The Good News

Start with the good. Below are 4 positive economic trends which have made the rounds among economists and pundits at the end of 2023:

1. While interest rates have climbed and the inflation rate has fallen, employment rates have held *relatively* strong (Figure 1), defying the standard linear Phillips curve model, which assumes a negative and linear relationship between the inflation rate and the unemployment rate: i.e., lowering inflation leading to higher unemployment.

   

2. Inflation, which was a major thorn over the last few years, appears to be largely under control in the USA, especially when compared to other Western nations.

3. Real incomes, particularly for lower income workers, have risen substantially over the last few years.

   

4. In 2023 the stock-market had its best year since 2009

   

   In short, average Americans are still spoiled for job choices (though quit rates have slowed and job openings have decreased in the last few months), have seen an improvement in real incomes over the last few years, and have witnessed steady improvements in their 401Ks.

   This is best reflected in *real* consumer spending, which has remained strong through all of 2023.

   

   Why So Sad?

   But according to the University of Michigan’s November 2023 consumer sentiment survey, which aggregates numerous indexes on consumer perceptions about current and future business conditions, consumer confidence still hasn’t fully recovered to pre-COVID levels. Indeed, the index for consumer sentiment is considerably lower now than it was following the outbreak of COVID. 

The COVID Hangover Remains

What’s going on here? To start, as argued by former Federal Reserve economist Claudia Sahm, the COVID-19 shock has left behind a trail of long-lasting negative effects and trauma. One prime example of this is the loss in student learning across the United States, which is best illustrated by the precipitous decline in student test scores in math and reading post COVID-19.

Other lingering effects of the pandemic include, but are not limited to, reduced social interaction, increased rates of loneliness and more time spent at home.

Consumers Still Feel the Inflation Shock

The second and most crucial reason why consumers are so gloomy is the simple fact that prices for many goods and services are a lot higher now than they were even 2 years ago. This is best illustrated in Figure 7, which shows that over 40% of Americans listed high prices as a reason for worse personal finances towards the end of 2023.

Indeed, the reason why economists are cheering while laypeople are scowling is that higher prices have yet to become entrenched as “normal” prices. The best example I have of this comes from a friend who works in finance and recently asked me, and I’m paraphrasing here: “if inflation has been tamed then why are prices still so high? Why are they not back at pre-2021 levels?” In a sense, my friend was asking me why the Fed doesn’t pursue a policy of deflation to get back to *normal prices,* a strategy that would have Keynes, who witnessed the post-WW1 Great Britain deflation pain firsthand, shaking his head in his grave…

Such a view of inflation is quite common and exacerbated by another fallacious but widely shared belief: that there is little relationship between inflation and nominal wages. Specifically, Americans don’t understand that an inflationary environment can be a boon to specific segments of the workforce, through the mechanism of increased real wages: i.e. for some households income growth outpaces CPI growth in an inflationary environment.

This fact is laid stark in a late 90s paper by Yale Economist Robert Shiller, where when survey respondents were asked to explain the reasons why their incomes changed over the last five years: “most people spoke of their accomplishments and progress” rather than citing inflation as the primary driver for increases in income.

Simply put, real wage gains are neither a macro-trend that consumers care about nor one that they understand.

Business Conditions, Layoff Fears, and the Media

Another interesting driver of low consumer confidence is the public’s expectations of future employment conditions, which was significantly lower in 2023 than at any time in the last decade.

One data point that could be driving this negative sentiment has to do with the 2023 layoffs. Looking at data from Google trends, searches for layoffs were almost twice as high at their peak in 2023 than at any point in the last 5 years. This is surprising because the actual number of layoffs in 2023 was unremarkable.    

What’s driving the discrepancy between reality and consumer beliefs? One plausible driver is an increase in news articles on layoffs starting in 2022.   

