Economics and Business

The success of electric vehicles is easy to see, with Tesla seeming to be every other car on the road in my hometown. But how is the EV market actually doing after the removal of the $7,500 rebate for electric vehicle purchases?

At least in the short term, the outlook is not particularly good. The federal clean-vehicle credit officially ended on September 30, 2025, and the subsequent decline in EV sales revealed just how heavily demand had been supported by government incentives. Battery-electric vehicles made up a record 12% of U.S. light-duty vehicle sales that September, but their share of total vehicle sales fell to only 6% in the first half of 2026 (U.S. Energy Information Administration). However, Americans are not running back to gasoline either. Conventional hybrids reached a record 16% of vehicle sales in the second quarter, while all electrified vehicles together increased to 24% of the market (U.S. Energy Information Administration). At the same time, the ongoing war with Iran and disruptions to Middle Eastern oil supplies have driven U.S. gas prices substantially higher, making the long-term cost of owning a traditional gasoline vehicle more expensive. This creates a difficult trade-off for consumers, where the removal of EV incentives has made electric cars more expensive to purchase, while the war has made gasoline cars more expensive to operate. That leaves the Hybrids more attractive, allowing consumers to reduce their exposure to higher gas prices without paying the premium of a fully electric vehicle.

After all, much of the appeal of hybrids comes down to cost. As the Wall Street Journal recently showed, the average EV lease payment rose from $538 in July 2025 to $707 by June 2026 after the period of generous lease subsidies ended (Davis). Purchasing an EV remained expensive as well, with the average new EV costing $56,238 in June, compared with $49,758 for the overall new-car market (Kelley Blue Book). Even with automakers offering incentives worth an average of 13% of an EV’s price, nearly double the industry average, EVs remained a more expensive option for many consumers (Kelley Blue Book). EV owners may be more satisfied with their cars than ever, but that does not necessarily mean consumers are willing to pay hundreds of dollars more each month to own one (J.D. Power).

A similar path is now beginning to emerge in China, though its EV market is already far more developed than America’s. More than 13 million electric cars were sold there in 2025, accounting for nearly 55% of new-car sales (International Energy Agency). Much of that success can be traced to years of industrial policy that expanded battery production, increased manufacturing scale, and helped drive down costs. By 2025, nearly 70% of battery EVs sold in China were already cheaper than comparable gasoline cars, even without incentives (International Energy Agency). This cost advantage has fueled a fierce domestic price war and pushed Chinese automakers toward overseas markets as profit margins shrink. 

China is now beginning to scale back some of that support as well. EVs purchased in 2024 and 2025 could receive a full purchase-tax exemption worth up to 30,000 yuan, while vehicles bought in 2026 and 2027 receive only half the exemption, capped at 15,000 yuan (State Council of the People’s Republic of China). This does not mean China is abandoning EVs. Instead, the government appears to be testing whether the industry it spent years supporting can now remain competitive with less government assistance.

Of course, much of the government support for EVs in both the United States and China was originally justified by their environmental benefits. A 2026 lifecycle study found average emissions of 183 grams of CO₂ equivalent per mile for battery EVs, compared with 445 for hybrids and 521 for gasoline vehicles (Santero et al.). But the greatest incentive for consumers to purchase electric vehicles is still predominantly based on sticker prices, monthly payments, and convenience.

In the current American market, hybrids may dominate the transition because they offer greater fuel efficiency without requiring consumers to rely on charging stations. EV growth will likely depend less on another massive subsidy and more on whether manufacturers can actually lower prices and produce profitable mass-market models. China has already shown what happens when EVs become cheaper than gasoline cars. The real test for the American auto industry is whether it can reach that point on its own, rather than relying on taxpayers to make EVs affordable.

A recent injury forced me to experience firsthand the dysfunction of the American healthcare system. After being sent through numerous referrals, I ultimately had to pay out of pocket because every specialist my primary care doctor referred me to was out of network. Even more frustrating was the wildly different prices for the exact same procedure: one testing site quoted me $1,400, another $500, and another just $398. Then there was the time lost traveling between doctor’s offices, labs, imaging centers, and surgical centers, each requiring a separate appointment. Even something as simple as getting medication meant another trip to the pharmacy. What should have been a straightforward process instead became an endless series of appointments, providers, and facilities. I have personally seen healthcare systems in other countries where diagnosis, testing, treatment, and even medication can all be provided under the same roof in a general hospital. So why does the U.S. healthcare system seem so fragmented and inefficient by comparison?

The truth is, America doesn’t really have just one healthcare system. There are employer plans, Medicare, Medicaid, Marketplace plans, hospital and pharmacy networks, deductibles, referrals, prior authorizations, and different rules for almost every insurer (Commonwealth Fund, 2026). The list seems endless. Even if a doctor says you need a test, your insurance company can still delay it. After treatment, you get separate bills from different providers, and a single coding mistake can mean your claim is denied. In 2024, administrative problems caused a quarter of in-network claim denials on HealthCare.gov plans (KFF, 2026). Many parts of the healthcare industry have profited from these inefficiencies and have little incentive to improve the system. The result is enormous administrative waste, higher costs, and a system in which patients often spend as much time navigating healthcare as receiving it.

