Guest User

April 2, 2026

Episode 403: Patrick Adams - When Stock Crashes Matter for Long-Term Investors

Guest User

April 2, 2026

Patrick Adams is a PhD Candidate in Finance at the MIT Sloan School of Management. His research focuses on asset pricing and household finance, using large administrative datasets to understand household savings and investment decisions. Before starting graduate school, he worked on macroeconomic forecasting and monetary policy research as a senior research analyst in the Federal Reserve Bank of New York's Macroeconomic and Monetary Studies function.

What if your biggest investment risk isn’t the stock market—but your own income?

In this episode, we are joined by Patrick Adams, a PhD candidate at MIT, for a fascinating deep dive into how income risk, spending commitments, and liquidity constraints reshape what “optimal” investing actually looks like. Drawing on large-scale administrative tax data, Patrick challenges the conventional wisdom that young investors should be heavily—or even fully—invested in equities.

We explore why stocks appear safe over long horizons but become risky when real-world constraints force investors to sell at the worst possible times. Patrick explains how high-income households behave during market downturns, why their income risk is closely tied to stock market performance, and how consumption commitments like mortgages and childcare create hidden financial leverage. The conversation also introduces a new life-cycle model that incorporates these frictions—leading to surprisingly conservative optimal equity allocations for working-age investors. This episode reframes asset allocation as a problem of liquidity and risk management, not just return maximization.

Key Points From This Episode:

(0:00:00) Introduction to the podcast and overview of the episode’s focus on asset allocation and new research.

(0:01:18) Patrick Adams’ background, MIT PhD research, and how the paper was discovered.

(0:07:08) Why stocks are considered safe for long-term investors based on historical returns.

(0:08:37) When the “stocks for the long run” logic breaks down—forced selling during downturns.

(0:10:35) Evidence: High-income households sell stocks during crashes instead of buying.

(0:12:24) Data source: Administrative U.S. tax return data and its advantages/limitations.

(0:14:23) Investors shift into fixed income during crashes rather than staying invested.

(0:16:52) Financial reality: High wealth, but low liquid assets relative to income.

(0:18:00) Human capital: Income is risky and correlated with stock market downturns.

(0:20:15) Typical allocation: About 25% of liquid wealth in stocks for working-age households.

(0:22:36) Higher-income households have more volatile flows and greater exposure to stock risk.

(0:23:42) Income shocks drive stock selling—not just panic or behavioral mistakes.

(0:25:29) Why households draw down assets instead of cutting spending sharply.

(0:27:26) Consumption commitments (mortgages, childcare) act like hidden leverage.

(0:27:57) Key risk factors: Income volatility, low liquidity, and inflexible expenses.

(0:31:31) Traditional models vs reality: People don’t cut spending—they use savings.

(0:35:25) New model incorporates income risk, market crashes, and spending frictions.

(0:38:33) Core finding: Optimal equity allocation for working-age investors is only 10–40%.

(0:40:55) Practical takeaway: Asset allocation is fundamentally about emergency funds.

(0:42:35) Higher fixed expenses require larger safe asset buffers.

(0:43:49) Counterintuitive result: Retirees may optimally hold more equities than workers.

(0:46:56) Scenario analysis: Selling during downturns destroys long-term returns.

(0:49:12) Key drivers of results: Income-stock correlation and spending rigidity.

(0:51:11) Why this model differs from others suggesting 100% equity portfolios.

(0:53:20) When 100% equity could make sense: low risk, high wealth, high risk tolerance.

(0:56:28) Personal impact: Patrick rethinks his own savings, risk, and spending commitments.

(0:57:34) Advice for listeners: Focus on liquidity, income risk, and fixed expenses.

(0:59:58) Defining success: Impactful research, teaching, and meaningful personal relationships.

Read The Transcript:

Ben Felix: This is the Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making from two Canadians. We're hosted by me, Benjamin Felix, Chief Investment Officer, and Cameron Passmore, Chief Executive Officer at PWL Capital.

Cameron Passmore: Welcome to episode 403, another super interesting episode. You said a line at the end of this one, Ben, in our conversation with Patrick Adams that people love research that supports 100% equity. Well, today is not one of those days, which is kind of the point of the podcast, right?

Just to get more information to help people make, as you've said, 403 times better, smarter, investment decisions. This one was particularly interesting from that standpoint, because it is a different piece of research, which I'll let you describe. The second interesting piece I took away, because Patrick's a PhD candidate at MIT, he talked about the impact of your work on the podcast on him and his cohort that are looking for subjects for their PhD work.

I thought that was really interesting. With that, why don't you tell us more about Patrick, his work and how you discovered him?

Ben Felix: He did say about the podcast that it sounds like a lot of PhD candidates listen. It's a medium where you can sit down and listen to a very accomplished researcher in many cases. In this case, Patrick, as he says at the end of the conversation, is a relatively new researcher, but you still get to dig into his research.

You get to sit down with people who have done research and hear them talk about it in plain language and really tease out the relevant pieces of it for people who are making financial decisions today. It's an interesting medium. If I were a PhD candidate, I would probably want to listen to this kind of thing too.

Patrick is, as you mentioned, Cameron, a PhD candidate at MIT. His research interests include asset pricing, household finance, international finance, and macroeconomics. He is on the 2025-26 academic job market.

I'm sure an interesting time in his life. The closest thing I have to that is when I remember being a basketball player going around touring at universities trying to decide where to commit to. I'm assuming it's like that except maybe a little different.

It's probably way different. Prior to MIT, and this is interesting, Patrick worked as a senior research analyst in the Federal Reserve Bank of New York's macroeconomic and monetary studies function. He graduated from the University of Connecticut.

Now, his research that we talk about, I discovered his research because Jonathan Parker, who's at MIT, is on Patrick's dissertation committee. He tweeted Patrick's paper. I don't even know if I follow him on Twitter, Jonathan Parker, but somehow his tweet shows up in my feed.

I opened the paper and flipped through it. I was like, oh man, this is so good. I messaged him right away and asked if he'd be interested in coming on the podcast.

He told me that he's listened to many episodes and that he would love to. The paper is basically like, okay, we know stocks are not that risky for long-term investors. He asked, okay, we understand that, but they are risky for long-term investors if you need to sell your portfolio in the short term, which basically makes you a short-term investor.

It's one of those things where it's like, oh, of course we should look at that. He looked at empirically how high income households behave with respect to the stock market during bad times. The findings, I won't spoil them, but they're very interesting and they do call into question being 100% equity for your liquid wealth.

