Last week I laid out my own expectations for what economic policy would look like in a Trump or Harris presidency. Now after yesterday’s market reaction, we can infer what market participants as a whole expect by roughly doubling the size of yesterday’s market moves. Prediction markets had a 50-60% change of Trump winning as of Tuesday morning’s market close, which moved to a 99+% chance by Wednesday morning. Look at how other markets moved over the same time, multiply it by 2-2.5x, and you get the expected effect of a Trump presidency relative to a Harris presidency. So what do we see?
Stocks Up Overall: S&P 500 up 2%, Dow up 3%, Russell 2000 (small caps) up 6%. My guess this is mostly about avoiding tax increases- the odds that most of the Tax Cuts and Jobs Act gets renewed when it expires in 2025 just went way up. Lower corporate taxes boost corporate earnings directly, while lower taxes on households mean that they have more money to spend on their stocks and their products. Lower regulation and looser antitrust rules are also likely to boost corporate earnings.
Bond Prices Down (Yields Up): 10yr Treasury yields rose from 4.29% to 4.4%. This is the flip side of the tax cuts- they need to be paid for, and markets expect they will be paid for through deficits rather than cutting spending. The government will issue more bonds to borrow the money, lowering the value of existing bonds.
Dollar Up: The US dollar is up 2% against a basket of foreign currencies. I think this is mostly about the expected tariffs. People like the sound of the phrase “strong dollar” but it isn’t necessarily a good thing; it makes it cheaper to vacation abroad, but makes it harder to export, even before we consider potential retaliatory tariffs.
Crypto Way Up: Bitcoin went up 7% overnight, Ethereum is now 15% up since Tuesday. Crypto exchange Coinbase was up 31%. Markets anticipate friendlier regulation of crypto, along with a potential ‘strategic Bitcoin reserve’.
Single Stock Moves: Private prison stocks are up 30%+. Tesla is up 15%, mostly due to Elon Musk’s ties to Trump, but also due to tariffs. Foreign car companies were way down on the expectation of tariffs- Mercedes-Benz down 8%, BMW down 10%, Honda down 8%.
Sector Moves: Steel stocks are up on the expectation of tariffs, while solar stocks (which can’t catch a break, doing poorly under Biden despite big subsidies and big revenue increases) were down 12% in the expectation of falling subsidies. Bank stocks did especially well, with one bank ETF up 12%. This gives us one hint on what to me is now the biggest question about the second Trump administration- who will staff it? I could see Trump appointing free-market types, or wall-streeters in the mold of Steve Mnuchin, or dirigiste nationalist conservatives in the JD Vance / Heritage Foundation mold, or an eclectic mix of political backers like Elon Musk and RFK Jr, or a combination of all of the above. The fact that bank stocks are way up tells me that markets expect the free-marketers and/or the Wall-Street types to mostly win out.
Just Ask Prediction Markets: If you want to know what markets expect from a Presidency, you can do what I just did, look at moves the big traditional markets like stocks and bonds and try to guess what is driving them. But increasingly you can skip this step and just ask prediction markets directly- the same markets that just had a very goodelection night. Kalshi now has markets on both who Trump will nominate to cabinet posts, as well as the fate of specific policies like ‘no tax on tips‘
I doubt anyone has been waiting for my take on the Trump and Harris economic plans to decide their vote. More than that, it is entirely reasonable to vote based on things other than their economic plans entirely- like foreign policy, character, or preservingdemocracy. But either Trump or Harris will soon be President, and thinking through their economic plans can help us understand how the next 4 years are likely to go.
The bad news is that both campaigns keep proposing terrible ideas. The good news is that, thanks to our system of checks and balances, most of them are unlikely to become policy. The other good news is that our economy can handle a bit of bad policy- as Adam Smith said, there’s a lot of ruin in a nation. After all, the last Trump admin and the Biden-Harris admin did all sorts of bad economic policies, but overall economic performance in both administrations was pretty good; to the extent it wasn’t (bad unemployment at the end of the Trump admin, bad inflation at the beginning of Biden-Harris), Covid was the main culprit.
Note that this post will just be my quick reactions; the Penn Wharton Budget Model has done a more in-depth analysis. They find that Harris’ plan is bad:
We estimate that the Harris Campaign tax and spending proposals would increase primary deficits by $1.2 trillion over the next 10 years on a conventional basis and by $2.0 trillion on a dynamic basis that includes a reduction in economic activity. Lower and middle-income households generally benefit from increased transfers and credits on a conventional basis, while higher-income households are worse off.
