Health reporters have difficulty writing about preexisting conditions accurately.

This article, for example, commits a number of errors when it states: “About 54 million, or 27%, of U.S. adults under age 65 had a pre‐​existing condition in 2018 that would have rendered them uninsurable on the individual insurance market before Obamacare, according to an analysis by the Kaiser Family Foundation.”

• First, it is not accurate to say those conditions were uninsurable on the individual market. The individual market could have insured maybe 99.99 percent of them with secure, long‐​term coverage. All that was necessary was that those individuals purchase coverage before those conditions manifested themselves. The reason the individual market didn’t is that the federal government, via the tax exclusion for employer‐​paid premiums, effectively penalizes those individuals if they purchased secure, long‐​term, individual‐​market coverage. So right there, the article is blaming the victim.
• Second, the vast majority of those conditions were insured. Unfortunately, since they were insured through employer‐​sponsored insurance, it was short‐​term coverage that would last only as long as their relationship with the employer. When that relationship ends, so does the insurance. Crucially, what would have continued to be insured conditions on the individual market instead became uninsured and uninsurable preexisting conditions. This is not the fault of the individual market! It is a consequence of government penalizing people if they used the individual market. This error recurs when the article states, “Among those hurt most under the prior system were older adults who were laid off before age 65, who couldn’t find affordable coverage — or any coverage at all — to hold them over until they became eligible for Medicare.” The “system” that leaves these folks without coverage is not the individual market; it is the government. And it is not “prior.” With every passing day, federal tax policy is still turning otherwise‐​insurable conditions into uninsured and uninsurable preexisting conditions.
• Third, ObamaCare does not make those conditions insurable. It uses coercion to subsidize them. There is a big difference. Insurance is the pooling of like risk. If a health loss has already occurred, it is no longer a risk; it is a loss. ObamaCare does not and cannot insure a health loss that has already materialized, any more than one can insure a building that has already burned or a car that has already crashed. Insurance aligns incentives so that people voluntarily pay the medical bills of complete strangers. ObamaCare attempts to pay people’s medical bills by forcing others to act against their own perceived economic self‐​interest (to buy coverage they don’t want, to pay inflated premiums, to pay higher taxes, etc.). That is not insurance. The incentives for people to defect from such coercive arrangements are far greater, which means far more patients fall through the cracks.

Additional problems appear in this sentence: “Rhetoric aside, Trump’s actions as president have actively undermined pre‐​existing condition protections, some experts say.”

• First, it begins with “rhetoric aside” but ends by employing ideological rhetoric. The above links detail just some of the problems ObamaCare’s preexisting conditions provisions are creating for all enrollees, but particularly for very sick patients. It is therefore at best incomplete and at worst propaganda to refer to those provisions as “protections.” ObamaCare supporters call those provisions “protections” to hide that there are inherent tradeoffs, including higher premiums and lower‐​quality coverage. To call those provisions “protections” is to engage in card‐​stacking ideological rhetoric–i.e., to disseminate propaganda. A better, ideologically neutral term is “provisions.”
• Second, speaking of neutrality, the article does not acknowledge that other researchers (ahem) argue Trump has expanded protections against preexisting conditions and done more to solve that (largely government‐​created) problem than Biden has. Allowing consumers and insurers to make full use of the exemption for short‐​term, limited duration plans can help save people from “the prior system,” which strips people of their coverage and leaves them with uninsured and uninsurable preexisting conditions. It can even save people in employer‐​sponsored plans from ending up with an uninsured and uninsurable preexisting condition. The article makes no mention of this feature of short‐​term plans.

Getting this stuff right is hard. The economics of preexisting conditions is complex. An even bigger challenge is that any reporter who wants to get it right will run into an buzzsaw of health policy wonks, reporters, and editors who will disagree with whatever they write.

