Things that spur economic recovery include abolishing the corporate income tax, eliminating or reducing unemployment benefits and food stamp eligibility, eliminating the minimum wage, and slashing regulations.
So a bereaved father made this statement advocating the ban on assault weapons and high capacity magazines:
At the 15 minute mark, the father says:
I ask if there’s anybody in this room that can give me one reason or challenge this question … why anybody in this room needs to have one of these assault-style weapons or military weapons or high-capacity clips.
At this point, he pauses for effect, as if inviting people in the room to comment. When nobody says anything, he says: “And not one person can answer that question.” As if people’s silence proved he was right.
Then a few people say — not yell — things about the Second Amendment, some quoting the part about how the right to bear arms “shall not be infringed.” In this way, he was disallowed from arguing that the silence of people in the room signaled agreement with his position.
Then an official threatened to remove the people whose comments had been solicited, for the offense of responding to the father’s request for comment: “Please no comments while Mr. Heslin is speaking. Or we’ll clear the room. Mr. Heslin please continue.”
This was described as “heckling” by a number of people. You can watch the video above to confirm my description of the account, and reach your own conclusion about whether this constitutes “heckling.” Once you’ve reached your conclusion, you’ll probably want a list of people who described this as “heckling,” so you can factor this episode into your decisionmaking about whether to trust these people in the future.
Luckily, in a post that JD linked last night, Twitchy has compiled tweets from many of these people. I think they should be named. They include Eric Boehlert, Charles Johnson, David Frum, Andrew Kaczynski of BuzzFeed, John Marshall, Piers Morgan, Raw Story, Gawker, Slate, the Daily Beast, and HuffPo, among others.
Each used the word “heckled” to describe people a) giving comments that had been invited, and b) refusing to have their silence falsely portrayed as agreement with an opinion they rejected.
Allahpundit has the details on how Slate, Piers Morgan, and others retracted (Morgan acted the ass in his apology, as you would expect). Larry O’Donnell doubled down, pretending to ignore the fact that the father was calling for the BAN of these weapons, and that the father was falsely portraying silence as agreement.
Message to Eric Boehlert, Charles Johnson, David Frum, Andrew Kaczynski of BuzzFeed, John Marshall, Piers Morgan, Raw Story, Gawker, Slate, the Daily Beast, and HuffPo:
This is a good example of why we don’t trust you.
UPDATE: It’s a neat little Catch 22, isn’t it? If you speak out, even if invited to, you’re a jerk, because they are the parents of victims. If you are silent, you agree with them. Either you are for gun control or you’re an insensitive, terrible person. Now there’s a narrative Big Media can love.
How does this work out for the GOP? I think the argument is: you have to stop antagonizing Latinos and support anmesty that will legalize millions of people who aren’t ever going to vote for you, because otherwise you will lose elections.
That about sum it up?
That sounds like the kind of logic our GOP should go for.
But that’s election politics. What about the moral equation?
I’m not sure why people who came here illegally as adults should cut in line in front of people who tried to become citizens the right way. How to deal with people brought here at a young age is a more difficult question, since it’s not their fault they’re here. You could argue the incentive aspect, but as long as we have birthright citizenship, there is an incentive to come here illegally for your children’s sake. I don’t particularly mind helping out people who have spent their whole lives here and are technically illegal through no fault of their own.
But it’s different for adults.
If we believe amnesty is immoral because it allows lawbreakers to cut in line, where is this electoral benefit that mandates rewarding illegal behavior? Please explain.
One fella named Chip S. came along to say that the whole argument was a ridiculous strawman; nobody really believes that result.
Chip S. was annoyed because I had posited, without doing research on it, that this study would be the type of thing Big Media and Freakonomics types would write about:
You can easily see journalists writing an article that wows the public. Call the Freakonomics guys. Can’t you envision a section of a chapter talking about this surprising result, and discussing the likely reasons for it? Perhaps the shoppers were paralyzed by indecision when presented with so many choices. Valuable information, certainly, for any marketer to know.
Valuable — and almost certainly wrong.
Was I wrong that this would be the sort of study Big Media and Freakonomics types would jump on?
Please. Would I ask the question so publicly if the answer were unflattering to my predictive powers?
I looked this evening. There is a New York Times article pushing the idea. There is a book that features the study as an example of how choice can paralyze people. There are blog posts making the same point. And plenty of my commenters came out in support of the jam study’s conclusion — seemingly overlooking Manzi’s assertion (as reported by my post) that, if anything, studies show the opposite of what the jam experiment purports to show.
