwan has both a cost advantage and a productivity edge over the United States. Taiwanese engineers achieve about one-quarter more output per worker despite wages that are roughly 2.5 times lower than those of their American counterparts.
Energy: Costs are structurally higher in Europe’s industrial heartland and Advanced Asia than in China and the United States
Each region has pockets of competitively priced energy. This is true not only in China and the United States, where industrial electricity users in the cheapest regions paid on average $50 to $55 per megawatt-hour in 2024, but also in parts of Europe such as Scandinavia, where rates ranged from $40 to $65 per megawatt-hour. Industry in China and the United States is largely clustered near this low-cost energy, having moved from early centers of industrialization: from the upper Midwest to the southern United States because of shale gas discoveries, for example, and from the Yangtze River Delta to Inner Mongolia in China, which has high irradiation and wind.
By contrast, most industries in Europe remain in the old industrial heartland around the Rhine and Rotterdam corridors, which formed around ample coal resources. Electricity in these regions now trades at an average of more than $150 per megawatt-hour, creating a drag on the competitiveness of energy-intensive industries. More recently, new capacity additions for power-hungry industries such as materials processing for batteries have been in Iberia and the Nordic countries, where electricity prices are cheap in comparison. But industry has not relocated to the extent it did in China and the United States, supported by national industrial policy. Japan, South Korea, and the United Kingdom also lack low-cost energy resources
Among our ten cases, data centers and steel are examples of energy-intensive industries. Electricity prices explain almost 60 percent of the levelized cost gap of a colocation data center built in China compared to the United Kingdom. In steelmaking using the DRI–EAF process, energy, mostly in the form of natural gas and, to a lesser extent, electricity, accounts for more than 90 percent of the cost differential between steel production in Oman and Sweden. To offset this disadvantage, Germany and other European countries are currently subsidizing energy costs for heavy industry, sometimes by more than half the total cost, although the debate is also intensifying about shifting the most energy-intensive stages of production to locations with lower-cost energy.
The levelized cost perspective in this research focuses on new, greenfield plants, but energy costs matter even more for existing, brownfield sites, where capex requirements for life extensions are lower, and operating costs, including energy, become the main driver of competitiveness.
Materials: The United States has an advantage in fossil feedstocks and Mainland China in manufactured input materials
Materials, being tradable, should theoretically be the great equalizer in investment cases. All companies can source inputs on world markets and should therefore pay similar prices, with any gap due primarily to transportation costs and tariffs. There are two important exceptions, however, related to feedstocks derived from natural gas and to dense supplier ecosystems for manufactured materials.
Natural gas and gas-derived products are important feedstocks that are not easily tradable where no pipelines exist. Prior to 2022, Asian, European, and US natural gas prices traded near parity. The war in Ukraine, however, stopped the flow of piped gas from Russia to Europe, and so markets in East Asia and Europe set liquefied natural gas (LNG) prices, which averaged roughly three to four times US prices from 2022 through 2025. They spiked again after the closure of the Strait of Hormuz in March 2026 to five times the US level. In addition to higher feedstock costs, gas-importing regions such as Advanced Asia and Europe are also much more exposed to price volatility.
For example, countries with ample natural gas resources, such as Saudi Arabia and the United States, can produce polyethylene by cracking ethane, a simple gas derivative. Countries without such resources rely on naphtha, which can only be transported by ship or in specialized pipelines. Germany, a historic stronghold for chemicals production, pays roughly double the cost to produce polyethylene as Saudi Arabia and the United States. The difference in feedstock prices and energy prices together explain roughly two thirds of this gap, with capital expenditure responsible for the remainder. The same challenge applies in other industries relying on inputs derived from natural gas, such as fuels and fertilizers.
Large differences in feedstock prices help explain why even brownfield petrochemical investments are increasingly difficult to justify in Europe, and why the continent has lost close to 40 million metric tons of petrochemical production capacity since 2022. While Mainland China also imports LNG, brownfield sites remain operational, and even greenfield projects still proceed. In our calculation, lower capital and labor costs cannot make up for the cost difference in gas prices, meaning that Chinese operators may accept lower returns on their projects or receive public support of some sort.
Manufacturing industries such as batteries, semiconductors, and pharmaceuticals rely on manufactured products that are more easily transportable. Yet material costs are much lower in Mainland China thanks to its dense local supplier ecosystem. Mainland China accounts for three-quarters of global lithium refining capacity, about 60 percent of nickel-manganese-cobalt (NMC) cathode active material production, and well over 90 percent of lithium iron phosphate (LFP) cathode active material production and graphite anode active material production. This upstream dominance is reinforced by a deep base of equipment suppliers and gigafactory construction, which collectively reduce purchase prices, logistics costs, installation and commissioning costs, and learning-curve losses.
In Europe and the United States, thinner supplier bases, smaller order volumes, and greater reliance on imported equipment and processed materials raise costs and increase exposure to volatility. Competitiveness in materials-intensive industries therefore depends not only on access to cheap energy but also on whether companies operate within dense, scaled, and integrated industrial ecosystems.
Time to market: Especially in industries with rapid innovation cycles and winner-takes-most dynamics, time to market matters
Speed affects project economics in several ways. For example, increasing management oversight or needing to rent a variety of equipment over the course of a project (which we quantify as part of construction costs) can increase project costs directly. Additionally, longer-duration projects reduce the value of a product in industries with rapid technical progress or limited patent durations, such as automotive and life sciences, as well as in industries with cyclical capacity constraints, such as semiconductor chips.