Ryan Bourne and I examined the economics and politics of wealth inequality in this 2019 study. We considered whether the wealthy tilt our political system in a conservative direction, which many liberals worry about. We found that the political preferences of the wealthy are not much different than other Americans, and that plenty of top wealth is plowed into liberal causes.

That reality struck me in examining income, sales, and property tax measures on state ballots. Two‐​thirds of income and sales tax questions on ballots are for higher taxes, not lower taxes, and wealthy liberals often fund the tax‐​increase proposals. Funding by businesses and labor unions also play a large role in ballot battles over taxes.

Sometimes wealthy people campaign to raise taxes on the wealthy. In Illinois this year, billionaire J.B. Pritzker has given $57 million to support a ballot measure to replace the state’s flat income tax with a multi‐​rate system aimed at hitting high earners. Billionaire Kenneth Griffin has contributed $47 million to the campaign against passage.

More often, wealthy people campaign to raise taxes on the non‐​wealthy. In many states, they have pushed to raise sales taxes, carbon taxes, gas taxes, soda taxes, and cigarette taxes.

The following are some wealthy folks and their tax‐​increase efforts, with the dollar figures from Ballotpedia unless otherwise linked:

• Mark Zuckerberg and his wife, Priscilla Chan, gave $7.1 million to support Proposition 15 in 2020 to raise California property taxes.
• Stacy Schusterman gave $500,000 and Pat Stryker gave $250,000 in 2020 to support Proposition EE to raise Colorado cigarette taxes.
• Bill Gates and Michael Bloomberg each gave $1 million to support Initiative 1631 in 2018 to impose a carbon tax in Washington. The initiative failed.
• Michael Bloomberg gave $2.1 million to oppose Measure 103 in 2018 to ban grocery taxes in Oregon. The measure failed.
• Gail Miller gave $250,000 to support Question 1 in 2018 to raise Utah gas taxes. The question failed.
• Merle Chambers and Judi Wagner each gave $100,000 to support Amendment 73 in 2018 to raise Colorado income taxes. The amendment failed.
• Peter Kelley, Laura Arnold, John Arnold, and Menno van Wyk each gave more than $100,000 to support Initiative 732 in 2016 to impose a carbon tax in Washington. The initiative failed.
• Stacy Schusterman gave $2 million, David Boren gave $462,000, and the George Kaiser foundation gave $350,000 to support Question 779 in 2016 to raise Oklahoma sales taxes. The question failed.
• Tom Steyer gave $11.5 million and Michael Bloomberg gave $500,000 to support Proposition 56 in 2016 to raise California cigarette taxes. The proposition passed.
• Tom Steyer gave $1.7 million to support Proposition 55 in 2016 to extend increases in California income taxes. The proposition passed.
• Michael Bloomberg gave $18 million to support ballot measures in San Francisco and Oakland to raise soda taxes in 2016. John and Laura Arnold gave $3.3 million in support of the San Francisco measure. Both measures passed. Bloomberg has spent millions of dollars on soda tax efforts in other cities.
• Bill and Melinda Gates gave $1 million to support Amendment 66 in 2013 to increase Colorado income taxes. The amendment failed.
• Molly Munger gave $44 million to support Proposition 38 in 2012 to raise California income taxes. This campaign was remarkable in that total campaign spending was $48 million in favor and just $42,000 against, but the proposition failed with just 29 percent voting in favor.
• Lance Armstrong gave $1.5 million and Michael Bloomberg gave $500,000 to support Proposition 29 in 2012 to increase California cigarette taxes. The proposition failed.
• Tom Steyer gave $29.6 million to support Proposition 39 in 2012 to increase California business taxes. The proposition passed.

If you favor limited government, you may want to avoid living in states such as California because they are dominated by liberal politicians. But you may also want to avoid such states because they are home to wealthy liberal elites frequently pushing to raise state taxes. They often fail, but they keep on trying.

For further notes on some of these ballot measures, see Cato’s governor report cards.

