The Fed's operating framework drastically changed after 2008 with its quantitative easing program. These asset purchases now lead to increased financial market volatility.
High February inflation was primarily driven by shelter and energy. These components do not accurately portray current economic conditions. Overall inflation is still trending down.
Critics who levy concerns about the size of private financial institutions show little concern about the balance sheet of the Federal Reserve—whose assets have grown exponentially since the financial crisis.
Recently, CMFA published an article and a working paper that detailed the Federal Reserve's departure from rules‐based governance following the financial crisis of the late 2000s. As per academics and Fed officials, the era of rules‐based governance facilitated the Great Moderation – a stable economic period characterized by less volatile macro indicators such as inflation, output gap, and unemployment. In academic parlance, macroeconomists refer to this situation as determinacy. Despite conflicting evidence, the prevailing view is that the Fed facilitated the Great Moderation by establishing a determinate economic environment through rules‐based governance that focused on keeping inflation low. Previous CMFA papers had posited the question as to whether the Fed's departure from this "successful" era of monetary policy may have instead led to indeterminacy. This article provides evidence that indeterminacy did occur during this period. Determinacy is a feature of an economic system whereby outcomes such as inflation, output, etc., can be precisely determined based on a given set of initial conditions and policy rules. Under determinacy, the economy (as represented by a mathematical model) has a unique equilibrium outcome. In simple terms, under determinacy, the economy has only one possible resting state and is also stable with no large spirals or variability. Conversely, indeterminacy occurs when there are multiple possible equilibria that could result from the same initial conditions and policy rules. This state can create uncertainty in predicting the future state of the economy, as different equilibria may lead to significantly divergent economic outcomes. Simply put, the economy could end up in multiple possible states, some of which may be highly volatile, depending on how individuals form their expectations and make decisions. Academics generally believe that a strong Fed response to inflation (a more than one‐to‐one increase in the target federal funds rate to inflation changes) can ensure a determinate system. This is known as the Taylor Principle. A greater than one‐to‐one response to inflation is deeply entrenched in the economic literature; most empirical macroeconomic studies simply assume determinacy and fix the Fed's response to inflation at a number higher than one or use estimation techniques that entirely exclude the possibility of indeterminacy. This determinacy bias has serious implications for policy analysis because economic models (such as those used by the Fed) exhibit significantly different dynamics in an indeterminate system. Additionally, even approaches that account for indeterminacy, including seminal papers, fail to take consumers' inflation expectations seriously. As noted above, expectations matter drastically when determining equilibrium selection. They should be included in the datasets used by empirical methods. I utilize a simple macro model – connecting output gap, inflation, and the federal funds rate – to test the determinacy of the U.S. economy during the period when the Fed abandoned rules‐based governance (2009 through 2022). I use actual U.S. time series data for the three variables listed above as well as a measure of consumers' inflation expectations – one year ahead inflation expectations collected from the Michigan Survey of Consumers.[1] I fit the macro model to the data using a Bayesian estimation procedure under both determinacy and indeterminacy to see which fits the data better. I find that the model under indeterminacy significantly outperforms its determinate counterpart in fitting the data set. That is, the model under indeterminacy has a much higher "goodness‐of‐fit" versus determinacy. Goodness‐of‐fit values from Bayesian analysis are unlike the usual R2 value reported from regressions. Bayesian model comparison is conducted through marginal likelihoods which are then converted to an odds ratio (similar to betting odds) called the Bayes factor. The estimated odds of determinacy to indeterminacy are 1 to 1.5 x 1015 – making determinacy an extremely unlikely event. To understand exactly how unlikely, let us compare these odds to another extremely unlikely event – being struck by lightning. The odds of being struck by lightning are much higher in comparison: 1 to 1.5 x 104. In other words, the odds of being struck by lightning are significantly higher than the odds that the U.S. economy was determinate from 2009 through 2022. Consequently, the probability that the U.S. economy was indeterminate following the financial crisis is nearly 100%. The (indeterminate) model with a 0.57 estimated inflation response coefficient fits the data better than the (determinate) model with a 1.13 coefficient estimate. The results confirm that the Fed did not target inflation in line with the Taylor Principle. These findings raise an important question: how responsible is the Fed in keeping the economy determinate with a unique and stable outcome? If it is, as several academics and Fed officials have claimed, then they must answer why they did not conduct policy in a way that ensured the economy's determinacy. If they are not responsible for keeping the economy determinate (as several recent studies are now finding), then the Fed's reputation for stabilizing the economy is undeserved, and the public should question why an unelected governmental agency exerts such a high degree of influence over the political economy discourse if it is ineffective in maintaining prices or keeping the economy stable. A forthcoming paper will further examine the history of the Fed's effectiveness in achieving determinacy. The author thanks Jerome Famularo for providing research assistance during the preparation of this essay. For more information on the model, empirical methodology, and posterior distribution please click here.
[1] Respondents are asked the question: 'By what percent do you expect prices to go up, on the average, during the next 12 months?' The average of all responses is used as the measure for inflation expectations.
From the moment the Fed announced its decision last month to hold target rates steady, it seemed a future rate hike was inevitable. Minutes from that FOMC meeting already showed some disagreement, with a few voices such as Dallas Fed President Lorie Logan publicly calling for further rate increases. Additionally, Fed Chair Powell's description of June's rate pause as a "skip" (he immediately walked it back) indicated that future FOMC meetings would conclude with rate hikes. In a post last month, we credited the Fed for its decision to keep target rates unchanged, an improvement from its earlier Covid‐era policymaking. The available evidence from macro indicators such as inflation and unemployment simply did not warrant a rate hike. With the Fed seemingly set to increase rates again, we reiterate our recommendation that the Fed should keep its target unchanged. Our previous post detailed the flattening of average month‐to‐month inflation (as measured via the Consumer Price Index). The inflation numbers released today continue along the same trend. The CPI increased only 0.2% from May to June – an annualized rate of 2.4% — keeping it within range of the Fed's 2% inflation target. As we have pointed out before, the correct measure of inflation is short‐term indicators like month‐to‐month, not year‐over‐year price changes (which is currently at 3%). This is because the annual rate may remain elevated, especially when keeping last year's extreme inflation in mind, even though the monthly changes stay flat. The newest CPI numbers do not indicate any need for a rate hike. The Taylor rule, an approximate relation between Fed policy and its dual mandate macro indicators – inflation and unemployment, would not advise a rate increase either. Here is a simple version of the Taylor rule: FFRt = 0.8 x FFRt‑1 + ( 1 — 0.8 ) x [ 1.5 x Inflationt - 0.5 x ( Unemployment Ratet — NAIRUt ) ]
In June, the realized federal funds rate (FFR) was 5.08%. Latest month‐to‐month CPI inflation was 0.2% – annualized to 2.4%. Using June's unemployment rate of 3.6% and a 4.42% natural rate (NAIRU), the implied FFR for July should be: FFRJuly 2023 = 0.8 x ( 5.08% ) + 0.2 x [ 1.5 x ( 2.4% ) - 0.5 x ( 3.6% — 4.42% ) ] = 4.866%
So, the Fed's target range of 5.0 to 5.25% is already above the rule implied rate. The standard policy rule does not indicate any reason to keep raising rates; if anything it suggests a slight lowering of the target to a 4.75 to 5% range. To reiterate, there are dangers to the Fed raising its rate target by too much, or too quickly. It may worsen credit market conditions and reduce economic activity, triggering a recession. We restate the recommendation from our prior article: The recent inflation figures appear to be on the right track, with annualized rates getting closer to the Fed's regular 2 percent target. Given the stakes, holding steady makes perfect sense.
