There were two stand-out, runaway favorites in the New Hampshire primary results: Ned Augenblick and Scott Nicholson. Their names weren't on the ballot per se, but their theory on ballot position and choice fatigue certainly was.

Augenblick and Nicholson found that voters would be more likely to vote for things that appear earlier in the ballot, and this result was very much confirmed in New Hampshire where the official list of republican presidential candidates was much longer than the national list. Kasich was the only nationally known candidate still in the race to appear in the top half of the list, and as the decision-fatigue theory predicted, he massively outperformed the polls and came in second over all.

Of course, Trump and Sanders also won their primaries, for whatever that's worth.

Clinton and Rubio were the biggest losers. Rubio was expected to surge into second place after his better-than-expected Iowa performance. New Hampshire at best interrupts his momentum, at worst confirms that Christie's attack in the last debate--probably the single most effective attack against a major candidate ever launched--was as destructive for Rubio as everyone thought. As for Clinton, for someone who not long ago was supposed to win all the primaries without much trouble, the tie in Iowa and loss in New Hampshire represents a pretty serious upset.

The United States is one of the few developed countries that still does not have a sick leave program. Most countries have a publicly funded sickness program that pays workers not to go to work. Over 102 countries offer workers more than a month of sick leave, at varying levels of wage replacement. In the US, by contrast, sick leave programs are administered by employers, if they choose to have one at all, and typically only offer 5 days off.

Thus, there's a substantial movement in the US to make sick leave benefits universal by mandating that all employers provide at least 5 paid sick days off to all employees. There are lots of benefits to having sick days. For one, it's the humanitarian thing to do—when someone is violently ill, we should let them stay home and take care of themselves, or to go to the doctor if necessary. For another, having a sick person at work can, for example, increase risk of workplace accidents. There are lots of other benefits as well, but one that is most often touted is that letting sick peoples stay home will reduce the spread of diseases in the workplace.

Unfortunately, I think that last particular benefit is overstated—US-style sick leave policies have only minimal effect on the incidence of disease.

The problem is that the typical sick leave policy allows only 5 days off, and even then we're faced with strong social norms prohibiting workers from using them effectively to prevent contagion. Your employer and co-workers will suspect you of shirking if you call in sick but don't sound violently ill, and you're expected to only take one sick day—2 at the very most—for a particular illness.

Surveys show that for the flu, one of the more aggressive and dangerous of the common illnesses, workers with access to paid sick days take fewer than 1.8 days off on average. The problem is that the flu remains contagious for 5 days, and up to 2 weeks for some people, so taking only 1 or 2 days off from work does not substantially reduce your co-workers' exposure. Even taking all 5 days would not eliminate the risk of spreading flu at work. The result is that access to paid sick days only reduces workplace transmission by less than 6 percent.

Aside from food poisoning and hospital-acquired infections, most common contagious illnesses these days are viral and not amenable to treatment with antibiotics. Most of these viral illnesses have a pretty similar menu of symptoms, differing in severity, including fever, congestion, runny nose, sore throat, nausea, and diarrhea. But epidemiologically, they're all over the map. Some viruses become contagious before people develop any symptoms, others remain contagious after the symptoms disappear, and many viruses can be transmitted by people who never develop any symptoms. The notorious norovirus that infected Chipotle restaurants on two recent occasions, for example, remains contagious 3 days to 2 weeks after their symptoms go away, and 30 percent of people who have norovirus infections never develop any symptoms at all. Most of these viruses remain contagious for longer than the 1 or 2 days workers typically take off from work.

Having more sick days could help. In other countries with public sick leave programs, workers typically take 5 to 10 days off a year for sickness, much more than the 1.8 in the US. And some theoretical and empirical estimates in the US suggest that having access to 7 to 10 days off a year could be associated with a much larger reduction in workplace transmission, especially during larger epidemics. But even then, sickness leave policies will leave large gaps as workers come to work whenever they lack symptoms, even if they're still contagious.

Why is this so hard?