Conventional wisdom among the D.C. punditocracy is that protectionism, while likely bad economics, is good politics because it can boost critical “Rust Belt” swing states that have large manufacturing sectors and have been hit hard by globalization. A new St. Louis Fed study, however, shows why this rudimentary calculus is misguided.

Examining the effect of President Trump’s “trade wars” (i.e., tariffs and foreign retaliation) on U.S. manufacturing industries and states that are disproportionately dependent on imports or exports, authors Ana Maria Santacreu and Makenzie Peake find that several such states — including Michigan and Ohio — experienced weaker economic growth and employment in 2018 than their less‐​exposed neighbors. In particular, they make the following findings:

First, the U.S. manufacturing industries that more heavily rely on imported intermediate products (and are thus “exposed” to potential U.S. tariffs) are (i) Coke and petroleum; (ii) Motor vehicles and trailers; (iii) Other transport equipment; (iv) Basic metals; and (v) Rubber and plastic products. The U.S. states that most heavily specialize in these trade‐​exposed industries (and are thus “exposed” too) are (i) Louisiana; (ii) Michigan; (iii) Hawaii; (iv) Washington; and (v) Ohio. For Michigan, in particular, the authors note that it “is one of the top U.S. producers in the Motor vehicle and trailers industry, which accounts for 43 percent of its total value added.” And, as you can see from the map below, all of the states in America’s “auto alley” face similar levels of import reliance (and thus trade war exposure).

Second, the U.S. industries that export more intermediate goods to the world (and are thus “exposed” to potential retaliation by foreign governments) are (i) Other transport equipment; (ii) Computer, electronic, and optical; (iii) Machinery and equipment; (iv) Electrical equipment; and (v) Chemicals and pharmaceuticals. The states specializing in these products (and are thus “exposed” too) are (i) Washington; (ii) Connecticut; (iii) Massachusetts; (iv)
Arizona; (v) Rhode Island; (vi) Oregon; and (vii) California. Arizona’s exposure, the authors note, comes from specializing in computers and electronics, as well “other transport equipment.”

Third, states that were more exposed to President Trump’s trade wars — in terms of imports (U.S. tariffs), exports (foreign retaliation), or total trade (both) — experienced less GDP growth and even less employment growth in 2018. The following chart shows the strong negative correlations between state‐​level import/​export exposure and these measures of economic activity:

The authors therefore conclude (emphasis mine):

(i) There is a negative and significant correlation between the initial exposure to trade and economic activity; (ii) the negative correlation is stronger with employment growth than it is with output growth; and (iii) the negative correlation is stronger with import exposure than it is with export exposure. That is, those states more exposed to trade experienced lower increases or even decreases in output growth and employment growth between 2018 and 2019. These findings reflect that firms operating in states very exposed to trade adjusted their employment and production decisions after announcements of tariff increases. The adjustments were stronger in terms of employment than in terms of output, and they were stronger in states very exposed to U.S. tariffs than in states very exposed to retaliatory tariffs.

Fourth, a similar exercise for just the U.S.-China trade dispute, which only began in mid‐​2018 and accelerated after the period of review, again finds Michigan in the crosshairs and negative correlations between a state’s trade exposure and its economic performance. However, the correlations here are weaker overall.

Although the study’s authors are careful to note that these findings do not prove that President Trump’s trade wars caused these states’ weaker economic performance in 2018, they nevertheless state that the strong negative correlations between trade exposure and employment/​production suggest that the tariffs, retaliation, and related uncertainty played a significant role. Furthermore, their findings indicate that “the trade war initiated by the United States may have had a stronger impact on U.S. employment and production than what is found through the lenses of standard models of trade,” because those national models might mask the concentrated pain that U.S. tariffs and foreign retaliation inflicted on certain trade‐​exposed states.

