Data Update 7 for 2026: Debt and Taxes

   In my fifth data update, I examined hurdle rates in 2025, and in my sixth data update, I looked at the profitability and return metrics for firms. Both hurdle rates and profitability metricsmcan be affected by how much debt companies choose to have in their financing structure, and it enters explicitly into my cost of capital calculations, both through the costs of equity/debt and the mix of the two, and into my accounting return calculations, for net margin and return on equity. In this session, I start with an examination of the trade off that all businesses face when it comes to choosing between debt and equity to fund their operations, and then look the debt choices that companies made in 2025. As with every other one of my data updates this year, AI enters this conversation not only because of the huge investments that are being made into AI architecture, but also because a non-trivial portion of this investment is coming from debt, with private credit as a key contributor.

Debt versus Equity: Choices and Tradeoff

    The discussion of the tradeoffs that businesses face on whether to borrow money (debt) or use owner's funds (equity) has to start with a clear distinction between what it is that sets them apart. While that distinction may seem trivial, since accountants do break financing down into debt and equity on accounting balance sheets, accountants are not always consistent in their categorization, and I think that understanding what sets debt apart from equity can help catch these inconsistencies. There are three dimensions where debt and equity deviate:

1. Nature of claim: Debt gives its holders a contractual claim on the cash flows, insofar as the terms of interest and principal payments are laid down contractually at the time of the borrowing. Note that these contractual claims cover both fixed rate debt, where the interest payments are fixed over the lifetime of the debt, and floating rate debt, where the interest payments will change over time, but in ways that are specified by the bond/loan agreements. Equity gives its holders a residual claim, i.e,, a claim on cash flows, if any, that are left over after other claim holders have been paid.
2. Priority of claim: This follows from the first distinction, but debt holders get first claim on the cashflows, when the firm is in operation, and on liquidation proceeds, if the firm ever goes bankrupt. It is this priority of claims that should generally make debt safer than equity in almost every enterprise that employs both.
3. Legal consequences: A company that fails to pay dividends to its equity investors, no matter how deeply set their expectations of receiving these dividends, may see its stock price drop, but it cannot be held legally accountable for the failure. A company that fails to make its contractual obligations on debt can not only be sued, but can be pushed into bankruptcy, effectively ending its business life.

There are three other distinctions, which do not always hold, but are usually true:

1. Tax Treatment: In much of the world, the tax code is tilted in favor of debt, with interest payments being tax deductible and cash flows to equity (dividends or buybacks) coming out of after-tax cash flows, but there are three caveats. The first is that the tax savings from debt kick in only when a company is generating a taxable profit, though laws on tax loss carry-forwards can allow even money-losing firms to get tax benefits, albeit with a delay. The second is that there are parts of the world, such as the Middle East, where the tax code explicitly bars interest tax deductions, though companies find work arounds sometimes to get the benefits. The third is that there are a few countries that try to even the playing field by either giving a tax deduction to companies for some payments to equity investors (interest on capital as a tax deduction in Brazil) or to investors directly by allowing them credits for corporate taxes paid, when they receive dividends.
2. Role in management: In most businesses, equity investors are given supremacy when it comes to managing the company, exercising that power through either direct ownership or corporate governance mechanisms (such as boards of directors). Again, there are exceptions, as is the case where lenders are given seats on boards of directors or veto power over major operating decisions, but these exceptions are usually triggered when companies violate covenants in loan agreements. 
3. Maturity: Debt usually has a finite maturity, though as we saw with the Google hundred-year bond issuance just a few weeks ago, that maturity may be well beyond the lifetime of the buyers of the bond. Equity, in contrast, is, at least on paper, an instrument with no finite due date, and may have cash flows that last into perpetuity. 

The figure below captures the differences between debt and equity in the context of a financial balance sheet:

With these distinctions in place, and given that businesses have a choice of using either debt or equity to fund their operations, let us look at the trade off, starting with what the fictional (but often used) reasons for using one source of funding over the other: 

One of the most common (bad) reasons that I hear business owners and CFOs of even large companies give for borrowing money is that debt is cheaper than equity. On the face of it, that is of course true, but it is an illusion, at least without the tax benefits kicking in. If the debt is fairly priced, i.e., you are being charged an interest rate that reflects your default risk, borrowing money will make your equity more risky and leave your cost of capital unchanged (if you have no default risk) or raise it (if you have default risk). Intuitively, your cost of capital is designed to capture the risk in your operations, and playing games on the financing side cannot change your operational risk. Among risk-takers, a common reason for using debt is that it will increase your return on equity, and while that again is technically true, it will also raise your cost of equity and magnify the impact of both your successes and your failures. Thus, if you want to borrow money to magnify the payoff to you, as an equity investor, from a successful trade or investment, you should do so, but dispense with the illusion that this is a free lunch.  Those who avoid debt have their own share of illusions, starting with the argument that the interest payments on borrowed money will lower net income. That is true, but since you have less equity invested, you may still come out as a beneficiary. They also argue that debt will increase default risk, and lower their bond ratings, but of which are likely to happen, but the objective in business is not to maximize bond ratings, but to increase value; a BBB-rated firm that borrows money and gets tax advantages can be worth more than the same firm with a AAA rating and no debt.