It sounds like a big finding and I don't want to diminish the research. It is a very interesting finding, but I think it boils down to, and when we talked about it during the episode, you need to have an emergency fund. You can invest in stocks, but your overall asset allocation, including your emergency fund, is going to be very conservative in your liquid accounts, like your non-retirement accounts that you could sell from.

When you account for a 12 month of expenses emergency fund, if you think about your overall wealth, when you have relatively low liquid wealth, your equity allocation in your liquid accounts, of course, is going to be super low because it should mostly be in an emergency fund in many cases. As your wealth increases, your overall allocation to equities can increase. This research does flip on the idea that, well, young investors should be 100% in stocks.

I think he does that in a very interesting and useful way.

Cameron Passmore: It's really interesting intersection of stock returns, the risk on your own personal income, your labor income, and as he said, the consumption commitments you've made, you intersect all these and that's what helps you get to an asset allocation information piece.

Ben Felix: It really makes you think about the added risk of consumption commitments. That's like a mortgage, you're not going to miss a mortgage payment. If the stock market drops and your income drops at the same time, which is empirically what he's showing tends to happen, particularly for very high income earners, you're not going to let your house get foreclosed on or whatever happens if you start missing mortgage payments.

You're going to sell some of your stocks. If you sell them when they're down a lot, all of a sudden, the whole stocks for long term investors thing, it dies. You're taking on a huge implicit cost by selling your stocks at the worst possible time.

It's the kind of thing where it's like, oh, well, you wouldn't do that. You wouldn't sell your stocks when they're down. Patrick's research is showing, well, a lot of high income earners in fact do that.

Cameron Passmore: They do.

Ben Felix: Yeah. We can say, stay disciplined, but you have good behavior, look at the data, all that kind of stuff.

But Patrick's showing in a lot of cases, people just aren't able to do that because they don't want to stop paying for daycare or miss their mortgage payment. Anyway, super interesting research. We talked about that paper with Patrick.

We went through kind of all the thinking behind it and how it affected his thinking about asset allocation.

Cameron Passmore: Excellent. Okay. Let's go to episode 403 with Patrick Adams.

Ben Felix: Let's go. Patrick Adams, welcome to the Rational Reminder Podcast.

Patrick Adams: Ben, Cameron, thank you very much for having me. As I've told you before, the podcast played an important role actually in the research I'm going to talk about today. So it's great to be here.

I do just need to first state one important disclaimer since the paper uses data from the US Census Bureau. And that's just that they haven't reviewed the paper for any accuracy or reliability. They don't endorse its contents.

And all the conclusions I'm going to express today are purely my own and don't represent the views of the Census Bureau or any other government agency. However, the census has reviewed the results that I'm going to talk about to ensure appropriate access use and disclosure avoidance protection of the confidential source data used in the paper.

Ben Felix: Interesting. Very cool to hear that this podcast played a role in your thinking and your approach to the research.

Cameron Passmore: Definitely.

Ben Felix: By the way, I read your paper and as soon as I read it, even when I got to the abstract before I even read the paper, I was like, oh man, we need to have Patrick on because it fits so well with a lot of the other research that we've talked about in the last couple of years. To get us started here, can you explain why stocks are often characterized as relatively safe for long-term investors?

Patrick Adams: In a lot of conventional investing wisdom, particularly for US investors, stocks are considered safe for a lot of long-term investors because in the past in the US data, they've historically had relatively safe returns over long holding periods, such as 5, 10, 20 or 30 years, even when we adjust those returns for inflation. Going back all the way to the start of the 19th century, there's not even a single 20-year period where stocks had a negative cumulative real return. And the same is not true for inflation-adjusted returns on other safe investments like cash or long-term bonds.

Now, of course, over shorter holding periods, stocks can look quite risky. And even in the 21st century so far, we've already seen two separate 24-month periods where those real cumulative stock returns fell as low as negative 40% for the overall market. One of the key empirical facts in finance, though, is that stocks have historically recovered from many of these large price crashes within the span of often just a few years.

This is one particular example of Robert Shiller's Nobel Prize winning insight that, of course, stocks tend to be excessively volatile and returns mean revert over time. Now, all of these observations are what ultimately motivate the portfolio prescriptions, for example, in Jeremy Siegel's famous book, Stocks for the Long Run, that stocks are a relatively safe investment for long-term buy and hold investors who can avoid selling during these short-lived price crashes.

Cameron Passmore: When does this logic break down?

Patrick Adams: One of the most important ways that this logic can break down is if you have to sell or rotate out of stocks during one of these large price crashes. Essentially, by selling the dip, you're going to miss out on the recovery that tends to follow. I think a few examples here help to illustrate this.

So suppose you're an investor who starts the year 2008 with $100,000 invested in a broad U.S. stock market index. Now, by the end of the year, you're going to be down almost 40% from where you started. If you stay fully invested in the stock market in this case, you would recover most of that initial investment in real terms by roughly the end of 2012.

However, if you shift out of stocks at the end of 2008 into some safer store of value, then shift back into stocks only later at the end of 2010, it may ultimately take you as late as 2016 to recover that initial investment from before the crisis. We could even do the same exercise at the start of the year 2000. A buy and hold investor there would ultimately lose more than 40% of their initial wealth by the end of 2002, but will be roughly back to the level they started at around the end of 2007.

Now, if that investor instead shifted out of stocks at the end of 2002, then back in at the end of 2004, they would potentially have to wait until well after the financial crisis to recover that initial investment. But in either case, if that investor instead had to withdraw $50,000 from their brokerage account at the bottom of the market, they would wipe out nearly all of their financial wealth and would barely benefit from that recovery in stock prices. (10:13) As portfolio guidance for long-term investors, stocks for the long run really relies crucially on your ability to avoid selling your holdings during these large price crashes.

Ben Felix: You have done this research that asks, such an obvious question now that you've asked it, nobody has really done it before. So empirically, what do typical high-income households' flows into and out of the stock market look like?

Patrick Adams: In the paper, I'm going to ultimately use information from individual income tax returns to study the savings behavior and investment decisions of high-income working-age households. And just to set the stage, these are going to be households that rank in the top 20% of the wage and private business income distribution within their age group. Those households collectively own about one-third of total U.S. household stock market wealth, including retirees. And about half of that wealth is held in taxable brokerage-type accounts, while the other half is in tax-advantaged retirement accounts like IRAs and 401ks. The main measure that I construct in the paper is their flows into and out of the stock market within their taxable accounts. I'd love to get into the details of exactly how that's measured from the information we see in the tax data.

What's really striking about these measured flows is that they are very strongly pro-cyclical. So during these major stock market crashes in the early and late 2000s, we see large average outflows from stocks among these households, in contrast with pretty steady inflows during the expansion periods before and after. And moreover, those large average outflows are pretty concentrated among a small subset of investors, making really large drawdowns from their existing holdings.