Why, as it turns out, even the Freakonomics peoplewrote about it. What is especially funny about their post is that they clearly love the counter-intuitive finding, admit that it fits their preconceptions — and then quote someone showing the study’s results cannot be replicated consistently . . . and then . . . and then conclude that, hey, maybe people should streamline choices anyway:
So even if jam studies of the future prove inconclusive, it still seems wise to streamline choices whose complexity might otherwise hamper a good outcome.
In other words, the result is just so much fun, it’s a shame to toss it overboard just because it cannot be shown to be accurate.
People love this so much, I thought I would look for Manzi talking about this in a written format, and let him make the argument himself, rather than have me report to you about something I heard in a podcast. So I found Manzi discussing this in more detail at the Corner and thought it was worth quoting at length:
What are the odds that we would see one randomly chosen group of about 100 of the people who were given a coupon have a redemption rate that is ten times as large as another similarly sized random group of people given the exact same coupon? It’s larger than you might think. Consider an example. A recent in-store coupon executed by a large-format grocery-store chain was distributed to more than 1.3 million shoppers. I randomly divided them into about 13,000 groups of 100 shoppers each. I then randomly paired each of these groups with one other, creating about 6,500 randomly matched pairs of randomly selected groups of 100 shoppers. In a little over 9 percent of these pairings, the redemption rate was at least ten times as high in one group as in its matched pair. The jam experiment, by this simplified and indicative metric, would fail to achieve standard measures of statistical confidence required to reject the hypothesis that this was just random variation.
And while the specifics will vary for any given coupon – based on characteristics like product category, average redemption rate, time of year, and so forth – this indicative analysis almost certainly understates the actual probability of seeing this much difference between the two groups in the experiment. The two groups of jam buyers were not assigned randomly. Because the experiment was done for a total of ten hours in only one store, and because shoppers were grouped in hourly chunks, there are all kinds of reasons why the people who happened to show up during the five hours of limited assortment might have different propensity to respond to one-dollar-off coupons for a specific line of jams than those who arrived in the other five hour period. Maybe a soccer game finished at some specific time, and several of the parents who share similar propensities versus the average shopper came in nearly together, or maybe a bad traffic jam in a part of town with non-average propensity to respond to the coupon dissuaded several people from going to the store at one time versus another. Remember, all of the inference is built on the purchase of a grand total of 35 jars of jam. This is one reason why rigorous retail experiments, when a lot of money is at stake, are typically executed for dozens of randomly assigned stores for a period of weeks — and even sample sizes like that are pushing the envelope of causal inference.
But the result is at least interesting, and the right way to figure out whether or not the result is valid and generalizable is replication. Over the past ten years, a number of such experiments have been done by academics to evaluate the asserted paradox of choice for product categories ranging from mp3 players to mutual funds, and a paper was published in February (Scheibehenne, et al.) that conducted a meta-analysis of 50 of them (h/t Tim Harford). Across all of these experiments, the average effect of increasing choice on consumption or satisfaction was “virtually zero.” Further, this meta-analysis showed a positive average effect of increasing choices for those experiments that, like the jam experiment, tested the effect of choice on consumption quantity, rather than some measure of satisfaction, as the outcome. That is, when it comes to sales, more choice is better.
This is consistent with all of the unpublished assortment experiments that I’ve seen, and should not be surprising. As a store adds more and more products to a given product line assortment – say, canned soup – sales will rise sub-linearly with product count.
The key, again, is whether repeated experiments produce a predictable result — not how much fun the answer is, or whether it is in line with your preconceptions.
It’s a hard lesson to remember, but I think it’s a valuable one.
The Department of Homeland Security is seeking to acquire 7,000 5.56x45mm NATO “personal defense weapons” (PDW) — also known as “assault weapons” when owned by civilians. The solicitation, originally posted on June 7, 2012, comes to light as the Obama administration is calling for a ban on semi-automatic rifles and high capacity magazines.
Citing a General Service Administration (GSA) request for proposal (RFP), Steve McGough of RadioViceOnline.com reports that DHS is asking for the 7,000 “select-fire” firearms because they are “suitable for personal defense use in close quarters.” The term select-fire means the weapon can be both semi-automatic and automatic. Civilians are prohibited from obtaining these kinds of weapons.
Not everyone will have to abide by Senator Dianne Feinstein’s gun control bill. If the proposed legislation becomes law, government officials and others will be exempt.
“Mrs. Feinstein’s measure would exempt more than 2,200 types of hunting and sporting rifles; guns manually operated by bolt, pump, lever or slide action; and weapons used by government officials, law enforcement and retired law enforcement personnel,” the Washington Times reports.