The numbers make it clear: Americans pay more for healthcare than anyone else. In 2024, the US spent $5.3 trillion on healthcare, which is about $15,474 per person and 18% of the economy (CMS, 2026). Compared to other developed countries, the US spends about two and a half times more, but life expectancy here is still below average (OECD, 2025). In 2022, private insurance plans paid hospitals about 254% of what Medicare pays for the same services (RAND Corporation, 2024). Therefore, Americans are not getting more care than others; they are simply paying way more for everything.

Other wealthy nations show that universal care does not require one clear-cut model. England has a tax-funded NHS that is generally free for use (Commonwealth Fund, 2026). Germany uses regulated insurance funds, while the Netherlands uses private insurers but requires them to accept applicants and provide a standard package (Commonwealth Fund, 2026). Japan uses several insurance plans but imposes a uniform national fee schedule, and China covers more than 95% of its population through basic medical insurance (National Healthcare Security Administration, 2024). These systems still face shortages and waiting times, but patients are not normally required to investigate dozens of networks or risk financial ruin if they become sick.

So, if the American healthcare system is this inefficient and expensive, who is actually making the money? Large hospital systems can use their market power to negotiate higher prices with insurers (RAND Corporation, 2024). Brand-name drug manufacturers benefit from patent protections that limit competition (FDA, 2026). Insurers and pharmacy benefit managers profit from managing networks, claims, drug coverage, and rebates, while private-equity firms have increasingly bought medical practices and healthcare facilities in search of higher returns (HHS, 2024). The FTC has also warned that highly concentrated, vertically integrated PBMs may inflate drug costs and favor their own affiliated pharmacies (FTC, 2024).

So why doesn’t the government do more to protect patients? Illegal kickbacks and healthcare fraud do happen and are prosecuted (DOJ, 2025), but most industry influence is perfectly legal. It comes through lobbying, campaign contributions, and the revolving door between government and the healthcare industry. In 2024, pharmaceutical and health-product companies spent about $387 million lobbying the federal government, while hospital-related organizations spent another $116 million (Korostoff-Larsson et al., 2026). With so much money at stake, many powerful groups have a strong incentive to resist reforms that could lower prices or reduce their influence.

Healthcare should be designed around treating patients, not forcing them to navigate a maze of insurers, networks, facilities, and bills. The system can be fixed, but not through small reforms alone. It needs structural change. That means continuous basic coverage, simpler and standardized insurance rules, limits on prior authorization, lower prescription drug prices, tougher action against hospital monopolies, and equal payment rates so the same procedure does not cost more because a hospital owns the doctor’s office (MedPAC, 2022). Ultimately, no one seeking medical care should have to spend more time figuring out the healthcare system than actually receiving care.

Five years ago, conversations about weight loss were usually centered around diet, exercise, and lifestyle changes. Today, a new solution has entered everyday conversations: GLP-1 drugs. Medications such as Ozempic, Mounjaro, and Zepbound were originally developed to treat diabetes or related metabolic conditions, but have quickly become a cultural phenomenon, increasingly viewed as a quick solution for those seeking weight loss. Celebrity transformations, social media posts, and online clinics have made weekly injections appear easier and more accessible than traditional approaches to managing weight. Neighbors, friends, and even family members are now using these drugs.

The popularity of these medications is not surprising. For people struggling with weight loss for years, GLP-1 drugs appear to offer a simple solution by suppressing appetite, reducing cravings, and achieving dramatic results without the same level of effort required by traditional lifestyle changes (Christensen et al., 2024). However, these medications do not necessarily address why someone gained weight in the first place. Factors such as stress, genetics, emotional eating, poor sleep, mental health struggles, and unhealthy food environments can remain hidden beneath the surface (National Institute of Diabetes, n.d.).

While GLP-1 drugs can control hunger and support weight loss, they do not necessarily address the underlying factors that contributed to weight gain. This becomes especially important when users stop taking them, as hunger and appetite often return, and many people regain a significant portion of the weight they lost (Wilding et al., 2022). GLP-1 drugs are not addictive in the same way as nicotine or opioids because they do not produce a euphoric high. However, some users may develop a strong reliance on these medications to maintain their results (Wilding et al., 2022). Once people become accustomed to reduced appetite and continued weight loss, the fear of regaining the weight can make stopping treatment feel impossible.

From a business perspective, this creates an extremely profitable model. Pharmaceutical companies can attract customers with the promise of rapid weight loss, while the ongoing nature of treatment can encourage long-term spending (Aronne et al., 2024). Unlike an antibiotic that treats an infection and is then discontinued, GLP-1 drugs often require continued use to maintain their effects. Once patients rely on appetite suppression to manage their weight, they may feel pressured to continue purchasing the medication month after month.

This business model is further boosted by the marketing surrounding these drugs. Celebrity endorsements, including figures like Serena Williams, have helped position GLP-1 medications as symbols of confidence and transformation (Niasse & Singh, 2025). Advertisements emphasize dramatic results and freedom from hunger while often giving less attention to side effects, long-term costs, muscle loss, and weight regain. Telehealth companies, medical spas, influencers, and pharmacies have also joined the market, allowing consumers to request prescriptions within minutes (Chetty et al., 2026).