That's to say, the proportion of individuals who are liquidating a large share of their existing holdings varies a lot over the business cycle. So in the data, many high-income working-age households do not seem to behave like that idealized long-term investor who can weather the storm and ride out these temporary crashes in the stock market. And what I want to understand on the basis of that is what drives their savings and investment decisions, and what implications does this have for how they should allocate their financial wealth?

Cameron Passmore: You touched on this at the beginning, but what data set are your results based on?

Patrick Adams: So the main data set that I'm going to be using in the paper consists of some select information we see from individual income tax returns for a very large random sample of U.S. tax filers over the period from 1998 to 2023. Right now, tax season is approaching, and you or many of your listeners may be filling out your own individual income tax return Form 1040. Now, that form has many different lines on it that report the total income that you and potentially your spouse have received from many different sources, like a job that pays wage and salary income, any dividends or interest that you receive from your asset holdings outside of tax-advantaged retirement accounts, and even any income that you receive from a closely-held private business like an S-corporation or a partnership.

Now, the information that I work with ultimately consists of the dollar values from those lines on Form 1040. And I want to take one step back here. This is really an example of what we call administrative data and finance and economics research.

Over the past 20 years, there's been a huge surge in research using big data provided by governments and large financial institutions to uncover new facts about individuals' risk exposures and their economic decisions. But the advantage of these data sets is their large size and broad scope. They allow us to follow, in my case, millions of individuals over long time periods, spanning multiple boom-bust cycles in the stock market and the real economy.

But the challenge of working with these data sets is that they were often collected for a different purpose than what we want to use in our research. For example, there's not much information in these tax forms about how many stocks you purchased this year because the IRS really just cares about the capital gains taxes that you'll eventually pay when you sell them. So for that reason, we often have to be a bit creative to get the information we want from the information that we have in these government data sets.

Ben Felix: You mentioned that the flows into the stock market are pro-cyclical. How do the flows into bonds differ from the flows into stocks?

Patrick Adams: So if we look at the aggregate level for this group of households, their flows into safe fixed income assets look much less pro-cyclical than their flows into stocks. So I construct a similar measure for their net flows into, say, safe bank deposits, government bonds, municipal bonds, and other safe fixed income assets. During these large stock market crashes, many of these households are actively moving into fixed income, even though interest rates tend to be quite low at these times.

Here, many of the high-income working-age investors I study in the data do not appear to behave as our idealized long-term investor who leaves their portfolio untouched during these large stock market crashes or even actively buys the dips in the stock market.

Ben Felix: So you're working with income tax data, tax return data, which doesn't have flows. Like there's no flows data. How much stock did people buy? So how did you estimate flows for the research?

Patrick Adams: The challenge of working with the income tax data is that Form 1040 doesn't have a line that reports, as you say, this is the amount of stock that I bought or sold this year. It does have a line that reports this is the amount of dividend income I've received this year, which provides some indirect information about my taxable stock holdings. And I ultimately use that information to estimate households' net stock sales and purchases using something called capitalization methods.

So essentially, if I see your dividend income grow much faster than the overall stock market's dividends over a given time period, I'm going to infer that you bought a lot of stock then. Whereas if it falls a lot more than the market, I'm going to infer that you sold stock over that period of time. The capitalization part of the name refers to how we ultimately estimate the dollar value of those stock sales or purchases from that change in dividend income, just like an investor would value a stock based on its current dividends.

To take a step back, this measure can be pretty noisy for a single investor over a single time period. Of course, some people hold stocks like Amazon that don't pay dividends, and other people hold stocks whose dividends may fluctuate more than the overall stock market, even if they don't actively buy or sell. So a lot of work goes into validating these estimates using information from other data sources and ultimately determining what we can and can't say with them.

The bottom line there, I think, is that when we average over thousands or even millions of people in a given year that I see in the tax data, we can actually get a pretty good estimate of their average flows into or out of the stock market.

Cameron Passmore: This is really interesting. How would you describe the financial situation of the households you studied?

Patrick Adams: To understand their financial situation, it's ultimately useful to focus on their assets and income, drawing on some data outside of what we see directly in the tax returns and some surveys from, say, the Federal Reserve that provide a really detailed snapshot of their balance sheet. First, in terms of their assets, these are generally households with pretty high wealth and net worth in absolute dollar terms. However, a large share of that net worth tends to be tied up in the form of assets that are not very liquid.

These are things like a large house or a private business that may be difficult to sell on short notice, or retirement accounts like a 401k or IRA that they would have to pay a significant tax penalty to actually withdraw from. If we focus on just their liquid financial assets, that is, their bank account balances, stocks and bonds that they hold, and taxable accounts and mutual funds, or other assets that they can draw down on without paying these high transactions costs or tax penalties, that's a smaller share of their net worth. Just to put some numbers on it here, if we focus on 40-year-olds, saying the top 1% of the earnings distribution at their age group, the median household in that group has only about two-thirds of their pre-tax earnings saved up in liquid assets, or about eight months.

If we look further down in the earnings distribution, that number is even smaller. So if they had to tap into those liquid assets to cover their typical expenditures over a period of even just a few months, they would potentially exhaust a large share of them. The most important asset they own that doesn't directly appear on any balance sheet, and there's been the discussion of a lot of work on this podcast recently, is their human capital.

So even though these households own a lot of financial assets, the vast majority of their spending is financed not by returns on those assets, but by the income they earn from their job or a closely held private business. Now, I think one of the most important empirical facts that we've learned from work with administrative data over the past two decades, is that this income is actually quite risky and quite correlated with the stock market for many top earners. In particular, Fatih Güvenen at the University of Toronto and his collaborators have shown in a series of very important papers that many of these top earners experience large declines in their earnings around these major stock market crashes.

So for those same 40-year-old households that start out before the crash in the top 1% of the earnings distribution, about 17% of them are gonna lose half or more of their annual earnings during the stock market crashes in the early and late 2000s. These people don't necessarily go through prolonged periods of unemployment like those at the bottom of the income distribution, but they may have bonus pay or stock-based compensation that's very sensitive to the stock market and the overall economy. They may have to switch from an initial high-paying job to a different one that doesn't pay quite as well, or they may own a private business with very volatile profits.

But to sum up, these households that I study ultimately have a lot of illiquid assets like housing and retirement accounts, a smaller share of liquid assets in bank accounts or taxable brokerage accounts, and volatile labor or private business income that may force them to draw down on those liquid assets exactly when the stock market is doing poorly.

Ben Felix: If we look at just those liquid assets, what proportion does the typical household in your sample invest in stocks?

