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Hockey has a strange system to determine who makes the playoffs. Each team receives two points for every match they win, zero points for every match they lose in regulation and one point for each game that they lose in overtime. This point total, not overall record, determines which teams make the playoffs.
For simplicity, let’s assume in any given match that each team has an equal chance of winning. The expected value for any regulation match is one point (the average of the winner’s two points and the loser’s zero) and the expected value for any overtime match is one and a half points (the winner gets two, the loser gets one).
In-conference matches involve one team trying to gain ground on the other. The expected value is not important. In this situation, teams only care about the expected gain (or loss) in points relative to their opponent. An overtime win results in a net gain of one point while a regulation win awards a net gain of two.
Teams from different conferences don’t compete with each other for playoff spots. So while teams playing within their conference care about expected gain, teams playing outside their conference care about expected value. If teams try to maximize these values, they will prefer for conference games to end in regulation and non-conference games to go into overtime. This affects third period strategies in close games. More importantly, it provides plenty of incentive for unspoken collusion between teams in different conferences.
Expected value is a concept that allows us to factor in the probability of an uncertain event into our calculations. Imagine that you have a summer roofing job in Sandy, Oregon. I chose Sandy because it gets 182 precipitation days per year so on any given day there is a 50% chance of not working due to the weather. If you get paid $80 per day worked and $20 when you do not work due to rain, what should you expect to make in a twelve-week summer? Let’s break this down into a smaller problem.
The expected value of any given workday is the average of the payment received for working ($80) and not working ($20), which is $50. This is because there is an equal chance of either type of day occurring. By extension, the expected value of a five-day work week is $250 and of total summer income is $3,000.
What does this have to do with betting? A fair bet has an expected value of zero. For example, a bet of $10 on a coin flip is fair. There is an equal chance of losing or gaining $10. The average of these two values (+10 and -10) is zero. Casinos make their money by offering unfair bets. The expected value of (almost) every casino bet is negative (and none of them are positive). They cannot collect a guaranteed profit from a fair game so they count on you to play a rigged one. What do you suspect about the expected value of casino profits?
Economists and accountants are often thrown into the same category. Accountants look at dollar values. What differentiates the economist is the addition of a concept called opportunity cost. One of my favorite examples of this involves a friend offering you $500 to help him move. If this is an uneventful day, you will probably help. If it is a holiday, you may decline. If it is Super Bowl Sunday and you have tickets to the game, you most likely will decline. The key is that you have to weigh all of your other options before making a decision.
In his book, The Baseball Economist, J.C. Bradbury offers one of the most intelligent arguments I have ever heard for the absence of left-handed catchers. Since 1902, a left-handed catcher has been used in only sixty-three games. Bradbury sifts through some of the common arguments of why they rarely exist (difficulty throwing to third base, coordination with pitchers, throwing errors, etc.). Through cost-benefit analysis, he dismisses most of these as insignificant.
Where he concludes is extremely insightful. Being a catcher requires intelligence, a strong arm, and good vision. If you are left-handed and have these qualities, your coach is most likely not going to position you as a catcher. He will use you where your talents are most valuable–as a pitcher. No real bias against left-handed catchers exists. The cost is just too great to waste a southpaw at catcher when he could be stepping on the mound.
Picture a Coke machine next to a Pepsi machine. Let’s say a Coke and Pepsi each cost $1 today. Tomorrow, the price of Coke jumps up to $2. What do you expect will happen? Two things should come to mind. First, fewer people will buy Coke. It’s more expensive. This is the law of demand. The second effect is that some people will now switch from Coke to Pepsi. They are substitutes–when the price of one increases, people buy more of the other. Here are some interesting examples:
Certain nationalities have a relatively harder time gaining American citizenship through immigration and/or naturalization. We’d expect to see an increase in demand for substitutes among these groups. The closest substitute for naturalization is marriage to a U.S. citizen. U.S. immigration policy not only shapes the international marriage market, it does so with national bias.
In times of economic trouble, finding work can be tedious. It requires dedication, persistence, and patience among other things. When job search costs are high, we expect to see an increase in demand for substitutes. The three that come to mind are government assistance, crime, and civil lawsuits.
Huffing is the act of getting high by inhaling toxic fumes. Minor headlines revolve around fears of epidemics among teens. How can we reduce the amount of huffing? Increase the availability of substitutes. Keep some beer in the garage next to the paint. Fewer kids will choose a chemical high when alcohol becomes more available.
“My boss can’t find anything without me.”
“He’s a slob–his mother constantly cleaned up after him.”
“I can’t spell–I’ve got spell-check.”
Simply put, economics is nothing more than the study of decision making. Whether we’re car shopping, eating out, or contemplating stealing, part of us asks “What will this really cost me?” This implies that weaker punishments lead to more crime, but what about incentives involved in everyday bad behavior?
Housekeepers reduce the cost of untidiness; so those who use these services are messier than they would be without them. Similarly, spell-check reduces the cost of misspellings; while administrative assistants maintain the incentive for the big boss to remain unorganized. The stakes can get larger, however.