In automotive, EV platform economics are propelled by major up-front R&D investments that must be recovered over a platform’s lifetime. When development of an EV platform takes 36 to 48 months, which is common for legacy OEMs in advanced economies, revenues are pushed further into the future and discounted more heavily. In Mainland China, establishing such a platform takes 21 to 28 months, and revenue starts rolling in much earlier because EV companies have simpler portfolios and faster ways of working. A later launch also limits the period during which a platform can generate full-margin sales before its technology is superseded by, say, electric vehicles with longer ranges or more advanced driver assistance systems. In this analysis, speed explains 10 percent of the substantial cost gap between a legacy American automotive manufacturer and an EV-only player in China. If we exclude structural factors beyond the control of an individual manufacturer, such as wages and working hours, the share of the cost gap linked to time to market increases to one-third, making it the most important competitiveness driver within a manufacturer’s control.
In biotech, so-called fast-following Chinese companies can launch drugs roughly two years earlier than firms in Europe and the United States, where a 13-year development cycle is typical. This preserves more of the remaining patent life and thus extends the period in which to generate revenue.55 Time to market is one of the key drivers of the levelized cost gap in biotech R&D, explaining almost 40 percent of the total difference. In the case of pharmaceutical manufacturing, time plays a smaller role because production can be outsourced to contract manufacturers while a company gets its own plants up and running, thus avoiding loss of patent lifetime.
In datacenters, speed of execution has become the primary concern. AI frontier labs and hyperscalers face labor shortages, equipment lead times, permitting delays, and grid queues driven by the AI boom. Lead times to obtain key components such as generators, chillers, transformers, and switch gear have more than doubled since 2019, and some markets have waiting of up to a decade. In the case of AI training datacenters being built by hyperscalers, a one-year project delay can be the equivalent of doubling in electricity costs due to postponed revenues and changes in the pricing environment.56 As revenue and pricing effects are not part of the levelized cost methodology, this is not modeled in this report.
In semiconductors, prices per wafer are far higher when a node is still at the technological frontier and fall steadily as it matures and new entrants arrive, meaning that faster time to market has a direct impact revenue potential. As revenue and pricing effects are not part of the levelized cost methodology, this is not modeled in the waterfalls. Had we analyzed leading-edge or memory chips rather than 28-nanometer fabs or AI data centers driven by scarcity pricing, for example, time to market would have played a major role.57
It is important to note that speed also matters when it doesn’t show up directly in the line items of an investment case. This is because long lead times can limit the ability to capture market opportunities, absorb too much management attention, and conflict with shorter-term corporate growth objectives. As innovation cycles accelerate across many industries, speed is becoming more important.
Financing costs: Financing costs are similar for global corporations in advanced economies and China, but add to the costs in developing countries
Across Advanced Asia, China, Europe, and the United States, the weighted average cost of capital reported by listed companies varies more by industry than by region.
Examining the ten industries in this research, the weighted average cost of capital (WACC) in those countries ranges from 4 to 7 percent in anchored industries, like nuclear and solar; 7 to 8 percent for footloose industries, such as steel and polyethylene; and 8 to 10 percent for arena industries, like automotive R&D and advanced semiconductor fabs. This reflects that risks to investors are lowest in mature industries with contracted or protected revenue and highest in industries that are exposed to multiple overlapping risks in technology, operations, and demand.
It may be surprising to some that Chinese financing costs are closely in line with those reported by Western corporates. Companies in emerging markets typically report higher capital costs than in advanced economies, given higher governance and political risks. In China’s case, such risks may be canceled out by greater access to state-backed debt financing that compresses debt costs. This effect is compounded by sample selection: Listed Chinese companies are disproportionately large, state-adjacent firms, making them more comparable to blue-chip Western corporates than to the broader Chinese corporate universe or Western joint ventures operating in China.
While there are no systematic differences between advanced economies and China in our sample, there are major differences in WACC for emerging and developing countries. Solar PV is a clear example of this: China’s WACC is 4 percent, versus 6 to 7 percent in India and Brazil. The difference in financing costs affects levelized costs in capital-intensive industries directly. For instance, financing costs account for half of the difference in solar PV costs between India and China.
The biggest cost driver is not always the biggest determinant of cost competitiveness
In about half of our cases, the primary cost driver in the base-case location does not determine the difference in costs between countries. Taking a simple average of our ten industries, capital expenditures account for close to 45 percent of costs in the base-case location, and energy and materials account for an additional 40 percent. Looking at the difference between the highest- and lowest-cost locations, however, capital expenditures explain less than 30 percent of the difference, while the role of labor doubles to 35 percent, and performance drivers such as speed and scale introduce a wedge of almost 10 percent between the highest- and lowest-cost locations.
A more competitive levelized cost often signals higher investment intensity, although other factors matter
In almost all industries, countries in our sample with lower levelized costs have the highest investment intensity compared to their GDP, while countries with higher levelized costs invest less.
To be sure, the many exceptions to this general rule highlight the importance of other factors that have a role in investment decisions. Markets and ecosystems, as well as fast permitting and building, explain why Singapore builds more AI data centers than its high energy prices would suggest, while Sweden builds fewer than it could, given its competitive energy costs. Similarly, Germany remains the biggest investor in automotive R&D compared to its GDP, despite China’s significant cost advantage. AI data centers and EV platforms are examples of arenas in which ecosystems and speed matter most. Economic geography research suggests that it is extremely hard to manufacture new ecosystems59—but as the example of Shenzhen, China, shows, even complex ecosystems can be recreated if the fundamental economics warrant it.
Industrial policies, including subsidies and regulations, enable Germany to build more solar energy, the United Arab Emirates to build more nuclear plants, and China to build more polyethylene crackers than their relative cost position would suggest. Nevertheless, business cases clearly are critical for the long-term viability of an industry as well as for the amount of taxpayer money needed to close gaps with industrial policy, where that is intended.
Having established the extent of variation in levelized costs in investment cases, we next turn to what companies and governments lagging in investment could do to make themselves viable again.
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