Thursday, August 31, 2006

Example of Supply and Demand at work

The first graph we are learning in Intro to Micro is the well known Supply and Demand graph. Although some students may think this graph is a pure abstraction with no relevant applications, an article in the WSJ that came out today suggests otherwise.

http://online.wsj.com/article/SB115698145559550022.html?mod=pj_main_hs_coll

Note when reading this: Basic theory says that if suppliers face an inventory buildup they will cut prices. This is because when inventories are increasing it suggests that the price level is too high relevant to how much the company is producing. Therefore, if the company wants to sell all of its product that is already produced, it must cut the price level. A lower price level would then be an incentive for the firm to cut back on production of this item in the future. Now read this:

"Domestic car makers need to boost their sales efforts to get rid of 2006 inventory. In the most recent data for this summer covering the period of Aug. 1 to Aug. 20, it took GM an average of 84 days to sell a car, while Ford took 83 days and the Chrysler Group trailed with 90 days, according to the Power Information Network. In contrast, it took Toyota 26 days to sell a vehicle while it took Honda Motor Co. 37 days. The industry average was 64 days. High gas prices have favored the Asian auto makers as they are perceived to have more-fuel-efficient vehicles."

Tuesday, August 29, 2006

Course outline

I)Introduction

What is economics? Scarcity, Marginal benefit and cost.
MB1

Supply and Demand
Demand and supply curve, equilibrium price, determinants of supply and demand, price ceilings and floors
MB 3,4

Government and market failure
Complications to both simply supply and demand and government solutions to it
MB17

II)Consumer Behavior

Elasticity
Price elasticity of demand and supply, determinants of price elasticity, relationsthip between elasticity and revenues
MB7

Consumer Choice
Total vs Marginal utility, law of diminishing marginal utility, utility maximization
MB8

III) Cost of Production

Cost analysis
Production functions, marginal productivity, law of diminishing returns, accounting vs economic profit, long run costs and economies of scales.
MB9

IV) Market Structure

Perfect Competition
What is perfect competition? Output and price maximization, competitive firm in the short vs long run, economies of scale. How realistic is this market
MB10

Monopoly
What is a monopoly? Model of monopoly market Price discrimination,
MB11

Monopolistic competition
Differences between monopolistic competition and both perfect competition and monopoly. Price and output in price searcher market, real world competition
MB12
(216-222)

Oligopoly
Introduction to Game Theory and applications
MB12
(223-236)

V) Extensions

MB24

Monday, August 28, 2006

Movie Reviews, stars, box office revenue and normal probability distribution

One point I failed to take up in the post below was just what can be used to predict box office revenue. Luckily my masters thesis focuses on the impact critical reviews have on movie revenues (my undergraduate paper focused on in theatres while my masters extended and improved on a data set for video rentals). Essentially what the data tells us is the following:

Trying to come up with a formula for producing movies will not work. A feature of box office reviews is that there is no normal probability distribution---which is a fancy term for saying that while there is a mean (say \$100 million a movie) there is an infinite variance. When a data set has an infinite variance that means that most of the data is all over the place—one movie at 1 million, another at 800 million—and you can’t pinpoint exactly where the data will fall. For instance, in Stats101 you assume there is a “finate” variance and then you calculate what is called a standard deviation, which can be used to tell you how much data falls within a certain range of the mean.

This complicates any statistical analysis , but I tried to run what is called OLS on data available free online. My tentative conclusions—which I updated using 2001-2002 data)—is as follows.

1) The NY Times article is right—star power has little effect on overall box office returns.
2) Other factors, such as being a franchise, help you open a movie for the initial weekend but will not increase your returns much afterwords.
3) Critical reviews—which in my dataset is a compilation of all online and newspaper reviews as a % positive—are technically significant but will not make or break a movie. Overall, for instance, in increase from 50% positive to 70% positive will give the movie studio an extra \$10mn
4) Breaking down the effect of critical reviews show that the play both a small effect in the opening weekend and a decent effect on the amount of time the movie remains in the theatre. Using the same example from above, the 20% better reviews adds an extra \$3.25mn to box office revenue while extending the amount of time in the theatre 11 days.
5) Keeping in line with the article and the relevant literature, a bad review is a better predictor than a good review. That means reviews can kill a movie but they will not make one on their own.
6) Given the incentives of the movie industry (note below that the production company takes a much bigger share of the opening week revenue total than they do subsequent weeks), shorter term factors are more profitable. For instance, a movie that is a franchisewill add \$13.6mn during the opening weekend.But despite all this work I did for my masters thesis, the essential fact remains, it is almost impossible to predict what movies will make. Sometimes being a franchise will help (Pirates of the Caribbean?), but sometimes it won’t (Speed 2 anyone?).Yet given the almost infinite variance of movie revenue, perhaps having a Tom Cruise, a popular adaptation or a franchise will help lower the risk in making the movie.