To clarify, the layoffs of 2023 primarily hit the white-collar labor market, which as discussed in a previous post, has experienced a significant slowdown in hiring since late 2021. Specifically, an amalgam of well-known firms such as Google, Twitter and Facebook were among the firms laying off employees by the thousands, which made the layoffs more newsworthy and thus made the idea that layoffs were widespread more prevalent.

This is not a novel take. Indeed, if we compare the Federal Reserve Bank of San Francisco’s news sentiment index—a high-frequency measure of economic sentiment based on economics news articles—to the consumer sentiment index, we can see a strong correlation between the two variables over the last decade. And unsurprisingly we see that the news sentiment index was at its lowest point after the beginning of the pandemic in mid 2020.

Such a relationship is particularly concerning in light of recent research showing that news coverage has become “increasingly negative across all states in the past half-century.”

Why Poor Consumer Confidence Matters for 2024: Elections

To summarize the above, consumers have yet to recover from COVID-19 and inflation shocks of the early 2020s. Importantly, it is unclear to what extent the impact of these shocks on consumers will dissipate over the coming year. To further muddy the waters, persistently negative economics media coverage has helped untether consumer confidence from the reality of a strong and resilient economy. 

What this means is that further improvements in the macro-economic environment—reduced house prices, interest rates, inflation rate, etc.—may have a limited effect on consumer sentiment. 

This spells bad news for the Biden campaign as consumer sentiment about current and future business conditions has historically been a strong predictor of the president’s approval rating his/her odds of re-election.

Indeed, looking at data from the start of the Biden presidency I find a positive and statistically significant relationship (p<0.01) between Biden’s approval rating (both YouGov and Quinnipiac polls) and the University of Michigan consumer sentiment index. Specifically, I find that a percentage point increase in consumer sentiment during the Biden presidency leads to a 0.34% percentage point increase in Biden’s approval ratings. Of course, there are many other variables that will affect Biden’s odds of winning the election. What this analysis serves to illustrate is that consumer sentiment should not be discounted as we approach the biggest even of 2024.  

The other night, to the chagrin of my partner, I spent a solid five minutes researching the brand of the hand sanitizer at the local restaurant. All this fuss started when I worked at a chemical company known for its high-quality hand sanitizer.  Yet, curiously, until recently I paid no attention to the brand of the medication I’d been taking for hypothyroidism, a prevalent condition in the US.

Like most people, I assumed that the drug was safe and would remediate my condition. I’ve also never had a trouble finding my medication in both urban and rural areas of the country as I travel frequently for work and often forget to take my medication along with me.  Finally, the cost of the prescription is reasonable—about $20 for a 3-month supply.

But, as I recently learned, many patients across the United States don’t have this luxury.  Indeed, access to many critical generics prescribed to treat a range of conditions, from life threatening diseases like lung cancer to seasonal illnesses such as strep throat, has gotten worse over the last couple of years due to persistent supply shortages and vulnerabilities across the supply chain, which were laid stark after the COVID-19 pandemic.

And in addition to supply shortages, quality issues persist within the industry, which creates further uncertainty for patients and doctors alike.

The result is that the generics supply has become a national security priority for the United States. And given that many of the issues around supply and quality are inextricably linked with the globalization of the generics supply chain, the Biden administration has highlighted boosting local production of generics as a key intervention to combat issues such as:

• The complexity, vastness, and multinational nature of drug supply chains and the corresponding overdependence on foreign entities who may prioritize national interests above trade in an emergency

• Lack of redundant capacity in manufacturing

• Reduced incentives for existing manufacturers to invest in upgrading equipment, improving supply chains, or expanding capacity

The question is whether deploying subsidies to spur generics manufacturing will be worth the squeeze given the high potential cost. Is it worth pursuing a similar strategy to the semi-conductor sector where the Biden Administration’s CHIPS Act has earmarked $39 Billion in Federal subsidies for new semi-conductor plants in the United States?

At a high level, it is intuitive that the closer a product is to home, the easier it is to control it. But reshoring generics could also lead to some deleterious results, from reduced overall quantities of generics on the market, due to exits of foreign manufacturers, to significantly higher prices for drugs.