    So what are the real trade offs? The first and biggest benefit of debt is its tax treatment, with the tax benefits adding to firm value. Note, and this is said with no moral or ethical judgment attached to it, that this increase in value is coming from taxpayers and not from your operations becoming more valuable. A secondary benefit may come from imposing discipline on managers in public companies, with the need to make interest payments operating as a restraint on a headlong rush into poorly performing investments. On the other side of the ledger, the biggest concern you should have when you borrow money is that it increases the risk of bankruptcy, which if it happens, truncates business life, and even it does not, concerns about it happening can alter how customers, suppliers and investors interact with a business. The other cost that you face when you borrow money is that equity investors and lenders have very different interests, with equity seeking upside and lenders worrying about downside, and the costs of that conflict of interests plays out in covenants and restrictions on operating activity. The figure below summarizes these real trade offs.

The tax benefits versus bankruptcy cost trade off on debt is a simple and very powerful explainer of how much companies should borrow, but in the real world, there are companies that sometimes override the tradeoff and choose to borrow far more or far less than you would expect them to, and they are not necessarily being irrational. Here are three reasons why companies may choose a sub-optimal financing mix:

1. Shields against bankruptcy: If the biggest restraint on borrowing more is the fear of default, anything that reduces or eliminates that fear will cause companies to borrow more money. That default protection can come from governments acting as implicit or explicit guarantors of corporate debt, as was the case with Korean companies in the 1990s, or from seeing other companies in trouble being bailed out by the government, because they were too big to fail. 
2. Control versu Value: While businesses have the option of using either equity or debt to fund operations, raising fresh equity usually requires giving up ownership of the business to venture capitalists (at a private business) or to other public market investors (for public companies). For founders and family groups that value control over almost everything else, this can result in firms borrowing money, even though the fundamentals do not support the action. This can explain why Middle Eastern firms, many of which get no tax benefit from debt, may choose to borrow money to fund operations, usually with higher costs of capital, as well as the existence of venture debt, an almost absurd notion from a corporate finance standpoint, since you are lending to start-ups and young money-losing companies with unformed business models and 
3. Subsidized debt: If a business has access to debt with below-market interest rates, given default risk, it may make sense to borrow money at these subsidized rates. These debt subsidies are often granted to companies that are seen as delivering on a social purpose (green energy in the last decade) or a political/security interests (defense and infrastructure businesses), and you should therefore not be surprised if they all carry too much debt.

On the other side of the ledger, there are three reasons why companies may borrow less than they should:

1. Restrictive covenants: In markets where debt comes primarily from bankers, it is possible that the covenants that come with this debt are so onerous that businesses will choose to leave tax benefits on the table in order to preserve operating flexibility; this may explain why technology companies, even those with large and stable cash flows, often choose not to borrow money or if they have to, go directly to bond markets.
2. Overpriced equity: Financial markets make mistakes, and sometimes those mistakes may work in your favor as a company with your stock price soaring well above what you think is justifiable, given your fundamentals. In that case, you may choose to use equity, even if you have debt capacity, using your own overpriced shares as currency in funding acquisitions.
3. Regulatory constraints: In some countries and/or sectors, there may be regulatory restrictions on borrowing that cap how much debt you can take on, even though you have the capacity to carry more in debt. Those restrictions can take the form of limits on book debt ratios or on how much interest expense is tax deductible, as a function of revenues or EBITDA.

The picture below captures these frictional considerations:

In sum, the choices between debt and equity play out differently at different companies, depending not only on the characteristics of the company (tax rate, default risk etc.) but also on the management team making that decision on whether to borrow money. If you are an optimizer, by nature, you may this discussion too diffuse, since it points you in a direction (more or less debt) and not to a specific debt mix, but that is easily remedied, if you use the cost of capital as your optimizing tool to find the mix of debt and equity that minimizes your cost of capital. 

Download optimizer spreadsheet

Rather than try your patience by belaboring that process, I can point you in the direction of how that is done in my corporate finance class sessions, and with this tool.

Debt and Equity in 2025

    With this tradeoff on debt and equity in mind, let's turn to the data, and in particular, I plan to focus on the choices that companies made globally, on the financing question, in 2025. I will start by looking at the two forces that should have the greatest relevance in this decision, the tax benefits of debt and the default risk, and then look at the mixes of financing across sectors, industries and regions.

The Tax Landscape

    Any discussion of taxes has to start with reality checks. The first is that governments need tax revenues, to fund their spending, and corporations and businesses are a target, partly because they affect taxpayers (and voters) indirectly, rather than directly (as is the case with income and sales taxes). The second is that businesses do not like to pay taxes, and try to minimize the taxes they pay, mostly through legal means, with accountants, transfer pricing specialists and tax lawyers abetting, though they sometimes step over the line into tax evasion. When measuring the tax burden that businesses face, we have to distinguish between three measures of tax rates:

1. Marginal Tax Rates: The marginal tax rate reflects the tax rate you face on the last dollar of your taxable income, and thus comes from the statutory tax code of the domicile that the business operates in. While there are a few companies that try to report these tax rates, you are more likely to uncover them by going into the tax code. Fortunately, the leading accounting firms keep updated estimates of these marginal tax rates in the public domain, as do some tax watchdogs, and I used  The Tax Foundation for this year's updates across countries, and the numbers are in the picture below: 

   

   Download corporate tax rates, by country

   While your eye may be drawn to differences in corporate tax rates, across countries, these differences have narrowed, as the countries with the largest economies (and taxable business) are converging around a marginal tax rate of 25%. There are regional differences, with Latin America and Africa home to some of the highest corporate tax rates, and Eastern Europe and Russia home to some of the lowest. Clearly, there are exceptions within each region, with Ireland the leading outlier in Europe, with a marginal tax rate of 12%, and Paraguay in Latin America, with a marginal tax rate of 10%.
2. Effective tax rates: The effective tax rate is an accounting measure, reflecting the taxes paid and taxable  income line items in the income statement, which follows accrual accounting principles. The effective and marginal tax rates can deviate for many reason, including corporate income earned in other countries, tax deferral strategies and even differences between tax and reporting books. I estimated effective tax rates for the companies in my database, and report the averages, by sub-region of the world, in the table below:

