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Thursday, March 25, 2010

How big is government?

In the Principles class, when I start the section on the structure of the tax system, I always ask students if they believe taxes are "too high, too low or about right". The majority always answer "too high". After reading a recent article by Bruce Bartlett [hat tip to Mark Thoma] I'm now tempted to ask them more specific questions about their beliefs about taxes and the size of government, since Bartlett has done the work of finding the answers for me. I don't usually do such extended quotes but this is great stuff (I should also mention that the responses from the Tea Partyers are exactly why I think we need to teach this stuff in Principles):
Tea Partyers were asked how much the federal government gets in taxes as a percentage of the gross domestic product. According to Congressional Budget Office data, acceptable answers would be 6.4%, which is the percentage for federal income taxes; 12.7%, which would be for both income taxes and Social Security payroll taxes; or 14.8%, which would represent all federal taxes as a share of GDP in 2009...

According to the CBO, the highest figure for all federal taxes since 1970 came in the year 2000, when they reached 20.6% of GDP. As we know, after that George W. Bush and Republicans in Congress cut federal taxes; they fell to 18.5% of GDP in 2007, before the recession hit, and 17.5% in 2008.

Tuesday's Tea Party crowd, however, thought that federal taxes were almost three times as high as they actually are. The average response was 42% of GDP and the median 40%. The highest figure recorded in all of American history was half those figures: 20.9% at the peak of World War II in 1944.

To follow up, Tea Partyers were asked how much they think a typical family making $50,000 per year pays in federal income taxes. The average response was $12,710, the median $10,000. In percentage terms this means a tax burden of between 20% and 25% of income.

Of course, it's hard to know what any particular individual or family pays in taxes, but according to IRS tax tables, a single person with $50,000 in taxable income last year would owe $8,694 in federal income taxes, and a married couple filing jointly would owe $6,669.

But these numbers are high because to have a taxable income of $50,000, one's gross income would be higher by at least the personal exemption, which is $3,650, and the standard deduction, which is $5,700 for single people and $11,400 for married couples. Owning a home or having children would reduce one's tax burden further.

According to calculations by the Joint Committee on Taxation, a congressional committee, tax filers with adjusted gross incomes between $40,000 and $50,000 have an average federal income tax burden of just 1.7%. Those with adjusted gross incomes between $50,000 and $75,000 have an average burden of 4.2%.

Even though the Tea Partyers were specifically asked about federal income taxes, it's possible that they were thinking about other federal taxes as well, such as payroll and excise taxes. According to the JCT, when all federal taxes are included, those earning between $40,000 and $50,000 have an average tax rate of 12.3%, and those earning between $50,000 and $75,000 pay a rate of 14.5%.
To be fair, in states with income taxes (like California), I don't think people differentiate between state and federal taxes - they just see money being taken out of their paycheck. But even if you add in state income taxes, my guess is that adds maybe another few percent for most people, so still nowhere near 20%. The full survey is here, with some additional questions with equally fascinating /scary answers. 

Monday, March 22, 2010

Teaching thinking

I mentioned in an earlier post that I had to explain to my writing class why economists do specification checks (we've been reading some empirical journal articles) and how many of the students are not really familiar with the process that economists go through when we write empirical papers. I think that part of what is hard for students to grasp is the constant questioning we do (and this is true not only for economists, but anyone who does research). As an empirical economist, I'm always asking: does my model make sense? What else, other than the variables I'm focusing on, could be driving my results? Can I get data on those other variables? Is this really causation, or just correlation? Given that I will be teaching a data and statistics course next semester, I've been thinking about how I am going to teach students to ask similar questions.

With that in mind, I thought a recent Freakonomics post was a great example of this process. Eric Morris has had a bunch of posts about gender differences in driving, first pointing out that men are more likely to drive when they get in the car with women and then following up with why that might be and whether men or women are actually better drivers. I think the latest post in this series would be a great example for teaching about how economists think for several reasons. The article begins with this:
We’ve established that men are more likely to take the wheel when a couple rides together, but should we care? I say we should. Aside from the cultural, sociological and psychological implications, the gender driving disparity might be costing us lives and treasure. If women are more skilled drivers than men, perhaps we’d all be better off if they were behind the wheel and men were in the passenger seat knitting. What do the data say?
This is my favorite question about any research project: why do we care? What's hard to explain to students is that while this can sound normative, the way the justification is phrased is actually positive. Here, Morris isn't saying women should always drive just because it's his opinion; he's saying that IF women are more skilled drivers, THEN having more women drive might save lives (the normative part is assuming that people want to save lives but that seems fairly uncontroversial). And then we turn to the data to find out if women really are more skilled.

