Macro Roundup

OECD also has the household disposable income measure we've looked at in the past. The "gross" series captures transfers

Here are (some of) OECD's AIC series from the National Accounts data

OECD “Actual Individual Consumption Per Head At The Price Levels And ppP Of Year 2010,” National Accounts Of OECD Countries, 2019, https://read.oecd-ilibrary.org/economics/national-accounts-of-oecd-countries/volume-2019/issue-1_g2g9fe48-en

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OECD “Household Disposable Income Gross Adjusted US Dollars/Capita 2018 Or Latest Available,” OECD, Accessed May 2020, https://data.oecd.org/hha/household-disposable-income.htm

This is an interesting job market paper from some Boston University gradate students on the average propensity to consume by income level, note that Kotlikoff and Restrepo offered comments on it.

"....The answer to the old question whether the rich save more is still debatable. We define the average propensity to consume (APC) out of remaining lifetime net resources. Lifetime net resources consist of lifetime private wealth and human wealth, deducting net taxes....We define remaining lifetime net resources (also referred as net resources or resources) as the sum of private wealth and human wealth, deducting lifetime net taxes..... We use a novel software TFA, a detailed life-cycle consumption-smoothing program, to calculate human wealth and net taxes using the Health and Retirement Study data. Because of potential consumption behavioral factors that are linked to the ability to accumulate wealth, we construct wealth luck instruments to resolve the endogeneity issue. We identify a strong negative relationship between the APC and lifetime net resources. We divide households into five quintile groups by resources. The predicted APC of the highest resources cohort is about 0.01, which is three standard deviations smaller than the lowest resource cohort. Our finding shows that the rich consume less and save more. Testable implications of models indicate that both bequest motives and heterogeneity explain why the rich save more. The results do not change if we consider heterogeneous borrowing constraints among households. Breakdown of resources into four components, including liquid and illiquid assets, human wealth, and net taxes, shows that consumption rate does not decrease in liquid assets...."Abnormally large return rates causally increase resources and we assume households receive large return rates because of pure luck. Our key result is that consumption rate decreases in resources in the IV regression. Average propensity to consume (APC) decreases significantly and economically fast from 0.09 for the bottom 20% resources quintile to about 0.01 for the top 20% resources quintile. The difference is about 3 standard deviations. By testable implications in the model part, we conclude that bequest motives can explain why the rich save more..."

Elias Ilin, Victor Ye and Manni Yu, "Do the Rich Save More?," Boston University, October 2019, https://drive.google.com/file/d/1jPbGQX7Ngx6Pa_-Qg9am9m-iq1q8wBMg/view

new study finds a Flynn Effect was found for IQs ≥ 130, and a negative effect for IQs ≤ 70 though the negative Flynn effect for those with lower ability was worth highlighting"....lower ability levels are exhibiting worsening IQ over time..."

Jonathan Platt,Katherine Keyes, KatieMcLaughlin, Alan Kaufman, "The Flynn effect for fluid IQ may not generalize to all ages or ability levels: A population-based study of 10,000 US adolescents,"Intelligence, November-December 2019, https://www.sciencedirect.com/science/article/abs/pii/S0160289619301679

"....Generational changes in IQ (the Flynn Effect) have been extensively researched and debated. Within the US, gains of 3 points per decade have been accepted as consistent across age and ability level, suggesting that tests with outdated norms yield spuriously high IQs. However, findings are generally based on small samples, have not been validated across ability levels, and conflict with reverse effects recently identified in Scandinavia and other countries. Using a well-validated measure of fluid intelligence, we investigated the Flynn Effect by comparing scores normed in 1989 and 2003, among a representative sample of American adolescents ages 13-18 (n = 10,073). Additionally, we examined Flynn Effect variation by age, sex, ability level, parental age, and SES. Adjusted mean IQ differences per decade were calculated using generalized linear models. Overall the Flynn Effect was not significant; however, effects varied substantially by age and ability level. IQs increased 2.3 points at age 13 (95% CI = 2.0, 2.7), but decreased 1.6 points at age 18 (95% CI = −2.1, −1.2). IQs decreased 4.9 points for those with IQ ≤ 70 (95% CI = −4.9, −4.8), but increased 3.5 points among those with IQ ≥ 130 (95% CI = 3.4, 3.6).The Flynn Effect was not meaningfully related to other background variables. Using the largest sample of US adolescent IQs to date, we demonstrate significant heterogeneity in fluid IQ changes over time. Reverse Flynn Effects at age 18 are consistent with previous data, and those with lower ability levels are exhibiting worsening IQ over time. Findings by age and ability level challenge generalizing IQ trends throughout the general population...".