Patrick Adams: They do. And the typical average share of liquid wealth that's invested in stocks for the typical household in my sample is about a quarter, 25%. Although this varies a lot across households, some of them have no taxable stock holdings at all, may hold stocks only in their retirement accounts, while others have half or more of their entire liquid wealth invested in stocks.

I think it's important also here just to remember that this measure of total liquid wealth in the denominator there includes assets held outside of brokerage accounts like bank deposits. That's the single largest liquid assets on most households' balance sheet. If we look instead at their holdings within their retirement accounts, that average stock share is quite a bit higher at around 60% for these households.

But the stock share of liquid wealth also varies a lot across age groups, ranging from less than 20% around age 30 to more than 30% around 60 as households approach retirement. And that increasing stock share over the life cycle is essentially the opposite of what would be predicted by many portfolio choice models that have safe bond-like human capital or with strong horizon effects where young households with long expected holding periods have a better ability to ride out these short-lived price crashes in the stock market.

Cameron Passmore: So in addition to age, how does this vary across the income distribution?

Patrick Adams: Higher income households tend to actually hold a larger share of their liquid wealth in stocks. This is in part attributable to the fact that more of their financial wealth is held in those taxable liquid forms rather than tax advantage retirement accounts due to the contribution limits on those accounts that are particularly binding for high-income people. However, their stock shares of their total financial assets, including their retirement accounts, are also higher.

And I think this is a bit of a puzzling fact because these higher income households actually face more income risk in their jobs and their private businesses compared to households further down in the earnings distribution. My own view here is that these patterns probably reflect some differences across households and their risk aversion with more risk-tolerant people selecting into high-income, high-risk professions or businesses, but also at the same time, taking on more risk in their financial portfolios.

Ben Felix: What is the relationship between household income and stock market flows? Are the highest income households different in that sense?

Patrick Adams: Exactly. They are different because their flows into the stock market are much more volatile and pro-cyclical than households further down in the income distribution. I think there's two main facts that really drive this.

The first is they have more liquid wealth overall. And as I mentioned just now, they tend to invest more of that in stocks. So they have a lot more to potentially sell.

The second is that their non-financial income, their wage and private business income, is again, much more volatile and correlated with the stock market compared to lower income households. And this is really, again, a fact that we only learned somewhat recently when researchers gained access to these large, high-quality data sets where we can follow these top earners over many years and multiple real economic business cycles. So these higher income households have both a larger stock share of their liquid assets and a greater potential need to draw down on those assets during a stock market crash, which is exactly what we see them doing in the data.

Cameron Passmore: So what tends to be happening to a household's non-financial income when they're actually taking money out of the stock market?

Patrick Adams: So it tends to be falling. And this is one of the nice advantages of the income tax data that we can really zoom in on individual households and get a pretty complete picture of both their financial and non-financial income for every investor in my sample. So the investors who are taking large sums of money out of the stock market or their savings accounts are much more likely to have experienced these large 25% or 50% declines in their wage or private business income over the same time period that they're withdrawing.

And we can even flip the same exercise around and ask, when an investor gets hit with a bad shock to their non-financial income, for example, maybe there's a local economic downturn in their zip code, how do they adjust to that shock? What we see in the data is that they mostly adjust by drawing down on their liquid financial assets. Their net savings ultimately falls by between 50 to 85 cents for each lost dollar of wage and business income that we see.

Just to take a step back here, I think there's some sense among academics and maybe sophisticated investors that these retail investors' outflows during stock market crashes in particular are driven by purely behavioral factors like panic and fright. But I think what this new evidence suggests is that these losses in their non-financial income also play an important role in driving these flows. And in some sense, this is a deeper problem for these investors and their portfolio allocation problem than just trying to avoid panic selling when the market crashes.

Ben Felix: Yeah, that's a much bigger deal because you can't just say, well, no, don't sell. Don't panic. It's going to be okay.

Look at the data. But if people are selling because they have to fund expenses, it's a totally different conversation. Why are households spending their financial assets rather than holding their stocks and being disciplined and adjusting their consumption when they have income losses?

Patrick Adams: Exactly. It's a great question. It's key to the paper and to try to understand that, I draw on a different survey data set that provides a lot of detailed information about what these high-income working-age households actually spend their money on in a typical year.

And what we learned from that is that a large share of their typical budget goes towards forms of spending that would probably be difficult to reduce or defer over a relatively short time period. Take housing, for example. For the typical 40-year-old high-income household, housing-related expenditures are going to account for about a third of their annual budget.

Many of these people live in large, expensive houses and have large mortgages associated with that. And the cost of servicing that debt, plus utilities, property taxes, and maintenance, they all add up pretty quickly. Apart from their home, they also spend a lot of money on other things that may be difficult to cut back on within the span of, say, a year without making big changes in their lifestyle.

Things like healthcare and insurance premiums, childcare, school, or college tuition for their children. All of these types of services that involve some form of commitment over some fixed time period account for a large share of what they spend their money on rather than going out and buying boats and dinners at fancy restaurants. Taking a step back again, economists like Raj Chetty and Adam Seidel have thought in the past about these sorts of consumption commitments and how they might influence an investor's portfolio choice.

The point I want to emphasize here is that these consumption commitments are very relevant for households at the top of the income distribution, not just lower-income households compared to what people may have thought previously. And I think this ultimately helps to explain why these households have to dip into their financial assets so much when their income from their job or private business dries up.

Ben Felix: So this really relates a household's fixed expenses back to their ability to take risk in the stock market.

Patrick Adams: It's almost like a form of leverage you can think of. A lot of these commitments don't show up explicitly as debt on the balance sheet, but if you have to pay, say, insurance premiums or childcare over the course of a year, and it's maybe difficult to cut back on those in a financial emergency, that's almost another form of leverage that these households are taking on, even if it is an explicit debt commitment.

Cameron Passmore: What types of households seem to be particularly vulnerable or resilient to the selling your portfolio in bad times effect that you documented?

Patrick Adams: There's ultimately three main things that broadly determine how vulnerable investors are to this risk. The income risk that they face, the level of their liquid wealth, and their ability to cut back on that spending quickly if needed. First, for your income risk, if you're in a job or profession where you're more likely to experience a large drop in your income when the economy or the stock market are doing poorly, you're more likely to end up having to liquidate your portfolio in bad times.

Now, this risk is particularly high for private business owners. For W-2 employees, it's going to be very high for workers that are in cyclical industries like finance, tech, or consulting, and within a given industry or firm for individuals higher up in the earnings distribution that may have more volatile bonus pay or stock-based compensation that tends to fall at these times. But at the same time, there are many high-income jobs or professions that are not very exposed to the business cycle.

