Results for “concentration” 182 found
U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial concentration of patents and identify an underlying stability in their distribution. Software patents have exploded to account for about half of patents today, and these patents are highly concentrated in tech centers. Tech centers also account for a growing share of non-software patents, but the reallocation, by contrast, is entirely from the five largest population centers in 1980. Non-software patenting is stable for most cities, with anchor tenants like universities playing important roles, suggesting the growing concentration of invention may be nearing its end. Immigrant inventors and new businesses aided in the spatial transformation.
That is new research by Brad Chattergoon and William R. Kerr.
Here are some new results:
This paper uses new data to reexamine trends in concentration in U.S. markets from 1994 to 2019. The paper’s main contribution is to construct concentration measures that reflect narrowly defined consumption-based product markets, as would be defined in an antitrust setting, while accounting for cross-brand ownership, and to do so over a broad range of consumer goods and services. Our findings differ substantially from well established results using production data. We find that 42.2% of the industries in our sample are “highly concentrated” as defined by the U.S. Horizontal Merger Guidelines, which is much higher than previous results. Also in contrast with the previous literature, we find that product market concentration has been decreasing since 1994. This finding holds at the national level and also when product markets are defined locally in 29 state groups. We find increasing concentration once markets are aggregated to a broader sector level. We argue that these two diverging trends are best explained by a simple theoretical model based on Melitz and Ottaviano (2008), in which the costs of a firm supplying adjacent geographic or product markets falls over time, and efficient firms enter each others’ home product markets.
That is a new NBER working paper by C. Lanier Benkard, Ali Kurukoglu, and Anthony Lee Zhang. It is very supportive of recent research by Estaben Rossi-Hansberg (here and here, with co-authors) that market concentration simply has not been going up in recent times.
Here is a new piece from Joe Kennedy, here are his summary points:
Despite the persistent claims that increased market power has hurt workers, the scholarly evidence is weak, while the macroeconomic data is strong and clear in showing that this is not the principal cause.
Labor’s share of income has declined slightly over the past two decades, but not principally because capital’s share of income has increased.
Most of the decline is offset by an increase in rental income—what renters pay and what the imputed rent homeowners pay for their house. This increase is due to restricted housing markets, not growing employer power in product or labor markets.
Antitrust policy is not causing the drop in labor share, so changing it is not the solution. For issues such as employer collusion over wages or excessive use of noncompete agreements, antitrust authorities already have power to act.
Stringent antitrust policy would do little to raise the labor share of income, but it could very well reduce investment and productivity growth. The better way to help workers is with pro-growth, pro-innovation policies that boost productivity.
This probable untruth received a big boost about three years ago, in part through mood affiliation. Perhaps other data will yet rescue it, but for now I am watching to see how long it will take to die away. Ten years perhaps?
A new paper by Autor, Dorn, Katz, Patterson and Van Reenen (some real heavyweights) rebuts the notion that market concentration is rising because of inadequate antitrust concentration:
The fall of labor’s share of GDP in the United States and many other countries in recent decades is we ll documented but its causes remain uncertain. Existing empirical assessments typically rely on industry or macro data obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes push sales towards the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms, which have high markups and a low labor share of value-added. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm’s markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.
Here is coverage from Peter Orszag. As I’ve said before, people are opting for Philippon’s Great Reversal story because of ideology and convenience and mood affiliation, but it is not supported by the facts.
As you might expect, it is coming from Chang Tsai-Hsieh and Esteban Rossi-Hansberg, here is their abstract:
The rise in national industry concentration in the US between 1977 and 2013 is driven by a new industrial revolution in three broad non-traded sectors: services, retail, and wholesale. Sectors where national concentration is rising have increased their share of employment, and the expansion is entirely driven by the number of local markets served by firms. Firm employment per market has either increased slightly at the MSA level, or decreased substantially at the county or establishment levels. In industries with increasing concentration, the expansion into more markets is more pronounced for the top 10% firms, but is present for the bottom 90% as well. These trends have not been accompanied by economy-wide concentration. Top U.S. firms are increasingly specialized in sectors with rising industry concentration, but their aggregate employment share has remained roughly stable. We argue that these facts are consistent with the availability of a new set of fixed-cost technologies that enable adopters to produce at lower marginal costs in all markets. We present a simple model of firm size and market entry to describe the menu of new technologies and trace its implications.