This does not mean GLP-1 medications are without benefits. For people with obesity or serious weight-related conditions, they can provide major health benefits (U.S. Food and Drug Administration, 2023). The concern is how they are increasingly marketed as easy, universal solutions, including to people seeking only minor cosmetic weight loss.

As GLP-1 drugs become more connected to society’s ideas of health and beauty, will they remain responsible medical treatments for those who need them, or will the pursuit of weight loss transform them into another long-term source of profit for pharmaceutical companies?

AI is transforming the future of technology, but it is also taking a troubling turn. Gone are the days when a $20 monthly plan gave users access to the latest and most advanced models. Token costs are higher than ever, leading to $200 monthly plans and additional credit purchases. These expenses have quickly added up, especially for small businesses and independent developers.

While developing an app, I had to stop using Claude’s new Fable 5 model because I was constantly being prompted to purchase more credits. I was excited when OpenAI’s new 5.6 Sol model came out, hoping I could switch without breaking the bank. Unfortunately, it now has much stricter usage limits, making additional token purchases necessary for many complex tasks. I am frustrated by these business practices and concerned that the most powerful AI tools may become inaccessible to the average consumer.

So what has caused AI to shift from an affordable tool to something that increasingly feels like “pay to win”? Part of the answer lies in how the leading AI companies have structured their services. OpenAI and Anthropic still offer relatively affordable subscriptions, but access to their strongest models is increasingly divided between different plans, reasoning levels, usage limits, and credit systems. Instead of simply raising the monthly subscription prices, they can limit model access and charge users again once they reach their limits. This allows the companies to collect both subscription revenue and additional usage payments while offsetting the high cost of running their most advanced models. From a business perspective, it is a clever strategy: the initial plan draws users in, but once they become dependent on the AI for coding, research, or business operations, they may have little choice but to continue purchasing credits to complete their work.

The problem is that large corporations can absorb these costs far more easily than small businesses and independent users. They can afford enterprise subscriptions, millions of tokens, and entire teams dedicated to integrating AI across their operations. In addition, they can run multiple agents, repeat tasks until they achieve the best result, and pay for faster, more capable models. By contrast, an independent developer or small business may have to carefully ration prompts, switch to a weaker model, or abandon a project after reaching another usage limit. As a result, the gap continues to widen between those who can only use AI occasionally and those who can afford constant access to the most powerful models. Larger companies can then use this advantage to become more productive, earn more, and reinvest in AI, creating a cycle that smaller competitors may struggle to break. 

Cheaper models such as DeepSeek currently provide some hope by offering free chatbot access, low-cost APIs, and models that can be downloaded and run independently. However, there is no guarantee these services will remain free. OpenAI and Claude followed a similar path, initially offering generous access before gradually introducing more expensive plans and stricter restrictions. DeepSeek could eventually follow the same path once enough users and developers come to rely on it. This makes locally run AI a more appealing option because of its lower and more predictable long-term costs. You purchase or build the computer, download the model, and use it without constantly worrying about tokens, credits, changing plans, or unexpected usage limits. 

As AI becomes increasingly essential to our lives, will its most powerful models become another advantage reserved for wealthy individuals and large corporations?

I never fully understood the Labubu hype in the U.S. until my recent trip to Japan. While passing through a Pop Mart store in Osaka, I decided to buy a few blind boxes from the Labubu and Twinkle Twinkle collections. Seeing the images of all the possible toys on the sides of the boxes, along with their percentage chances, I immediately picked out my favorites from each collection and hoped I would get them. That suspense of not knowing what was inside made the unboxing even more exciting. I couldn’t even wait until I got back to the hotel room, so I opened them while eating in the restaurant. After getting a few of my favorites, I found myself wanting more. That was when I realized I was hooked. Finding every Pop Mart store suddenly became the top priority on the trip. From Japan to China, I somehow managed to visit many Pop Mart shops along the way. Each time, I convinced myself that just a few more boxes would finally get me my favorite toy. Of course, the more boxes you buy from the same collection, the more likely you are to start getting duplicates. I even started copying everyone else in the store by shaking the boxes before purchasing them, trying to analyze the weight and size like some kind of possessed toy detective. Thankfully, my trip ended before things got completely out of hand.

So what has made Pop Mart one of the hottest and fastest-rising toy companies in the world? The answer lies in its masterful use of consumer psychology. Most Pop Mart toys are sold through mystery blind boxes, usually as part of a larger series that includes one or two secret figures, with odds of around 1 in 72. This structure makes the buying experience feel less like a normal purchase and more like a game of chance. So when you buy one, and it is not the figure you want, you feel even more compelled to keep buying until you finally get it, as I did. But even if you do get the one you want, you may then want to complete the collection, especially by finding the secret figures. As a result, instead of selling a toy once, Pop Mart effectively sells the same character 10, 20, or even 50 times to the same customer. According to Pop Mart’s prospectus, about 70% of its consumers would purchase blind box toys three or more times for a specific design they want, which means that many customers are not just buying a toy; they are buying another chance to get the toy they actually want (126). This is where the psychology becomes especially powerful. The blind box system uses variable reinforcement, a mechanism similar to the one behind slot machines, because each purchase comes with the suspense of a possible reward. The key difference is that with a mystery box, you are still guaranteed to win something, even if it is not the toy you were hoping for.