One of those states is Michigan, which President Trump surprisingly won in 2016, has targeted again in 2020, but has trailed Democratic challenger Joe Biden by a wide margin since mid‐​2019. Trade‐​exposed battlegrounds Arizona and Ohio are closer, with Trump and Biden exchanging leads over the same period. Obviously, residents of these three states will cast their votes for a wide variety of reasons; culture, partisanship and personality may outweigh local economic performance; and COVID-19 has been a political and economic gamechanger this year. Nevertheless, the findings above — showing weaker jobs and output in trade‐​reliant swing states, and therefore indicating that Trump’s trade wars did significant economic harm in those states — should puncture the conventional wisdom that protectionism is a surefire political winner, even in the “Rust Belt.”

The detention of illegal immigrants is an important part of immigration enforcement. Immigrants who are apprehended at the border or in the interior of the United States are detained in Immigration and Customs Enforcement (ICE) facilities until they are removed from the United States. In recent years, many reports have surfaced of immigrants who have died while in detention or shortly after being released to medical facilities for treatment. This problem has worsened during the COVID-19 pandemic. The rate of death in ICE detention facilities is an important metric of how humane those facilities are.

There are two primary pieces of data required to calculate the death rate in immigration detention: The number of people in detention each year and the number of deaths. Immigration and Customs Enforcement (ICE) runs all of the detention facilities and they provide the number of deaths and admissions. The American Immigration Law Association provides some more recent numbers of deaths in detention, but I only include those that ICE also counts. The admissions into ICE detention facilities variable is closest to the number of unique individuals who were present in a detention facility in each year, so I use that number. Both variables run through the end of Fiscal Year (FY) 2020.

Twenty‐​one people died in immigration detention in FY2020, up from 8 in FY2019. During the same time, the number of admissions into ICE detention facilities fell from 510,854 to 177,391 (Table 1). The number of admissions to ICE detention facilities fell drastically because the U.S. government started immediately returning illegal immigrants apprehended at the border under Title 42 authority to halt the spread of COVID-19. The FY2020 death rate in ICE immigration detention was 11.8 per 100,000 admissions, a 656 percent increase from FY2019 and just below the highest ever recorded in 2004. 

Figure 1 shows the total number of ICE detentions and the total number of deaths in custody. The deaths in ICE detention facilities were highest during the George W. Bush administration at 91 total deaths with an average rate of 6.4 per 100,000 admissions per year. Those death rates fell rapidly after FY2004, the first full year when ICE was in operation, from 11.9 per 100,000 admissions to 2.9 per 100,000 admissions in 2008. The death rate rose 26 percent during the first year of the Obama Administration in 2009, then started falling again the next year with an average annual death rate of 2.3 per 100,000 admissions during his entire presidency. We only have data for four years of the Trump administration where the average annual death rate is 3.6 per 100,000 admissions.

This excellent study of death rates in ICE detention gives three reasons for why death rates fell so much during the Bush years and remained low thereafter. The first is that the length of time that immigrants spent in detention fell, which means there was less opportunity for each individual to die even though more were in detention. The second was that ICE increasingly relied on Secure Communities and local law enforcement to first arrest illegal immigrants and then transfer them to ICE. Local law enforcement agencies typically provided any healthcare that the immigrants needed before being transferred to ICE or, tragically, many of them died in local law enforcement custody. The third is that ICE medical policies and practices improved over time. Death rates in ICE detention increased in 2020 because there were many fewer admissions of young illegal immigrants and asylum seekers due to changes in other policies along the border and because of the COVID-19 pandemic.

Banned social media users have long petitioned for reinstatement via informal appeals amplified by prominent supporters. They may be public campaigns, involving supportive hashtags and mass retweets, or private pleas to platform staff known to the banned user or a verified friend. While platforms provide some formal appeal mechanisms, they rarely provide opportunities to solicit support, clarification, or additional context from other users. At scale, reversing an erroneous ban often seems like a matter of making enough noise to demand a second hearing. Sonya Mann presents this phenomenon as pseudo‐​feudal, highlighting the inherent inequality of informal collaborative appeals.