Perhaps the best example of this is tenured professors at business schools. And many of the ones that I've talked with over the past few months tend to be quite aggressive in their stock market investments. The second factor is going to be the amount of liquid assets that you have relative to your typical income and spending.

And that's going to determine the share of those assets that you'd have to exhaust if you were to draw down on them to cover your typical expenditures for some period of time. If you don't have a lot of liquid assets, then you're much more likely to deplete almost all of them in that scenario. And you don't benefit from the fact that stock returns are high going forward if you don't have much left in the stock market in your personal account.

So in contrast, the households in my data that have a lot of liquid assets do tend to significantly draw down on them after a bad income shock, but still have plenty left over after doing so. Finally, again, the third factor is your ability to cut that spending quickly if needed. How much of your annual budget goes to these sticky expenditures like rent, mortgage, utilities, child care, health care, and other things that would be difficult to cut back on without having to make large and potentially disruptive adjustments to your lifestyle?

So here, I think there's really two types of households that are particularly at risk in these cases. Homeowners that have a large mortgage and working parents that have multiple children, all of which tends to come with a bunch of expenditures that may be difficult to cut back on in a time of need. And in contrast, young households with more financial flexibility, FIRE, financial independents and early retirement investors may be in a much better position to adjust to these shocks if they occur.

Ben Felix: Man, so it sounds like a big thing is not letting your fixed expenses absorb variable portions of your income. If you get a lot of your income from stock-based compensation or bonuses or whatever, letting your regular fixed lifestyle expenses creep up to that level of income sounds like one of the risks that you're finding here.

Patrick Adams: Absolutely. I mean, it ties in with, I think, a broader societal discussion about lifestyle creep, keeping up with the Joneses. The people who step a bit too far in this direction, who are working in some of these risky industries and maybe financing a nice car lease out of their bonus pay in a given year, they're going to be more at risk of having to make some painful financial adjustments when things don't look quite as good in their job or their private business.

Ben Felix: Yeah, which could make that luxury purchase way more expensive if they have to sell their stock portfolio after it's dropped to keep making the payments or whatever it is.

Patrick Adams: Exactly. And of course, that's not going to be on the sticker price of the car that they sell to you.

Ben Felix: How do your empirical findings compare to the predictions of common savings and consumption models?

Patrick Adams: So the financial adjustments that I see households making in the data after a shock to their income differs quite a bit from what typical models of consumption and savings decisions would predict. And this ultimately makes a big difference in the optimal stock portfolio shares implied by the models. To take a step back here, what do these typical models actually predict about how households would adjust to this kind of shock to their wage or private business income?

If that shock is expected to be pretty persistent rather than temporary, as is the case for a lot of the large income shocks that these high-income investors face in the data, and if they can easily cut back on their spending at those times, then those benchmark models that we work with predict that this would actually be the main margin they would adjust on. That's to say, if a person loses their job and switches into a different one that pays $100,000 less, these models essentially predict that they would cut their spending by about $80,000 to $100,000 immediately in that year, and then in every year going forward. And this is essentially what Milton Friedman's permanent income hypothesis model predicts for how households should adjust their consumption following a permanent shock to their income.

Thinking intuitively for a second, that's a pretty big adjustment to make in your annual spending within a window of one or two years. I think a lot of working age households would struggle to cut that much spending over such a short horizon without making some major adjustments to their lifestyle, such as moving to a different house or apartment or finding some alternative childcare arrangements. And when we ultimately look in surveys to see how these households say they would adjust in difficult financial situations like this, they don't plan to cut back on their spending or borrow money through a credit card or home equity line of credit.

They plan to tap into their liquid assets at that point. And this is consistent with how we see households actually adjusting in the data. When they face these large and persistent shocks to their wage or business income, they're primarily adjusting by dipping into their liquid savings to smooth out that shock rather than cutting back sharply on their spending.

How does this ultimately matter for the models of portfolio choice we've worked with? Well, most of the models in that literature have this traditional model of consumption and savings behavior at their core. And what this means is that they ultimately understate the liquidity needs of these households.

That is, if the stock market crashes today and someone loses their job, these models essentially predict that they should avoid dipping into their liquid stocks, their bonds, their savings deposits, and instead they should cut their spending aggressively, leaving their financial assets mostly untouched. In practice, we think this is going to be difficult for many of them to do. The challenge is to then rethink their consumption, savings, and portfolio choice decisions in a model that more realistically captures their liquidity needs.

Ben Felix: We do have questions about the model, but I just want to make sure it's clear for listeners real quick. You observe in the data that when people have an income shock, when their income falls, that they're pulling out of their financial assets, and then you cross-reference that empirical observation with survey data where people are telling you or telling the survey that that is exactly what they would do in those cases.

Patrick Adams: Exactly. And again, that information is coming from this great survey, the Survey of Consumer Finances run by the Federal Reserve, where again, they go in and ask households, if you were to face one of these hypothetical financial emergencies, how would you adjust through your spending, through your drawing down in your savings, through borrowing? This is, I think, bringing in the rich set of data that we have to understand what we see in other data sets that don't have as much granularity, and then ultimately try and map that back to the models we work with and bring them closer into line with reality.

Ben Felix: Super interesting. So it sounds like we need a better model.

Patrick Adams: We do, yeah. And that's a big task of the second part of the paper.

Cameron Passmore: How did you set up your life cycle portfolio choice model to study optimal stock allocations in light of your empirical findings?

Patrick Adams: I work in the second part of the paper with one of these life cycle portfolio choice models that follows households from age 25, when they enter the labor market, through age 60, when they retire, and then through their retirement period. And at each point in the life cycle, they're going to decide how much to spend and consume, how much to save, and how much of those savings to allocate to risky stocks versus safe, risk-free assets. There are really three key features of the model, each of which has been studied in several previous papers in the literature, but not really combined in the unified way that matters a lot in the model I work with.

So the first is that expected stock returns and investment opportunities vary over time, just like in Robert Merton, a guest of the podcast, Intertemporal Capital Asset Pricing Model. That is, the model can capture the salient pattern in the data that stocks occasionally suffer from these large price crashes that are followed by swift recoveries and high returns for investors who stay in the market or even buy the dip. And this is what makes stocks look safe for long-term investors, despite their volatile short-term returns, a point that's, of course, emphasized in Jeremy Siegel's book, but also in more portfolio choice models in the literature studied by people like John Campbell, Luis Viceira, Jessica Wachter, Nicholas Barberis, and many others.