This week, the International Monetary Fund published a blog post and a working paper that show the contributions of profits, wages, and import prices to the recent inflationary spiral in the Euro area. While the authors note that their analysis represents an "accounting identity [which] does not allow for causal interpretation," it has nevertheless reopened media debate on the "greedflation" theory – the idea that corporate profiteering is responsible for the post‐Covid inflation spike across the world. At least four mainstream media outlets have published articles that attribute causal interpretation to the greedflation hypothesis, using the IMF's materials as their basis (see these articles from MarketWatch, Huffington Post, Guardian, and Telegraph). The problem with the greedflation theory is that it is not an explanation for inflation. It is the result of an accounting exercise that simply breaks down inflation into its constituent components. It does not, and cannot, offer an explanation as to why these components are above or below their normal thresholds. Inflation is a short‐run macroeconomic variable; in that sense it is caused by shocks to the economic system that move prices away from their equilibrium values. By definition, these shocks are exogenous to the economic system and cannot be the result of greedy CEOs, scheming to take advantage of economic turmoil. Inflation has been stable for decades in most advanced economies – from the mid‐1980s till the pandemic, inflation was close to its 2% target rate. Is it reasonable to assume that corporations were greedy since Covid but were disinterested in profits at any time between 1985 and 2020? Corporate profits are determined by price markups – the degree to which firms can charge a price that is higher than their costs. Firms cannot charge arbitrary prices. Optimal prices are set based on several market factors including demand, supply, costs, expectations, etc. As such, both cases – price increases and price decreases – may result in lost profits for a firm. Increased price markups are simply evidence of firms responding to economic conditions and reoptimizing prices. To further understand the dangers of drawing causal inference from accounting exercises, look at Figure 1 below which is a reprint, from page 9 of the IMF paper itself, of the breakdown of Euro area inflation from 1971 onwards. While corporate profits have recently become a majority factor, labor costs have historically dominated the accounting of inflation, especially during the massive inflationary spikes of the 1970s. Attributing current inflation to corporate greed is just as strange as attributing those inflation episodes to greedy workers that demand over‐inflated wages. During both cases, workers and firms were responding to shocks in the economy that temporarily increased their bargaining power in the market.
Figure 1: Breakdown of Euro Area GDP Deflator Inflation into Accounting Components (Source: Hansen, et. al. 2023. Euro Area Inflation after the Pandemic and Energy Shock: Import Prices, Profits and Wages. IMF Working Paper No. 2023/131. [Link]) Back to current Euro inflation – the key task of an empirical economist is identifying which shocks contributed to both price markups by firms and inflation overall. To that end, the economist should use a structural framework that allows for interactions between various economic variables and shocks so that there may be some causal implications. A seminal paper from 2003 already provides a benchmark analysis that researchers could replicate or extend (I employed a similar method when breaking down inflation in the US). Drawing causal inference from accounting identities only serves to obfuscate the true story of inflation and will not allow policy makers to accurately identify the facets of the economy that will contribute the most to a full recovery.
Recent articles by Politico and the Wall Street Journal detail the difficult economic environment the Fed must navigate in the coming months along with highlighting the missteps the Fed has made in dealing with post‐Covid inflation. The articles show that in response to inflation, the Fed executed its steepest and fastest series of rate hikes in 40 years. Once again, this has raised several questions into the internal workings of the Fed and the general obscurity with which it has been conducting monetary policy. While the Fed's recent performance has garnered significant media attention, as my new Cato working paper shows, this failure is only the latest episode in a long‐term trend of discretionary behavior dating back to 2009. From the mid‐1980s through to the mid‐2000s, Fed policy was generally considered to be good. Academics and Fed officials alike credited good monetary policy with keeping the economy stable during this period (often called the "Great Moderation"). In my working paper, I show that the Fed was much more likely to follow a rules‐based approach during this period as compared to after the financial crisis. In fact, every successive Fed chair since Paul Volcker has deviated further from the rules‐based policymaking that helped the Fed be successful in the first place. Just one fact from the paper: the correlation between the good policy rule of the Fed and their actual policy fell from 75% under Bernanke, to 17% under Yellen, to -2% under Powell. The primary concern with Fed policy has been that it has kept rates too low. While this has been true since the end of the Great Recession, it has been particularly problematic post‐Covid. In this period, while a standard Taylor rule suggested the Fed should tighten the economy by raising rates, the Fed was easing the economy further by keeping its target rates near zero and then proceeding to buy more assets. Consequently, it was 20 months too late in raising its target rates, by which time inflation had already become entrenched, requiring the sharpest rate hike in 40 years. Following a monetary policy rule offers several advantages: the Fed's actions remain clear and concise, it does not require the Fed to precisely gauge the true structure of the underlying U.S. economy, and social welfare has been higher under a rules‐based regime. It is unclear why the Fed has so frequently abandoned the guidance offered by the Taylor rule in the recent past. Particularly concerning is the Fed's departure from its self‐professed successful policy tools. For instance, a seminal paper by Richard Clarida and his co‐authors showed that good monetary policy kept the economy stable during the Great Moderation. Meanwhile, interest rates departed furthest from the Great Moderation while Richard Clarida himself served as Vice Chair of the Fed. Why did this happen? Given the benefits of following the Taylor rule, as well as the serious lapses in monetary policy when the Fed acts in an unclear and discretionary manner, perhaps it is time to revisit proposed regulation such as the FORM Act of 2015. This directive would require the Fed to formulate and abide by a rule as a default, but allow it to deviate from that rule provided it explains any departures. For a detailed analysis, please see my Cato working paper.
A few weeks ago, American Compass released Rebuilding American Capitalism, A Handbook for Conservative Policymakers. This Forbes column (American Compass Points To Myths Not Facts) provided a very brief critique of the handbook's Financialization chapter, and Oren Cass, American Compass's Executive Director, released a response titled Yes, Financialization Is Real. This Cato at Liberty post is the fifth in a series that expands on the original criticisms. (The first four in the series are available here, here, here, and here.) This post discusses the one remaining core argument American Compass relies on – income stagnation. It demonstrates that the evidence contradicts American Compass's income stagnation story. The idea that Americans' income has stagnated is central to American Compass's argument that American capitalism needs to be rebuilt. The foreword in American Compass's handbook uses this stagnation story as follows: What has happened to capitalism in America? Businesses still pursue profit, yes, but not in ways that advance the public interest. Over the past 50 years, corporate profits rose by 185%. Wages rose by 1%. [Emphasis added.]
It connects this supposed stagnation to financial markets as follows: Financialization shifted the economy's center of gravity from Main Street to Wall Street, fueling an explosion in corporate profits alongside stagnating wages and declining investment. [Emphasis added.]