Next, Morris points to data showing that women have fewer accidents than men. Many people would simply take that information and conclude women are safer drivers. But economists know that such simple statistics do not hold "all else equal" and Morris goes on to discuss some of the other issues that one should consider, like that men spend more time driving so you'd want to control for miles driven (men have fewer accidents per mile), or that not all accidents are the same so you might want to look at fatal accidents (more likely for men) separately from crashes involving just injuries (more likely for women). We also don't have data on who is at fault in these accidents or what time of day accidents happened (for example, men may be more likely to be driving at night). Or there might be selection bias because when a couple gets in the car, even if the man isn't a great driver, he might be better than his partner. In other words, we still don't know what is correlation versus causation.

By the end, Morris still hasn't definitively answered the question about whether women are 'better' drivers than men but the questions he raises are exactly the kinds of questions that one would want to have answered before making any kind of policy decision based on the empirical results.

Tuesday, March 16, 2010

Time-crunch blogging

I'm off to a conference this week (is it really going to be warmer in Richmond, VA than in San Diego by Friday?!?) so thought I'd just share a few links that I've been meaning to write more about...
  • Dan Hamermesh points out two examples of externalities on airplanes. As one commenter notes, I'm waiting for rules about crying babies...
  • If you don't read Jodi Beggs' blog already, Economists Do It with Models, you really should. Two recent posts I particularly liked were on the stupidity of charging for 911 calls (with an excellent explanation of public goods and common resources) and the opportunity cost of weddings (though that one's by a guest poster).
  • The New York Times Magazine had an outstanding piece on teaching that I really want to write more about but in the meantime, just go read it!

Friday, March 12, 2010

Teaching writing

There was an article in Inside Higher Ed last week about the difficulty of teaching writing. Rob Weir offers some useful advice about using visualization to help students organize their thoughts and structure their papers. He concludes with this caveat:
These models are strictly for students who struggle with organization. Every one of them is something that college students should have learned in high school. The models won’t add the magic that differentiates sparkling from pedestrian prose. They will not turn your students into Marlowe or even Sarah Vowell. Nor will they cure syntax errors, grammar, shallow thinking, or lack of command of the subject. What they can do is provide students with methods of imposing order upon randomness.
Unfortunately for me (from this particular perspective), the students in my writing class all seem to have a decent grasp of basic organization already. The reason this is unfortunate for me is that since they are solid on basic organization, I have to figure out how to help them improve the more nebulous aspects of their writing. Again, to quote Weir:
Teaching writing is hard on many levels, not the least of which is the gnawing suspicion that it's impossible. There are techniques instructors can share and exercises that sharpen student skills, but what is it exactly that makes one student’s writing sparkle while another’s lies pallid on the page? Answering that is akin to resolving the nature-versus-nurture argument by assigning precise percentages to each.
The writing class I teach focuses on writing like economists, so I focus on a) writing with and about data, and b) staying as much in the realm of positive analysis as possible. Getting students to write concisely, without the (often normative) rhetoric that they are used to throwing into other papers, tends to be the biggest challenge. I constantly struggle to figure out how to explain to them that such writing doesn't have to uninteresting. The only way I really know how to show them is by example, which translates into spending hours marking up their papers with suggestions for different ways to phrase things. But since I only do this on their final papers, I wonder how many of them really look at those suggestions or think about how to take those suggestions and incorporate them into the next paper.

I'm not really sure what my point is here except that teaching writing is hard...

Wednesday, March 10, 2010

Talking about teaching

In a recent post, Derek Bruff raises an issue that has often nagged at me when reading articles or watching presentations about teaching and pedagogy:
...one of the principles I attempted to uphold when writing my book was that everyone’s teaching context is different–different students, different disciplines, different institutions, different teaching styles and experiences.  I’m interested in helping instructors think more intentionally about their teaching choices, exploring the pros and cons of choices both traditional and innovative.  So while I may be more excited myself about smart phone systems, I always encourage instructors to select technologies and teaching practices that make the most sense in their particular teaching contexts.
As Bruff points out, every teaching context is different. Even when the contexts seem quite similar, different teachers may have different ideas about what will work 'best' for their students. Unfortunately, I often encounter people who forget this and instead seem to believe that everyone should do things the same way that they do them. Although I know these people are well-intentioned, I am generally a bit put off when I encounter someone telling me the 'right' way to implement a particular teaching innovation. It's one thing to point out that doing things a certain way has specific pedagogical benefits; it's another to judge teachers who choose to do things a different way. A good example is using clickers for peer instruction - I certainly believe that it's better for my students to have them grapple with well-designed peer instruction exercises. But I would never suggest that someone who 'only' uses clickers to check basic understanding of concepts is doing something wrong (and Bruff isn't just being modest in the quote above - I think he does an excellent job in his book of providing options without any judgment).