We estimate that the Trump Campaign tax and spending proposals would increase primary deficits by $5.8 trillion over the next 10 years on a conventional basis and by $4.1 trillion on a dynamic basis that includes economic feedback effects. Households across all income groups benefit on a conventional basis.
We are already running way too big a deficit; candidates should be competing to shrink it, not make it worse. This isn’t just me being a free-market economist; Keynes himself would be saying to run a surplus in good economic times so that you have room to run a deficit in the next recession.
Now for my lightning round of quick reactions:
No tax on tips: both campaigns are now proposing this; it is a silly idea, there is no reason to treat tips differently from other income. The good news is that this almost certainly won’t make it through Congress.
Taxes: Trump’s Tax Cuts and Jobs Act of 2017 is set to expire in 2025. He says he wants to renew it and add more tax cuts, though he will need a friendly Congress to do so. Harris wants to let most of it expire, but renew and expand the Child Tax Credit while raising taxes on the wealthy and corporations. There’s a good chance we end up with divided government, in which case probably only the most popular parts of TCJA (increased standard deduction and child tax credit) get renewed and no big new changes happen.
Price controls: both campaigns, especially Harris‘, have talked about fighting ‘price gouging’, leading economists to worry about the price controls (any intro micro class explains why these are a bad idea). My guess is that no real bill gets passed, President Harris gets the FTC to make a show of going after grocery stores but nothing major changes.
Tariffs: Harris would probably leave them where they are; Trump is promising to raise them 10-20% across the board and 60% on China. This would lead to higher prices for US consumers and invite retaliation from abroad; we saw the same things when Trump raised tarriffs in his first term, but he is promising bigger increases now. This is worrisome because the President has a lot of power to change tariffs unilaterally; it would take a bill getting through Congress to stop this, and I don’t see that happening.
Regulation / One in two out: The total amount of Federal regulation stayed fairly flat during the Trump administration thanks to his one in two out rule, while regulation increased during the Biden-Harris administration. I expect that a second Trump admin would behave like the first here, while a Harris admin would continue the Biden-Harris trend.
Antitrust: FTC and DOJ have been aggressive during the Biden-Harris administration, blocking reasonable mergers and losing a lot in court. But Trump’s VP candidate JD Vance thinks FTC Chair Lina Khan is “doing a pretty good job”, so we could see this poor policy continue either way. More generally, voters should consider what a Vance presidency would look like, because making him Vice President makes it much more likely (Trump is 78 and people keep trying to shoot him; plus VPs get elected President at high rates).
Immigration: Immigration rates have been high under the Biden-Harris admin, while Trump’s top two planks in his platform are “seal the border” and “carry out the largest deportation operation in American history”. Economically, this would lead to a reduction in both supply and demand in many sectors, with the relative balance (so whether prices go up or down) depending on the sector. The exclusion of Mexican farmworkers in the 1960’s led to a huge increase in mechanization, to the point that domestic farmworkers saw no increase in their wages; presumably this also limited the potential harm to the food supply.
Crypto: The Biden admin has been fairly negative on crypto; both Harris and Trump are making pro-crypto statements in their campaigns, particularly Trump.
Marijuana: The Biden admin is in the process of rescheduling marijuana to no longer be in the most restricted category of drugs. I think Trump would probably see the process through, while Harris definitely would.
Elon Musk / Civil Service: Elon Musk has thrown his support hard behind Trump, spending lots of money, tweeting continuously, and attending rallies. It’s hard to know how much of this is genuine support for a range of Trump’s policies, how much is to get the Federal government to stop suing his companies so much, and how much is to get himself a direct role in government. In any case, it is a safe bet that more Federal civil servants get fired in a Trump admin than in a Harris admin. What’s much harder to say is how many get fired, and what proportion of firings come from a genuine attempt to improve efficiency vs a purge of those Trump sees as disloyal. Personally I think government could stand to treat its employees a bit more like the private sector, making it easier to fire people for genuine poor performance (not political views), but also allowing for more flexibility on improved pay, benefits, and the ability to focus on achieving goals more than following the way things have always been done. But I doubt that’s on the table either way.