American Compass's very reason for existence is to argue that American capitalism no longer flourishes largely because "globalization and financialization" are "undermining the nation's prosperity." The alleged evidence is that the typical American worker's income has been stagnating for decades. The third sentence of Cass's 2018 book, The Once and Future Worker, laments that "while gross domestic product (GDP) tripled from 1975 to 2015, the median worker's wages have barely budged." This stagnation story, just as American Compass's claims regarding talent, profit, and investment, does not hold up to scrutiny. The empirical evidence undercuts American Compass's stated reason for existing. To be clear: It is true that America has many economic problems. In fact, Cato scholars regularly discuss countless ways to fix many of these problems. Unfortunately for American Compass, though, a broad stagnation (or decline) in Americans' income is not a problem. The opening lines of Cass's book (reproduced above) provide an excellent starting point for this discussion. While it is very easy to verify something like GDP growth for any given period, it is not so straightforward to evaluate "the median worker's wages" because the median worker can be defined in any number of ways. The term could reference, for example, someone who earns the median wage of all U.S. employees, the median wage of all private employees, or the median wage of all production and nonsupervisory employees (excluding managerial staff). Arguably, the term should exclude all part‐time workers or all workers under the age of 16. There simply is no single way to define the median (or typical) worker. This basic problem is magnified by multiple definitions of income, including total compensation (wages plus fringe benefits, such as health insurance) and household income (both before and after taxes and transfers). Separately, for any given measure of income, adjusting for inflation with different price indices results in large disparities in real income growth over long periods of time. And, of course, choosing different time periods from within the overall length of a series can easily produce a deceptively low (or high) growth rate. These problems are all further complicated because the "typical" household from distant decades is no longer the typical American household – aside from multiple other demographic changes, more household income is now typically spread over fewer family members. It is straightforward to use Cass's example to illustrate some of these points. For instance, using the Consumer Price Index (CPI) to adjust average hourly earnings of production and nonsupervisory employees suggests that real wages have grown less than 1 percent from 1975 to 2015, consistent with Cass's statement. However, adjusting the same earnings data with the Personal Consumption Expenditures (PCE) index indicates that real wages grew 22 percent – obviously not stagnant. Interestingly, using either a longer or shorter timeframe provides a very different growth figure than Cass's 1975 to 2015 period. For example, examining the same income series from 1964 – the first year the data is available from the Bureau of Labor Statistics (BLS) – to 2015, while adjusting for inflation with the CPI, shows that real wages grew almost 9 percent from 1964 to 2015. Using the PCE shows that real wages grew a bit more than 39 percent from 1964 to 2015. Separately, using the CPI to examine the same income series from 1991 to 2015 (both 1975 and 1991 mark the end of a recession) shows that income grew almost 15 percent. Using the PCE to adjust for inflation suggests that income grew 27 percent for this period.
Figure 1: Real Wage Growth in the U.S. from Varying Start Year (1964–2000) to 2015 As Figure 1 demonstrates, "income growth" is highly influenced by the chosen inflation metric and the starting point for the period of analysis. Figure 1 plots the growth rate in real income – average hourly earnings of production and nonsupervisory employees – with the rate calculated using every year from 1964 to 2000, respectively, as the starting point, and 2015 as the ending year. It shows the analysis using both the CPI and PCE to convert nominal wages to real. (Real adjustments made using the PCE, the Fed's preferred price measure, always result in a higher growth rate.) Using 1975 as the starting point for this analysis, for CPI adjusted income, produces the lowest possible (positive) growth rate. Using only this method – the one Cass uses – while ignoring all the others gives the false impression that real income was stagnant. Similar issues arise using the Census Bureau's household income figures, but even the basic data, as reported, contradicts the stagnation story. For instance, without making any adjustments for changes in demographics, Census reports that real median household income increased 34.18 percent from 1967 to 2018.[1] That's hardly stagnant. Still, because the number of people in each household declined 23 percent from 1967 to 2018 (from 3.3 individuals to an all‐time low of 2.53),[2] the Census income distribution figures understate how well individuals have been doing. Larger household incomes are now divided among fewer people, so adjusting for only this change in household size shows that real median household income increased 74 percent, from $14,355 in 1967 to $24,972 in 2018.[3] That's more than double the increase shown in the unadjusted data, far from stagnant. While many journalists have let go of the income stagnation story, others have (even if unintentionally) fueled the false narrative. Take, for instance, an article in The Atlantic that discussed the U.S. Census Bureau's 2018 report Income and Poverty in the United States. The author noted: Around 13 percent of households made more than $150,000 last year; a decade ago, by comparison, 8.5 percent did. While that's something to cheer, without a solid middle class, it's not indicative of an economy that is healthy and stable more broadly.
At best, the author is guilty of a major understatement. The 2018 Census report shows that more than 5 million households – not individuals, but families – moved into the high‐earning category. That shift is undoubtedly something to cheer, but the author still implies that these numbers support a "disappearing middle class" narrative. As Mark Perry from the American Enterprise Institute confirms, the very same Census report shows that the share of households earning between $35,000 and $100,000 fell from more than 53 percent in 1967 to 42 percent in 2018, and that the share of households earning more than $100,000 essentially tripled, from less than 10 percent in 1967 to more than 30 percent in 2018. Moreover, while The Atlantic article largely ignores it, the share of households earning less than $35,000 fell, from approximately 36 percent in 1967 to less than 28 percent in 2018. Together, these statistics show a broad increase in prosperity. In fact, this increase is even more impressive considering that the number of American households essentially doubled from 1970 to 2018. For anyone interested in additional evidence that typical Americans – and even, in many cases, lower income Americans – have been earning higher and higher incomes during the last several decades, here are a few references: William Cline, U.S. Median Household Income Has Risen More Than You Think Richard V. Burkhauser, Jeff Larrimore, and Kosali I. Simon, A "Second Opinion" On The Economic Health Of The American Middle Class Salim Furth, Stagnant Wages: What the Data Show Michael Strain, The Myth of Income Stagnation Scott Winship, Stagnationists Are Simply Wrong and What You Need to Know from the New CBO Income Figures Gerald Auten and David Splinter, Income Inequality in the United States: Using Tax Data to Measure Long‐Term Trends Thomas Hirschl and Mark Rank, The Life Course Dynamics of Affluence Scott Lincicome, The American Wealth Machine and Its Misguided Discontents and The Annoying Persistence of the Income Stagnation Myth John Early, The Myth of American Income Inequality In 2020, perhaps after recognizing that the basic income stagnation story does not hold up, American Compass began releasing its Cost‐of‐Thriving Index (COTI) to provide "a better way to understand the challenge for working families." According to Cass, his COTI is better than looking at inflation‐adjusted (real) income: Economists rely on inflation‐based adjustments to compare costs of living over time, but this method measures the cost of buying the same set of things in different eras. Perhaps a family could more easily afford a 1985 quality of life in 2015 than in 1985, but being in the middle class in 2015 means affording a 2015 quality of life.