What are the alternatives? I will explore that later, but first let me explain how we got here.

How We Got Here

In theory firms should be able to re-create a drug so long as they have the formula and the means to manufacture it. This fact, along with the desire to reduce costs for patients (the AIDs epidemic was a major driver for the push for generics), led to the passage of Hatchman-Waxman act in 1984, which codified the view that generics and brand name drugs are perfectly substitutable (clinically referred to as bioequivalence), which in turn significantly eased the process for obtaining regulatory approval for new drugs.

Since then, new applications for generics have grown exponentially, with manufacturing firms in emerging markets such as China and India now dominating the supply base. For example, the number of Chinese based Active Pharmaceutical Ingredient (API) manufacturers registered with the FDA more than doubled from 188 to 445 between 2010 and 2015. What’s more, the Administration for Strategic Preparedness and Response (ASPR) estimates that almost 95% of sterile injectable (drugs used for acute care) generics now rely on critical materials from China and India.

The globalization of generics manufacturing has created two key challenges. The first concerns quality. As outlined in Katherine Eban’s gripping book “Bottle of Lies,” a race to the bottom for drug prices has sharply increased the variance in drug quality.

The primary case study that Eban cites is Ranbaxy, an Indian manufacturer, one of the first producers of an off-brand anti-viral for AIDS, which eventually fell from grace after several whistleblowers exposed the firm for a host of fraudulent activity, from faked drug quality test data to forged drug applications. While this case study was particularly egregious, it is certainly no anomaly.

Through several case studies the book lays bare the logistical and political challenges that regulators face as they attempt to monitor foreign manufacturers. For example, Eban outlines that while inspections in American plants are as a protocol unannounced, inspections at foreign manufactures are typically announced well in advance, due to a desire to maintain cordial relations with foreign governments. These challenges are further exacerbated by poor or non-existent data on the pharmaceutical supply chain, and a dearth of specially trained government inspectors who are willing to travel to remote manufacturing sites across the world.

The second key challenge for generics is supply resiliency in the face of shocks. This is best outlined in a new job market paper out of Princeton by Anais Galdin, which analyzes the effect of offshoring a generics drug on the probability of a shortage of that drug. Specifically, Galdin finds that generics that are offshored are 12% more likely to experience a shortage than similar drugs that continue to be manufactured in the United States. What’s more, she finds that shortage periods for offshored generics drugs last on average 125 days longer than shortage periods for drugs that were never offshored.

Indeed, two charts from Galdin’s study shown below best illuminate the challenge with offshoring generics. Chart (a) on the left shows that after a drug shortage event, the number of drugs in customs drops sharply. And chart (b) shows that for sterile injectable drugs, there is a strong correlation between the share of foreign manufacturers producing the drug and whether a drug has experienced a shortage or not.

Is Reshoring the Right Solution for Generics?

As stated earlier, one of the Biden Admin’s supply chain resiliency task force’s key priorities is to boost domestic production of generics and semiconductors. At a high level the policy goal for both sectors is to secure the supply of products that are critical to national security and reduce the USA’s dependence on foreign manufacturers.

With regards to semiconductors, I can see some merit in reshoring. For one, semiconductor manufacturing is highly complex, making it a sector with high barriers to entry—this is good. Reshoring will also likely spur further innovation in chip manufacturing, boost adjacent industries, and perhaps most importantly, reduce the United States’ reliance on Taiwan, a country that could soon come under the direct influence of China.

This is not to say that turning the USA into semi-conductor manufacturing hub will be easy. For example, one key concern is that the US will not have the requisite talent to support semiconductor manufacturing plants as they come online.

However, I find it hard to make the same argument for reshoring the manufacturing of generics. For one, while some generics are complex to manufacture, they do not represent a cutting-edge industry.  Put another way, an optimal industry policy strategy should aim to promote investment into innovation and novel products (e.g., branded bio-pharma products) rather than subsidize non-leading-edge sectors such as generics. Second, unlike the semi-conductor supply chain, which has become almost entirely dependent on Taiwan (90% of advanced chips are made in Taiwan) as a manufacturing base, the generics supply chain is more dispersed across emerging markets.