That's the first feature of the model. The second is labor income risk and its relationship with stock returns. So shocks to households' earnings are going to be drawn from a fat-tailed distribution so that most households in a given year experience relatively little change in their long-term earnings prospects, while a small subset of these unlucky investors experience really large negative shocks capturing events like job loss or transition.

In the model, a large crash in the stock market is going to directly shift the left tail of that earnings growth distribution, which is going to lead to only a modest decline in average or median earnings, but a really substantial change in the probability of these disastrous labor market outcomes. And all the parameters there are going to be disciplined by measures of labor income risk computed from this administrative income data and its correlation with stock returns over time. And modeling labor income in this particular way is ultimately going to make human capital look much more like a risky stock than a safe bond.

The third key feature is frictions in adjusting household consumption. I'm going to assume they have to pay an extra cost to reduce their spending below its level from the previous year. And this cost is much higher for very large cuts in their spending.

This is ultimately going to force them to actually draw down on their savings following these large shocks to their income instead of simply cutting their spending aggressively and leaving their financial assets untouched. And the magnitude of those costs is ultimately going to be disciplined by that size of that savings response to these income shocks that I estimate in the tax data. And these costs are going to be crucial for realistically capturing those households' liquidity needs during a stock market crash.

Ben Felix: Everyone is on the edge of their seat, waiting for the answer to this question. What does the model say about the optimal equity share for a working age household?

Patrick Adams: So the model says that the optimal share of liquid wealth invested in stocks is relatively low for the average working age household. Ranging from 10 to 40 percent, depending on factors like their age, risk aversion, and magnitude of these frictions in adjusting their spending. This optimal stock share also increases strongly with the household's age and with the amount of liquid wealth that it owns relative to its labor income.

Now, these stock shares of liquid wealth and their patterns over the life cycle fall in the ballpark range of values that we see most of these households investing in the data. However, it's a lot lower than the optimal shares implied by many life cycle portfolio choice models in the literature, particularly for those young households. What is it then that makes stocks so risky for these young investors in the model, despite the fact that returns are relatively safe over their long potential investment horizon?

And it's ultimately these liquidity needs they face during these stock market crashes. So in the model and in the data, many of them experience these large declines in their income during these crashes. And if it's difficult for them to cut their spending in response, they're going to have to draw down to the liquid assets at that time.

And if you have those liquid assets fully invested in stocks, then they're going to have to liquidate their holdings exactly when prices are low, but expected to bounce back in the near future. They won't actually benefit from that rebound if they have little financial wealth left after smoothing out from this shock. So as a result, the optimal stock share of liquid wealth is quite low in the model, particularly for these young households without much liquid financial wealth.

It's that combination of their risky income and inflexible spending that forces them to draw down on their assets in bad times and make stocks ultimately look less attractive.

Ben Felix: Let me give you a very basic interpretation of your findings, and you can tell me if it's right. It sounds like you've basically found in this research that people should have an emergency fund that's going to be liquid wealth, and it's going to be decreasing as their overall liquid wealth increases to like a fixed period of expenses in an emergency fund. You should have whatever, 12 months of expenses in an emergency fund, which would line up with your finding that as liquid wealth increases, your share of equities can increase, but as you've got low liquid wealth, the share of equities is really low, the optimal share of equities.

So it's really, you can invest in stocks with your liquid wealth, but you should probably have an emergency fund.

Patrick Adams: Absolutely. And personally, when I think about how this evidence changes my own investing, that's exactly the way I frame it, or when talking with some of my friends working in some of these risky industries, like finance or portfolio management, how many months of your difficult to adjust expenditures do you have saved up in these safe liquid assets, rather than some of these riskier assets that may decline a lot in value exactly when you need to draw down on them.

You can exactly think of this as a fixed emergency fund covering say, 12 months of your difficult to adjust expenditures. That's going to represent a smaller share of your overall liquid wealth as you start to accumulate more of it and can then think about investing that more aggressively in some of these riskier assets, like stocks.

Cameron Passmore: How do high consumption adjustment costs affect optimal savings behavior?

Patrick Adams: So in the model, I think we've sort of talked about what we think is going on in the data and in reality, those high consumption adjustment costs are going to give households a very strong incentive to save more, particularly in these safe risk-free assets.

The reason is that they're going to anticipate having to draw down on those savings if they face a large income loss and they can't cut their spending easily in response. In the current calibration of the model, that I show in the paper, this actually leads households to accumulate a bit more liquid wealth than what we see in the data. This is a paper that I'm always working to improve.

It's partly, I think, because of strong assumptions I make about the illiquidity of their housing and their retirement accounts. I'm currently working with some high-powered NVIDIA GPUs to enrich the model along these dimensions. Despite that high level of liquid wealth that they accumulate, the optimal share of it that they invest in stocks is still quite low.

Ben Felix: If you have high fixed expenses, you need a bigger emergency fund, basically.

Patrick Adams: Precisely. On the other hand, if you can easily cut back on that spending in bad times, you can feel free to invest a lot more of those liquid assets in some of these riskier forms, provided that you have the market discipline to avoid selling them if there's a big crash.

Ben Felix: So interesting. I thought about it as like an asset allocation paper, which it still is, but it's really about emergency funds.

Patrick Adams: Exactly. A form of asset allocation. You can think of this almost as really taking like a risk management or cash flow management sort of view of the household balance sheet and the different sources of risk that they face.

One way I try to frame it is that they've got sources of funds that are pretty volatile and uncertain, especially for these high-income wealthy households. And they've got uses of funds that are pretty sticky, even beyond their actual fixed debt commitments and payments that they have to make. That's a very useful way to think about household risk management, which is ultimately an asset allocation problem between these safe and risky or liquid and illiquid assets.

Ben Felix: Super interesting. You've mentioned this a couple of times, but I'm still going to ask it. What does the model say about the difference in optimal equity shares between a working age household and a retired household?

Patrick Adams: The model is ultimately going to say that optimal stock shares that they should invest in their liquid wealth should actually be lower for most working age households compared to most retired households, which I think would be a bit of a puzzling result from a lot of the portfolio choice models we've seen in the prior literature. And for recent retirees, that optimal stock share in the model is generally going to be above 50%, with the precise value, depending on some factors like the risk aversion and the remaining investment horizon. That value, I think, should be interpreted a little bit carefully in my current set of results because of exactly how I model the income flow and asset allocation in their retirement accounts, or don't model it, actually.

The broad point is that within the model, stocks ultimately look much less risky for retirees than for these young working age investors.

Cameron Passmore: Wow. What explains this counterintuitive difference?

Patrick Adams: So I think this result can really seem counterintuitive from the work that we've seen previously, given that we're used to thinking of stocks as being particularly attractive for young investors who have long potential investment horizons and safe bond-like human capital. There's really two major places where this intuition breaks down in my model. First, when we look at the administrative data, investors' labor income actually looks quite risky.