While it is true that price indices are imperfect, and they tend to make older incomes look larger than they really were, Cass's description of inflation‐based adjustments over time is highly flawed. Adjusting nominal income to "real" income essentially converts the dollar amount to a quantity, such that it indicates how much "stuff" someone can buy. And both the CPI and the PCE account for (as best as possible) the different quality of goods and services available to people over time, as well how people may buy different products (substitute), including those that they were previously unable to purchase. Setting this flaw aside, American Compass uses its COTI to argue that living standards have declined, supposedly explaining why "America's working families" are correct to "feel that they have come under increasing economic pressure." However, as the American Enterprise Institute's Scott Winship and Jeremy Horpedahl have documented, American Compass's COTI methodology is just as flawed as its understanding of inflation‐based adjustments. In their new paper, Winship and Horpedahl demonstrate that the American Compass COTI decline is the direct result of its design choices. Specifically, American Compass's COTI ignores taxes and transfers (which tend to boost lower earners' incomes), excludes full‐time workers younger than 25 years old, and excludes full‐time female workers. American Compass's COTI also includes a very narrow range of goods and services, defining food, transportation, housing, health care, and higher education as "needs," yet leaving purchases of clothing, home furnishings, utilities, and communications technology out of the COTI. American Compass's COTI methodology is consistent with its propensity for selectively choosing data to give the appearance of supporting evidence for its claims. Thus, Winship and Horpedahl reach a reasonable conclusion regarding American Compass's COTI report: Against these data, Cass asks us to believe that, in truth, living standards are down by 36 percent. We have shown that this claim bears no relationship to reality. … While Cass's claims are out of line with all plausible estimates by serious researchers, they align neatly with his organization's view that American capitalism requires "rebuilding."
It is also worth mentioning that American Compass's COTI conflicts with other research that uses separate alternative measures of well‐being that do not depend on inflation‐adjusted income metrics. For instance, Bruce Sacerdote's 2017 National Bureau of Economic Research (NBER) paper reports that consumption for two‐person households with below median income increased as much as 164 percent from 1960 to 2015. The paper points out that spending on food and clothing grew slower than the growth in total consumption during this period, and that this falling share of total consumption for food and clothing is consistent with real income growth being higher than income‐based measures suggest. Another consumption‐based measure of well‐being is the number of work hours needed to purchase the same goods at two different points in time. Researchers can use this metric to gauge whether, for example, real income stagnated from 1975 to 2015. If the amount of time someone would need to work to buy the same bundle of consumer goods in 1975 is no different than it is in 2015, then real income has stagnated. On the other hand, if the required work time to purchase the same bundle has fallen, then the evidence suggests that real income has increased. Using a sample of 400 consumer products, George Mason's Don Boudreaux reports that only one good–men's work boots–costs more in work time in 2019 than in 1975. (In Myths Of Rich And Poor: Why We're Better Off Than We Think, Michael Cox and Richard Alm use the same method and report similar results.) The Simon Project, an endeavor of the Cato Institute's HumanProgress.org, formalizes these ideas by creating an index based on the time price (how long someone must work to acquire a good) of 50 basic commodities. Their index shows that the average time price of these 50 commodities fell more than 72 percent between 1980 and 2018. In practical terms, this figure means that if it took one hour of work to buy a commodity – such as sugar, coffee, pork, or lumber – in 1980, it took only about 17 minutes of work to buy that same commodity in 2018. Put differently, if it took one hour of work to buy an item in 1980, that same hour of work would buy almost four units of the same good in 2018. This Cato post has demonstrated that American Compass's bleak income stagnation story is a false narrative. American Compass selectively chooses its preferred time periods and economic measures so it appears as if the evidence supports its story. Moreover, as previous posts in this series established, American Compass displays this same propensity to selectively pick terms and dates that appear to support its "financialization" narrative. In all these cases, though, the evidence contradicts American Compass's claims.
[1] Authors' calculations using the following U.S. Census income and household size data: Table A‑2. Households by Total Money Income, Race, and Hispanic Origin of Householder: 1967 to 2018, https://www.census.gov/library/publications/2019/demo/p60-266.html, and Table HH‑4. Households by Size: 1960 to Present, https://www.census.gov/data/tables/time-series/demo/families/households….
[2] Mark Perry, "More Charts And Commentary Based On This Week's Census Bureau Report On Income," American Enterprise Institute, September 12, 2019, https://www.aei.org/publication/more-charts-and-commentary-based-on-this-weeks-census-bureau-report-on-income/.
[3] Author's calculations using the following U.S. Census income and household size data: Table A‑2. Households by Total Money Income, Race, and Hispanic Origin of Householder: 1967 to 2018, https://www.census.gov/library/publications/2019/demo/p60-266.html, and Table HH‑4. Households by Size: 1960 to Present, https://www.census.gov/data/tables/time-series/demo/families/households….
A few weeks ago, American Compass released Rebuilding American Capitalism, A Handbook for Conservative Policymakers. This Forbes column (American Compass Points To Myths Not Facts) provided a very brief critique of the handbook's "Financialization" chapter, and Oren Cass, American Compass's Executive Director, released a response titled Yes, Financialization Is Real. This Cato at Liberty post is the fourth in a series that expands on the original criticisms outlined in the Forbes column. (The first three in the series are available here, here, and here.) This post demonstrates the evidence does not support American Compass's claims regarding investment. It also further documents American Compass's failure to clearly specify terms and dates, as well as its selective use of examples that appear to support its positions. To recap, the American Compass handbook states the following: American finance has metastasized, claiming a disproportionate share of the nation's top business talent and the economy's profits, even as actual investment has declined." [Emphasis added.]
As with profits, the "Financialization" chapter does not specify a single preferred measure of investment or any time frame for analysis. It simply complains that "In recent decades…actual investment has declined." [Emphasis added.] The original critique stated, "The claim that investment has declined is also easily verified as false," and then used National Income and Product Account (NIPA) data to show "investment in fixed assets has been steadily increasing since 1970, a trend that holds even if the data is adjusted for inflation." Cass takes issue with the original critique's use of absolute investment dollars rather than investment as a share of GDP. Cass's response states: Of course, investment rises in absolute dollars as the American population grows and economy expands. Who would claim otherwise? The question is what has happened relative to GDP.