Instead, policymakers would be better off focusing on interventions to:

1. Increase transparency in the bio-pharma supply chain for regulators and firms alike This would make monitoring, evaluating, and preparing for shortage events in the supply chain simpler for government agencies and firms. Indeed, this is best exemplified in the complex mapping exercise that Galdin had to go through to undertake her analysis on shortages in the generics market:

2. Look beyond price when purchasing generics

   1. Currently prices set by Group Pharmacy Organizations (GPOs) for generics are fixed, even during a shortage. Instead, a policy to set a market clearing price during a shortage would incentivize firms to hold more buffer stock.

   2. Second, a pure focus on price when purchasing generics can often lead to deals with manufacturers with poor quality control. What’s more, such a policy is anti-competitive. Indeed, a working paper from 2017 found that 40% of generics markets are supplied by just one manufacturer. As such, expanding the variables used in purchasing a product beyond price would incentivize more expensive, sustainable and reliable generic brands to enter the market and increase the sphere of competition.

3. Ramp up Quality Inspections Companies must be upheld to much more rigorous testing standards. In addition, more transparency around quality testing would give consumers and doctors more confidence in generics. In short, further investment here would go a long way, either inside the FDA or through a secondary market subsidized by the Federal Government.

Not only will these interventions take less time to implement than a reshoring strategy, but they will also likely be more cost-effective. Indeed, of the three potential interventions —subsidies for reshoring, shortage penalties and market clearing prices during shortages—  Galdin’s study finds reshoring to be the least optimal intervention, leading to both highest increases in generics prices and the largest decreases in generics volume on the market:

Subsidizing reshoring unequivocally results in an increase in the unit price of drug products…..a suggested 10% tax break translates into a 30% increase in prices over injectable markets. A 15 to 20% tax break could lead to up to a 50% increase in price across injectable markets.”

What do autoworkers and Hollywood actors and writers have in common? For one, they both went on immensely disruptive strikes this year, which lasted months and crippled production and supply chains at large (at the time of writing, the United Autoworkers Union (UAW) had just reached a deal with Chrysler parent Stellantis, which included a 25% pay hike for workers, along with improved retirement benefits. While in Hollywood striking actors were in the process of reviewing a final offer from studios). But perhaps more importantly, both were galvanized by recent macro-technology shocks, which unions correctly perceive as credible threats to employment, wages, and benefits in these sectors.

For autoworkers, the technology shock has been the rise in electric vehicle (EV) demand and manufacturing in the United States, which requires fewer parts and more automated processes. Since 2020, demand for EVs has accelerated and by 2023 the IEA forecasts that EVs will account for 60% of new cars sold globally. And for Hollywood actors and writers, it was Generative AI, which though still unable to mimic the creativity of top fiction writers (see paper on LLM performance against New Yorker fiction pieces), can surely crank out prosaic scripts for family favorites such as Two and Half Men or the Marvel Franchise.

Increasing adoption of these technologies will no doubt create many new tasks/jobs that previously did not exist. For example, it is projected that the United States will need more than 100 battery cell manufacturing sites by 2035 to support demand for new EV vehicles, which could easily translate to the creation of hundreds of thousands of new jobs in the car manufacturing sector over the next decade. 

Nevertheless, both technology shocks—EV production and Generative AI—spell bad news for many workers as they effectively reduce the demand for labor in the production process in the traditional car manufacturing and film production industries respectively.

In an ideal labor market, workers whose tasks are rendered obsolete by technological change would retrain, upskill, and seamlessly re-allocate their labor supply towards different jobs or newly created jobs. But in reality, the bulk of these workers will not have the skills, aptitude, or desire to do the “tasks of the future.” And even if they did, I wouldn’t bet on their success— history is replete with failed programs to train workers.