CFTC/ Prediction Markets: The Biden CFTC has tried to crack down on prediction markets, though they have mostly failed in the courts, and the growth of Kalshi and Polymarket mean that prediction markets are now bigger than ever. Most of the anti-prediction-market decisions have been 3-2 votes of the democrats vs the republicans, so a new republican appointee could lock in the legal gains prediction markets have made, though this is far from guaranteed (not all Rs support this).
Final Thoughts: So much of how things turn out will depend not just on who wins the Presidency, but on whether their party wins full control of Congress. Because the Democrats have a lot more Senate seats up for grabs this year, Harris is much more likely to be part of a divided government (especially once you consider the Supreme Court).
Because of this, and because of the ability of the President to raise tariffs unilaterally, I see Trump as the bigger risk when it comes to economic prosperity, as well as non-economic issues. Harris with a Republican Senate is the best chance of maintaining something like the status quo, whereas a Trump victory is likely to see bigger changes, many of them bad.
That said, predicting the future is hard, and this applies doubly to Presidential terms. I’m struck by how often in my lifetime the most important decisions a President had to make had nothing to do with what the campaign was fought over. Who knew in 1988 that the President’s biggest task would be managing the breakup of the Soviet Union? In 2000, that it would be responding to 9/11? Bush specifically tried to distinguish himself from Gore as being the candidate more against “nation-building”, then went on to try just that in Afghanistan and Iraq. In 2004, who knew that the biggest issue of the term would be not Social Security or foreign policy, but a domestic financial crisis and recession? In 2016, who knew that they were voting on the President that would respond to the Covid pandemic? In 2020, who knew that they were voting on who would respond to Russia’s invasion of Ukraine?
The most important issue for the next President could easily be how they address China or AI, because those are clearly huge deals. I won’t vote based on this, because I don’t know who has the better plan for them, because I have no idea what a good plan looks like. Or the most important issue could be something that comes completely out of left field, like Covid did. Not even the very wise can see all ends.
What I do know is that, while much of the Libertarian Party has recently gone from its usual “goofy-crazy” to “mean-crazy“, Chase Oliver is so far the only candidate pandering to me personally. But it’s not too late for other politicians at all levels to try the same.
See you all again next Thursday, by which time the election will, I hope, be over.
If you want to know how many pigs were killed in the United States yesterday, the USDA has the answer. But if you want to know how many humans were killed in the US this month, the FBI is going to need a year or two to figure it out. The new Real Time Crime Index, though, can tell you much sooner, by putting together the faster local agency reports:
Trends currently look good, though murders still aren’t quite back to pre-2020 levels.
In addition to graphing top-line state and national trends, the Real Time Crime Index also offers the option to download a CSV with city-level data going back to 2018. This seems like a great resource for researchers, worthy of adding to my page of most-improved datasets.
Kalshi just announced that they will begin paying interest on money that customers keep with them, including money bet on prediction market contracts (though attentive readers here knew was in the works). I think this is a big deal.
First, and most obviously, it makes prediction markets better for bettors. This was previously a big drawback:
The big problem with prediction markets as investments is that they are zero sum (or negative sum once fees are factored in). You can’t make money except by taking it from the person on the other side of the bet. This is different from stocks and bonds, where you can win just by buying and holding a diversified portfolio. Buy a bunch of random stocks, and on average you will earn about 7% per year. Buy into a bunch of random prediction markets, and on average you will earn 0% at best (less if there are fees or slippage).
This big problem just went away, at least for election markets (soon to be all markets) on Kalshi. But the biggest benefit could be how this improves the accuracy of certain markets. Before this, there was little incentive to improve accuracy in very long-run markets. Suppose you knew for sure that the market share of electric vehicles in 2030 would over 20%. It still wouldn’t make sense to bet in this market on that exact question. Each 89 cents you bet on “above 20%” turns into 1 dollar in 2030; but each 89 cents invested in 5-year US bonds (currently paying 4%) would turn into more than $1.08 by 2030, so betting on this market (especially if you bid up the odds to the 99-100% we are assuming is accurate) makes no financial sense. And that’s in the case where we assume you know the outcome for sure; throwing in real-world uncertainty, you would have to think a long-run market like this is extremely mis-priced before it made sense to bet.
But now if you can get the same 4% interest by making the bet, plus the chance to win the bet, contributing your knowledge by betting in this market suddenly makes sense.