Yet, American Compass uses the term actual investment in the introduction to the "Financialization" chapter and purposely uses aggregate data in levels when doing so suits its purpose. But importantly, American Compass fails to settle on any definition of investment. Here's a list of direct quotes describing investment from the "Financialization" chapter: Unfortunately, in the United States, productive business investment has been in long‐term decline and the financial industry now specializes in trading assets around in circles. [Emphasis added, no dates given.] Economy‐wide, business investment has fallen significantly as a share of GDP. [Emphasis added, no dates given.] They instead become savers themselves by acquiring financial assets, effectively deferring the earthy and material work of productive capital investment to others. [Emphasis added, no dates given.] Statistically, this transition began in the 1980s, as the share of corporate investment in tangible assets declined and the acquisition of financial assets climbed. [Emphasis added.] Despite this ambiguity, Cass's response insists that readers should know exactly what investment data American Compass's handbook is referring to because "the Rebuilding American Capitalism handbook is a synthesis of our analysis and recommendations and provides copious references to further reading alongside each proposal." So, here's a list of direct quotes from two other American Compass reports, none of which provide a clear answer: Actual‐investment, by which I mean the allocation of capital toward the development of new productive capacity—the building of structures, the installment of machines, the creation of intellectual property—has been weakening in America for decades now. [Found in "The Rise of Wall Street and the Fall of American Investment" – emphasis added.] As non‐investors have overrun the banks and markets and taken control of corporations, actual‐investment has slowed. The nation's capital base is smaller by literally trillions of dollars as a result, representing untold enterprises never built, innovations never pursued, and workers never given opportunity. [Found in "The Rise of Wall Street and the Fall of American Investment" – emphasis added.] Net non‐residential fixed investment as a share of GDP has fallen by almost half, from 4.1% in the 1970s and 80s to 2.5% in the 2010s. [Found in "The Rise of Wall Street and the Fall of American Investment" – emphasis added.] The classic categories of investment, structures and equipment, account for 87% of the nation's capital base and the rate of investment there has been declining in both gross and net terms. [Found in "The Rise of Wall Street and the Fall of American Investment" – emphasis added.] Net investment as a share of value‐add averaged 4.3% during 1998–2000 and then 0.5% during 2002-04. During 2000–17, the average was 2.2%, leading to a $1.0 trillion shortfall over the period, relative to the 1970–99 rate. [Found in "The Rise of Wall Street and the Fall of American Investment" – emphasis added.] As we have seen, the cumulative gross investment shortfall during 2009–17 as compared to 1970–99 amounted to $3.4 trillion. [Found in "The Rise of Wall Street and the Fall of American Investment" – emphasis added.] Nationwide, net investment as a share of GDP has fallen sharply, and the shortfall since the Great Recession totals roughly $3 trillion (equivalent to the excess outflow from public companies). [Found in "Confronting Coin‐Flip Capitalism" – emphasis added.] This creates a vicious cycle in which business leaders pursuing promising opportunities become harder to find, further encouraging the financial sector to develop strategies for deriving profits disconnected from actual investment. [Found in "Confronting Coin‐Flip Capitalism" – emphasis added.] From 2009 to 2017, the nation needed $22.9 trillion in gross investment to match the average growth rate of the capital stock during 1970–99 (3.8% of GDP annually). Instead, investment totaled only $19.6 trillion. [Found in "Confronting Coin‐Flip Capitalism" – emphasis added.] Even the market fundamentalists—indeed, especially the market fundamentalists—recognize that higher investment levels would be beneficial. [Found in "Confronting Coin‐Flip Capitalism" – emphasis added.] Setting aside American Compass's failure to explain whether any of these versions of investment is its single preferred measure of investment to study "financialization," it is true that there are many ways to describe investment. Indeed, there are even many different time periods, inflation adjustments, aggregation issues, and sub‐components of investment that influence how an aggregate investment series behaves. Moreover, if investment (however defined) declines, or declines slower than some metric, that fact alone would not be evidence that investment is less than optimal. While many American Compass reports imply investment is suboptimal, American Compass has not provided evidence that investment is less than what it should be. Take, for instance, American Compass's claim that "Net non‐residential fixed investment as a share of GDP has fallen by almost half, from 4.1 percent in the 1970s and 80s to 2.5 percent in the 2010s." If American Compass believes that that 4.1 percent was the optimal share in 1970, and a 1.6 percentage point lower share in the 2010s "threatens our future prosperity" and requires America to rebuild capitalism, then the least it can do is state a clear hypothesis and make an empirical case. Such critics cannot simply argue that a lower number is less than optimal. (For what it's worth, American Compass's "The Corporate Erosion of Capitalism" also fails to provide such evidence – it is merely an accounting exercise without any economic analysis of the optimal levels of real investment individual firms need to sustain their own operations.) It turns out, though, that the long‐term trend in most of these investment measures is not decreasing. The only way to show that "investment" has declined is to selectively define the measure and period for analysis. Otherwise, it is impossible to say that investment has declined. Regardless, there is no inherent economic reason that investment, whether in absolute amounts or relative to GDP, whether net or gross, or real or nominal, must constantly increase. A developed economy with evolving working patterns, for instance, would not need to constantly invest more in new corporate structures. Similarly, the rate of growth of investment does not have to constantly match or exceed GDP (or profit) growth in any historical period. The mere fact that some metric of investment grows slower than some other economic measure – even for an extended period – does not indicate that the economy will be harmed much less that "financialization" caused the "slow" growth. Our analysis now turns to the actual time series of real investment and real GDP, respectively (see Figure 1 and Figure 2). Contrary to what Cass claims in his response, the right question is not always "what has happened [to investment] relative to GDP." (Even if it was the correct question, simply dividing investment by GDP would not adequately account for confounding factors such as population growth, the cost of investment, productivity, feedback loops, etc.) Bluntly, it is not at all clear that using a relative measure is the "right" way to look at investment.
Figure 1: Real Gross Private Investment in the U.S., Annual from 1929 to 2022
Figure 2: Real Gross Domestic Product in the U.S., Annual from 1929 to 2022 For starters, nobody invests in amounts relative to GDP, and even American Compass often refers to levels of investment. Regardless, there are some basic mathematical issues that suggest, at the very least, researchers must be very careful drawing inferences from relative investment measures. As Figure 1 and Figure 2 show, real (gross private domestic) investment and real GDP both display a sharp upward trend. However, the two series exhibit an enormous difference in size and volatility – the standard deviation of investment growth is five times greater than for GDP growth. A 20 percent year‐to‐year decline in investment is normal, but it would be highly unusual for GDP. Moreover, any decline in the ratio can easily mask the causal relationship between investment and economic growth. Put differently, GDP is stable but one of its components – investment – fluctuates rapidly. This stability arises as investment accounts for only 13 percent of GDP on average and fluctuations in investment can be offset by counter‐cyclical fluctuations in other components of GDP, such as consumption or fiscal spending. Consequently, measuring investment relative to GDP can give the appearance that something dreadful has happened even though such deviations may be the result of a perfectly normal economy, even one with optimal decision making. Investment's high volatility is a commonly known macroeconomic fact. Benchmark macro models dating back to the start of macroeconomic modeling itself have highlighted investment's significant volatility in comparison to the rest of the economy. Successes of models since then are measured (at least in part) by whether their simulated time series can match the observed volatility of macro indicators such as investment. Leaving the appropriateness of using levels aside, we now examine nominal investment relative to nominal GDP (i.e., the investment‐to‐GDP ratio), as well as several of its component measures. (See Figure 3.) These nominal metrics are available from 1929, but in fairness to American Compass, we only present the data from 1950 onwards. The series exhibits high volatility between 1929 and 1950 and starting the graph in 1929 biases the data toward a steeper increasing trend for investment and its component measures. (Incidentally, replicating Figure 3 with real investment and GDP figures also shows the ratio exhibiting an increasing trend.[1]) As Figure 3 shows, the investment‐to‐GDP ratio exhibits variation around a very mildly increasing trend for all of modern U.S. economic history. As for component measures, non‐residential investment has grown significantly as a share of the economy, offsetting the decline in the share of residential investment. Finally, net private domestic investment has declined over time. From this set of investment measures, focusing only on net private domestic investment to argue "actual investment" has declined equates to selectively using a sub‐component of investment while ignoring others.