Pethokoukis on risks of redistribution, “…Maybe it’s worth reviewing, say, newsfrom the St. Louis Fed where “the evidence suggests that both innovation and venture capital investment increased significantly after the Tax Cuts and Jobs Act.” …One more thing: That bit from the New York Times about “experts have an imperfect understanding of what drives innovation” caught in my brain. Where had I read something similar? Then it hit me. Check out this from “Taxation and innovation in the 20th century” by Ufuk Akcigit, John Grigsby, Tom Nicholas, and Stefanie Stantcheva: “Understanding how taxation influences innovation is of central importance to create investment incentives for R&D, yet our knowledge remains limited due to a lack of data, especially covering a long period of time.”…”

James Pethokoukis, "Here’s just how big a risk Elizabeth Warren and The New York Times want America to take,"American Enterprise Institute, November 8, 2019, https://www.aei.org/economics/heres-just-how-big-a-risk-elizabeth-warren-and-the-new-york-times-want-america-to-take/

Here’s just how big a risk Elizabeth Warren and The New York Times want America to take

The New York Times editorial board is truly, madly, deeply confident that if the United States taxes rich people and corporations in a way no other advanced economy does, all will be well. Keep calm and carry on, Silicon Valley! Although conceding in a new editorial that “experts have an imperfect understanding of what drives innovation,” Team NYT goes on to trippingly conclude that “there is little evidence to justify … concern that tax increases of the magnitude proposed by Ms. Warren and other candidates for the Democratic presidential nomination would meaningfully discourage innovation, investment or economic growth.”

Or not. Maybe it’s worth reviewing, say, news from the St. Louis Fed where “the evidence suggests that both innovation and venture capital investment increased significantly after the Tax Cuts and Jobs Act.”

But let’s think broadly for a moment about the novel and risky experiment being proposed by the “broken capitalism” crowd. The World Economic Forum’s new global competitiveness report ranks the US economy as the most competitive big economy in the world, calling it an “innovation powerhouse.” Likewise, no other big economy generates as many super-entrepreneurs or high-impact startups. Jeff Bezos, the Google Guys, Mark Zuckerberg, and Elon Musk aren’t superrich because their parents were billionaires or they were cronies of top politicians. They built companies that consumers and customers greatly value, with their wealth — as massive as it is — reflecting only a tiny portion of that value creation.

Now here comes the Warren plan. First, tax the wealthy in a way and at levels that most other advanced economies have abandoned. (Only four of the 15 European countries that tried even a tiny wealth tax in recent years have stuck with it. And, by the way, the much-praised egalitarian nations of Scandinavia have as many billionaires, relatively, as the US does)

Second, tax corporations at levels all other advanced economies reject. (Rich countries have top corporate rates only slightly higher than the US rate, with Scandinavia about the same.)

Finally, characterize the entire economy as “rigged” and thus all successful people and companies as pretty much corrupt flim-flammers. (When Europeans wonder where their Googles, Amazons, and Apples are, the issue of a corrosive anti-success attitude is frequently mentioned). But what big lesson does Warren take from Europe? That there need to be worker representatives on corporate boards, like in Germany.

One more thing: That bit from the New York Times about “experts have an imperfect understanding of what drives innovation” caught in my brain. Where had I read something similar? Then it hit me. Check out this from “Taxation and innovation in the 20th century” by Ufuk Akcigit, John Grigsby, Tom Nicholas, and Stefanie Stantcheva: “Understanding how taxation influences innovation is of central importance to create investment incentives for R&D, yet our knowledge remains limited due to a lack of data, especially covering a long period of time.”

Well, the NYT got it right — but only partly. The researchers then conclude as follows in a column based on their work (italics by me): “This column uses newly constructed datasets from the 20th century to examine the effects of both personal and corporate income taxation on inventors, as well as on firms that do R&D. It finds consistently negative effects of high taxes on innovation over time as well as on individual inventors and firms.”