   

   Corporate Marginal and Effective Tax Rates, by Country

   In the aggregate, the effective tax rates were lower than the marginal tax rates in about 60% of the companies in my sample, and the difference is a rough proxy for the effectiveness of a tax system, with marginal tax rates running close to or behind effective tax rates in more effective tax regimes. By that measure, India has the least effective tax code among the regions, with an effective tax rate of 22.33% and a marginal tax rate of 30%, followed by the United States and Japan, though the caveat would foreign sales in lower tax locales, in each of these cases. The tax rate statistics, broken down by industry, for global companies, is at this link, if you are interested.
3. Cash tax rates: The cash tax rates also come from accounting statements, with the information in the statement of cash flows used to convert accrual taxes paid to cash taxes paid, and are reflective of what companies actually pay to governments during the course of the year. In 2025, the average cash tax rate across companies with taxable income was 25.86% (21.02%) for global (US) firms, about 1% higher than the effective tax rate in both cases.

For the debt question, it is the marginal tax rate that is most relevant, at least for computing tax benefits, since interest expenses save you taxes at the margin; interest expenses get deducted to get to taxable income, and it is the last dollars of taxable income that thus get protected from paying taxes.

The Default/Distress Landscape

    In a world where companies never default, and you still get tax benefits from borrowing, companies push towards higher and higher debt ratios. In the real world, default acts as a brake on debt, with higher default risk translating into lower debt ratios. While default risk is company-specific, the exposure for default risk, across all companies, will vary over time, largely as a function of how well the economy is doing. The ratings agencies (Moody's, S&P and Fitch) track defaults on a year-to-year basis, and in 2025, they all recorded a drop in default rates across the globe, with US companies driving much of the decline. S&P, in its review of 2025 default and distress, reported that a drop in corporate defaults from 145 in 2024 to 117 to 2025, with the US share of defaults declining from 67% to 62%.  To provide historical context, I looked at corporate default rates on loans (using data from FRED) on a quarterly basis going back to 1986:

Corporate loan default rates

While the low defaults in 2025 were a positive sign for lenders, especially given the economic turmoil created by tariffs and trade wars, there were some worrying trends as well. In May 2025, Moody's estimate of the probability of default at US companies spiked to 9.2%, its highest value since the 2008 crisis. On the bond ratings front, you had more ratings downgrades than upgrades during the year, and almost $60 billion in corporate bonds slipped below investment grade during the  year.  Breaking down all rated companies, by S&P ratings class, and by region, at the end of 2025:

Source: S&P Cap IQ

The US has the highest percentage of listed companies with bond ratings, but even in the US, only 11.43% of companies carry that rating, and that percentage is far lower in other parts of the world. Among rated companies, the US has the highest percentage of below investment-grade ratings, suggesting that in much of the rest of the world, there is a self-selection that occurs, where only companies that believe that they will get high ratings are willing to go through the ratings process. Finally, at the start of 2026, there are only AAA rated-companies left in the world, at least according to S&P, in Johnson & Johnson and Microsoft. Looking at 2025, through the lens of default, the numbers look comforting, at least on the surface, with the number of defaults decreasing, but there was disquiet below, as bond buyers wrestled with the consequences of a changing economic world order, and worries about another crisis lurking in the wings. 

Debt Burden in 2025

    With the background data on tax rates and default risk in place, I will turn to measuring the debt in publicly traded firms, in 2025, and differences in debt burdens across companies, sectors and regions. That mission requires clarity on how to measure debt burdens, and the picture below offers the choices:

Broadly speaking, debt burden metrics can capture debt comfort, i.e., the buffer that businesses have built in to meet their debt obligations and debt level, where you look at debt as a percent of overall funding. In the former group, there are two proxies that you can use to gauge the borrowing buffer  - the interest coverage ratio, measuring how much companies have as operating income, relative to their interest expenses, and the debt as a multiple of EBITDA, capturing how many years it will take a company to pay off its debt, if current EBITDA is sustained. In the latter, I will look at debt as a percent of capital invested, using both accounting measures of capital invested (book value) and market value measures.

1. Debt comfort

    When companies borrow money, the contractual claims from that debt usually take two forms. The first is interest expenses, and ongoing claim that gives you tax benefits but has to be covered out of income generated each year, and the second is repayment of principal, which comes due at maturity. The interest coverage ratio focuses entirely on the former, and interest payments are scaled to how much a company generates in operating income:

Interest coverage ratio = Earnings before interest and taxes/ Interest expenses

This ratio is simple, with high values associated with less default risk and more safety, at least from a lending perspective. It is still powerful, and it remains the financial ratio that best explains differences in bond ratings across non-financial service companies, and I use it to estimate synthetic bond ratings for firms in my corporate financial analysis.

    The problem with interest coverage ratios is that they ignore the other contractual obligation that emerges from debt, which is principal payments due, and the ratio that is most often used to measure that exposure scales total debt at a firm to its earnings before interest, taxes and depreciation:

Debt to EBITDA = Total Debt/ EBITDA

With this ratio, lower values are associated with less default risk and more safety, because a firm, at least if it wanted to, could pay off its debt in fewer years with its operating cash flows.