When regular users run afoul of the algorithm, or are dinged by a moderator, it’s common for them to reach out to accounts with larger followings. The hope is that their pleas will be sent to the top by a sympathetic intermediary. It’s not unlike begging a duke to bring your grievance to the king. Jack Dorsey doesn’t care if some random Twitter account gets shut down, but he might lift a finger if a sufficiently prestigious bluecheck brought it to his attention. Or at least that’s the theory.

As COVID-19 has sent human moderators home and increased platforms’ reliance on algorithms, the value of informal appeals has only increased. This should be of concern to platforms as well as users. Content moderation is a top‐​down process. Unable to draw upon democratic legitimacy, moderators have increasingly attempted to legitimize their governance by adhering to procedural values. The Santa Clara Principles, a set of commitments intended to provide users with due process endorsed by Facebook, Twitter, and Youtube, requires “meaningful appeals” and “the ability to present additional information.” If, in practice, only the loudest accounts have this ability, users’ expectations of procedural fairness will be frustrated.

Last month, @MENA_conflict, a mid‐​sized conflict studies and suburban farming account operated by a former infantry marine was banned from Twitter, apparently after being mass‐​reported by would‐​be QAnon‐​hunters, before being eventually reinstated. The account received a deluge of support from journalists and prominent users, including Jack McCain. Its operator reported that he returned to “like 2500 notifications from y’all harassing twitter to reinstate me.”

Informal appeals may have saved @MENA_Conflict in this case, but they present a broader problem. Platform responsiveness to such mass appeals undermines the legitimacy of moderation as a neutral process. They are not equally accessible, often in ways that mirror off‐​platform power structures. However, these sorts of public appeals often provide moderators with otherwise inaccessible or illegible context. Knowledge of a videographers’ portfolio, past citation of a pseudonymous expert, or the jovial nature of #bitcheswhobrunch can all help inform platform decisions. Unfortunately, from the outside, it can be difficult to know whether moderators have caved to public pressure or independently determined that their initial decision was made in error.

This is not exclusively a Twitter problem, though the platform’s default openness may make the issue more visible there. A formal mechanism for the provision of additional context would improve other platforms, as well. Ford Fischer, an independent videographer, was banned from Facebook after posting footage of armed protestors before being reinstated after appealing to his followers on Twitter. He writes:

I wish I had a formal avenue to say, “I cover — not participate in – activism including that of paramilitaries in my capacity as a journalist.” Instead, I had to resort to a viral post on Twitter.

Off‐​platform calls to action have long been a popular method of informal appeal. When Rose McGowan was locked out of her Twitter account after castigating Ben Affleck for denying knowledge of Harvey Weinstein’s predatory behavior, she took to Instagram to protest the decision. However, like other sorts of informal appeals, off‐​platform pleas turn on celebrities, placing them beyond the reach of most users. In Fischer’s case, one Facebook employee even contacted him via Twitter to tell him that Facebook staffers had submitted internal appeal requests on his behalf. These may have gotten the job done but, as Fischer explains:

My qualm here is that most people do not have the extraordinary following that I do. When I had a much smaller following, I could have just as easily lost my account without the community backing to speak out.

Platforms could formalize the ad hoc process of collaborative appeals and bring it back on‐​platform by allowing banned users to tag their followers or those familiar with their case in the appeals process. Tagged users could then choose to submit written testimony or pertinent evidence that might alter moderators’ analysis of the incident or content in question. In many cases, moderators might not need that much additional information. The knowledge that a given user is a journalist merely covering a riot or that a quote deemed hateful comes from the Declaration of Independence is not difficult to convey.

Providing a formal mechanism for collaborative appeals would reduce the perception of unfairness that accompanies platforms’ responsiveness to the informal process, potentially making such appeals more useful to moderators at the same time. It would provide a counterweight to mass bad‐​faith reporting — a frequent misuse of platform user reporting tools. While moderators have limited resources to examine additional evidence, the mere fact that a given decision receives substantial pushback often indicates that it warrants further review.