In this context, the unions are behaving perfectly rationally—i.e., they are attempting to get the best deal they can, while they can. After all, workers don’t know what future jobs will look like, where they will be located or whether they’ll be qualified for them.

A Historical Example

Indeed, past technological shocks support this view. Take the case of the Mckay Sticher, a positive technology shock that disrupted the shoe-making business in the late 19^th century and which was the subject of a new, ground-breaking job market paper out of the University of Chicago.

Specifically, the author of the study finds that in counties that were most exposed to the arrival of the Mckay Sticher (the machine was first introduced in New England in 1861), 70% of traditional shoemakers left the shoe-making business altogether—for reference there were 130,000 shoemakers in the United States in 1860. What’s more, the author finds that shoemakers in counties more exposed to the Mckay Sticher were more likely than other craftsmen to become laborers and farmers (traditionally very low paying jobs) and were estimated to have lost wealth equivalent to 1.3 years of wages by 1870.

Perhaps most strikingly, the author finds that the children of shoemakers when compared to the children of other craftsmen were less likely to follow the family trade, more likely to enter low-paying manufacturing work, less likely to own a home and less likely to be full-time students.

In short, not only did shoemakers lose from the arrival of the Mckay sticher, but their children lost out as well. This is not to say that autoworkers, Hollywood writers and actors will necessarily follow the same trajectory.

What the example illustrates is that technology shocks can lead to persistent negative and potentially multi-generational effects for a host of workers, a reality that should not be taken lightly by unions, businesses, and policymakers.  

Such market analyses come on the back of the introduction of weight loss drugs Ozempic and Wegovy (Semaglutides), which recently hit the market following successful clinical trials. The patients treated with these drugs over a two-year clinical trial witnessed an average body weight change of -15.2% compared to -2.6% for the control group.

At first glance the potential impact of the drug appears to be massive as the market size for obesity in America is huge – about 30% of American adults are obese— and the number is growing every year (see section on market size).

But like Nicorette, there is only so much a *miracle* weight loss drug can do. For one, patients will need to take the drug indefinitely to maintain weight loss. Second, over time the patients who take the drug will likely develop a tolerance to it, rendering it less effective. Third, the drug comes with side effects, which may dampen its use. And lastly, in the immediate term the high cost of the drug (>$10,000 a year) will likely deter many users from taking the drug and insurers from covering it.  (See section on barriers to adoption for more detail).

Nevertheless, assuming the above barriers prove to be minor or temporary, the long-term effects on the market will be significant, from reduced costs for airlines (fuel costs) to reduced demand for specific types of food and drink products, to downstream effects in the food, beverage, and grocery supply chains (in the last section I dive a bit deeper on the fast-food industry). Indeed, firms like Walmart have stated that they are already seeing the effects of the drugs on consumer demand.

Market Size: Obesity in America

Figures 1-3 give a broad view of the market size of obesity in America. For example, one can see that obesity rates have been increasing across the country, which can partly be explained by a population that is aging—in 2011 the median age was 37.2, while it was 39.7 in 2019 (Figure 1).

Specifically, in some of the most obese states such as Alabama and Arkansas, obesity rates were closing in on 40% of the adult population in 2021, while for the least obese states, they have been creeping up to 25% of the adult population (Figure 2). It’s also worth noting that while some states like California have some of the lowest obesity rates, their large population sizes mean that they also have some of the largest counts of obese adults in the United States (Figure 3).

Short to Medium Term Consumer Adoption

Ok so the market size is massive and will likely continue to grow. But what slice of this market will adopt the drug?

Supply

Currently drugs such as Ozempic and Wegovy are approved to be prescribed as treatment for type 2 diabetes, which afflicts about 8-11% of the total population. Doctors can also prescribe the drug for weight loss on a case-by-case basis, but most insurers are not covering for weight-loss, meaning that most patients would need to fork out about $10,000 or more a year on prescriptions.

However, even with these drawbacks, demand for the drug is still far exceeding supply.