This matters not just for long-run markets like the EV example. I think we’ll also see improved accuracy in long-shot odds on medium-run markets. I’ve often noticed early on in election markets, candidates with zero chance (like RFK Jr or Hillary Clinton in 2024) can be bid up to 4 or 5 cents because betting against them will at best pay 4-5% over a year, and you could make a similar payoff more safely with bonds or a high-yield savings account. Page and Clemen documented this bias more formally in a 2012 Economic Journal paper:
We show that the time dimension can play an important role in the calibration of the market price. When traders who have time discounting preferences receive no interest on the funds committed to a prediction-market contract, a cost is induced, with the result that traders with beliefs near the market price abstain from participation in the market. This abstention is more pronounced for the favourite because the higher price of a favourite contract requires a larger money commitment from the trader and hence a larger cost due to the trader’s preference for the present. Under general conditions on the distribution of beliefs on the market, this produces a bias of the price towards 50%, similar to the so-called favourite/longshot bias.
We confirm this prediction using a data set of actual prediction markets prices from 1,787 market representing a total of more than 500,000 transactions.
Hopefully the introduction of interest will correct this, other markets like PredictIt and Polymarket will feel competitive pressure to follow suit, and we’ll all have more accurate forecasts to consult.
Other than being the smallest state, of course. In other places I’ve lived, it was more obvious what made them stand out. Boston has the most high-quality universities, including the oldest one (though it is expensive and traffic-ridden). New Orleans has the best food, live music, and festivals (though terrible crime and roads). I’ve lived in Rhode Island since 2020 and I’ve enjoyed how it seems to have no big negatives the way many other places do- it’s been pretty nice all around. But it has been harder to see anything where Rhode Island really stands out.
What should a tourist see or do here that they couldn’t do elsewhere? The Italian food is great, but that’s true of several other cities. You can find Portuguese food here in a way you can’t in most of the US. Probably the Cliff Walk in Newport is our best entry: a 3-mile trail along cliffs where you can see the Atlantic on one side, and Gilded-age mansions on the other.
For those living here, what stands out is the compactness. This makes sense for the smallest state, but it is even more true than you would expect, because even within Rhode Island most people are clustered within the small portion of the state that is within 5 miles of Providence.
Because of this, I almost never feel the need to drive more than 10 miles or 20 minutes; this wasn’t so true any of the other ~dozen places I’ve lived. I can easily walk to the Bay, the Zoo, and my kids’ school; then its a 20 minute drive or less to work, several good hospitals and universities, sailing, several beaches, forest hikes, the state capital, the excellent airport, Amtrak, every good grocery store, leaving the state, et c. Most other places either lack some of those things entirely or involve longer drives to get to them, though probably there’s somewhere else like this I don’t know about.
Or perhaps the best thing about Rhode Island is our people:
What do you think I missed about Rhode Island? Or if you haven’t been here, what do you think is most special about where you live?
Ray Fair at Yale runs one of the oldest models to use economic data to predict US election results. It predicts vote shares for President and the US House as a function of real GDP growth during the election year, inflation over the incumbent president’s term, and the number of quarters with rapid real GDP growth (over 3.2%) during the president’s term.
Currently his model predicts a 49.28 Democratic share of the two-party vote for President, and a 47.26 Democratic share for the House. This will change once Q3 GDP results are released on October 30th, probably with a slight bump for the dems since Q3 GDP growth is predicted to be 2.5%, but these should be close to the final prediction. Will it be correct?
Probably not; it has been directionally wrong several times, most recently over-estimating Trump’s vote share by 3.4% in 2020. But is there a better economic model? Perhaps we should consider other economic variables (Nate Silver had a good piece on this back in 2011), or weight these variables differently. Its hard to say given the small sample of US national elections we have to work with and the potential for over-fitting models.
But one obvious improvement to me is to change what we are trying to estimate. Presidential elections in the US aren’t determined by the national vote share, but by the electoral college. Why not model the vote share in swing states instead?