When teachers find something that works for their students, especially if that something is relatively innovative, it's easy to feel like everyone else should do the same thing. But part of good teaching is also figuring out what works for your students, what is comfortable for you, and recognizing that whatever that is, it may not be the same as what works for someone else.

Monday, March 8, 2010

Letting students fail?

I did something today that I don't normally do - I directly confronted a student (actually, two) who wasn't engaged in class. I had asked a clicker question related to elasticities and gotten a really mixed answer distribution so I asked students explicitly to draw the graphs associated with each of the four possible responses (basically, the four possible combinations of elastic/inelastic supply/demand) and then I was going to re-ask the question. While they were supposedly drawing the graphs, I walked around the room. When I do this, there's always a disturbing number of students who are not doing what I've asked them to do. Even more disturbing is that there are always some students who are do not even make a pretense of caring; they aren't taking notes, they just sit there, sometimes texting on their phones but often, I really have no idea what they are doing. I usually ignore these students - I will sometimes remind them that if they never practice doing economics, they won't actually learn economics but my generally philosophy is that they are (supposedly) adults and if they choose not to take responsibility for learning anything, it's not my job to "make" them. But for some reason, today it was really bugging me. Maybe I'm tired and it's Monday, maybe it's the cloudy weather, or maybe we've just hit that point in the semester when I really need a break, but it just suddenly was incredibly annoying that I was putting in all this effort and these students were just sitting there - and when they fail the class, they will probably blame me - and something inside me sort of snapped. So I stopped next to one of these students who was just sitting there, staring into space (nothing in front of him, no notes, no pencil, nothing), and I asked him, "I'm curious - do you find that you can remember everything without taking any notes?" He looked up at me and seemed surprised (though I'm not sure if he was surprised at my question or the fact that I was talking to him at all) and said, "No, I never take notes, in any of my classes." I just said, "Um, OK..." and kept walking. And across the aisle was another student who was not only just sitting there, staring into space, but had these big headphones on (I'm talking old-school padded stereo headphones, not even little earbuds) and didn't appear to even have a backpack with him. So I stopped in front of him and asked, "Can I ask you, why exactly are you here? You're not taking notes, you're not even listening. Why bother coming to class at all?" He protested that he was listening, his headphones weren't even plugged in, showing me the unplugged cord. I made a somewhat sarcastic remark about keeping his ears warm and suggested he at least bring something to write with next time. At that point, I went back to the podium and engaged the clicker question.

Interestingly, headphone-guy came up to me after class and said that he has to miss class on Friday and just wanted to check what we would be covering so he could keep up. I got the feeling that he was feeling guilty and I felt a little bad. But I also am wondering if I should do that sort of thing more often. On the one hand, I really don't think that I should have to tell college students that they should take notes, and I shouldn't have to badger them into attempting the graphing questions I give them. On the other hand, if they don't do these basic things, their chances of failing my class are even higher. At what point does their failure become more their responsibility than mine?

Friday, March 5, 2010

Experiments in large classes

I primarily use Aplia to do experiments, rather than problem sets. When I started teaching the 500-seater, one thing I knew was that I didn't want to give up activities like having students participate in a market auction but I couldn't imagine how that would work in class so I adopted Aplia.Well, as I mentioned a while ago, there were a couple of presentations at the TIP conference in January that downright inspired me and one was by Jose Vazquez-Cognet, at the University of Illinois, Urbana-Champaign, who discussed the double-oral auction that he does with his class of 800. To be clear, he does this in class, not using Aplia or some other computer simulator - he actually has 800 students milling around, trying to buy and sell from each other! I would never have imagined trying this in such a large class but listening to him explain what he does, it actually does sound do-able. One thing that helps is he creates smaller trading pits within the room: students can trade with those in their immediate area but they can't go running around to the other side of the room. He also has figured out a way to have students switch roles, from buyer to seller or vice versa, without having to pass out new information sheets. I'm sticking with Aplia this semester but am definitely tempted to give it a try next semester...