    In the table below, I look at interest coverage ratios and debt to EBITDA values, by sector, for US and global companies, using the same approach I employed in my last update and reporting a ratio based on aggregated values as well as the distribution of the ratio across companies:

As you can see, with both the US and global groupings, technology companies have the largest safety buffers when it comes to debt, with very high interest coverage ratios and low debt to EBITDA, whereas real estate and utilities have the least buffers, with low interest coverage ratios and high debt to EBITDA. As always, the contrast between the aggregated and median values indicate that larger companies, not surprisingly, operate with stronger buffers than smaller companies in almost every sector grouping. Finally, the debt comfort numbers are not computed for financial service companies, for the same reasons that we did not compute costs of and returns on capital for these firms - debt to a bank is raw material and not capital.

2. Debt level 

    If you go back to the financial balance sheet structure that I started this post with, the debt measure that emerges is one that scales it to the equity invested in the firm (debt to equity) and to the capital invested (debt to capital). These measures have resonance in corporate finance in valuation, because they become drivers of the costs of equity and debt and ingredients in the cost of capital.That said, you can measure this ratio using book value debt to capital (or equity), where you stay with the values of debt and equity reported on accounting balance sheets or with market value debt to capital (and equity ratios), where you use market values for debt and equity. At the risk of sounding dogmatic, book value debt ratios should never come into play in financial analysis and it is market value ratios that matter for two reasons. The first relates back to all of the criticisms I had of accounting invested capital in the context of computing account returns - it is dated and skewed by accounting contradictions and actions. The second is that it is unrelated to what you are trying to measure in a cost of capital, which is what it would cost you to acquire the firm today, where it is market price that determines how much you have to pay, not book value. That said, there remain a fairly large subset of analysts and firms who swear allegiance to book value for a variety of reasons, most of which have no basis in reality. I report book and market debt to capital ratios for all publicly traded firms, broken down by sector for global and US companies:

As you can see, companies look significantly more debt-laden with book value numbers than with market value, and in sectors like technology, where accountants fail to bring the biggest assets on to the books, the difference is even starker. The results in this table reinforce the findings in the debt comfort table, with technology companies carrying very little debt (3-5% in market cap terms) and utilities and real estate carrying the highest. I also reported, on the aggregated numbers, the gross and net debt ratios, with the latter netting cash holdings from debt.

AI Investing and Debt

    In every data update post that I have written so far this year, AI has become a component of the discussion, reflecting the outsized role it played not just in market pricing during 2025, but also in business decisions made during the year. To see the connection between AI and debt, I will start with AI investing side, where hundreds of billions were spent by companies building AI infrastructure and large language models (LLMs) during 2025, with plans to spend more in the years to come. A sizable portion of this AI capital expenditure have come from big tech companies, with Meta, Alphabet, Amazon, Oracle and Microsoft all making large bets on the future of AI, and the extent of their investment is visible in the graph below, where I look at capital expenditures and cash acquisitions at these firms (with Broadcom added to the mix) from 2015 to 2025:

The shift at these firms from capital-light to capital-intensive models over this period has been staggering, with the collective investment in 2025 alone hitting $400 billion, with guidance suggesting that they are only getting started. It is worth noting that while big tech has garnered the AI cap ex headline, there are a whole host of other companies that are investing in AI architecture, which include real estate, data centers and power, and many of these companies are still not publicly listed. Going back to investment first principles, you can debate whether these companies can expect to generate positive net present value from their AI investments, and I have argued in earlier posts that it is very likely that they are collectively over investing, with over confidence and a fear of being left behind driving their both corporate investments and investor pricing, in keeping what you would expect when there is a big market delusion.

This big market delusion is a feature, not a bug, and we have seen it play out with dot com stocks in the 1990s, online advertising companies about ten years and even with cannabis stocks in the early years of their listing. The belief that the AI market will be huge, and have two or three big winners, is driving an investing frenzy not just at the big tech companies, but also in smaller start-ups and young firms, but the the market is not big enough to accommodate the expectations across all of these firms, and that will inevitably lead to a correction and clean up. 

    The AI investing boom enters the financing storyline, which is the focus for this post, because it needs immense amounts of capital. For many of the big tech companies, much of that capital has come from their existing businesses which are cash machines, although the AI cap ex will deplete the free cash flows available to return to shareholders. That said, though, the ramping up of capital investment has been so dramatic that even the cash-rich bit tech companies have turned to debt, as you can see in the graph below:

In 2025, the big tech companies collectively borrowed $160 billion, but given their cashflows and market capitalization, that debt does not put them at risk. For many of the smaller and lower-profile companies investing in this space, where internal cashflows are insufficient, there is a need for external capital, with some coming from equity and a significant portion coming from debt. It is in the context of the debt that I have to pick up on another storyline, which is the rise of private credit as an alternative to banks and the corporate bond market.  

As you look at the explosive growth of private credit in this graph, it is worth emphasizing that private credit has been available as an option for borrowers for as long as borrowing has been around, but its usage explode in the last two decades. As AI has increasingly taken a starring role in markets, evidence is accumulating that more private debt is being directed to financing the AI investment boom,. With more than $200 billion in private debt going to AI firms in 2025, AI-related debt is rising as a percent of private credit portfolios.  