Tom Cruise's firing and economics

The New York Times has an interesting article out on Tom Cruise and economics here http://www.nytimes.com/2006/08/28/business/media/28cast.html?ref=business

Interestingly enough, this topic discusses both my undergraduate and graduate thesis, what exactly drives box office revenue. The jist of the article is that there are many factors that go into making a big move, not simply whether Tom Cruise is in it or not (budget, whether it is a sequel, etc.).

In one study, Mr. De Vany and W. David Walls, an economist at the University of Calgary, took those factors into account. Looking across a sample of more than 2,000 movies exhibited between 1985 and 1996, they found that only seven actors and actresses — Tom Hanks, Michelle Pfeiffer, Sandra Bullock, Jodie Foster, Jim Carrey, Barbra Streisand and Robin Williams — had a positive impact on the box office, mostly in the first few weeks of a film’s release. In the same study, two directors, Steven Spielberg and Oliver Stone also pushed up a movie’s revenue. But Winona Ryder, Sharon Stone and Val Kilmer were associated with a smaller box-office revenue. No other star had any statistically significant impact at all.

So what are stars for? By helping a movie open — attracting lots of people in to see a movie in the first few days before the buzz about whether it’s good or bad is widely known — stars can set a floor for revenues, said Mr. De Vany.

One factor not discussed is the impact of "critical reviews." In the review of literature, I did not find one good test of this impact, so this was what my study focused on. My conclusion: critical views had a statistically significant but small impact on movie revenue (probably on the order of 1-2mn of a 100mn dollar movie, depending on the % of positive reviews). Other interesting conclusions were that bad movies are predicted to be failures better by critical reviews than are successful movies. Also, good reviews have a bigger impact on the amount of time the movie remains in the theatre. However, most movies make their most money during the first few weeks becuase the incentives are set up that way. The production companies get the biggest percentage of box office take during the initial weeks (a rough estimate is around 80%) rather than 5 weeks out (less than 50% and it declines the more weeks the movie is in the theatre). Therefore, the movie industry has a built in financial incentive to market big budget, star driven monster movies rather than critically acclaimed movies. This, I believe, explains the well noted drop in the quality of movies over the years and the increasing amount of focus on "event" pictures.

Friday, August 25, 2006

Economic Applications: Asymmetrical information and dating:

As I mentioned in my syllabus, economics has broad applications that are not narrowly focused on money. One example of this is in today’s WSJ, you can view the article here if you have a subscription. http://online.wsj.com/article/SB115646646975445112.html?mod=todays_us_nonsub_page_one

One of the first models we will learn is the model of perfect competition. In order for this model to work, however, certain conditions must hold. One condition that is sometimes not met easily in the real word is the condition of “perfect information.” That is, both the buyers and sellers in the market place must have all relevant information about the transaction. If not, then complications will arise. What may be less clear is that this type of market problem—technically called asymmetrical information—has applications for online dating.

These days, Mr. Schwarz is thinking about how to use economics to save attractive women from unwanted solicitations on an Internet dating site

Dating is a classic example of how people attempt to solve “asymmetrical information” When we first meet someone we are attracted to, we do not (usually) jump right into a relationship but rather meet various times (data) in order to obtain the relevant information we need to decide whether to date someone or not. Online dating presents a particular problem, especially for women, because the information tends to be tilted towards the guy requesting to talk/meet with the women. That is, the guy has all the relevant information he needs to at least go on a date—I am attracted to her—but certain types of women tend to attract more requests than others. What’s worse is that they have no real way to weed through all the requests and decide which ones to pursue further. What if one guy that looks like a possibility is only looking for a one night stand and has requested close to 200 women to see who responds? Hence, there is an information problem (which is why in my experience online dating tends not to work great, although clearly there are exceptions).