Although Pop Mart did not invent the blind box concept, which originated in Japan’s popular Gashapon capsule toy machines, it has become one of the biggest winners in the blind box frenzy. What sets Pop Mart apart is not just the mystery-box format, but the characters themselves and the powerful IPs built around them. Unlike a traditional toy company, Pop Mart operates more like a talent scout for IP. It discovers and signs trendy toy designers with strong market potential, then invests in their characters, turning them into recognizable brands (Reuters). As consumers fall in love with the IP first, they become more willing to buy the blind boxes built around it. Since its first proprietary IP, “Molly,” in 2016, Pop Mart has operated more than 90 intellectual properties. More than 85% of the company’s 2024 revenue comes from exclusive products developed with artists (The Wall Street Journal).

As with any viral phenomenon, there is always a risk that the hype will fade. According to Goldman Sachs, the typical lifespan of popular trendy toy IPs is often only two to three years. With many countries tightening regulations on blind boxes and viral toy trends often fading quickly, Pop Mart is trying to reduce its dependence on blind-box sales by expanding its IPs into new revenue streams (Yang). This includes opening Pop Land, a theme park in Beijing where visitors can interact with life-size Labubu characters, and developing a film and animated series. It has also expanded into clothing, jewelry, and dessert lines, helping the company become more of a lifestyle brand, similar to Hello Kitty.

No one knows what the future holds for Pop Mart, but if it can successfully diversify its revenue streams, extend the life cycle of its IPs, and build a stable of characters strong enough to carry the brand the way Mickey Mouse has carried Disney for nearly a century, then Pop Mart could prove that its success is more than just a passing blind-box craze. In the meantime, I need to restrain myself from buying more blind boxes online. Luckily, there is no actual Pop Mart store nearby to test my self-control.

AI is rapidly changing everything in our lives, from education to productivity, and is already reshaping the jobs market. Many fear that it may eventually replace large portions of the workforce.

The impact of AI on employment is often misunderstood. Instead of immediately replacing entire jobs, AI is gradually reshaping work by taking over specific tasks and functions within roles (MIT Sloan). It is especially effective at repetitive digital work, such as summarizing information, drafting basic text, handling routine customer service queries, reviewing documents, generating code, and organizing data. Many jobs are therefore unlikely to disappear overnight, but will be significantly redefined in how they are performed. However, the data still shows that the threat is legitimate. The ILO found that many workers are in jobs exposed to generative AI, with clerical and administrative roles being among the most vulnerable. The World Economic Forum also predicts that millions of jobs will be displaced by 2030, even though many new jobs will also be created. In the United States, companies have already cited AI as a reason for major job cuts, and some large firms have openly stated that they expect to need fewer corporate workers as AI becomes more useful (Challenger). This shows that AI is not just a future concern but something already influencing companies’ recruitment and workforce planning decisions.

As a result, the value of certain skills in the labor market is changing. Workers in highly repetitive roles may face declining demand, as AI can now perform many of these tasks faster and more cost-effectively. This is especially concerning for entry-level workers because many early jobs involve routine tasks such as basic research, writing, spreadsheets, and summaries that AI can now assist with. If companies require fewer entry-level workers for this type of work, it becomes more difficult for young people to gain experience and progress in their careers. At the same time, AI may also create new opportunities for those who know how to use it effectively. The workers who benefit most will likely be the ones who can combine AI skills with judgment, communication, creativity, leadership, and knowledge of a specific field.

As Jensen Huang stated in his Carnegie Mellon commencement address, “AI is not likely to replace you, but someone using AI better than you might” (Huang). The solution for everyone is not to avoid AI but to learn how to use it productively. People should focus on developing skills that AI cannot easily replicate, such as critical thinking, decision-making, problem-solving, persuasion, and, most importantly, understanding human needs. At the same time, AI should be treated as a tool for enhancement, whether in research, organizing ideas, analyzing information, or project development. Ultimately, the most effective path is not to compete directly with AI, but to become someone who can use it to create greater value in the workplace.

While building a website on Replit last month using its Claude Code-based agent, I noticed it had shifted from using Claude’s Fable to the “most advanced model” (Replit). After a quick search, I realized that the US government had ordered the temporary suspension of public access to the latest model. In addition, the government has also delayed the release of GPT-5.6. This makes me wonder why there are limits on the newest AI models and what the implications are.

The main reason for this restriction is national security, particularly the fear that the most advanced AI models could be used for cyberattacks, vulnerability research, biological research, or other harmful purposes (Reuters). In Anthropic’s case, the government cited national security concerns and ordered access to Claude Fable 5 and Mythos 5 to be suspended for foreign nationals. As a result, Anthropic had to disable the models for all users because it could not reliably verify users’ nationalities in real time. They later explained that the concern stemmed from a report suggesting that Fable 5 could identify software vulnerabilities and generate functional code demonstrating how they could be exploited (Anthropic). Additionally, OpenAI has also begun a limited preview of GPT-5.6 for trusted partners at the U.S. government’s request before a broader release (OpenAI). These recent cases reveal an evolution in AI restrictions, as it is now treated not only as a consumer or business product but also as a strategic technology similar to encryption or defense systems. However, for small businesses that build workflows and entire platforms around access to frontier AI models, this can pose a serious challenge.