    As private credit has grown as an option, core questions remain of what it brings to a market as  differentiating features that allow it to supplant more traditional lending alternatives, i.e. banking and the corporate bond market. Here are some of the reasons offered by private credit advocates for why it may be a preferred choice for entities, in general, and for those investing in AI architecture, in particular: 

1. Better default risk assessments: One of the arguments that private credit lenders make is that they have the technical know-how to use data, that banks and bond markets have been more averse to using or have been constrained from using, to get better assessments of default risk. Those assessments, assuming that they are right, allows private credit to lend to entities at rates that are lower than they would be charged, with conventional risk assessments. In principle, that is a solid rationale, but I am unclear about what data it is that traditional lenders are not utilizing that private credit can use, but it is possible that technology and access to the internals of borrowing entities may provide an edge. In fact, the only way to gauge whether this argument of better credit assessment holds up is with a credit shock, where defaults spike across the board.
2. Cashflows-based versus Asset-based lending: A second argument is that traditional lenders, and especially banks, are focused too much on the value of the assets that they are lending against and too little on the cash flows. It is true that bank lending in particular is too focused on asset value, but that focus would provide an opening for private credit in AI, only if AI data centers and architecture investments are poised to start delivering large and positive cash flows soon, and banks are holding back on lending them money. I am hard pressed to think of too many AI investments that have these near-term payoffs.
3. Speedier and more Flexible/Customized Responses: IThis may be the biggest selling point for private credit in the AI investment world, where the investing entities are not just spending billions on AI architecture, but are in a hurry to do so. The regulatory and institutional constraints built into bank lending will stretch the process out in time, and issuing bonds, even if it were an option, comes with its own delay components. In addition, the debt for AI investments may need far more customization than what banks and bond markets can offer, or are allowed to offer, giving private credit an advantage. The problem with speed and customization being the biggest sales pitches for private credit is that it can go with taking short cuts on due diligence and adding terms to loans that cut against prudence, and those can be fatal to lending businesses.

Clearly, these reasons for the presence of private debt have merit, but only to a subset of borrowers, mostly smaller and private, and without a long borrowing history, and for a subset of projects. None that these reasons resonate for the larger tech companies, which have options to borrow money quickly and at fair market rates both from banks and the bond market, and Google's recent hundred year bond issue is an indication of how much slack bond markets are willing to concede to these firms. When a private credit fund lends Meta for an AI investment, as Blue Owl did in this transaction, the skeptic in me sees either a below-market-rate loan or one with terms that no prudent lender would accept in a loan, and neither is a sustainable lending strategy in the long term. 

    The coming together of the two storylines on AI and private credit comes with a risk that may extend well beyond the players in these spaces. If you agree with my contention that companies are collectively over investing in AI, driven by the big market delusion, there will be a time when that delusion  dissipates and markets will have to correct. In an all or mostly-equity driven space, the pain will be borne by shareholders or owners of these companies, but while painful to them, its ripple effects will be limited. When debt enters the picture, as it has in the AI investment space, the effects of a correction will no longer be isolated to equity investors in these companies, and as private credit gets repriced (from the marking of debt down to reflect higher default risk), the pain to the rest of the economy increases. In effect, we will have a banking crisis created primarily by non-banking lenders behaving badly. We saw some of this start to happen in the last year, as the glow came off the AI rose, and S&P noted the stresses that it put on private credit players. Private credit has had a good run, in terms of delivering returns to investors in it, but it has, in my opinion, the relentless selling of it as an alternative investment class has made it much too big. A shakeout is overdue, which will separate the sloppy lenders from the good ones, and perhaps shrink private credit to healthier levels.

YouTube Video

Data links

1. Marginal and Effective tax rates, by country (January 2026)
2. Debt comfort ratios, by industry (US and Global)
3. Debt load ratios, by industry (US and Global)

Spreadsheet

1. Capital structure optimizer 

Paper on Big Market Delusion

1. The Big Market Delusion (with Brad Cornell)

Data Update Posts for 2026

1. Data Update 1 for 2026: The Push and Pull of Data
2. Data Update 2 for 2026: Equities get tested and pass again!
3. Data Update 3 for 2026: The Trust Deficit - Bonds, Currencies, Gold and Bitcoin!
4. Data Update 4 for 2026: The Global Perspective
5. Data Update 5 for 2026: Risk and Hurdle Rates
6. Data Update 6 for 2026: In Search of Profitability
7. Data Update 7 for 2026: Debt and Taxes

Data Update 6 for 2026: In Search of Profitability!

     Crass and mercantile though this may sound, the end game for a business is to make money, and a business that fails this simple test cannot survive for long, no matter how noble its social mission, how great its products and how much it is loved by its customers and employees. In this post, I start with a defense of this mercantile objective, and argue that attempts to expand it to incorporate social good leave both businesses and societies worse off.  I look at business profitability, first in absolute terms in 2025, and then relative to revenues, examining why profit margins vary across businesses and sectors. I then raise the ante and argue that making money is too low a standard to hold companies to, since the capital invested in these companies can generate returns elsewhere, opening the door to bringing in the opportunity costs (costs of equity and capital) that I introduced in my last post. 

The Business End Game

    In 1970, Milton Friedman argued in a New York Times article that the social responsibility of a business is to deliver (and increase) profits. That view has come under attack in recent decades, but even in the immediate aftermath of the article’s appearance, there was some push back. Some came from people who argued that Friedman was missing details, with a few noting that it is cashflows, not earnings, that businesses should focus on, and others arguing that it is profits over the long term, not just immediate profits, that should be the focus of a business. My guess is that Professor Friedman would have agreed on both fronts, arguing that he was talking about economic, not accounting, profits, and that there was nothing in his mission statement that foreclosed a focus on long term profits.