Here is how Schwarz attempts to solve the problem:

One idea employs the concept of "scarcity," rationing the number of free messages each lothario can send. Another uses full disclosure, by displaying how many people a suitor has already approached

As you can see, economics can be used to help improve online dating!

Note: for further discussion on this topic, take a look at www.marginalrevolution.com

Thursday, August 24, 2006

Course Syllabus - Microeconomics

Nassau Community College
Department of Economics and Finance

Course Outline: Economics 208: Principles of Microeconomics, 2005 – 2006

Required Text: “Microeconomics” Custom17th Edition.
Campbell R. McConnell and Stanley Brue; Irwin/McGraw-Hill 2006.

Optional Texts: Other articles that I will incorporate into the class will either be provided by me or available free online.

“The ideas of economists and political philosophers, both when they are right and when they are wrong, are more powerful than is commonly understood. Indeed the world is ruled by little else. Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist. Madmen in authority, who hear voices in the air, are distilling their frenzy from some academic scribbler of a few years back”

John Maynard Keynes 1935

Instructor: Matthew Festa, MA E-mail: M.fest19@gmail.com
Telephone: (cell) 516-987-0299 Dept: 516-572-7181
Office: None Office Hours: by request

Part I: What is this course about?
Catalog Description: . Overview of the economic problem, the traditional value theory, division of labor and its application to international trade. Analysis dealing with the behavior of individual elements in the economy. Organization of business, the various market structures, the theory of consumer behavior, price determination in the product and factor markets. Historic perspective of unions and their impact on the economy will be considered.

My Description: While economics can sound boring, it is actually a fascinating subject that has many broad applications. Essentially, the discipline focuses on a problem. That problem is that human desires are infinite. We all would like more stuff: tv’s, cars and vacations. However, there is not nearly enough “stuff” in the world to satisfy these unlimited needs. Therefore, we are forced to choose---economize---selecting A over B or B over C. This is essentially the problem that economics studies. Further, we economists have come to realize that people are often times not stupid in their desires as they oftent know what they want. With this further insight we can study an interesting phenomenon known as the invisible hand--- that is, people acting in their own self-interest tend to do what’s best for the economy as a whole. Granted there are important exceptions and limitations to this, but as a broad principle a market economy left on its own tends to produce better results than any comparable alternative that is more "planned." Finally, economics is not simply a dry discipline narrowly focused on “money.” Rather, economics has wide applications in politics, sports, movies, home life and a host of other subjects you would never think could be studied “economically.” I will try and incorporate various thinking on these subjects into the material.

Online resource: This semester I will try and incorporate the internet into the class. I found last semester that lots of quizzes, articles and even this very syllabus went missing for mysterious reasons that defy explanation. Therefore, I will try and get around that problem—and save some trees in the process—by posting most take home quizzes, class outlines, article, the syllabus and the course outline online on my blog. You can access this material here: http://increasing-returns.blogspot.com/ On the right hand side are the links to all important documents so you do not have to search for them.

30% exams (2 tests)
30% Final
30% Quizzes
10% class Participation

So what about class Participation? I am basing your class participation grade mainly on your attendance and your participation in class (i.e. questions are good, sleeping is not). I will allow up to 3 absences without penalizing your class participation grade. This should allow you room in the event that you cannot make any one class for whatever reason may arise.

Extra Credit: As a student I always loved extra credit opportunities and I believe they are a good learning tool. So here is how I will help you. If there is any article that you come across that is relevant to the class (either on your own or on the website) I want a 1-2 page analysis of what the article is saying and how it applies to what I have taught you. You can do up to three with each one worth 2.5 points.

Math Background: Economics is an empirical science and thus knowledge of mathematics is essential to success in the discipline. However, being that this is a principles class, I am going to restrict the math to the basics: so knowledge of arithmetic is required for this class. Calculators are permitted (as they will be when you get a job). You do not need to know advanced math, but I will ask you to do some arithmetic work on the quizzes and tests.

Withdrawal Policy – Department Policy for withdrawals is as follows: Students can withdraw from a course at any time up to and including the official withdrawal date of March 26th, 2007. After that date, students will only be given withdrawal for extraordinary reasons supported by appropriate documentation. This documentation should be copied and retained by the instructor.

The “W” grade is only guaranteed to those students who officially withdraw from class and obtain the faculty member’s signature during the automatic withdrawal period. Most important, a grade of “W” cannot be granted to any student who takes the final examination.