Demand

Cost Barriers

Naturally, in the medium-term supply will catchup as manufacturing is ramped up, but how will demand change? I think it’s fair to assume that at some point the cost to the average patient will drop significantly (rise of generics, reduced manufacturing costs, etc.), which will lead to far greater adoption of the drug. Indeed, a survey conducted by KFF health found that 45% of adults would be interested in taking a safe and effective weight loss drug, but that this interest drops to 16% if the drug was not covered by insurance.

Non-Cost Barriers

Administration

Currently, one of the main barriers to adoption is the need for patients to administer the drug intravenously. In the same survey from KFF health, only 23% (of 45% originally) of adults were still interested in taking the drug once they found out they had to administer the drug intravenously.

Dosing for life

The secondary barrier is the need to take the drug indefinitely to maintain weight loss. According to the results of a randomized control trial published last year, patients who stopped using Ozempic after 68 weeks of treatment gained two-thirds of their prior weight loss. Indeed, in the same KFF survey when patients were told that they would have to take the drug indefinitely, interest in adopting the drug fell to 14%. 

Side effects and drug efficacy over time

Finally, it is still unclear what percent of patients will experience side effects (and as a result stop their prescriptions). In clinical trials 44% of patients experienced nausea and 31 percent had diarrhea among other side-effects. What is more, it remains to be seen how effective the drug is in enabling patients to maintain weight loss over an extended period of time.

In short there are several factors that could affect how deeply the drug penetrates the market in the short to medium term: the price of the drug, barriers to adoption, costs to continue using the drug (increasing dosage due to increasing tolerance), side effects, and most importantly the percent of patients that stick to the treatment indefinitely.

Industry Impacts of Increased Adoption: An Example

How will increasing adoption of Semaglutides affect local industries? One clear example is the quick-service industry in the United States, which Statista estimated to have reached a total market size of $330 Billion in 2022. Will states, in which a significant percent of obese adults adopts these drugs, witness exits of fast-food chains in their local markets? It is very plausible.

For example, in the Figure 4, I show fast food restaurants per capita against obesity rates in 2019, where one can see a moderate and positive relationship between fast food restaurants per capita and obesity rates across America.

Exits of fast-food restaurant locations across the United States will naturally lead to knock-on negative effects downstream in the supply chain from producers (e.g., Keystone), hospitality cleaning product providers (e.g., Ecolab) and food and beverage distributors (e.g., Sysco), and spirits, wine and beer makers (e.g., ABinBev, Pernod Ricard) and distributors (e.g., Southern Glazer).  What’s more, in states where adoption rates of Semaglutides are highest, one would also expect reduced demand for fast-food workers. According the Bureau of Labor Statistics, the QSR sector employs ~4.5 Million food service workers nationwide.

Subscribe now

Since then, debtors have been paying down their student loans in droves, as demonstrated in the Figure 1 below. Preceding this, one can also see two other events of interest: 1) A drop in loan repayments after March 2020—at the start of the pandemic the Biden Administration paused interest and accumulation on student loans as an emergency relief measure; 2) A further drop in loan repayments following the Biden Loan forgiveness proposal in August 2022.

Specifically, students lowered their debt repayments from March 2020, and then lowered them even more with the expectation of debt forgiveness. As such, the restart of loan repayments will come as a significant shock for this cohort of Americans, and will no doubt have major implications on their spending, borrowing, and saving in the months to come.  

What’s more, the student debt repayment shock also comes at a time of rocketing credit card debt and a loosening white-collar labor market both of which exacerbate the problem.

For credit card debt, as shown in Figure 2, balances are at almost a $1 trillion, up from around $850 Million pre-pandemic.

And with regards to the labor market, we can also see that things are not so rosy for student debt holders. This is best demonstrated in LinkedIn’s hiring trends, which one could argue are the best proxy for labor demand for white-collar workers—postings on Linkedin are typically for jobs that require a college degree or higher. Specifically, Figure 3 shows that overall hiring on Linkedin was below pre-pandemic levels in August 2023 and trending downwards.