    In the decades since, there has been a more fundamental critique of the Friedman business end game, coming from those who believe that his view is far too cramped and narrow a vision for a business, and that businesses have obligations to society and the planet that need to be incorporated into decision-making. Initially, these critics argued for imposing social and environmental constraints on the profitability objective, and while Friedman may have taken issue with some of these constraints, arguing that that is what laws and regulations should be doing, he would (probably) have gone along with most of them, given real world frictions. Later, though, these critics decided to go for the jugular, arguing that the business objective itself be reframed to include these broader responsibilities, with some arguing for stakeholder wealth maximization, where businesses seek to maximize value to their different stakeholders (employees, lenders, customers). That idea gained traction among some academics, many of whom never grappled with putting this objective into practice in real businesses, and among some CEOs, who realized that being accountable to everyone effectively meant being accountable to no one, but I am not a fan.  About two decades ago, stakeholder wealth maximization was supplemented by ESG, an acronym that quickly got buy-in from the establishment. In 2020, when I first looked at ESG, it was at the height of its allure, with investment managers (led by Blackrock), consultants (with McKinsey up front) and academics, all pushing for its adoption. Given the broad buy in, I expected to see clear and conclusive evidence that ESG was not just good for investors and businesses, but also for society, and I was disappointed on every front. The alpha that was attributed to ESG in investing was accidental, coming almost entirely from its overload on tech stocks in its early years, the evidence that ESG helped businesses deliver higher growth and profits was laughably weak, and on almost every societal dimension that ESG was supposed to make the world a better place, it had failed. Even on risk, the one dimension where a rational argument can be mounted for companies following the ESG rulebook, its impact was hazy, with no discernible effects on costs of capital and only anecdotal (and mostly ex-post) evidence for protecting against reputational and catastrophic risks. In the last five years, ESG has fallen out of favor, largely undone by its own internal inconsistencies, but the gravy train that lived off its largesse has moved on, and taken much of what filled the ESG space, repackaged it, and renamed it sustainability. While advocates for sustainability try to create distance between ESG and sustainability, in my (biased) view, much of that discussion is akin to painting lipstick on a pig and then debating what shade of lipstick suits the pig best, rather than attempting to create real change.

    It is with intent, therefor, that I named these three forces - stakeholder wealth maximization, ESG and sustainability - the theocratic trifecta in a post that I wrote three years ago, and argued that they failed for the same reasons.

First, by rooting themselves in virtue rather than in business sense, they rendered a disservice to their own cause. After all, once you decide that you are on the side of goodness, any critics of what you do, no matter how well merited their criticism might be, are quickly consigned to the badness heap, and not just ignored, but also reviled for lacking moral fibre. The problem, of course, is that if an action makes business sense (increases profitability and value), you would not need a virtue brigade to push for that action in the first place. Second, by leaving the definitions of their central ideas (stakeholder wealth, ESG and sustainability) amorphous, they made it easier to sell to investors and companies, but at the expense of consistency and focus. In my 2022 post on ESG, where the Russian invasion of Ukraine had forced its defenders to morph in the face of evidence that that world was more dependent on fossil fuels and defense companies than they had been willing to concede in earlier years, I noted the loss of credibility that comes from shifting definitions of goodness. Third, and most critically, in their zeal to push these concepts to a wider audience and get more people to buy in, they sold a lie, i.e., that you can be good (whatever that definition of good may be) without sacrifice. I have no idea whether ESG and sustainability salespeople meant what they said when they argued that investors could earn higher returns, by adding ESG constraints to their portfolios, and that companies could become more profitable, if they incorporated environmental and social considerations into decision making, but my categorization of people in these spaces as either useful idiots or feckless knaves stems from a refusal to face up to the inherent trade offs.

    After decades of pushback from critics of the Friedman business end game, I, for one, believe that Milton Friedman was right, and that we would all be better off to follow up and ask the question of what can be done, given that businesses are profit-seekers, to advance social good and curb externalities. I don't believe that the disclosure route, which seems to have become the fallback for some seeking better business behavior, will accomplish much, and it may do more harm than good. While laws and regulations can provide a partial fix, they are blunt instruments, and in a setting where businesses can move easily across borders, they may not be effective. Ultimately, we (as consumers and voter) get the businesses we deserve, and if after paying lip service to social causes, we buy products and vote for governments hat undercut those causes, no acronym or word salad will repair the breach.

Profitability in Businesses

    I meant to have a short lead-in on why profitability matters at businesses, but as you can see from the previous section, I did get side tracked, but the underlying message is that making money is central to business success and survival, and that measuring profitability is therefore a necessary part of assessing business success and value. 

Economic versus Accounting Profits

    The Friedman view on the business endgame may have been driven by a vision of economic profits, but in the real world, we are dependent on accounting measures of profits, which are, at best, imperfect substitutes for economic profits. The table below looks at an accounting income statement, highlighting the many measures of profits - gross, operating and net - that you will find in it:

Each profit measure has utility, with gross profits reflecting unit economics, the difference between gross and operating profits capturing economies of scale and the difference between operating and net profits being driven by taxes and choices that businesses make on debt and non-operating assets. In 2025, looking at the aggregate values (in millions of US $) for these line items across sectors, here are the numbers, for both global firms and just the US subset:

In the aggregate, global firms generated $6.2 trillion in net income and $7.7 trillion in operating income on revenues of $72.4 trillion, in 2025; during the same year, US firms generated $2.2 trillion in net income and $2.9 trillion in operating income on revenues of $22.7 trillion in revenues. Across sectors, and looking at revenues, industrials carried the most weight for the global sample, but health care generated the most revenues across the US sub-sample.