This is likely to prove one of the most important papers of the year, here is the pdf link. The authors open with the example of The Cheesecake Factory, and also health care:
The standardization of production over a large number of establishments that has taken place in sit-down restaurant meals due to companies such as the Cheesecake Factory has taken place in many non-traded sectors. Take hospitals as another example. Four decades ago, about 85% of hospitals were single establishment non-profits. Today, more than 60% of hospitals are owned by forprofit chains or are part of a large network of hospitals owned by an academic institution (such as the University of Chicago Hospitals).
…rising concentration in these sectors is entirely driven by an increase the number of local markets served by the top firms.
Here is a key point:
…we find that total employment rises substantially in industries with rising concentration. This is true even when we look at total employment of the smaller firms in these industries. This evidence is consistent with our view that increasing concentration is driven by new ICT-enabled technologies that ultimately raise aggregate industry TFP. It is not consistent with the view that concentration is due to declining competition or entry barriers, as suggested by Gutierrez and Philippon (2017) and Furman and Orszag (2018), as these forces will result in a decline in industry employment.
This is interesting too, and it departs from say what Amazon is doing:
…we show that the top firms in the economy as a whole have become increasingly specialized in narrow set of sectors, and these are precisely the non-traded sectors that have undergone an industrial revolution. At the same time, top firms have exited many sectors. The net effect is that there is essentially no change in concentration by the top firms in the economy as a whole. The “super-star” firms of today’s economy are larger in their chosen sectors and have unleashed productivity growth in these sectors, but they are not any larger as a share of the aggregate economy.
The paper is titled “The Industrial Revolution in Services.“
That is part of the title of a new paper by Sharat Ganapati, here is the abstract:
American industries have grown more concentrated over the last few decades, driven primarily by the growth of the very largest firms. Classical economics implies that this should lead to hikes in prices, reduction in output, and decreases in consumer welfare. I investigate forty years of data from 1972-2012 using publicly available market shares and price indices for both the manufacturing and non-manufacturing sectors and find mixed evidence. Manufacturing concentration increases are indeed correlated with slightly higher prices, but not lower output. However concentration increases are correlated with increases in productivity, offsetting a large portion of the price increase. In contrast, non-manufacturing concentration increases over the last twenty years are not correlated with observable price changes, but are correlated with increases in output.
In other words, the output restrictions are not there. The amazing thing is that, over the last few years, I have seen a few dozen journalists and also economists handle this question, without ever asking much less trying to answer this question (Noah Smith being an exception).
Already, there are 14,000 one-story cinder block Dollar Generals in the U.S.—outnumbering by a few hundred the coffee chain’s domestic footprint. Fold in the second-biggest dollar chain, Dollar Tree, and the number of stores, 27,465, exceeds the 22,375 outlets of CVS, Rite Aid, and Walgreens combined.
Here is the full Bloomberg piece, by Mya Frazier. One point here is that “retail concentration,” which we do observe in the data, is unlikely to lead to very high prices. A subtler point is that the dollar store sector itself is somewhat concentrated. But that is yet another way of seeing why concentration indices can be misleading: “They’ve taken over a big chunk of the nation’s dollar stores!” isn’t exactly a recipe for sustained high prices, if anything the contrary. Yet another point is that we may be rather deliberately moving to an uglier but cheaper world.
That is the topic of a new paper by James E. Bessen, and it appears the answer is yes:
Industry concentration has been rising in the US since 1980. Why? This paper explores the role of proprietary information technology systems (IT), which could increase industry concentration by raising the productivity of top firms relative to others. Using instrumental variable estimates, this paper finds that industry IT system use is strongly associated with the level and growth of industry concentration. The paper also finds that IT system use is associated with greater plant size, greater labor productivity, and greater operating margins for the top four firms in each industry compared to the rest. Successful IT systems appear to play a major role in the recent increases in industry concentration and in profit margins, moreso than a general decline in competition.
I expect further work in this area.
From Lyman Stone:
…no matter the adjustment, the US is always one of the lowest-concentration countries, along with China, India, Brazil, Germany, and Japan. We have a very diversified metropolitan ecology, as do those countries.