Figure 3: Investment Metrics as Share of NGDP in the U.S., Annual from 1950 to 2022 Of course, there are still many other ways to describe investment. Assume, for example, that net nonresidential (or business) investment is the "right" measure to analyze, as Cass's response suggests. Figure 4 presents real net business investment and its subcomponents from 1967 to 2021.[2] It shows that net business investment exhibits a sharp increasing trend. (Figure 3 showed that nonresidential investment as a share of GDP exhibits an increasing trend.) While the trends are not as steep for the subcomponents, Figure 4 shows that net investment in business equipment and intellectual property also display increasing trends. However, net business investment in structures exhibits a decreasing trend. (Interestingly, in The Rise of Wall Street and the Fall of American Investment, American Compass groups structures and equipment together to demonstrate that investment in "Structures & Equipment" is declining.)
Figure 4: Real Net Nonresidential Investment and its Components in the U.S., Annual from 1967 to 2022 Obviously, it would make little sense to argue that "actual investment" is declining by focusing only on the decline in the net structure subcomponent, or any other component of investment for a shorter period. Put bluntly, American Compass is incorrect to use declines in any of these subcomponents to argue that there is some kind of broad decline in investment. Still, the trends in these subcomponents on Figure 4 are even more problematic for American Compass. Not only do the trends contradict that investment is in a general decline, but American Compass's story requires an explanation for: (1) why the highly developed U.S. economy needs constantly increasing growth in structures; and, (2) how "financialization" is responsible for a decline in structure investment and a simultaneous increase in equipment and IP investment. It is also worth noting that while there's nothing inherently wrong with using net investment figures, as American Compass sometimes does, neither the Bureau of Economic Analysis's depreciation estimates nor accounting depreciation perfectly coincide with economic depreciation. In other words, even when someone fully depreciates a piece of equipment for tax or accounting purposes, it does not mean that the equipment is no longer useful and must be immediately replaced. More generally, from a macroeconomic perspective, there is no reason to distinguish between different sub‐components of investment. The primary macro indicator of economic health is real GDP growth away from trend (or similar metrics such as output gap and unemployment). Investment is a means of facilitating capital accumulation and it is not immediately clear why one component of it is necessarily better than any other. This is why seminal empirical economic papers always focus on investment as an aggregate. Even highly cited papers that explicitly model net investment don't bother to include it in their results, instead focusing again on aggregate investment. Overall, aggregate investment in the United States is not in decline. Yet, American Compass relies on a wide array of investment descriptions, in various time periods, to argue that American investment is in a general decline and below optimal levels. American Compass's error is only compounded by its imprecise definition of financialization. This combination of errors leaves American Compass with little more than a set of stories that appear to provide evidence financial markets threaten American capitalism. In the next post, we will conclude this series by discussing American Compass's flawed characterization of Americans' income.
[1] It may seem unintuitive that shares would be different between nominal and real variables (prices on the numerator and denominator should cancel out), but the relative price of investment has changed significantly in comparison to overall GDP. Specifically, the deflator for investment has been significantly higher than for GDP, equalizing only since the 2010s.
[2] The BEA provides values for sub‐components of investment that only go back to 1967.
A few weeks ago, American Compass released Rebuilding American Capitalism, A Handbook for Conservative Policymakers. This Forbes column (American Compass Points To Myths Not Facts) provided a very brief critique of the handbook's "Financialization" chapter, and Oren Cass, American Compass's Executive Director, released a response titled Yes, Financialization Is Real. This Cato at Liberty post is the third in a series that expands on the original criticisms outlined in the Forbes column. (The first and second in the series are available here and here.) This post demonstrates that the evidence does not support American Compass's claims regarding profits. This post also documents American Compass's failure to clearly specify terms and dates, as well as its selective use of examples that appear to support its positions. To recap, the American Compass handbook states the following: American finance has metastasized, claiming a disproportionate share of the nation's top business talent and the economy's profits, even as actual investment has declined." [Emphasis added.]
The original critique in Forbes pointed out: "It's impossible to know exactly what American Compass means by profits because they don't cite anything, but the National Income and Product Accounts provide financial and nonfinancial company profits dating back to 1998." With nothing else to base an analysis on, the critique then summarized the NIPA data, stating: While the annual share of total corporate profits in the NIPAs has varied, at the end of 2022 it was 18 percent for financial companies versus 82 percent for nonfinancial companies. In 1998 the share for financial firms was a touch higher (20 percent) compared to nonfinancial firms (80 percent).
The original Forbes critique didn't make clear, however, that these respective shares do not suggest either sector "claimed" a share of total available profits at anyone's expense. They're merely part of the Bureau of Economic Analysis's national accounting exercise that estimates the value of all final goods and services produced in the United States. There is nothing inherently wrong with a higher (or lower) profit share in either sector. In his response, Cass points out that the NIPA data goes back to 1929. He then shows that the share of total corporate profits for financial firms is twice as high in the 2010s versus in the 1950s (using 10‐year averages for each decade), and finally complains that the original critique's "focus on the 2022 data as the endpoint is unfortunately misleading." While Cass still neglects to specify any kind of preferred profit metric, fails to explain why his use of 10‐year averages for each decade between 1950 and 2019 is appropriate, and fails to stipulate what the optimal share of profits should be, at least he acknowledges the NIPA data goes back to 1929. (For the record, it is just as misleading for American Compass to focus on 1950 to 2019 as evidence of an increase in the financial sector share as it would be for us to focus on the decline since 2009 as evidence of a decrease.) While it is true, as Cass states, that the financial sector share was 28 percent in 2019, it is also true that the series exhibits a high degree of volatility. The standard deviation of the full series is about seven percentage points, and the financial sector share peaked at an unusually high value in 2002 (37 percent) before crashing to an unusually low value in 2008 (8 percent). This high degree of volatility makes it especially important to focus on the long‐term trend rather than on any specific period. As Figure 1 demonstrates,[1] using the NIPA data, the long‐term trend for the financial sector's share of total corporate profits increases slowly throughout the roughly 100‐year period. The slope of the trend line in Figure 1 indicates the financial sector's share of corporate profits increased by about 0.2 percent per year between 1929 and 2022.
Figure 1: Financial v. Non‐Financial Share of Corporate Profits, Annual from 1929 to 2022 But that's all the series reveals. It does not provide evidence that the financial sector "claimed" a "disproportionate share" of the economy's profits, much less that this rate of change harmed the broader economy. Importantly, it is not the case that corporate profits in the non-financial sector have been falling throughout this period. That is, even though the financial sector's share of NIPA corporate profits has been slightly increasing for 100 years, profits in the non‐financial sector have been steadily growing, as has the broader economy. Figure 2 provides a similar analysis. It shows that financial sector profits as a share of GDP have averaged less than two percent from 1929 to 2022. The series exhibits a slightly increasing trend, rising about 1.5 percentage points throughout the period, with a recent downtick since the early 2000s. While it would be misleading to claim that this recent downtick demonstrates a major failure of capitalism, selectively fixating on a narrow period to draw incorrect inferences mirrors American Compass's approach to other claims it has made.