So, should the government be able to restrict research and development itself? On one hand, there is a reasonable argument that government oversight is necessary because AI models are becoming powerful enough to support cyber operations and other high-risk tasks. On the other hand, such restrictions could create a significant disadvantage for innovation. If every major model release depends on government approval, research may become slower, less open, and more politicized. Companies with the best lawyers, lobbyists, and government relationships may gain access first, while smaller competitors are left behind. This creates a double standard, where the government claims these models are too dangerous for broad public access, yet still wants access for national security agencies and “trusted partners” (OpenAI).

From a business perspective, this shifts the AI market from pure competition over technological advancement to competition over regulation, compliance, and political access, weakening the open innovation that has made American technology companies so dominant in the first place. Ultimately, this restriction reveals a contradiction in the current administration’s promise of a “golden age” for American business. If access to cutting-edge technology continues to be selectively controlled, then the next stage of technological development and overall economic growth may be shaped more by politics than by open competition.

On my recent news feed, I stumbled across an article published May 13, 2025, from NPR titled, “Why aren’t Americans filling the manufacturing jobs we already have?” (NPR, 2025). I found it particularly interesting because it reframed the issue: rather than asking how to create more manufacturing jobs, it examined why Americans aren’t taking the jobs that already exist.

That question becomes even more urgent when placed alongside recent policy efforts. Even after more than $2 trillion in federal industrial investments (via the Infrastructure Investment and Jobs Act, the CHIPS and Science Act, and the Inflation Reduction Act) and stronger tariff protection, manufacturers still report nearly half a million vacancies, and 65% say hiring and retention are their top challenge (Business Insider, 2025). Why are these fiscal tools failing to boost employment and fill new job vacancies, and why are tariffs failing to nudge production onshore, stimulating domestic output and discouraging reliance on foreign inputs?

The answer is that America’s manufacturing labor crunch is less a policy failure and more a cultural, educational, and workplace-design problem. Manufacturing still carries a stigma: many Americans picture dirty, repetitive, dangerous jobs, when modern plants are often “clean, bright, and full of technology” (Lee, 2025). The skills workers have are also badly misaligned with the jobs being created. Only about 2 in 5 manufacturing roles are directly involved in making goods; the rest are in R&D, engineering, and advanced operations, and roughly half of current openings require at least a bachelor’s degree, something many unemployed workers do not have (NPR, 2025). Companies report needing 1–2 years to teach core skills and another 1–2 years to bring workers up to full productivity (Deloitte & The Manufacturing Institute, 2024). Add an aging workforce and a coming wave of retirements, and the gap widens just as industrial policy expands demand. This results in millions of openings in the next decade, with few to fill the gaps (NPR, 2025). The benefits of tariffs are slow to materialize as well: converting protection into real domestic capacity typically takes 5–10 plus years, while training and hiring needs are immediate. Some of this public money, therefore, needs to be redirected toward technical schools and apprenticeship-style programs, as in parts of Europe. Free or low-cost pathways would give people a concrete incentive to gain relevant skills; one study of the FAME earn-and-learn model finds that five years after completion, graduates earn nearly $98,000 compared with about $52,783 for similar non-FAME participants, a difference of more than $45,000 a year (Jacoby & Haskins, 2020).

Beyond stigma and skills, the very experience of manufacturing work helps explain why productivity and retention lag. The French novelist and philosopher Albert Camus wrote, “Without work all life goes rotten. But when work is soulless life stifles and dies.” Work keeps us alive not just financially, but psychologically; when labor is engineered to squeeze out agency, understanding, and purpose, it starves the self. Traditional assembly-line manufacturing, where the same simple motion is repeated for hours, is a textbook case. The job ceases to be a source of identity. After all, “a man is bigger than his job”: if workers never feel integral to the larger chain of production, they burn out faster, switch jobs more often, and are less productive while they stay. This is one place where AI and automation can benefit workers. As the most monotonous tasks are automated away, new openings increasingly emphasize troubleshooting, set-ups, and continuous improvement, conditions under which work begins to regain meaning (Deloitte & The Manufacturing Institute, 2024). But automation is a double-edged sword. If it merely strips away hands-on tasks without giving workers more say in how systems run, it recreates the same problem at a higher level: people passively supervising processes they don’t feel they own. Automation will only support a manufacturing revival if firms deliberately redesign roles so that more efficient systems increase workers’ agency and problem-solving responsibilities rather than erase them.

All of this is layered on top of a deeper cultural hierarchy of work. Because higher U.S. wages keep many domestically made goods costlier than imports unless productivity rises (The Manufacturing Institute, 2025), we need more than factory subsidies; we need a culture that values and feeds the skills that drive productivity. In several East Asian contexts, industrial craftsmanship and collective contribution carry high prestige, and there is more acceptance of stable, skilled work as a worthy end in itself. By contrast, American career culture often prizes rapid upward mobility and white-collar identity. This hierarchy slowly devalues manufacturing jobs, even when they are technologically sophisticated and well-paid. Correcting this requires a cultural reset that treats modern manufacturing as “tech work with tools.” That could mean scaling paid, employer-led apprenticeships and community-college partnerships (similar to FAME’s 21-month work-school model) (FAME USA, 2024), as well as public investments in advertising and social media that portray the realities of these jobs and combat outdated stereotypes. It also means dropping bachelor’s degree requirements wherever they are not essential, so that more workers can realistically move into manufacturing roles.