Place to one side for now the fact that, in light of the purpose of the Second Amendment, it raises questions for government officials to have the right to bear arms that citizens can’t. I think anyone would agree that the military should be able to have weapons citizens can’t, and the same arguably applies to law enforcement. Your neighbor doesn’t get to have a nuclear bomb.
But when “government officials” are not subject to the same laws as citizens, there is a problem.
That alone is reason to oppose Feinstein’s bill.
And why are assault weapons “suitable for self defense in close quarters” when used by government officials, but not necessary for citizens who want to defend themselves.
I have been discussing what I learned in a podcast in which Jim Manzi cautions people to be very skeptical about the authority of conclusions reached by social scientists, including economists. The point he consistently makes is that, to have reliability, any phenomenon should be repeatable in different situations in different contexts, allowing people to make consistent and reliable non-obvious predictions. One important corollary is not to make too much of a single study — no matter how interesting the result might be, or how much it seems to confirm your pre-existing biases.
We all do this. Here’s a fun real-world example showing why it’s a bad idea.
Economic theory tends to hold that greater choice leads to greater demand and consumption — thus, if you want to sell more, offer more choices to your consumers. But Manzi tells the story of researchers who set out to test this. They ran an experiment in which they set up a table at a grocery store on two successive Saturdays. At the table, they had a selection of jams and jellies. One Saturday they had a selection of six different jams and jellies, and the other Saturday they had 24 varieties. On each day, they asked shoppers to taste their wares, and if they liked them, the shopper would be given a dollar coupon to redeem at the checkout counter to purchase one of the jams or jellies.
Conventional economic theory would hold that the day where the greater choice was available, a higher percentage of coupons would be redeemed. But the researchers found something counterintuitive and interesting. On the day where they had six different jams or jellies for purchase, fully 30% of the shoppers used a coupon to buy jams or jellies. On the day when they had 24 different varieties of jams or jellies, only 3% of shoppers redeemed the coupon.
Fascinating, huh? Reducing choice actually increased sales. You can easily see journalists writing an article that wows the public. Call the Freakonomics guys. Can’t you envision a section of a chapter talking about this surprising result, and discussing the likely reasons for it? Perhaps the shoppers were paralyzed by indecision when presented with so many choices. Valuable information, certainly, for any marketer to know.
Valuable — and almost certainly wrong.
Manzi says it was a mistake to draw sweeping conclusions from this single experiment. After all, look at how extreme the results are.
Can it really be true that all you have to do to increase sales by a factor of 10 is to remove 75% of your supply from your shelves? If this is the case, Manzi says, retailers everywhere are leaving “suitcases of money on the ground.” That is a HUGE effect — and frankly, so remarkable that it should raise a red flag.
The effect was so remarkable, in fact, that people have tried to replicate this experiment using other products, in other contexts, to see if the results can be repeated. And they can’t be. Manzi says that the experiments produuce a wide range of distributions — and that the general trend is that greater choice leads to greater demand.
Remember this the next time a single social science study comes to a conclusion you like. It’s tempting to cite such a study — we’re almost all guilty of this. But I am personally going to try to be aware of this in the future. Unless a phenomenon is proven through repeated observation in different contexts, allowing people to make repeatable, reliable, non-obvious predictions, the result of a social science study should always be viewed with immense skepticism.
I recommended this podcast in which Jmes Manzi argued that the confidence we have in social science predictions depends upon the ability of the “scientist” to make accurate predictions about the future that are non-obvious and can be repeated.
One phenomenon he discusses is the way people react in economics if their predictions go wrong. Manzi said that, before the the $820 stimulus was passed, he said he didn’t know whether it would work — but he did know that its supporters would say it worked regardless of the data:
[At the time I said:] I don’t believe any of the folks making these confident assertions really know what the effect will be. And the only prediction I’ll make is this: I’ll predict that, in early 2011, you know, professor, famous economist X said: unemployment will be about x%, say 10 percentage points without the bill and 8% with the bill. When it gets to be 2011, if unemployment is 10%, here’s what that professor is going to say: You know, conditions were worse than we thought they were; so without the bill unemployment would have been 12%, not 10%. Now unemployment is 10%. See, I was right all along; it lowered it by 2 points. And that’s exactly what happened, of course. That’s exactly what the economist said. And it has nothing to do with Democrats versus Republicans, by the way. If John McCain had been President, it would have been Republican advisors, too. And what I said is you cannot know the counterfactual reliably.