Doing this well would make for a good political science or economics paper. I’m not going to do a full workup just for a blog post, but I will note that the Bureau of Economic Analysis just released the last state GDP numbers that they will prior to the election:
Mostly this strikes me as a good map for Harris, with every swing state except Nevada seeing GDP growth above the national average of 3.0%. Of course, this is just the most recent quarter; older data matters too. Here’s real GDP growth over the past year (not per capita, since that is harder to get, though it likely matters more):
Region
Real GDP Growth Q2 2023 – Q2 2024
US
3.0%
Arizona
2.6%
Georgia
3.5%
Michigan
2.0%
Nevada
3.4%
North Carolina
4.4%
Pennsylvania
2.5%
Wisconsin
3.3%
Still a better map for Harris, though closer this time, with 4 of 7 swing states showing growth above the national average. I say this assuming as Fair does that the candidate from the incumbent President’s party is the one that will get the credit/blame for economic conditions. But for states I think it is an open question to what extent people assign credit/blame to the incumbent Governor’s party as opposed to the President. Georgia and Nevada currently have Republican governors.
Overall I see this as one more set of indicators that showing an election that is very close, but slightly favoring Harris. Just like prediction markets (Harris currently at a 50% chance on Polymarket, 55% on PredictIt) and forecasts based mainly on polls (Nate Silver at 55%, Split Ticket at 56%, The Economist / Andrew Gelman at 60%). Some of these forecasts also include national economic data:
Gelman suggests that the economy won’t matter much this time:
We found that these economic metrics only seemed to affect voter behaviour when incumbents were running for re-election, suggesting that term-limited presidents do not bequeath their economic legacies to their parties’ heirs apparent. Moreover, the magnitude of this effect has shrunk in recent years because the electorate has become more polarised, meaning that there are fewer “swing voters” whose decisions are influenced by economic conditions.
But while the economy is only one factor, I do think it still matters, and that forecasters have been underrating state economic data, especially given that in two of the last 6 Presidential elections the electoral college winner lost the national popular vote. I look forward to seeing more serious research on this topic.
I missed Alan Kreuger’s 2019 book on the economics of popular music when it first came out, but picked it up recently when preparing for a talk on Taylor Swift. It turns out to be a well-written mix of economic theory, data, and interviews with well-known musicians, by an author who clearly loves music. Some highlights:
[Music] is a surprisingly small industry, one that would go nearly unnoticed if music were not special in other respects…. less than $1 of every $1,000 in the U.S. economy is spent on music…. musicians represented only 0.13 percent of all employees [in 2016]; musicians’ share of the workforce has hovered around that same level since 1970.
there has been essentially no change in the two-to-one ratio of male to female musicians since the 1970s
The gig economy started with music…. musicians are almost five times more likely to report that they are self-employed than non-musicians
30 percent of musicians currently work for a religious organization as their main gig. There are a lot of church choirs and organists. A great many singers got their start performing in church, including Aretha Franklin, Whitney Houston, John Legend, Katy Perry, Faith Hill, Justin Timberlake, Janelle Monae, Usher, and many others
The Federal Reserve cut interest rates yesterday for the first time since 2019. They raised rates dramatically in 2022 to fight off high inflation, and kept them high since. This cut signals that they are now less worried about inflation, which is now nearing (but not at) their 2% target, and more worried about the slowing (?) labor market. To me their action was reasonable, but doing a smaller cut or waiting longer would also have been reasonable, because the labor market is giving such mixed signals at the moment.
Most concerning is that unemployment increased from 3.5% last July to 4.3% this July. On previous occasions that unemployment in the US increased that rapidly, we then saw recessions and much more growth in unemployment. But unemployment ticked down to 4.2% last month, and layoffs have been flat:
How do you get a big increase in unemployment without a big increase in layoffs? There are two main ways, one good and one bad, and we have both. The bad news, especially for new graduates, is that hiring has slowed:
But the better news is that there are simply more people wanting to work. This is generally a good sign for the economy; in bad economic times many people don’t count as “unemployed” because they are so discouraged that they don’t bother actively looking for work. In July though, prime-age labor force participation hit 84%, the highest level since 2001:
The prime-age employment-to-population ratio just hit 80.9%, also the highest level since 2001:
Labor force participation and employment-to-population among all adults are not so high, though it could be a positive that many people under 25 are in school and many people over 54 are able to retire. Finally, total payrolls got a big downward revision, but one that still implies positive growth every month.
Looking beyond the labor market though, GDP grew at a strong 3.0% in Q2, and is projected to be similar in Q3. Inflation breakevens are exactly on target. Overall it looks like some recession indicators that worked historically, like the Sahm Rule and Yield Curve Inversion, are about to break down- especially now that the Fed cutting is rates.