User flagging is undoubtedly a useful and necessary feature that helps platforms catch violative content their moderators might otherwise miss; like other social media tools, however, it can be used irresponsibly. Often guided by quote tweets, users report non‐​violative content en masse merely because they disagree with it or dislike its author. Sometimes, as may have occurred in @MENA_Conflict’s case, this deluge of false reports is enough to spur platform action. While user flagging remains valuable despite this potential for abuse, the effects of its misuse could be curbed by the addition of collaborative appeal features. Given the difficulty of modifying the reporting feature to prevent bad faith flagging without undermining its usefulness, formalizing the emergent norm of meeting brigade with brigade seems like the best way forward.

Obviously, this would not eliminate inequalities between high and low follower accounts, but it would allow small accounts to access some aspects of the informal appeal currently enjoyed by larger ones. It might also enable moderation to be more responsive to context without forcing moderators to pick between competing sets of facts. Determining context, or the correct context in which to view some content, remains one of the most difficult aspects of content moderation. However, there are good reasons to privilege, or at least recognize, the meaning of speech as understood by its most immediate recipients or participants in the original conversation. They are its local, intended audience — those most likely to appreciate its meaning.

Use of nonstandard English vernacular is often deemed offensive by overzealous algorithms, despite universal agreement as to its inoffensive connotations by the original speakers and listeners. Perhaps we could think of it as recognizing the “original public meaning” of speech, accepting that, as in the physical world, the internet’s little platoons often have their own dialects. Like a common law jury of one’s peers, a formal collaborative appeal mechanism could provide an understanding of local norms and conditions likely to be overlooked by external experts.

Users tagged in an ostensibly threatening post could easily be queried to provide additional information, for example, that the post’s author was merely quoting her friend’s lighthearted threat to kill her husband if he removed her plate. This low‐​hanging fruit – preventing moderation from treating conversations between friends as harassment – might not need a human in the loop at all. Machines may struggle to glean context, but they can accept a “not offensive” input from an apparent victim.

Features that allow users’ friends or participants in a specific conversation to offer testimony would provide benefits for large and small accounts alike. The informal appeal has emerged to solve a particular problem inherent to content moderation at scale and, inegalitarian as it may be, it cannot be wished away. However, by formalizing this redress mechanism, platforms can transform an elite privilege into a tool for everyone.

The most famous ballot question on fiscal policy is California’s Proposition 13 passed in 1978. Voters passed the constitutional change to limit property taxes statewide by a large margin, 65 percent to 35 percent.

Howard Jarvis led the drive for Proposition 13 and made the cover of Time magazine, as shown. California property taxes are generally capped at one percent of purchase price plus an annual inflation factor. The large margin for Proposition 13 passage was impressive given that only some voters are property owners while many are renters.

This year Californians will decide whether to partly scrap the property tax limit. Proposition 15 would repeal the cap for commercial and industrial properties to raise taxes by up to $12 billion a year. These properties would be assessed at market value, not purchase price.

The teacher unions are the main funders of the campaign to pass Proposition 15. But Mark Zuckerberg and his wife, Priscilla Chan, have also contributed $7.1 million. The tax‐​hike side has substantially out‐​raised the opposition side of the ballot campaign.

My intern, Hunter Brazal, helped me tally statewide votes on tax issues over the past decade from Ballotpedia. We found that voters supported the anti‐​tax side on 60 percent of income tax measures and 76 percent of sales and excise tax measures.

What about property taxes? We found 72 statewide property tax measures on the Ballotpedia list, many of which were narrow tax cuts for specific groups. Voters supported the low‐​tax side 81 percent of the time. We don’t know how complete the Ballotpedia data is, so our results can be considered a sampling of the universe of statewide tax votes.

Will Californians defend their wallets against the teacher unions? Is the fiscal conservativism that fueled the 1978 tax revolt still alive or has it waned as state politics have moved left? Polls indicate that Proposition 13 continues to be popular, but support for hiking taxes on commercial and industrial properties has grown. Californians will deliver their verdict on November 3.