Third, I’ve highlighted Nordic (purple) and Anglo (orange) countries. Notice that all of the Nordics are much more concentrated than the United States, as are all of the Anglo countries! That one was surprising to me, as I expected large countries like Australia and Canada to be much more comparable to the US. As it is, in terms of population concentration, Poland is more American than Canada.
…my most concentrated countries are indeed Mongolia and Peru. Not kidding here. Both results surprised me given that both countries are fairly large and have big rural populations and, in Peru’s case, my impression was that there were a good number of meaningfully sized cities. But it turns out that, in Peru, Lima metro area alone is almost 30% of the population, and then the other cities are pretty small by comparison; and Lima is, of course, also the capital. In Mongolia, Ulaanbaatar metro area is over half of the nation’s population!
So. If you want to know what country is the most city-state-ish, I would have to answer… it’s Mongolia.
Here is the full essay, noting that Singapore is normalized as a polar option at 100% and thus cannot win the competition. Also scroll down to the interesting graph on “State and Local Taxes Collected as a Share of GDP”: I am surprised to see Sweden come in at number one. For all the talk of American federalism, we are just at the OECD average and in fact slightly behind Iceland in these rankings.
Dayton sits on one side of a growing divide among American cities, in which a small number of metro areas vacuum up a large number of college graduates and the rest struggle to keep those they have.
The winners are cities like Bridgeport, Conn., San Francisco and Raleigh, N.C., where more than 40 percent of the population has a college degree. Cities like Youngstown, Ohio, Bakersfield, Calif., and Lakeland, Fla., where less than a fifth of the population has a college degree, are being left behind. The divide shows signs of widening as college graduates gravitate to places with a lot of other college graduates and the atmosphere that creates.
“This is one of the most important developments in recent economic history of this country,” said Enrico Moretti, an economist at the University of California, Berkeley, who just published a book on the topic, “The New Geography of Jobs.”
Here is more.
Many people have bandied about numbers suggesting that the market for health insurance is highly concentrated. Here is the President:
But these statistics only include people insured by "insurance companies" even though nationally just over half of all employees get their health insurance from a firm that self-insures. In other words, as John Lott points out, over half of the market for insurance is being left out of these concentration statistics.
Since about half of employees are insured by a self-insurer, concentration statistics–as typically presented –should be cut roughly in half (precise numbers vary by state). Firms that self-insure typically outsource benefits management and claim
administration to highly competitive third party administrators. A key fact according to this paper (which is outdated although I wouldn't expect the basic finding to have changed) is that the populations served, the benefits paid and the premiums paid are about the same for firms that self-insure and firms that buy insurance from a health insurance company. Thus, concentration among that part of the market served by health insurance firms appears to be well disciplined by the larger market for self-insurance.
It is commonly alleged that media concentration is on the rise. Ben Compaine, in the January issue of Reason magazine (not yet on-line), debunks this myth. In the mid 1980s, the top ten media companies accounted for 38 percent of total revenue. In the late 1990s the figure was higher, but only barely, up to 41 percent. More importantly, different companies shape our media experiences. Where was Comcast, now the largest cable company, twenty years ago? Bertelsmann, now a giant, was barely visible in American markets. Amazon.com and other Internet-related enterprises are new on the scene as well. If media companies are monopolies, their market power is extremely fragile.
Nor are smaller media outlets necessarily better than the larger conglomerates. The larger outlets are much more likely to win awards for their quality, nor are they obviously more biased. Clear Channel radio is now a poster boy for media critics, but its 1200 stations comprise only slightly more than ten percent of a total of 10,500 American stations. Note also that there were only 8000 radio stations in 1980. We now have satellite radio and Internet radio as well.
Compaine makes a nice point in closing:
It may indeed be that at any given moment 80 percent of the audience is viewing or reading or listening to something from the 10 largest media players. But that does not mean it is the same 80 percent all the time, or that it is cause for concern.
The bottom line: When it comes to media, we have more choice and more competition than ever before.
This paper documents a longitudinal crisis of midlife among the inhabitants of rich nations. Yet middle-aged citizens in our data sets are close to their peak earnings, have typically experienced little or no illness, reside in some of the safest countries in the world, and live in the most prosperous era in human history. This is paradoxical and troubling. The finding is consistent, however, with the prediction – one little-known to economists – of Elliott Jaques (1965). Our analysis does not rest on elementary cross-sectional analysis. Instead the paper uses panel and through-time data on, in total, approximately 500,000 individuals. It checks that the key results are not due to cohort effects. Nor do we rely on simple life-satisfaction measures. The paper shows that there are approximately quadratic hill-shaped patterns in data on midlife suicide, sleeping problems, alcohol dependence, concentration difficulties, memory problems, intense job strain, disabling headaches, suicidal feelings, and extreme depression. We believe the seriousness of this societal problem has not been grasped by the affluent world’s policy-makers.