And the model captures that observed relationship between stock returns and these negative tail outcomes in the labor market and ultimately makes households' human capital look much more like a risky stock than a safe bond. If you think of retirees, on the other hand, they have much more stable income sources in the form of social security and pensions. Second, I think the other important factor is that while households have long potential investment horizons, spanning all the way until they retire and beyond that, their effective investment horizon may end up being quite a bit shorter if they experience a shock that leads them to draw down on their assets before then.

Early on in their career, most of their usual spending is financed exactly by this risky labor income, as we discussed previously. If it's difficult for them to cut back on that spending when that income falls, they're going to have to draw down on their assets, particularly at times when the stock market is doing poorly. And as a result, their effective investment horizon shrinks and becomes much shorter at exactly the most inopportune times as an investor.

And if you're a retiree instead who consumes only a small fraction of your financial wealth every year, those same size withdrawals wouldn't really jeopardize your financial situation and put you in a scenario where you would exhaust most of that liquid wealth. This is what's ultimately going to allow these older investors to ride out these stock market crashes more effectively. Ultimately, I don't believe we should think of most young investors, particularly at the top of the income distribution, as having the safe bond-like human capital and long effective investment horizons.

You should think of them as having risky stock-like human capital and potential liquidity needs that may lead them to draw down on their assets well before they retire.

Ben Felix: You kind of did this early on, but can you walk us through a hypothetical scenario that illustrates why the optimal equity share is so low for the working age households?

Patrick Adams: I think it's helpful here to step into the shoes, say, of a hypothetical household around the global financial crisis in 2008. Based on some of the statistics I talked about previously, I'll assume they start the year in 2008 with around $300,000 in annual income in their jobs and $200,000 in liquid financial assets. Suppose October 2008 comes and at the height of the financial crisis, one of the two people in the household loses their job and their total income falls by $150,000.

Based on my estimates from the tax data, I'm going to assume that they draw down two-thirds of that amount from their liquid assets over the following months. Two-thirds of $150,000, that's $100,000. If we suppose that their liquid assets start out fully invested in stocks at the start of 2008, then by the time they actually start drawing down on their stock holdings in October, they will have declined by almost a third in value.

And at that point, that $100,000 outflow represents a much larger share of the remaining liquid wealth than it did just a few months prior. And if we follow them through to the end of 2010, when a buy and hold investor would have fully recovered their initial wealth, our hypothetical household has only about $50,000 left in that case. In addition to the $100,000 that they would actually withdraw from their account, there's effectively an extra $50,000 cost they pay from the high returns they forego after having to liquidate their stock holdings exactly when prices are low.

If they were to invest only half of those funds in stocks over the same time period, that extra loss would be only half as large, amounting to only about $25,000 in that case. And if they keep them fully invested in, say, safe bank deposits, then they're only out that $100,000 outflow and they could potentially even buy stocks when prices are low. The key idea here is that even if stock prices recover from some of these big crashes, you don't personally benefit from that as an investor if you end up having to exhaust most of your liquid financial wealth during the crash.

And that's what ultimately makes it risky to invest a large share of that wealth in stocks in my model.

Cameron Passmore: So let's put a finer point on this. Which parameters in your model have the biggest impact on the headline result of the lower optimal equity share for the working age households?

Patrick Adams: The most important parameters that matter for those working age households portfolio decisions are going to be ultimately the relationship between stock returns and their labor income risk and how costly it is for investors to cut their spending. First on the labor income risk side, in my baseline calibration, I assume that a large crash in the stock market significantly increases the probability that a working age investor experiences a large, persistent negative income shock. If we were to weaken that channel by making labor income shocks either independent from stock returns or even normally distributed without the fat tails that we see in the data, then the optimal equity share is much higher in those cases because human capital ultimately looks more like a safe bond under those assumptions than a risky stock.

For a subset of investors who are employed in professions that are relatively safe or insulated from the business cycle, this may be the appropriate case for them to consider. But for the typical high income working age investor, they do face significant labor income risk and that should play a big role in determining their portfolio allocation decisions.

Ben Felix: It's cool to hear you go through the parameters. I think that's super helpful for listeners.

Patrick Adams: Exactly. Of course, the other one that's going to matter here is those consumption adjustment costs. It just determines how much you actually have to draw down on those liquid assets when you face one of these big income shocks.

If it's easy to cut your spending, you can leave those assets untouched. You can weather the storm, ride out these price crashes and act like that ideal Jeremy Siegel long-term investor who doesn't have to sell their stock holdings at those times.

Ben Felix: We've had a couple of guests, James Choi most recently and Scott Cederburg a while ago now, whose life cycle portfolio choice research generally suggests 100% equity portfolios for working age households. Their papers were really comprehensive and they thought about modeling labor income in different ways and all that kind of stuff. What would be the key differences driving the differing advice between your model and their models?

Patrick Adams: Both of them are obviously fantastic researchers and those are great papers that I personally learned a lot from reading. The primary difference at the end of the day between those models and mine is how we capture the relationship between stock returns and labor income risk and whether this makes human capital look more like a risky stock or a safe bond. In my model, again, a large crash in the stock market has a very direct effect on the probability that a given household experiences a really large decline in their earnings, consistent with what we observe in administrative income data.

Here I should note I'm building off of similar models studied by one of my advisors, Lawrence Schmidt at MIT and Sylvain Catherine at Wharton, who showed that modeling labor income in this way makes human capital, again, look much more like a risky stock and can even help to explain the equity premium puzzle, that is why stocks are so risky and earn such high average returns in the first place. Importantly, labor income still looks very risky in these models, even though the average household's earnings don't fall dramatically when the stock market crashes. Most households experience a small change in their income, but an unlucky subset of them lose a large share of their initial earnings.

I should also note international stocks don't really look like a great hedge against this form of tail risk in the labor market because they also tend to crash in years when US stocks do, as we've seen over the last 25 years. And finally, I just want to note, I think another important difference between my model and many previous ones studying the literature are these consumption adjustment costs, because these models have been used in past work, often assume that households can pretty easily make these large immediate cuts to their spending if they have to, and it turns out to be the main way that they adjust following these persistent shocks to their income. It's at odds with what I find in the tax data, and the consumption adjustment costs they put in the model help to generate a much more realistic savings response and liquidity needs that make stocks look very risky for these working age investors.

Cameron Passmore: So I'm sure this next question is shared by many listeners. Is there a set of parameter specifications where your model does find an optimal 100% equity share for a working age household?