Figure 2: Financial Profits as a Share of Nominal GDP, Annual from 1929 to 2022 For instance, in The Rise of Wall Street and the Fall of American Investment, American Compass claims that corporate profits have stagnated. Sort of. For instance, the report states: Corporate profits from domestic industries fell for four straight years, from 2014 to 2018, even as the stock market was surging. The level in 2018–19 was 11 percent lower than at the prior business cycle's peak in 2005-06.
The report then presents a graph of pre‐tax real corporate profits from 1998 to 2019, titled Profits Stagnating. The graph displays a very clear upward trend for the full period, but the report only discusses the decline in the level of profits from 2014 to 2018, and the level of profits in 2018 and 2019 relative to the peak in 2005 and 2006. In other words, American Compass's claim that corporate profits have stagnated ignores the broader trend and relative measures of profits, and carefully selects periods for comparison. The above examples demonstrate American Compass's propensity to pick and choose metrics and time periods that appear to provide evidence for its claims. But, overall, these statistics do not provide evidence that "In recent decades, American finance has metastasized, claiming a disproportionate share of…the economy's profits." Of course, if American Compass has an optimal share for the financial sector in mind, it should clearly explain what that number is and why it is optimal. In the next post, we will discuss claims involving "financialization's" alleged effect on investment.
[1] The figure omits data for 1932 and 1933 as these values, during the Great Depression, turned aggregate corporate profits negative. For the sake of completeness, the numbers are presented here. In 1932 and 1933, corporate profits are -$0.2 billion in each year, financial firms' profits are $0.6 billion and $0.8 billion respectively, and non‐financial firms' profits are -$0.8 billion and -$1 billion respectively.
A few weeks ago, American Compass released Rebuilding American Capitalism, A Handbook for Conservative Policymakers. This Forbes column (American Compass Points To Myths Not Facts) provided a very brief critique of the handbook's "Financialization" chapter, and Oren Cass, American Compass's Executive Director, released a response titled Yes, Financialization Is Real. Today's Cato at Liberty post is the second in a series that expands on the original criticisms outlined in the Forbes column. (The first in the series is available here.) This post deals with American Compass's claim that the financial sector has siphoned off "top business talent" to the detriment of the rest of the economy. The evidence does not support American Compass's claims. The post also points out the inconsistency between American Compass's complaints about (allegedly) stagnant American income and an influx of people working in higher‐paying fields. To recap, American Compass's handbook states the following: American finance has metastasized, claiming a disproportionate share of the nation's top business talent and the economy's profits, even as actual investment has declined." [Emphasis added.]
The original critique was that American Compass failed to provide supporting evidence for these claims, and that such supporting evidence doesn't exist. It also pointed out the number of people employed in the Finance and Insurance industry, as a share of total nonfarm employees, has barely budged from 4.5 percent since 1990. To provide evidence that the nation is, in fact, losing its top business talent to the financial industry, Cass's response pointed to two paragraphs in a separate report that Cass wrote, Confronting Coin‐Flip Capitalism. Our critique assumes that "coin‐flip capitalism" is the same phenomenon as "financialization." The first of the two paragraphs is reproduced here: Graduates of America's top business schools provide a useful proxy for the attraction of various industries and, from 2015 to 2019, nearly 30% of graduates from Harvard, Stanford, Wharton, Booth, Kellogg, Columbia, and Sloan went into finance. In 2020, the finance industry was the most popular and offered the most generous compensation packages for graduates of the MBA programs at both Harvard and Stanford. [See also, our Guide to Private Equity.]
This first paragraph does not provide evidence that finance has claimed a disproportionate share of the nation's top business talent. It merely refers to several years of placement data from some of America's top business schools, not a systematic study. The paragraph provides evidence that a large portion of top business school graduates choose to work in finance. That fact is hardly surprising, and it is not evidence that the proportion has changed or that businesses have been harmed. The second paragraph is reproduced here: Engineers have likewise flocked to Wall Street, as compensation at equivalent education levels surged in finance as compared to engineering after 1980. The probability of an engineer switching to a finance career increased more than four‐fold from the 1980s to the 2010s; the share of "STEM" jobs in finance doubled over that period while the share in manufacturing fell by half. Lest one think these are the engineers who couldn't hack it in engineering, Nandini Gupta and Isaac Hacamo of Indiana University's Kelley School of Business find that "financial sector growth attracts exceptionally talented engineers from other sectors to finance."
Citing three research papers, American Compass bemoans the finding that "Engineers have likewise flocked to Wall Street." Our critique assumes that engineers should be included in the category of "top business talent." First, even if business majors and engineers do choose finance versus other fields, that fact alone says nothing about why they make such choices, much less whether such choices cause harm to the nation's economy. Such choices could simply reflect that people tend to seek opportunities to earn higher compensation, and the outcome could be beneficial to the economy. And, in fact, between 1968 and 2022,[1] average annual real wage and salary growth was higher in finance than in several other sectors, including engineering. (See Figure 1.)
Figure 1: Real U.S. Annual Wage Growth Statistics by Sector, 1968 to 2022 Average annual real wage and salary growth is 1.73 percent in finance since 1968, but 1.26 percent in engineering and 1.36 percent in computer services. Thus, even though wages in finance are lower than in computer sciences or engineering (see Figure 2), their higher growth rate could help explain why many people would choose finance jobs relative to other fields.
Figure 2: Annual Wages in the U.S. by Sector, 1968 to 2022, inflation adjusted with Personal Consumption Expenditures (PCE) None of these facts are indicative of an economic problem. If American Compass believes that people earning so much more in the computer field harms Americans, they should say so. Similarly, if American Compass believes that a 0.47 percentage point difference in average income growth between the financial and engineering sectors reveals businesses have been harmed, they should state their hypothesis clearly and make an empirical case. Surely, though, an organization such as American Compass, one that constantly complains about stagnant income, would not begrudge Americans for choosing to work in a higher paying field. (Figure 1 and Figure 2 also demonstrate that Americans' income is not stagnant. Real wage and salary growth has been positive across almost all sectors and time periods, with cumulative growth of 71 percent even in the manufacturing sector. We'll return to this issue in a future post.) Of course, even this compensation growth data tells us very little about why the different rates of growth occurred in the various sectors. However, one of the academic research papers Cass cites in his response does provide an explanation for this difference. Specifically, we're referring to the paper by Thomas Philippon and Ariell Reshef, titled "Wages and Human Capital in the U.S. Finance Industry: 1909–2006," which was published in the prestigious Quarterly Journal of Economics in 2012. In that paper, the authors show that the labor market in finance was artificially suppressed between 1940 and 1980 due to an over‐bearing regulatory environment. In other words, overall wages and employment in finance would have been much higher without the heavy regulation in that sector. Consequently, the uptick in wages and employment after 1980 are likely due to the finance labor market reverting back to its non‐suppressed state (similar to pre‐1940) after the regulatory environment changed (precisely what economics would predict). Here's a quote from page 1552: We find a tight link between deregulation and the flow of human capital in and out of the finance industry. In the wake of Depression‐era regulations, highly skilled labor leaves the finance industry and it flows back precisely when these regulations are removed in the 1980s and 1990s. This link holds for finance as a whole, as well as for sub‐sectors within finance. Our interpretation is that tight regulation inhibits the creativity of skilled workers.