Until we destigmatize manufacturing work, redesign jobs so they have purpose, and undertake cultural and educational changes that restore respect for technical labor, America’s manufacturing revival cannot and will not be achieved through protectionist policy alone.

(Image Sourced From Robyn Beck/AFP via Getty Images)

Reading through my Economist news feed, I came across an article detailing how quickly health systems in parts of Africa have unravelled as USAID donor funding dries up (The Economist, 2025). Based on my previous research into how humanitarian aid often failed to meet Sphere standards for adequate nutrition even before USAID was dismantled, I was curious to see how aid networks and the countries in Africa most affected by the crisis are coping now, especially since that external aid makes up at least 20% of many of their government health budgets (Center for Global Development, 2025). The results are grim, with clinics shuttered, vaccination stalled, and maternal-child services vanishing (The Economist, 2025). 

The Trump administration cut the program on January 20, 2025, after signing Executive Order 14169, which aimed to decrease fiscal spending abroad and refocus on domestic affairs under the “America First” agenda (Executive Order 14169, 2025). The effects outlined in the Economist article are devastating. Immunisation campaigns have been cancelled due to shortages of fuel, syringes, and logistical support (The Economist, 2025). HIV clinics are reducing hours as drug deliveries shrink, with UN estimates warning that there could be more than six million new HIV infections and four million more AIDS-related deaths by 2030 than would otherwise occur (UNAIDS, 2025). Midwives are being forced to manage a growing number of complications with fewer referral options. In eight African nations that rely on nearly 50% of external aid, core services are collapsing entirely (Center for Global Development, 2025). In many places, it is the difference between functioning primary care and system failure. 

The case for keeping USAID in place remains strong, especially given its cost-effectiveness and the number of lives saved. Programs like seasonal malaria chemoprevention can save children’s lives for just a few thousand dollars each (Gilmartin et al., 2021). Pooled vaccine procurement has brought down costs to only a few dollars per dose, creating huge returns on every US dollar spent (Vaccine Economics Lab, 2022). The long-running President’s Emergency Plan for AIDS Relief is one of the best examples, as it has saved about 25 million lives since its launch (HIV.gov, 2025). However, while the marginal benefits of each dollar can be enormous, the aid actually received is far short of the amount given. 

Corruption and waste are real and rampant in some locations. The WHO estimates that about 7.3% of global health spending is lost to corruption through bribes, phantom workers, and inflated invoices (World Health Organization, 2023). The Organisation for Economic Co-operation and Development (OECD) finds that up to one-fifth of health spending in many countries may be ineffective or wasted through administrative overhead, low-value care, or ill-designed programs (OECD, 2017). While some critics claim that 30–40% of USAID funds are wasted, this level of misuse has only been documented in specific programmes in Afghanistan, not in the hardest-affected crisis regions in Africa (Special Inspector General for Afghanistan Reconstruction [SIGAR], 2017). It is also important to note that U.S. foreign aid accounts for only about 1.2% of total federal fiscal spending (Pew Research Center, 2025). Yet, it has a huge impact on saving lives and stabilizing fragile health systems in developing countries. 

Given the current reality, there are two key policy reforms that could both reduce foreign spending and continue to aid those in urgent need. First, instead of broad cuts, the U.S. could protect a targeted group of high-impact programs such as childhood immunizations, malaria prevention, emergency obstetric care, and HIV treatment. This could be implemented by tying funding to clear results and matching it with domestic contributions from partner countries, gradually decreasing over time to help build long-term independence. Another way to slash spending while continuing to provide effective aid is to remove unnecessary third parties from aid transactions by providing digital payments directly to clinics, using pooled procurement platforms to lower the cost of medicines and vaccines, and intensifying audits and transparency to cut corruption and waste. 

There are better ways to reduce foreign aid spending without turning our backs on the people who need it most. Pulling the plug overnight does not just cut costs; it causes real human suffering. I strongly urge the Trump administration to seriously reevaluate its foreign aid policy and focus on targeted, efficient reforms that protect the programs saving lives every day. 

(Image Sourced From Simon Townsley/Panos Pictures)

Economic policy plays a vital role in promoting stability, growth, and equity within society. In my current IB Economics unit on policy, we explored both demand-side and supply-side approaches, as well as their respective impacts on the economy. What I found most interesting was the realization that effective governance depends on balance: knowing when and how to apply different policy tools to achieve sustainable outcomes.