Look, the US needs to become even more innovative and productive. At least, that’s if it wants to grow anywhere near as fast in the future as it has in the past. A novel experiment in heavy taxation of risk taking and investment seems misguided at best.

paper finds that in the mid 1990's the relationship btw an industry’s q and its funding rate changed. prior to 1996 the "high-funded" industries generally had a higher q than the "low-funded" industries after 1996 that relationship inverted, "high-funded" industries had a lower q then "low-funded" industries.

"....Assuming that a proxy for an industry’s Tobin’s q measures the industry’s growth opportunities, we find that, until the middle of the 1990s, the industries with the highest funding rates were industries with better growth opportunities relative to the lowest funding rate industries, as expected for functionally efficient capital markets. After the middle of the 1990s, capital no longer flows more to the industries with the best growth opportunities. From the middle of the 1990s until 2014, industries with the lowest funding rates have better growth opportunities than the industries with the highest funding rates. We show that this change is entirely due to high q firms that invest less after the middle of the 1990s and use the resulting excess cash flow to repurchase shares. Without these firms, there is a positive correlation between an industry’s funding rate and its growth opportunities throughout the sample period rather than only before the middle of the 1990s.We reach these conclusions using Tobin’s q as a measure of industry growth opportunities, which is defined as the ratio of the market value of the assets of the industry divided by their book value. As we rely on the use of medians and non-parametric tests, however, our conclusions are less sensitive to Tobin’s q mismeasurement than typical parametric approaches. Nevertheless, we confirm that our conclusions are robust using Tobin’s q estimates that account for intangibles and are not an artifact of measurement error in Tobin’s q......The median q of the industries in the top funding rate quintile is 1.33. This median q is not significantly different from the median q of 1.29 for the industries in the bottom funding rate quintile. We expect the greater inflow of resources to be associated with higher capital expenditures and higher asset growth for the most funded industries in comparison to the least funded industries. We find that this is the case. The differences in capital expenditures and asset growth between the two quintiles of industries are large. For capital expenditures, the median ratio of capital expenditures to assets is 66% higher for the most highly funded industries compared to the least funded industries. Asset growth of the most highly funded industries is more than three times the asset growth of the least funded industries......Given the change in regime that appears to take place in the middle of the 1990s, we split our sample into two sub-periods. The first sub-period is from 1971 to the end of 1996 and the second from the end of 1996 to 2014. With this split, we find that in the first sub-period the allocation of capital is exactly what one would expect from the efficient capital allocation hypothesis. During this sub-period, the median Tobin’s q of the industries that are most highly funded is 17% higher than the Tobin’s q of the least funded industries (1.30 versus 1.11) and the difference is significant at the 1% level. A significant q difference emerges between the two groups of industries three years before the year when these industries are classified as most-funded and least-funded. The q difference disappears in year 2 after the selection year. Consequently, the evidence for q is also supportive of the convergence hypothesis before the end of 1996 After 1996, the pattern is opposite. The median Tobin’s q of the industries that are most- funded is 15% lower than the Tobin’s q of the least funded industries (1.37 versus 1.58). The difference is significant at the 5% level and is extremely persistent as it is significant for five years after industries are assigned to the funding rate quintiles. Further, the difference five years after assignment is greater than in the year of assignment, which directly contradicts the convergence hypothesis.....In summary, the relation between an industry’s q and its funding rate changes drastically around the middle of the 1990s. In the 25 sample years before 1996, the high-funded industries (top funding rate quintile) tend to have a higher q than the low-funded industries (bottom funding rate quintile). Further, there is a positive correlation between industry q and the funding rate across all sample industries. After 1996, the opposite occurs: the high-funded industries have a lower q than the low-funded industries and the cross-industry correlation between industry q and the industry funding rate is negative.....With functionally efficient capital markets, we expect capital to flow more to the industries with the best growth opportunities. As a result, these industries should invest more and see their assets grow more relative to industries with the worst growth opportunities. We find that industries that receive more funds have a higher industry Tobin’s q until the mid-1990s, but not since then. Since industries with a higher funding rate grow more, there is a negative correlation not only between an industry’s funding rate and industry q but also between capital expenditures and industry q since the mid-1990s. We show that capital no longer flows more to the industries with the best growth opportunities because, since the middle of the 1990s, firms in high q industries increasingly repurchase shares rather than raise more funding from the capital markets...."

Dong Lee, Hyun-Han Shin and René Stulz, "Why does capital no longer flow more to the industries with the best growth opportunities?," Ohio State University, December 2016, https://papers.ssrn.com/sol3/papers.cfm