So, this paper does not support American Compass's position that anything bad has happened; instead, it argues that any employment increase seen in finance is essentially a reversion to a state where skilled workers' creativity is no longer inhibited. Another of the three papers is a Kelley School of Business working paper from 2022 by Nandini Gupta and Isaac Hacamo. This paper is an even stranger choice for American Compass to cite as proof of some kind of harm caused by financialization (or coin‐flip capitalism). It shows that the net effects of people working in finance boost entrepreneurship. Here is the relevant language (from two separate paragraphs on page 4 of the paper): Our results show that the finance wage premium increases overall entrepreneurship. This may occur because engineer‐financiers are more likely to become entrepreneurs. Or, because talented engineers in finance facilitate entrepreneurship by others. We find that engineers who take finance jobs are less likely to subsequently start firms. Therefore, we study a potential peer effects mechanism where engineer‐financiers may help their classmates become entrepreneurs. … We find the following results: First, we show that top engineers exposed to a higher finance wage premium at graduation are more likely to take jobs in entrepreneurial finance (EF) jobs in venture capital, private equity, and investment banking. Second, we show that engineers who don't take finance jobs are more likely to become transformational entrepreneurs the more classmates from the same school‐major‐graduation year who are in venture capital, private equity, and investment banking firms. For example, an engineer with 5 classmates in entrepreneurial finance jobs is 9% more likely to become an entrepreneur and 18% more likely to create a transformational firm that issues patents, employs workers, and has a successful exit, relative to the mean.
At the very least, the paper's results are consistent with the literature on peer‐effects "whereby engineers in investment banking type jobs help their classmates start transformational firms." Obviously, it's very odd to cite this paper as evidence that financialization is some kind of blight on capitalism. It implies the opposite: the overall labor market trend is good for the economy. The third paper is a 2022 working paper by Giovanni Marin and Francesco Vona, and the evidence it provides does not show that finance is now claiming a disproportionate share of STEM talent. For instance, the authors show that the probability a STEM graduate starts working in finance rose between 1980 and 2019, from 4 percent to 6.8 percent. However, they also report a substantial increase for non‐STEM graduates – it rose from 6.5 percent in 1980 to 8.2 percent in 2019. (See page 9.) The authors of this third paper also report (see pages 3 and 4) that they "observe a pronounced task reorientation towards math in finance and business occupations, which is associated with a change in the types of education required in these occupations." (Emphasis added.) In other words, they observe a change in education requirements for multiple occupations, one that (especially in finance) is "more pronounced among experienced workers."[2] Additionally, the paper corroborates that the drift of STEM graduates to finance is simply a result of people finding the best match of talent and innovation: These empirical patterns are associated with profound technological changes affecting the financial industry more than the rest of the economy. Finance is an information‐intensive industry that benefited from improvements in information and communication technologies (ICT) more than other industries did. The STEM biasedness in the demand of college graduates is consistent with the complementarity between ICT technologies and STEM graduates.
Finally, Marin and Vona report (see graph B on page 10) the share of hours worked by college graduates in the finance industry for both STEM and non‐STEM graduates between 1980 and 2020. Both STEM and non‐STEM groups display an increasing trend, and the share for non‐STEM graduates remains roughly two percentage points higher than for STEM graduates for the full period. Though not quite as damning as the previous two papers, this one, too, fails to support the idea that finance has started claiming a disproportionate share of talent. So, on balance, none of this evidence – especially not the papers cited by American Compass – supports the idea that finance is responsible for robbing the nation's businesses of talent. Nor, as American Compass argues in Confronting Coin‐Flip Capitalism, does any of this evidence support that finance is robbing talent "from the real economy" and "further discouraging productive investment." On page 102 of his book, Cass supports the "tracking of less academically talented students toward vocational training," so he may have some optimal employment arrangement in mind for the financial sector. Perhaps someone else at American Compass has some idea what the optimal quantity of workers should be in the financial sector, but the "Financialization" chapter does not mention it. In the next post, we will discuss claims involving financialization's alleged effect on profits.
[1] Figure 1 and Figure 2 report annual average growth rates and actual amounts, respectively, for real annual pre‐tax wage and salary income, by sector, from 1968 to 2022, using the IPUMS-CPS, University of Minnesota, www.ipums.org.
[2] Figure VI (on p. 1571) from Philippon and Reshef (2012) also confirms this finding. Finance jobs dramatically increased in complexity while tasks in the rest of the labor market became substantially less complex.
Testifying before the Senate Banking Committee last week, Fed Chair Jay Powell acknowledged inflation has come down but suggested it hasn't slowed because of monetary policy. Insisting that the Fed still has work to do to bring inflation down, he told the Committee: I won't say [food and energy are] not affected at all by monetary policy, but they're principally affected by other things in the economy. Really, where monetary policy takes effect is in the service sector, and that's where we haven't seen much progress. Inflation, broadly, is coming down, but as I said in my remarks, we still have a long way to go. Inflation's still running between 4 and 5 percent.
Powell's remarks bring up several interesting policy questions. For starters, the Fed does not have any particularly good price setting powers for different sectors of the economy, which is why all economists learn that monetary policy tries to stabilize the overall price level. Put differently, there is no reason to expect the Fed's tightening to affect only the services sector. Given that service‐based companies are generally less capital intensive than goods‐producing companies, it makes sense that the service sector may be even less responsive – at least directly – to monetary policy changes. Moreover, from February through April the average monthly change in the services category for Personal Consumption Expenditures is very close to its long‐term average. The long‐term average monthly change, measured from January 1959 to April 2023, is 0.32 percent, while the average change from February 2023 to April 2023 (the three most recent dates available) is 0.35 percent. So, price changes in the service sector have been trending down. It's also clear the annual rates of PCE services price increases are elevated at least partly due to the below average changes experienced prior to the COVID crisis. The average monthly change from January 2010 to February 2022, for instance, was just 0.2 percent, while the average from March 2022 to April 2023 was 0.45 percent. Beyond these simple comparisons of percentages, more sophisticated research suggests that there is little reason to expect monetary policy to have much of an effect on prices in the services industry. As a Cato study using a VAR technique finds, Fed policy has hardly mattered in explaining inflation (services or otherwise). Figure 1 below reproduces the breakdown of inflation into its demand, supply, and monetary policy components from 1960 onwards. As the graph shows, supply factors dominate – they account for over 80% of the variation in service‐sector inflation, both in the short‐term and long‐term. In the near term, monetary policy explains less than 2% of inflation. In the longer term, the effects increase but never account for more than 5% of service‐sector inflation.
Figure 1: Contributions to Various PCE Inflation Metrics by Source If, as some suggest, the Fed tries to rapidly tighten credit conditions now, it would be doing so primarily because the month‐to‐month change in service sector prices remains above its long‐term average. For the last three months, this average change was just 0.027 percentage points higher than its long‐term average. For the previous 12 months, it was only 0.13 percentage points higher. As we've argued before, it seems perfectly reasonable that the members of the Federal Open Market Committee would pause their tightening campaign. As a larger issue, it is unclear why people would want any government agency to have the ability to constrain credit for arbitrary reasons such as those discussed above. For a detailed analysis, please see this Cato working paper.