For background, see this Cato study on Proposition 13 and other state budget limits.

The Justice Department announced Tuesday that it was launching an antitrust lawsuit against Google alleging that the search giant’s deals with browser and operating system developers to make Google a default search engine amounted to anticompetitive behavior. The suit bears all the hallmarks of a political stunt—an unnecessary government intervention in the online search market that has little chance of yielding any meaningful benefit to consumers.

Oddly, the suit does not target Google’s dominance in the online advertising space, which has often been the focus of critics, but Internet searches, where it seems least plausible to claim the company enjoys anything like a monopoly. Internet users have a wide variety of easily‐​accessible options for online searches: While Google is the default search engine for most browsers and mobile operating systems in the United States, users can elect to use competitors such as Yahoo, Bing, and DuckDuckGo with almost no effort, either by manually visiting those pages, or by taking a few seconds to change their default engine settings. Though Google commands the lion’s share of search traffic, it is hard to seriously claim this is because consumers lack for choices—which would normally be a precondition of claiming a company enjoys a “monopoly.”

Just as Google itself rapidly displaced many older search engines like AltaVista and AskJeeves—which had become defaults for users in the 1990s—the company would quickly lose its dominant position if most users found that competitors yielded more relevant results, just as users routinely download and install apps that provide superior functionality to those already installed on their devices. Moreover, Google’s arrangements with operating system and browser developers are not materially different from, or more “anticompetitive” than, analogous deals for prominent product placement in stores familiar from brick‐​and‐​mortar markets. Indeed, those arrangements may produce consumer benefits by subsidizing the production of software that is free to the user. Nor is it credible to claim, as DOJ does that Google has established a stranglehold on search defaults by dint of its deep pockets: Its primary rival in competitive bids to be “default search engine” is the not‐​exactly‐​penurious Microsoft.

Some relevant evidence comes from the European Union, where antitrust regulators recently forced Google to unbundle its search and browser offerings from its Android mobile operating system. Android users are now presented with a menu of search engine choices when setting up a new device, rather than defaulting to Google. The primary result has been that Google began charging mobile manufacturers to license its operating system. Google’s share of the online search market in the EU, however, has not changed measurably at all. While it would be unsurprising if, over time, the new “choice screen” eventually shaved a few percentage points off Google’s share, there is not much evidence for the view that lazy and uninformed consumers are being systematically tricked into using a search engine they would eschew if they were only compelled, rather than merely permitted, to make an active choice.

Perhaps most disturbing, there are indications that this suit may be politically motivated. Attorney General Bill Barr reportedly overrode career antitrust attorneys who did not believe the case was sufficiently strong in order to rush a complaint out the doors. Rep. Jim Jordan (R-OH) responded to the suit by declaring on Twitter that “Big Tech” was “out to get conservatives,” and the Attorney General would not let them “get away with it,” though the suit itself is not explicitly concerned with the company’s supposed political leanings. Eleven state attorneys general have joined the Justice Department suit, all of them Republican.

In short, it is impossible to divorce this action from its political context: Pundits and elected officials on the right, not least among them the current president, routinely bash Silicon Valley by alleging (on the basis of, to put it charitably, highly dubious evidence) that tech companies systematically wage a vendetta against conservatives. Now, weeks before a national election, the attorney general has taken a very public swing at one of the primary villains of this narrative, employing arguments that seem conspicuously at odds with Republicans’ traditionally far more restrained view of antitrust. If this weak suit has been rushed to court in order to punish a company that many on the right perceive as harboring a “liberal bias,” it would constitute not just witless economic policy, but an egregious abuse of power.

Disclosure: While I try to not know which individuals or companies in my policy area may also be Cato Institute donors, my understanding is that Google has supported Cato in the past, and (for all I know) may still do so. For context, less than 3 percent of Cato’s total revenue comes from corporations.