Profits scaled to Revenues - Profit Margins

    The problem with dollar profits is that comparisons across companies, industries or sectors are skewed by scale differences, and one simple scalar for earnings is revenues, yielding variants of profit margins. While you are undoubtedly familiar with these margin variants, their real use in analysis is in providing insight into business models

I am not a believer in financial ratio analysis, but I do believe that the income statements for companies, especially examined over time, give us insight into their business models and can help frame valuation narratives. In the table below, I look at differences in margins across sectors in 2025, again looking across global firms, and just US firms:

I have estimated margins, by sector, using the aggregated dollar values for profits and revenues from the previous table, and also reported the cross sectional distribution of company-level margins. Comparing the aggregated margin with the median margin across the sector should give you a sense of how top-heavy the sector is in terms of profitability. In technology, which has the highest weighted operating margin (24.7%) of across sectors, the median operating margin is only 3.41% (-0.30%) across global (US) technology firms; the bigger tech companies are money machines in a sector that still contains a lot of younger and smaller money-losing firms. Note that the margins are not computed for financial service firms, since revenues are often unreported (and mostly meaningless) and gross and operating profits don't have the same measurement value as they do for non-financial service firms.

Industry Margins and the AI Threat

    Breaking down sectors into industries provides more granular detail, and there is a link at the bottom of this post that reports the margin statistics, by industry group. At the risk of stating the obvious, there are large disparities on margins across industries, reflecting differences in unit economics, economies of scale and leverage, as can be seen in this table that lists the industry groupings with the highest and lowest aggregated operating margins among US firms:

At one end of the spectrum, you have industry groups like basic chemicals, which has an aggregated (median) gross margin of 9.31%, making the margin hill much steeper to climb, since operating margins and net margins will be lower. At the other end of the spectrum, in addition to tobacco and railroads (surprised, right?), you have system and application software, delivering an aggregated gross margin of 71.72%, operating margin of 33.21% and net margins of 25.49%, capturing the strong unit economics that characterize the business. 

    While high margins are a desirable feature for a business, these same high margins can make a business vulnerable to disruption, and the AI sell off that we have seen play out in the last few months in software reflects the concerns that investors have of AI putting significant downward pressure on software margins. If your pushback is that the drop off in revenues and margins has not happened yet, and that it is unfair to software firms to mark their market pricing down preemptively, this is exactly what markets are supposed to do, and these software companies benefited earlier in their lives, when market prices were marked up well ahead of the run-up in margins. You live by the sword (expectations of growth and high margins), you die by it (expectations that growth rates will hit a cliff and margins will decline)!

Time Trends in Profits

    I have tracked profit margins for companies for a long time (about three decades) in my datasets, and there is clear evidences that they have trended upwards during the period. In the graph below, I look at the net profit margins for the S&P 500 in the aggregate in this century (from 2000-2025):

As you can see, net profit margins have climbed over the last two decades for US companies, with a number of stories competing for why.  

• The most cynical explanation is that this increase in margins is all sleight-of-hand, where accountants are pushing through changes, aided and abetted by accounting rule-writers, to make companies look more profitable. As someone who has taken issue with the gaming of earnings that you often see at companies, I am disinclined to take this criticism seriously, since many of the changes in accounting rules (such as the expensing of stock-based compensation and R&D) should push earnings down, and accountants have more power to move income across periods than they do to increase the level of income.
• A second explanation is that the macroeconomic environment makes it easier for companies to deliver profits, and this explanation had resonance when interest rates were at historic lows in the last decade. As rates have risen back to more normal levels and the economy limps along, I am skeptical of the reasoning in this explanation.
• A third explanation, and this one has been eagerly adopted by many on the political left, is that that this reflects the increase in bargaining power for capital, relative especially to labor, implying that the increase in profits are coming primarily at the expense of worker wages. While there are certainly pockets of the economy where this is true, the margins for most manufacturing and service businesses, which have the highest employee count and wage costs, have stagnated or decreased over the last 20 years, indicating that neither capital nor labor has benefited at least in these sectors.
• The fourth, and in my view the most salient rationale for margin increases, is that the composition of the market has changed, as technology companies supplant old-economy companies, bringing superior unit economics and economies of scale to play. Put simple, a market that gets the largest portion of its value from tech companies will deliver much higher margins that one that gets much of its value from manufacturing and service businesses.

Should we concerned that margins may compress in the future? Of course, and we always should, but that compression, if it happens, will depend almost entirely on how the economy performs and the effects of disruption, if it is coming, for tech companies. 

Value Creation in Business

    If we define the threshold for business success as generating profits, we are setting the bar too low for a simple reason. Starting a business requires capital, and that capital can earn a return elsewhere on investment of equivalent risk. If those words sounds familiar, it is because I used them in my last post on hurdle rates to describe the costs of equity and capital. Thus, value creation requires a business to generate a return on its equity (capital) that exceeds its cost of equity (capital). That is a simple proposition, and a powerful one, but the measurement challenge we face is in determining the returns that companies generate, and for better or worse, we are dependent on accounting measures of these returns. A good way to see what an accounting return is measuring or at least trying to measure is to look at returns on equity and invested capital in a financial balance sheet:

While accounting returns are widely used in practice, as a gauge of investment quality, they can be skewed not just by accounting inconsistencies but efforts by accountants to do the "right thing" (like writing off bad investments. I have laid out my concerns in exhaustive and incredibly boring detail in this paper on accounting returns, which is dated, but still relevant. I summarize the factors that can cause accounting returns on equity and capital to deviate from reality in the picture below:

    With those concerns about accounting returns in place, I computed the accounting returns on equity and invested capital for all of the companies in my global sample (48.156 firms) and my US sample (5994 firms), and the following table reports the statistics for both groups, by sector:

Again, I report the accounting returns computed based on aggregated values first, and then the distributional statistics (first quartile, median, third quartile) for the company-level accounting returns. As with profit margins, you can see that even in sectors where the aggregated accounting returns are high (such as technology and communication services), the median value reflects the reality that most companies in these sectors struggle to deliver double-digit returns.