For instance, monetary policy directly impacts everyday decisions, whether people take out loans, buy homes, or invest. Central banks use interest rates to influence demand, but this tool has broad and impersonal effects. The U.S. Federal Reserve, for example, raised rates sharply in 2022 and 2023 to slow inflation, but that also meant higher mortgage and credit costs, affecting first-time homebuyers the most. That trade-off made me realize that while monetary policy is useful for stabilizing the economy, it often does not address underlying issues such as consumer confidence, making it less effective on its own. (Federal Reserve, 2023)

Fiscal policy, by contrast, felt more direct and personal. I was especially drawn to how governments can decide who to help and how to do so. Tax cuts can encourage spending, but not all tax cuts have the same effect. Reducing corporate tax might boost investment, but it often benefits higher earners more. By contrast, transfer payments, such as stimulus checks or unemployment benefits, put money directly into the hands of those who need it most. I remember during the COVID-19 pandemic, when my mom was unable to work, those unemployment checks made an immediate difference for our family. (U.S. Department of Labor, 2020) Infrastructure spending, on the other hand, may take longer to implement but creates lasting value. Programs like the American Recovery and Reinvestment Act provided not just roads and broadband, but also short-term stimulus designed to boost consumer confidence and help the economy recover from the 2008 recession. (Congressional Budget Office, 2015) Still, these policies are only as effective as their design. Poor targeting or political delays can waste resources, and crowding out can occur in the private sector as loans are bought up by the government to fund policies, sometimes producing the opposite of the intended economic effect.

What challenged my thinking the most was the role of the supply-side policy, especially the contrast between interventionist and market-based approaches. Interventionist policies involve the government directly, whether that’s funding education, supporting research, or expanding childcare to boost participation, all with the goal of increasing productive capacity. I was particularly struck by Singapore’s Skills Future program, which offers adults learning credits throughout their lives. (SkillsFuture Singapore, 2015) It’s a clear example of how investment in human capital can simultaneously boost productivity and reduce inequality. But I also saw the risks: large-scale public programs can fail if they become inefficient, politicized, or disconnected from real economic needs. On the other hand, market-based policies rely on reducing barriers, such as taxes, lowering regulations, or increasing competition. India’s 1991 reforms demonstrated how liberalizing the economy can unlock growth, but that growth alone doesn’t guarantee fairness and equity, as firms tend to profit more, while profits rarely trickle down to low-income earners. (Rodrik & Subramanian, 2004) What I found most valuable was not choosing one approach over the other, but recognizing how interventionist and market-based approaches can complement each other.

Overall, understanding macroeconomic policy provided me with a clearer understanding of how economic tools impact real people and the trade-offs they entail. More than picking sides between monetary, fiscal, or supply-side strategies, I’ve learned that strong governance depends on knowing how to balance and combine them.

Income Inequality has been a persistent issue for centuries, with wealthy aristocrats holding power. In the United States, despite major reforms in the 20th and 21st centuries, such as the New Deal programs and the Civil Rights Act, which seemed to help marginalized lower-income groups succeed, why do we still see the low household median income for the lower class continue to stagnate, while the households near the top continue to see rising living standards? 

One main reason is technological change. Over the last four decades, software, automation, and now AI have continued to replace routine, middle-wage, and blue-collar jobs while requiring and complementing high-skill work (OECD 2024). This shift pushes more returns toward capital owners and highly educated workers, creating an almost winner-takes-all dynamic, where the wealthy have opportunities to become even wealthier, and the less affluent have a higher chance of becoming unemployed and falling into a debt trap. Since 1979, economy-wide productivity has continued to climb, while pay for the typical worker has lagged far behind, indicating that economic growth is not trickling down to everyone (Economic Policy Institute 2025).

Politics is the main reason this inequality persists. In a system where elected officials must raise vast sums to fund their political campaigns every cycle, those who can supply money and mobilize influence gain the most access and have the largest say in economic policies. Lobbying is now a permanent industry, spending billions each year to shape tax rules, labor standards, procurement, and regulatory details, thereby influencing distributional outcomes (OpenSecrets 2025). This pressure, in the form of bribes and deals, tends to create policies that privilege short-term returns for the wealthy over long-term investments in broad worker prosperity, leaving many workers behind. A major accelerant was the 2010 U.S. Supreme Court case Citizens United v. FEC, which held that the government may not limit independent political spending by corporations and unions, as such spending constitutes protected speech (Citizens United v. FEC, 2010). This paved the way, enabling super PACs and a surge of outside spending that overwhelms small donors. The risk of “dark money” exacerbates the problem, as undisclosed donors have poured a record sum into the 2024 cycle, further skewing who gets heard (Brennan Center 2025).  

Thus, when the preferences of economic elites diverge from those of average citizens, policy outcomes tend to align with the elites. That is the vicious cycle: concentrated wealth buys influence, policy tilts toward those already on top, and the resulting rules (from tax treatment of capital to weakened labor leverage) feed the next round of lobbying. 

I firmly believe that it takes structural change to truly break this cycle, whether through campaign financing restructuring via constitutional reform or banning corporate lobbying and implementing public funding. As of now, it doesn’t matter whether it is the Democrats or Republicans; both parties draft policies that overwhelmingly benefit the upper class. Until this changes, the wealth gap will continue to widen, and lower-income voters will remain unheard.