That is from a new NBER working paper by .
Exposure to lead especially in childhood can have a lifetime of negative consequences:
According to the WHO, there is no known safe level of lead exposure. Relatively low levels of lead exposure that were previously considered ‘safe’ have been shown to damage children’s health and impair their cognitive development. Lead is a potent neurotoxin that, with even low-level exposure, is associated with a reduction in IQ scores, shortened attention spans and potentially violent and even criminal behaviour later in life. Children under the age of 5 years are at the greatest risk of suffering lifelong neurological, cognitive and physical damage and even death from lead poisoning.
In recent decades, some countries have begun to address the problem by removing lead from gasoline, paint, and pipes. Lead poisoning, however, remains a serious problem in South Asian countries such as Bangladesh. But where is the lead coming from?
Incredibly, one small study that examined the blood of pregnant women in Bangladesh for lead isotopes concluded that a major source of lead exposure is from turmeric consumption. Turmeric is a spice used in India and Bangladesh and other South East Asian both in cooking and for health. Lead from the soil could enter turmeric but the major cause seems to be lead pigments that are illegally added to turmeric to give it a pleasing looking yellow color. Lead in spices can exceed national limits by hundreds of times.
Our results indicate that turmeric Pb concentrations were as high as 1151 μg/g (Table 2). Eight of 28 market turmeric samples contained Pb above the 2.5 μg/g Government of Bangladesh limit for Pb in turmeric (Table S6). Using the simplified bioaccessibility extraction test, prior studies reported that the bioaccessible fraction of Pb in turmeric varied from 42.9 to 70% of total Pb. (12,39) Given that turmeric is used in dishes containing tamarind and other acidic ingredients, cooking could further increase the bioaccessibility of the Pb. (40) Other researchers hypothesized that PbCrO4 is added to turmeric to enhance its color or weight, but they did not test any turmeric processing powders to assess molar Pb/Cr ratios or Pb speciation. (12) We found that the yellow pigment powders used in turmeric processing contained 6–10% Pb by weight (61 870–101 300 μg/g Pb). Both pigment and turmeric samples also contained elevated chromium (Cr) concentrations, with average Pb/Cr molar ratios of 1.3 ± 0.06 (2 SD) and 1.1 ± 0.8 (2 SD), respectively. X-ray diffraction analyses indicated that all three pigment samples contained lead chromate (PbCrO4, 10–15%), that two of the pigments also contained lead carbonate (PbCO3, 2–3%), and that one also contained lead sulfate (PbSO4, 3%). Because PbCO3 and PbSO4 have a greater bioaccessibility than PbCrO4, our results support the parallel findings of high turmeric bioaccessibility reported in other studies. (12,39,41)
Respondents described turmeric, primarily purchased as a loose powder, as one of three essential spices consumed daily, alongside chili powder and cumin. Women reported adding turmeric in heaping spoonfuls to curries and other dishes for at least one meal per day.
I’d also worry about lead adulteration of safron, another yellow spice. The problem is not limited to Bangladesh, significant amounts of lead have been found in spices sold in in New York.
Hat tip: Alexander Berger.
Photo Credit: MaxPixel.
We use the price effects caused by the passage of rent control in St. Paul, Minnesota in 2021, to study the transfer of wealth across income groups. First, we find that rent control caused property values to fall by 6-7%, for an aggregate loss of $1.6 billion. Both owner-occupied and rental properties lost value, but the losses were larger for rental properties, and in neighborhoods with a higher concentration of rentals. Second, leveraging administrative parcel-level data, we find that the tenants who gained the most from rent control had higher incomes and were more likely to be white, while the owners who lost the most had lower incomes and were more likely to be minorities. For properties with high-income owners and low-income tenants, the transfer of wealth was close to zero. Thus, to the extent that rent control is intended to transfer wealth from high-income to low-income households, the realized impact of the law was the opposite of its intention.