Cowen’s 2nd Law states that there is a literature on everything. I would certainly expect there to be a literature on the best-selling musician in the world. And of course there is; Google Scholar returns 23,500 results for “Taylor Swift”, and we’ve done 5 posts here at EWED. But surprisingly, searching EconLit returns nothing, suggesting there are currently no published economics papers on Taylor Swift, though searching “Taylor” and “Swift” separately reveals hundreds of articles about the Taylor Rule and the SWIFT payment system. Google Scholar does report some economics working papers about her, but the opportunity to be the first to publish on Taylor Swift in an economics journal (and likely get many media interview requests as a result) is still out there.
Swift presents a variety of angles that could be worthy of a paper; re-recording her masters forcopyright reasons, her efforts to channel concert tickets to loyal fans over re-sellers, or her sheer macroeconomic impact. I’ve added a note about this to my ideas page (where I share many other paper ideas).
In the mean time, I’ll be giving a short talk on the Economics of Taylor Swift at 7pm Eastern on Monday, September 16th, as part of a larger online panel. The event is aimed at Providence College alumni, but I believe anyone can register here.
Update 10/25/24: A recording of the event is here, and a recording of a followup interview I did with local TV is here.
The answer sure seems to be “nothing”. I just went for an eye exam for the first time since Covid and realized that I’ve been wasting my money by paying for vision insurance.
The problem isn’t the eye exam- that went fine, and was covered fine with a $35 copay. But it was covered by my health insurance, not my vision insurance. So what is the vision insurance good for, if it doesn’t cover eye exams?
The answer is supposed to be “glasses”. It is supposed to cover frames up to $150 with a $0 copay, and basic lenses with a $25 copay, from in-network providers. That sounds ok- but there are two problems.
One is that almost none of the in-network providers (like Glasses dot com or Target optical) appear to actually offer lenses where the $25 copay applies; instead the minimum lens price is at least $85.
The second problem is that the premiums are high enough that even if I use them to get $25 glasses (which I eventually found I could through LensCrafters), it wouldn’t be worth it. They don’t sound high at first, which is how I got suckered into signing up for this scam in the first place. It’s just $5/month for single coverage; that sounds like nothing, especially for an employer benefit. It is a rounding error compared to health insurance premiums, and it comes out of pre-tax money. A small waste, but still a waste. Why?
Glasses are just so cheap if you can avoid the monopoly retailers and get them somewhere like Zenni. Zenni will sell you perfectly functional (and IMHO good-looking) prescription eyeglasses for $16. Their frames start at $6.95, lenses at $3.95, and shipping at $4.95. Catch a sale, or order enough to get free shipping, and you could actually get glasses for well under $16.
Or you can do what I did- order glasses from Zenni with premium options that pushed them up to $50- and find it is still cheaper than using the insurance I already paid for to get the cheapest pair available at most of their in-network retailers. The cheapest possible deal with insurance would be to pay $60/year in premiums, get glasses as often as the insurance allows so as not to waste the benefit (every 12 months- much more often than I find necessary), find frames listed under $150 to get for $0 copay, and find an in-network provider that actually offers lenses for the $25 copay. In this best-case scenario you are still paying $85 per pair of glasses. Given that the $60 in premiums came from pre-tax money, perhaps you can argue that it was really more like $40 in real money; but you can also buy glasses from a competitive retailer like Zenni using pre-tax money from an HSA or FSA.
So as far as I can tell, vision insurance really is useless. I certainly decided not to use it for my latest pair of glasses even though I had already paid years of premiums; Zenni was still much cheaper for a comparable product. I’m dropping vision insurance now that open enrollment is here. My take-home pay will be going up, and EyeMed will stop getting my money for nothing.
Is there anyone vision insurance makes sense for? I think it could makes sense for someone who really wants brand name glasses, or for someone who really wants to get their glasses in-person at the optometrist, and wants new glasses every year. For everyone else, run the numbers for your own plan, but I suspect you would also be better off just buying glasses directly.
Disclaimer: This post is not sponsored & doesn’t use affiliate links; Zenni is the best option I currently know of, but I’d be happy to hear of other competitive retailers you think are better, or an argument for when vision insurance is actually useful.
Economist Writing Every Day 