I recently came across an article in the Economist that caught my attention. It was regarding a new tax policy by the Trump Administration that would put a tax on money sent abroad from the U.S. This bill (Section 899) would allow the U.S. Treasury to impose an extra 5–20 percent tax on dividends, interest, or rents paid to residents of countries with “unfair” tax codes, and skim 3.5 percent off every dollar non-citizens wire abroad. Proponents pitch the package as the financial counterpart to recent tariffs: if Europe can target U.S. tech giants with digital-services taxes, Washington can reclaim a slice of cash exiting the country (The Economist, 2025). Officially recorded remittances to low- and middle-income countries should reach about $685 billion this year, and a bit more than $200 billion of that starts its journey in the United States (World Bank, 2024). A flat 3.5 percent levy on the U.S. share would net roughly $7–8 billion—money lawmakers say could patch potholes, fund workforce training, or simply trim the deficit, all while keeping dollars circulating at home. Treasury officials also find leverage: By dangling higher rates on outbound corporate profits, they hope to coax governments taxing U.S. firms into dialing back their own extraterritorial grabs, turning Section 899 into a bargaining chip rather than a blunt club (The Economist, 2025). 

The downside of this proposal will fall hardest on those who can least afford it. Approximately three-quarters of the transfers subject to the fee are modest paychecks that immigrants, earning below the U.S. median, send home for basic necessities like food, rent, and school fees. For instance, a hotel cleaner wiring $400 every other week would lose almost $14 each time, which amounts to more than a week’s wages over a year. The pandemic-induced economic downturn that led to a 20 percent reduction in Guatemalan remittances saw a sharp increase in child malnutrition, as reported by UNICEF (UNICEF, 2020). The compliance problem is evident from Oklahoma’s decade-old 1 percent surcharge on money sent abroad, where 96 percent of users never file for the refundable credit, and many shift to cash couriers or informal apps, thereby hindering the data trails regulators need for anti-money-laundering work (North, 2015). Moreover, foreign investors still hold nearly a third of marketable Treasuries—about $9 trillion—and may interpret a tax on family transfers as a warning shot that cross-border capital could be next, thereby increasing the risk premium just as Washington’s deficit tops six percent of GDP (U.S. Department of the Treasury, 2025).

It is crucial to evaluate different solutions to this proposal. Washington has already endorsed Sustainable Development Goal 10.c, which calls for driving average remittance costs below three percent; promoting fintech competition, publishing real-time price tables, and streamlining know-your-customer rules would leave more cash in migrants’ U.S. wallets and magnify poverty reduction abroad—without taxing family lifelines (UN DESA, 2024; World Bank, 2024). If Congress insists on a fee, it could offset the burden with a refundable, income-tested credit (North, 2015) or let workers invest the tax into SEC-registered diaspora bonds, mimicking Israeli and Indian programs that have raised more than $35 billion while keeping flows transparent (Ketkar & Ratha, 2007). In comparison to these targeted options, a blanket 3.5 percent remittance tax seems like a cost-saving strategy that could result in substantial legislative consequences.

I think the premise of this proposal is good for the US economy. Since remittances and repatriations are leakages for the US economy, they reduce the circular flow of the economy, meaning that there will be less money to go around for everyone. However, it is mostly low-income immigrants who send remittances and repatriations to their home countries, and with immigrants comprising a large fraction of the US workforce, this tax likely does more harm than good.  Lawmakers would be wiser to rewrite or simply drop the clause before it further alienates America’s immigrant community.

In the past few months, President Trump's administration has rolled out a number of new tariffs- taxes on imports from other countries. Designed to protect American industries and address trade imbalances, these policy measures have sparked widespread debate. People are divided on whether the tariffs will actually help or end up hurting the economy. Now, let's break down the pros and cons and their possible implications for the US economy. 

One of the recent tariff announcements included a 25% tariff on all goods imported from Mexico and Canada, alongside a 10% tariff on imports from China, effective as of March 2025 (Reuters). Additionally, Trump implemented a significant 25% tariff on all imported automobiles and auto parts, set to take effect in April and May 2025. 

The potential positives of these tariffs include encouraging growth in domestic industries by making imported goods comparatively more expensive. This can lead to job creation and increased investment in American manufacturing sectors. For example, tariffs on foreign automobiles might drive consumers toward U.S.-made cars, fostering growth in local auto manufacturing and related industries (White House Fact Sheet). In addition, the tariffs encourage American consumers to purchase more domestically produced goods since the price of imported, normally cheaper goods will be much higher.

However, there are some serious downsides to consider. Critics argue that these tariffs could lead to higher prices for consumers and reduce market choices. For starters, American consumers will feel the brunt of the impact. Even though the tariffs are supposed to push us toward buying U.S.-made products, those items often come with higher price tags due to increased production costs and pricier domestic raw materials. This means people could end up spending more for the same goods, reducing their overall purchasing power and possibly cutting back on spending, which could slow down the economy. In addition, if affordable imported goods become limited, lower-income families could be hit especially hard since they often rely on cheap imported goods for everyday essentials. If those prices go up, it could widen the already significant wealth gap. On top of that, retaliatory measures by trading partners, such as Canada and Mexico, further escalate trade tensions, negatively impacting exports and putting additional strain on industries like farming and manufacturing (Reuters). This uncertainty is rattling the stock market, leading to wild swings and causing investors to panic.

While the recent tariffs are meant to boost the U.S. economy and fix trade imbalances, I cannot help but worry about the risks they bring. I believe it is important that policymakers look beyond the short-term wins and think carefully about the long-term impact on both our economy and our relationships with other countries. Finding that balance is key if we want lasting growth and stability.