    Turning back to our value creation metric, where we compare accounting returns to costs of equity and capital, you have to be consistent, comparing equity returns to equity costs and capital returns to capital costs:

The excess return is a numeric, but as with all numbers in business, it is worth looking behind the number at its drivers, i.e., why do some business deliver returns that consistently outstrip their costs of equity and capital, whereas others struggle? The most powerful explainer of excess returns is not qualitative, since the capacity to generate excess returns comes from barriers to entry and competitive advantages. In the language of value investing, it is the width (strength of competitive advantages) and depth (sustainability of competitive advantage) of moats that determine whether a company can earn more than its cost of equity or capital:

If you are interested in this topic, and it is a fascinating one, Michael Mauboussin brings his erudition and knowledge into play in  this Morgan Stanley thought piece from October 2024.

    Since I have estimates of costs of equity and capital for each of my firms (see my last data update for details), I compute excess returns, by sector, for my global and US samples:

Given what you saw in the last table, with accounting returns, you should not be surprised to learn that only 29% (28%) of global firms earn returns on equity (capital) that exceed their costs of equity (capital). In fact, if you raise the threshold and look at companies that generate 5% or more as excess returns, the numbers drop off to 19% (17%) for equity (capital) excess returns. Most companies have trouble earning their costs of equity and capital, but if you look at the aggregated values, there are multiple sectors in the US (technology, consumer goods and communication services) that earn double digit excess returns, pointing again to larger companies within these sectors being able to set themselves apart from the rest.

    If your concern is that the global statistics are being skewed by regional differences, I compute the excess return statistics broken down by region:

As you can see, there is not a single geography where more than 50% of firms earn more than their required returns, with Japan ranking highest in percentages and Canada and Australia the lowest. Here again, the aggregated values tell a different story, with US companies collectively delivering excess returns of 8.44% on equity and 1.81% on capital, suggesting again that large US companies carry the weight of value creation in the market.

    Given how much time we spend in finance examining investments and developing decision rules (NPV>0, IRR>Hurdle rate) that are supposed to protect businesses from taking "bad" investments, you may be surprised at the prevalence of value destroying investments. Some of the failure at businesses to deliver returns on capital that exceed the cost of capital may reflect imperfections in our accounting return measures, since it is based upon earnings in the most recent year, and that may bias us against young and growing companies building up to scale. In my book on corporate life cycle, I highlight how accounting returns shift as companies go from youth to decline:

To see if this is a factor in our global findings on excess returns, I break companies down by age into deciles and compute excess returns across these groupings:

The table broadly reflects what you should expect to see, with a corporate life cycle, as the percent of companies that beat their cost of capital increase as companies age, but the aggregated excess returns peak in middle age (the middle of the life cycle), more pronounced with US than global firms.

A Profitability Wrap Up

    Looking at the data, and there is a danger here that I am overreaching, it seems to me that over the last four decades, moats have crumbled, partly as a result of global competition and partly because of disruption (which upends businesses, turning good businesses to bad ones), and the business landscape has tilted more decisively to larger firms, as more and more businesses become winner(s)-take-all. It is in this context that I take a more jaundiced view of what AI will do for company profitability and value. I believe that, as a disruptor, it will cause downward pressure on margins at most firms, and increase the advantages that larger firms have in each business. How do I reconcile this view with the happy talk of AI as a tool that will make companies more productive, and that the resulting lower costs will make them more profitable? Unless the AI tools that you are talking about are exclusive to these companies, in the sense that competitors cannot buy the same or equivalent tools, these AI tools will lower costs across the board, and competition will then kick in on the pricing front, lowering profitability. If that sounds like a reach, I would recommend a revisit of the US retail sector over the last three decades, as online retail, initially viewed as a boon by brick-and-mortar retail firms, ended up destroying most of them and reducing the margins for retail collectively. As consumers, we will benefit, but as investors or employees in the disrupted companies, we will pay a price that outweigh the benefits, for a sizable number of us. I do think that the AI disruption will be more akin to a slow-motion car wreck, in terms of its effect on overall profitability, and that the margin slippage will occur over time, but it will damaging. Time will tell!

YouTube Video

Datasets

1. Profit margins, by industry (US and Global)
2. Accounting returns and excess returns, by industry (US and Global)

Paper on Accounting Returns (Long and Boring)

1. Return on Capital, Return on Invested Capital and Return on Equity: Measurement and Implications

Data Update Posts for 2026

1. Data Update 1 for 2026: The Push and Pull of Data
2. Data Update 2 for 2026: Equities get tested and pass again!
3. Data Update 3 for 2026: The Trust Deficit - Bonds, Currencies, Gold and Bitcoin!
4. Data Update 4 for 2026: The Global Perspective
5. Data Update 5 for 2026: Risk and Hurdle Rates
6. Data Update 6 for 2026: In Search of Profitability