Patrick Adams: Definitely. And we can push on five different factors in the model that are going to nudge households towards an optimal 100% equity share, even when they are still saving for retirement and face this income risk in the labor market. Those factors are essentially if they have low risk aversion, low labor income risk, low consumption adjustment costs, high liquid wealth relative to their income, because the equity premium is varying a lot over time in my model.

If it's a time period in that given year where the equity premium is currently very high, say 10% or even 15% instead of the 5% baseline on normal times. All of these factors are either going to decrease the risk that the household will have to liquidate most of its assets during a stock market crash, or in the case of risk aversion or high equity premium makes them more willing to bear that risk in pursuit of those high average returns. For the typical high income household that does have risky labor income and moderate financial wealth and more conventional risk preferences, the optimal stock share is going to be much lower than 100% consistent with what we observe in the data.

I would encourage listeners to maybe figure out which of those five buckets they fall in if they're really tempted to select a 100% equity share in their liquid portfolio.

Ben Felix: People love the 100% equity advice when a paper comes out that supports it. I don't know if it's because it's just so straightforward or people just like stocks, I guess. Maybe that's because returns have been so good for a while.

Maybe if we have a prolonged bear market, people will change their minds.

Patrick Adams: Exactly. Well, let's hope not, at least for my sake.

Ben Felix: Yeah. What kind of comments are you getting when you present this paper? You're kind of going against the grain of a lot of the past research in this space.

What are you hearing from other researchers when you present?

Patrick Adams: Everyone I've talked to, even the people working on similar topics who have conclusions that differ a bit from mine, they've all been very receptive, very thoughtful and scholarly in terms of their engagement with the work. And so I'm really delighted by how great the people I've talked with have been, even when I say things that may go against some of the things they claim. But a lot of the people I present this paper to are academics, in particular early career ones with a mortgage and young children.

They find this idea of consumption commitments very personally relatable because they ultimately spend a lot on housing and childcare in many of these high cost of living areas around the US. At the same time, many of those people are also tenured professors with stable, predictable income who have that bond-like human capital, so they don't personally find that part of the paper very relatable. But many of them do have friends, family, or even former PhD students who work in risky industries like finance or tech.

And some of those people did lose or switch their jobs during these large stock market crashes over the last 25 years. And some of those people did end up having to sell their stocks at the bottom of the market. So these anecdotes from other people's past experiences do line up with what I document in the paper and I think helps to convince them of my results.

Cameron Passmore: So how has your work on this affected your own decisions around your own asset allocation?

Patrick Adams: There's one very practical way that's been related to my own job search over the last 12 months, which is that we know that from prior research using this administrative data, that people searching for a new job are particularly vulnerable to the state of the business cycle because these job openings tend to be very volatile compared to, say, layoffs for existing hires. Because of that, I personally held off on moving some of my own savings into stocks over the past year while I was waiting for that particular uncertainty to resolve. Looking forward, I now think a lot more, as I mentioned previously, about how much of a safe liquid asset buffer I should have given the risks I face in my income and some of those spending commitments that are starting to add up to a larger share of my own annual budget.

And I should say, I'm definitely more hesitant now to sign up for some of these large expenditure commitments, like a big apartment lease or a mortgage, than I was before I started working on this paper.

Ben Felix: You mentioned listeners wanting to consider which of the five buckets that you talked about a minute ago, which one they fall in. What would you say to the working age listeners who do currently have 100% stock portfolios?

Patrick Adams: The usual caveat first applies here, which is that I am not a financial advisor and this is not investment advice. That being said, I would first remind them that these stock portfolio shares that we're talking about are measured as a fraction of their total liquid financial assets, not just what's in their brokerage account. Almost all of them surely have some bank deposits or other safe liquid assets.

And I think the key question is whether those assets are enough to get them through some potentially difficult financial situations. I think it's useful here to take a risk management perspective similar to a corporation thinking about its own cash flow management. Think about your sources of funds that you have.

In particular, what risks do you face in your job, your labor income, maybe in a private business you own? And are these risks likely to be correlated with the overall stock market and the real economy? Or are they mostly independent of that?

Think about your uses of funds that you have. What expenditures do you have that would be difficult to cut back on within the span of a year or two? And how many months of those expenditures could you fund with just your existing safe liquid asset holdings before you would have to sell stocks or withdraw from your retirement accounts?

I don't focus as much on asset allocation within retirement accounts because of some limitations on what we can see in the tax data. However, these investors' liquidity needs actually may flip some of the conventional way that we think about tax optimization for these high income working age investors. Many of them are told to think about holding their fixed income assets like bonds in their retirement accounts given the high ordinary income tax rates that they face on their interest income.

If you have to draw down your financial assets in a time of need, it may make sense to hold more of those safe fixed income assets outside of retirement accounts as a first or second buffer against a large income shock. Any stocks that you hope to avoid selling at those times, you could instead hold in retirement accounts even if that's going to give up some of the preferential capital gains tax treatment that these assets enjoy when they're in your taxable brokerage accounts. I think this is obviously a really important set of issues that are going to be a main focus of some of my work going forward.

Ben Felix: Oh man, I was expecting your asset allocation commentary. I was not expecting you to also flip asset location on its head. That was awesome.

Patrick Adams: Think carefully about that given the liquidity needs that these investors face.

Cameron Passmore: Final question, Patrick. How do you define success in your life?

Patrick Adams: This is a tough one because I'm just starting my academic career. So I think I'm probably the least accomplished person to appear on your podcast in its history. So this is all mostly based on my aspirations and not my actual achievements so far.

I hope that this research and other projects that I do can provide individuals, firms, and policymakers with some useful information that they can take to go and make better financial decisions. I think a lot of these high income households in particular work in important high growth industries or maybe entrepreneurs creating jobs through their private business. So I hope that this evidence can potentially help them to better prepare and respond to the risks that they face in that work.

On the other hand, in my future teaching, I hope to similarly provide the students I work with with the tools to make sound financial decisions in their personal lives or their work in the private sector or maybe even in public service. As many people on the podcast say, I think the richest parts of my life are definitely outside of work. There, I'm very fortunate to have a wonderful family and a wife who's been here with me on this academic journey for over a decade since we first met in college.

And that's obviously the single biggest part of how I define success in my life.

Cameron Passmore: Great answer.

Ben Felix: Thanks a lot, Patrick. This was a great conversation. We really appreciate you coming on the podcast.

Patrick Adams: Thank you, Ben. Thank you, Cameron. It's been great to finally talk with both of you and keep up the great work, inspiring lots of PhD students to get the ideas for their dissertations with this excellent podcast.

Ben Felix: Thank you. Will do.

Cameron Passmore: Great to meet you.

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