Note: The “W” grade may possibly impact financial aid and Academic Standing
Days Off

Note: There may be one or two times when a 6:30 start time may be slightly problematic (meaning I may be 10-15 minutes late). I will notify you a week beforehand as I can anticipate any possible problems.

Supply, Demand and the Oil Market

The Latest New York Times "Economics Scene" Column contains a good article discussing oil prices http://www.nytimes.com/2006/08/24/business/24scene.html?_r=1&oref=slogin. It illustrates some basic concepts in supply and demand we will be learning, but are worth a post on this site because they are topical.

This first quote illustrates a classic supply curve shift

"So when BP announced this month that it might have to suspend as much as 8 percent of the nation's oil production because of corrosion in pipes on the North Slope of Alaska, the price of crude oil immediately shot up by 3 percent and wholesale gasoline prices simultaneously increased by about 2 percent"

That is, when BP cuts the amount of oil production there is less oil to sell. This shifts the supply curve to the left, increasing price and lowering quantity in the market. The reason why quantity declines is easy: it is because there is less oil on the market. Price increases due to economic theory: since there was no shift in the demand curve this creates a temporary shortage. Realizing this suppliers increase the price until the quantity demanded equals the quantity supplied.

However, the article lists one major complication with this analysis: supply will be cut in the future, it will not immediately change the quantity supplied now. Why, then, did prices rise?

To spell out the argument, imagine that you own a storage tank full of gasoline that is currently worth \$2 a gallon at wholesale prices. It is widely believed, however, that the price of gasoline will be \$2.10 next week. You would be crazy to sell your gasoline now: just wait a few days and the higher price will be yours. But if everyone waits a few days, there is no gasoline to be sold now and the resulting shortage pushes the price of gasoline up. How high does it have to go? The answer is \$2.10 a gallon. That is the price necessary to induce those who have gasoline to sell it now rather than to wait till next week.

There are a few things that I want you to get from this.

1) Markets are usually forward looking. Producers and consumers try and anticipate and make their plans accordingly.
2) Thus, the expectation that the supply will decline causes the entire market to adjust.
3) The article later points out that the oil market has a lot of people in it, making the adjustment quick (literally changing current oil prices overnight). This is related to the economic concept of liquidity. The more participants there are--who know what they are doing--the better the price adjustment in.
4) As part of his analysis, he points to two possible complications (one directly one indirectly). One is that not all the participants know what they are doing. This is one criticism of basic supply/demand theory that we will be discussing in this class. The second is implied indirectly in that there may not be a lot of people in the market. What this suggests is that basic supply/demand may not describe all markets (we will be talking about monopoly/oligopoly markets later in this class, which function differently)

Wednesday, August 23, 2006

I figure that in my inaugural post I should give a hat tip to Greg Mankiw, who gave me the idea of integrating an economic commentary blog with the classes I teach for micro and macro economics. Therefore, I would like to extend his analysis of tradesports probabilities for the 2008 election, which you can view here. http://gregmankiw.blogspot.com/2006/08/potus-2008.html#links

Specifically, I would like to apply his conditional probability analysis towards baseball. According to trade sports the top 4 teams in each league who are expected to win the World Series are

World Series
1) NY Yankees 21.4
2) NY Mets - 14.3
3) Detroit Tigers - 12.4
4) Chicago White Sox - 9.5
5) St. Louis - 8.5

However, it would be incorrect to draw the inference that the Mets are the second best team in baseball because they play in a much weaker division and will thus have an easier time in the division/NLCS playoffs than other American teams that are better quality teams

Therefore, in order to calculate who the markets view as the best team we have to apply conditional probability based on the likelihood of winning the World Series conditioned on winning the pennant.

AL
1) NY Yankees 32.3
2) Detroit - 22
3) Chicago White Sox - 14
4) Oakland - 11.5

NL
1) NY Mets - 35.5
2) St. Louis - 21.2
3) LA Dodgers - 14.2
4) Reds - 8

As Mankiw did with the presidential probabilities, we divide the probability of winning the world series by the probability of winning the pennant and we get.

1)Chicago - 67.8
2)NY Yankees 66.3
3) Detroit 56.4
4) NY Mets 40.3
5) St. Louis - 40.1

We can thus see that the AL teams are more likely to win the World Series if they make it versus the NL team. Thus, any NL team that makes it to the World Series will be most likely viewed as underdogs.