Deep Dive: Who Has Student Debt?

In short, from the story above, the picture doesn’t look great for student debt holders. But what does it look like at a detailed level?

To elucidate this question, I reviewed data from the Federal Reserve Board of Governors’ Survey of Households to get a more detailed view of the average student debt holder and, to better understand the financial situation of student debt holders.  

The survey includes a range of questions (demographics, income, debt, financial well-being, etc.) with a primary focus on household finances. The survey was conducted in October 2022, not long after the Biden Administration’s debt forgiveness proposal, and includes responses from 11,000 adults.  

High Level Data (Individuals with Student Loans)

To start, here are few high-level stats on student debt holders. First, 15% of respondents in the survey hold student debt. Of those individuals:

• 57 % White and 20% Black vs. 69% White and 11% Black for all respondents

• 47% under the age of 35

• 36% Bachelor’s, 29% Master’s, 34% some college (i.e., have Associates degree or partially completed bachelor’s degree)

• Mean Income: $80,000, Median = $65,000

In short, student loan holders are on average young, disproportionality black and a mixture of undergraduate, advanced, and non-degree holders. They also have household incomes that hover around the mean/median household income in the United States.

Debt and Income Among Student Loan Borrowers

Next comes the meat—how are these individuals doing financially. To start, I analyzed the breakdown of student debt amounts among student loan holders. In line with prior research, I find that individuals with a master’s degree have higher debt burdens than individuals with a bachelor’s degree or just some college education (Figure 4).

Then I looked (at a high-level) at whether individuals with student debt were facing other credit constraints. Here is the breakdown:

Spending

• 7% borrowed from money retirement savings (past 12 months)

• 15% have struggled to pay bills (past 12 months)

• 25% spending more than their income (past month)

Credit

• 49% have credit card debt they don’t expect to pay next month (compared to 30% for respondents with at least some college)

• 24% have increased their level of credit card debt since a year ago (compared to 13% for respondents with at least some college)

Of the above, the main data point that sticks out is credit card debt. Specifically, almost half of the respondents who hold student debt are not regularly paying off their credit card debt. What strikes me about this is that the survey was conducted a year after the pause on loan repayments and interest, and right after the Bidens proposal to forgive student debt. This begs the question as to how much more credit card debt these individuals will amass in the months following the restart of student loan repayments.

Moving on to the income side, first I confirm (again in line with prior research on the college wage premium) that there is a positive relationship between the level of education obtained and household income (Figure 5).

Second, I find that the average student debt holder has a slightly higher income distribution than that of the non-debt holder. This makes intuitive sense given the fact that students with debt are more incentivized to take on jobs/careers with high salaries so that they can pay down their debt more quickly. These findings also do not change markedly when only sampling individuals with a bachelor’s degree or higher, as shown in Figure 6.

Finally, I evaluate whether individuals with more student debt also had higher incomes, finding that the distributions are largely similar across different levels of debt (Figure 7). Specifically, one can see that there is positive correlation between the level of student debt and household income, but the relationship is weak at best. And, when only looking at respondents with a bachelor’s degree or higher, there appears to be no relationship at all (Figure 8).

Conclusions

At a macro level, reduced demand for college-educated workers (fewer Linkedin job postings), coupled with the restart of loan repayments will create significant headwinds for student debt holders.

The review of household survey data from late 2022 also supports the macro view. Specifically, I find that among respondents with at least some college education, student debt holders had on average higher incomes than non-loan-holders but also struggled more to pay down their credit card debt. Based on this, one would expect credit card debt among student debt holders to increase following the resumption in student loan repayments.

In addition, looking within the cohort of student debt holders, I find a linear and positive relationship between the level of education obtained and household income (this is in line with the broader research on the college-wage premium).

On the other hand, I find little or no relationship between household income and the amount of student on an individual’s balance sheet. This likely means that there is a large percentage of student debt holders that have debt burdens that are not manageable with their existing incomes.

Share