In The Armchair Economist, Steven Landsburg suggests that safety regulations (seatbelt laws, mandatory air bags, etc.) increase the number of accidents. He argues that the cost of driving carelessly is lowered in terms of expected injury or death. Likewise, competent nurses diminish the costs of doctors making mistakes, leading to more errors. Birth control reduces the cost of unprotected sex, thereby increasing its frequency.
What about those who never had the incentive to learn how to be good drivers, competent doctors, or responsible sexual partners? Much like spell-check users on a handwritten exam, when these individuals leave their coddled environment, they cannot simply switch to demonstrating good behavior because they never learned good habits in the first place. Once they lose their safety nets, the potential damage they can inflict greatly increases.
In the spring of 2011, Ray Lewis made the prediction that crime would increase if the NFL lockout prevents the football season from occurring. For some people, like the kids mentioned in his statement, football is a substitute for causing trouble. Ray Lewis (and subsequently LaVar Arrington) left out half the story. A group exists that causes crime because of football. Examples include football drunks and overly aggressive fans (e.g. the baseball incident in May 2011). Without football, the first group will cause more crime while the second group will commit less crime. Due to the uncertainty of the relative sizes of these two groups, predicting the end result is not so easy. I would’ve suggested that crime would decrease, but I am no better of a predictor as we are all victims of the same type of bias.
Mr. Lewis and Mr. Arrington believe the number of aspiring players is larger than unruly fans. I suggest the opposite. Why? Tversky and Kahneman’s availability heuristic suggests that we tend to think there are more of the types of people or things that can easily be brought to mind. The aforementioned NFL players believe that in the average community there are more aspiring athletes than fans. They grew up in such communities. I grew up in a place with relatively more fans, so I fall for the same type of selection bias by asserting the contrary. None of us has experienced the random sample necessary to make a reliable estimate. One of us is likely right, but based on poor methods of estimation.
- Principles of Microeconomics:
Fall 2014-Loyola (1)* | Fall 2014-Loyola (2)* | Spring 2013-UIC | Fall 2011-NEIU
- Principles of Macroeconomics:
Fall 2013-Loyola* | Spring 2013-NEIU | Spring 2012-NEIU | Spring 2011-UIC
- Intermediate Microeconomics:
Fall 2014-Loyola (1)* | Fall 2014-Loyola (2)* | Fall 2010-UIC
- Intermediate Macroeconomics:
Summer 2012-NEIU**
- Econometrics:
Fall 2013-UIC | Summer 2012-UIC | Spring 2012-UIC | Summer 2011-UIC | Fall 2008-GMU
- Behavioral Economics:
Fall 2012-UIC | Fall 2012-NEIU
- Mathematical Economics:
Fall 2011-UIC
- Health Economics:
Spring 2014-UIC | Spring 2014-Loyola
- Business and Economics Statistics II:
Spring 2013-NEIU
- Labor Economics:
Fall 2011-NEIU
- Industrial Organization:
Spring 2012-NEIU
- Micro / Macro Discussion Sections:
Fall 2009-UIC
- Fundamentals of Business Economics (MBA Course):
Fall 2012-NEIU
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* Awaiting responses
** Not available because of technical issues with new online evaluation system
I was fortunate to have some outstanding teachers in my life. They shaped me as a person, a student, and a teacher. As they inspired my learning, they also created my passion for teaching. In the last few years, I have taken almost every teaching opportunity I can. The process inspires new ideas for my research, strengthens my communication of the material, and renews my passion for the field.
Good teaching requires empathy and enthusiasm. I have been a student my entire life. This gives me the ability to understand what students expect and also what they should be given by their instructors. Students can sense when people do not care about what they are presenting. I am lucky to be teaching something that I am truly passionate about. I am rewarded when I see understanding in my students.
I push my students hard. I have a reputation as a rigorous instructor and a fair grader. Education is what you make of it. Students often enter my classes very concerned about grades. They quickly learn that I am concerned about their understanding of the material. Attendance is taken in all my classes. My exams are tough. I curve grades, but each semester I have a handful of students that require no curve to achieve a natural A. I often encourage these students to aim higher than simply graduating.
I believe in outside reading. I love books. In almost every class that I teach there is a required book other than the textbook. Economics is about telling good stories. There is no shortage of quality writing outside of journals and textbooks. I embrace these works in the classroom and my spare time.
I treat every class I teach as a performance. A quality education should combine good stories with a memorable delivery. While presentation is important, content is king. I believe this to be very true in higher education. I strive to bring the clearest, most relevant, and most memorable content into my classroom.
Technology is changing the way we learn. This year, I have incorporated clicker response systems into my courses. It has changed the dynamic of the classroom and allows students to observe their own economic behavior in real time instead of some given data. Also this year, I began creating content for a company that specializes in non-linear learning. It is as if a virtual tutor is guiding you through the material. This is the future path of learning.