I think it helps to make a comparison to vaccination programs. Vaccines obviously aim to give individual-level immunity to the individuals who get it, but when administered to the entire population they also provide a second level of protection known as "herd immunity," where the transmission of the virus is impeded so much that it is unable to infect even those without individual-level immunities. Even with vaccines that are highly effective at producing individual-level immunity, you often still have to vaccinate more than 90 percent of the population before you start to see significant herd immunity effects. Paid sick leave policies aim to create a herd immunity effect—impede the transmission of illnesses to the non-immune—without any of the individual-level immunity that makes this work for vaccines. If we really want to see a significant effect here, we'd need to dramatically ramp up the coverage of paid sick days. Not merely extending those 5 days off to the whole population, but also increasing the number of days and ensuring that workers take weeks, not days, off whenever they get sick. Without that dramatic step, I doubt most work places will see much effect on illnesses from their sick leave policies.

Update 2-24-2016: post has been updated to add more links to sources.

Bryan Caplan announces that he's won his bet with Tyler Cowen. Caplan bet that unemployment would recover, Cowen bet that it wouldn't:

...U.S. unemployment will never fall below 5% during the next twenty years. If the rate falls below 5% before September 1, 2033, he immediately owes me $10. Otherwise, I owe him $1 on September 1, 2033.

The unemployment rate in January dropped to 4.9 percent. Never the less, Tyler Cowen feels that he's the one who won the bet.

No one agrees with Cowen (sorry). Here's Paul Krugman and Noah Smith piling on. Nevertheless, Cowen's position is not totally unreasonable. The essence of why Caplan and Cowen disagree who won the bet is this trend in labor force participation:

The participation rate certainly doesn't, prima facie, appear to have recovered at all from the recession, and since this determines the denominator in the unemployment rate calculation, in Cowen's mind this means he was right overall but merely didn't anticipate that workers would actually drop out of the labor market.

But it's still not that simple. The peak year for baby boomers was 1947 and births remained elevated until 1960. 1947+65=2012, which means that we hit a big wall of retirees at the same time as the recovery from the great recession—labor force participation rate was always anticipated to decline over this period. No doubt some baby boomers retired early because of the economy in 2009—realistically, no one who retired early at 62 is going to rejoin the labor force now that they're 69. In this respect, recessions have a ratchet effect on labor force size that make the recoveries look slower than they really are.

I think that ratchet effect is most of what we're seeing in Cowen's graph here.

One way to adjudicate this is to look at pre-recession projections that estimated what would happen to the labor force as a result of demographic trends alone. These projections aren't perfect—relevant factors could have changed since then—but they are very clean in the sense of being totally immune to our current biases about the recession and recovery since these were not known at the time. BLS has such a projection dating from 2002: they estimated that aging of the baby boomers would cause labor force participation to fall to 64.6 percent by the end of 2015 and that further aging of the population would eventually reduce participation to 60.2 percent by 2045. The labor force participation rate is now 62.7 percent. That suggests that at least half of the fall in labor force participation was just normal population aging. Combined with the ratchet effect described above, early retirements could explain all of the fall.

What have we learned?

My real point though is not to explain that Cowen is wrong about the labor market but that Caplan and Alex Tabarrok are wrong about betting. Tabarrok declared that bets are—pardon my language—"a tax on bullcrap," and force people to reveal their true beliefs rather than cheap talk. And yet here we are with Cowen and Caplan both declaring themselves winners on the opposite sides of the same bet.

I wrote at the time that Tabarrok and Caplan were wrong to claim bets reveal beliefs. The problem, I argued, is beliefs are always necessarily conditional predictions. I believe the earth will warm by more than 2 degrees unless the governments of the world take dramatic action to curb greenhouse emissions, for example. A bet on the earth's warming does not reveal my beliefs about climate change, it reflects a complex combination of beliefs about climate change and geo-politics and lots of other things. My beliefs about what the economy will do (not fall in recession) are conditional on my unrelated beliefs about what the Fed will do (not raise interest rates too quickly), among lots of other things.

Oh, sure you could make conditional bets. Cowen could have bet that unemployment will not fall unless labor force participation falls. Highly conditional bets will usually not payoff either way though, so they don't actually tax incorrect claims. In this case, if Cowen had made such a bet, there'd be no payoff since both Caplan and Cowen's positions allow that unemployment and labor force participation falls. Moreover, listing out every single factor that weighs in your belief system simply isn't practical.

Ultimately, the problem of identifying beliefs through bets is exactly the same problem as identifying causality through econometrics. Econometric models, after all, do nothing more than generate predictions about the data, which we then try to use to form beliefs about the data-generating process. And that's really hard and doesn't work out a majority of the time.