The other thing stimulus supporters say is: it would have worked better if it had been bigger.
In other words: if the data don’t prove your policy successful, you always say the situation was worse than you had realized, and the cure should have been more extreme.
This takes place in politics as well. If your candidate loses, one side will say it was because he wasn’t moderate enough, and he frightened off undecideds. The other side will say it was because he wasn’t principled/hardline enough, and he lost the base.
Each side will always draw the lessons they want to draw, and a plausible case can generally be made. But generalizing from specific instances is well-nigh impossible. Moderate candidate x might do great while moderate candidate y tanks; hardline candidate a might wow the electorate while hardline candidate b loses them. If winning elections were always about providing candidates closer or further from the center, winning elections would be easy.
In the economic context, our inability to predict the future with perfect accuracy leads people like me to believe we should have less government involvement, because it is often hubris to believe your particular intervention will have the desired effect on the economy. Far better to leave decisions to the collective expertise of society, which in the aggregate knows far more than any set of people in a room in Washington D.C., no matter how smart and well-informed they may be.
In the context of politics, our inability to predict the future leads people like me to suggest that candidates simply advocate what they believe. (Shocking suggestion, I know.) If you can’t be sure how to manipulate people, how about not trying to manipulate them at all?
And maybe — just maybe — your sincerity will actually win them over. Even if not, at least you don’t have to remember what your positions are supposed to be. You can just remember what they actually are.
We all make the error of confidently saying that this or that governmental policy is certain to have this or that effect. But while studying history and economics is important, perhaps a little humility is in order.
I have told you that I am a fan of Russ Roberts’s Econ Talk podcast. Today I listened to one in which the guest questioned whether people can confidently use economic (and other social science) theory to confidently predict the effects on human behavior of changing certain variables. Do we truly know that a stimulus is going to increase GDP . . . or that it is not?
The hour-long podcast summarizes concepts in a denser and more complex book. I’m going to dumb it down even further and summarize three or four of the points the guest made that stuck in my head. I’ll do so over a series of posts, so let’s start with a single observation that is central to the guest’s thesis.
Essentially, the guest distinguished social sciences from hard sciences that give one the ability to make consistent non-obvious predictions about the future. One example he gave to make the point:
[I]magine you are the President of the United States and you are receiving, you are considering an Iranian nuclear weapons program, what to do about it.
And into the room walks your science advisor and she says: Look, if the Iranians take the following amount of physical material and combine it in this size and using this method, it will create an explosion big enough to blow up the city.
And next into the room comes an historian. And the historian says: Well, you know, if an attempt to subvert the Iranian nuclear weapons programs, my reading of the history of Iran is that the people will want this enough they will continue to replace, one way or another, the government until this happens. So it really is not a good idea to try and stop this.
And what I say is, no, even if this happens to be President Carter, trained as a nuclear engineer, even if you know nuclear physics, for the President to sit there and begin debating the empirically validated laws of physics with his physics advisor is kind of foolish. On the other hand, not debating the historian, not bringing in different historians of different points of view, talking to people who have lived in Iran, personal introspection about human motivations, would be equally foolish.
And so really you ought to treat the prediction made by the physicist very different from the one made by the historian. Both are very valuable. I would never advise taking action without listening to both those. People make lots of use of historian experts and non-historians make lots of useful predictions about this situation.
And then imagine, third, his economic advisor walks into the room. And she says: Well, you know, the CIA has a program to counterfeit currency in Iran. And this amount of currency will create this amount of inflation and unemployment. The question I pose is: Should you as the President treat the economist’s prediction more like the historian’s prediction or more like the physicist’s prediction? And what I say is: A lot more like the historian’s prediction.
Economics is not hard science like physics. It’s more like history. There are too many complex variables to make consistent predictions about exactly how changing one variable will affect the economy.
This, by the way, is why I tend to oppose any government intervention in the economy. There are so many documented examples of unintended side effects that I think it’s best to leave a complex system to the distributed intelligence of the nation and indeed the world, rather than trust a group of supposedly smart guys in a room with their hands on the financial levers. The more humility you have, the less apt you are to opt for the government solution.
The big government guys are the arrogant ones. We free marketeers believe in the market precisely because we don’t think we know everything.
UPDATE: It’s also worth noting, as I have noted many times, that capitalism is the only economic system fully compatible with freedom. My comments about supporting capitalism in this post are made in the context of discussing what economic system is most likely to work. But freedom is an independent reason for supporting capitalism. Everyone who regularly reads my blog understands this.
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