In the fourth chapter of Freakonomics the main focus is the question of the relationship between abortion and crime rates. The study by Levitt and Donahue looks at the same question. They both find that higher abortion rates seem to lead to less crime and more importantly less violent crime. The books defense is the family dynamic of the baby that grows up even though the mother wanted an abortion. In many cases women chose to have an abortion because they are not in a position to raise a child. If they have to have their child then it makes sense that the child will feel less love, grow up poorer, have a lower quality of life, and in general be angrier. This type of person would then theoretically be more prone to crime. The critique, however, argues that not every child that the mother would have aborted turned out to be a criminal and therefore the evidence is laking. In a lot of ways law enforcement has also improved so although abortion rates might have an effect it might not be the only influence. It hard to argue with the evidence that states with higher abortion rates have less crime. It makes sense that the data and theories can be manipulated to show what the author desires so every statistic needs to be taken with a grain of salt especially when reading two opposing ideas.
As far as the ideas go the book and Levitt and Donahue do a more convincing job of arguing their point which is why I am more prone to think that abortion has an effect on crime rates. Like the book states a child that grows up in poverty with a single parent is more likely to lead a life of crime. Since a majority of abortions fell into one of those two categories it does justify the claim with theory. Still though one could argue that killing criminals in general would reduce the crime rate. One implication for me would be that capital punishment should be more readily used. Essentially the book is saying that aborting a baby that is likely to be a criminal reduces crime, so why wouldn’t killing criminals reduce crime? Yes its a controversial comparison but its the same idea that less criminals leads to less crime.
Either way even with correlations between the rates it is impossible to prove. When a baby is aborted there is no way of knowing what the baby would have become. I think the articles and book do the best they can with the limitations of concrete evidence and provided a very convincing argument that higher abortion rates is related to a lower crime rate.
The focus of this chapter was on lending to the poor through the use of microcredit by microfinance institutions. The idea is that these companies are one of the most successful ways of helping the poor rise out of certain moneylending traps. When the poor apply for a loan they have a high risk associated with them, this leads to a multiplier effect which in turn means that they have to pay very high interest rates. This leaves them in a situation where they have to continually repay loans and can never get out of debt. Since they are so high risk of defaulting the banks were unwilling to give them loans, so they had to turn to moneylenders. Several people noticed this and decided that there had to be a better way to help lend the poor money, Padmaja Reddy’s inspiration came when she realized that if a woman could buy a cart instead of renting it she would have a much greater amount of money for everything else. So she started loaning to people that banks would shy away from due to risk.
In theory it would seem that the MFIs would dramatically reduce poverty and help almost everyone out of the hole. However, in practice while it does improve the lives of those that borrow from them it is not very drastic. This is one of the reasons that I can believe the authors statistics. Since the authors are presenting the data to show that while these kinds of loans are improvements they are small, it seems believable. Perhaps it is underestimated but that would seem to go against the authors purposes. To me they want to show the reader that this is a good thing for the poor, and by presenting the facts even though they are small it would indicate that it is true.
It is sad to me that other people would step in to destroy a system that is meant to help the poor. The government’s corruption is an unfortunate reality that must be dealt with when considering this kind of company. The business world is always cut throat but it seems wasteful to be so in an industry that is there mainly to serve others. What makes it worse is that good ideas and potentially successful firms have to go unrealized because of greed. Although I still have to wonder if there is not a reason people like Miao Lei are successful and others are not. Perhaps it is better that not everyone has free access to credit. This way only those that are determined and have a sound business idea can survive. Something to consider is that the poor should be helped to be lifted out of their poverty but also to remember that not everyone with an idea would be a successful entrepreneur.
Gas Prices Rise, but So Do Auto Sales
The article talks about how car sales are rising in the face of gas price increases. There answer for this phenomenon is that there are just so many fuel efficient cars. Since there are so many choices of fuel efficient cars it makes buying a new car practical to replace old less efficient models. It is also harder to leave the lot with nothing when so many cars offer an opposition to the high gas prices with their fuel economy. Even when competing against the same model the fuel efficient versions win out, for instance Ford’s F-series has multiple models all with varying fuel efficiencies and engine sizes but the smaller more efficient models are by far out selling the bigger models. Many of the companies have begun focusing on the small car industry because it offers the highest fuel economy. Most of the major companies experienced growth during the gas price increases. Even the smallest company Chrysler had a double digit increase. Chrysler’s success came from finally being able to produce a small fuel efficient car. It would also seem that in general the market is becoming more predictable which is a good sign for the auto industry and for a potential resurgence of some of those American jobs.
This helps me to consider that not just gas prices and fuel economy matter but also how many other choices the consumer has. Since there are so many varying models it is easy to find a fuel efficient car that you like and so find one you are willing to buy. It also shows that gas prices may not have an effect on car sales in total at all. This reassures my decision to check based on individual model types, like small car or large SUV, because the data is not universal. An increase in gas prices will not cut all demand but it will cut demand for bigger engine sizes. So it is better to consider each group as a market rather than the entire auto industry. So the small car group is one market, midsize SUV is another, large car is another, so on and so forth.
It does not inherently give other sources of data or further reading. Other variables to control for would be popularity of a model if such a variable could be created and used. I would think that a new model would be more susceptible to gas prices because there are other more trusted models available in times of gas price increases.
Kilian, Lutz, and Eric R. Sims. “The Effects of Real Gasoline Prices on Automobile Demand: A Structural Analysis Using Micro Data.” University of Michigan, 18 Apr. 2006.
The paper is about how general gas price changes effect the price of cars. They find that gas price changes have very little effect on car prices if the shock was unexpected. Another important finding is that an increase in the price of gas matters more than a decrease in the price of gas. Meaning that car price are unresponsive to decreasing gas prices but react to increases in fuel costs.
It brings to light several other variables to consider in the regression. The paper looks at auto prices and gasoline, but also includes life expectancy of the car, discounting of the future, expected usage, and includes an expectations model.
The author suggests that the effect of changes in the price of gas has a non-linear effect on automobile prices. The author shows that a pervious study which used a linear model had near perfect collinearity and his correlation coefficient came to 0.97. However, his findings are still similar to that of the original data which leads the author to believe that gas prices have a non-linear relationship with automobile demand.
I am not sure if his issues will also be my issue, we are using similar data but testing for different things. I am looking more at car sales rather than car prices. His issue is that changes in gas prices have an asymmetric result on car prices, because decreases in price have much less of an effect then increases. However, if the issue is that the price of gas is not a linear model then perhaps it needs to be linearized in some manner. The methods used by the author seem to create different results for every manipulation so I do not know which one would be best. I suppose the best way to fix it would be to test different ways of linearizing the model.
For my project I am analyzing the automotive market in terms of gas prices, combined with various other factors such as safety features. My prediction is that as gas prices rise large vehicle sales, such as trucks and SUVs, will decline in favor of compact cars.
- The main interest is looking at how gas prices affect car sales. This is across styles of cars. For instance truck and SUV sales based on gas versus compact car sales. It would be expected that as gas prices rise large vehicle sales would decrease. This would be especially true during initial spikes in gas prices.
- This question is interesting because gas prices have been steadily rising but there are still a large amount of trucks and SUV’s on the road. One would expect more compacts and less trucks. It also can shed light on car manufacturer adaptive strategies as they adapt to changes in gas prices.
- Other variables that need to be considered are safety feature improvements and things like number of new construction jobs. Although I would predict that they have a smaller effect on car sales.
i) The essential question is what features effect a cars sales the most? The prediction is that it would be fuel economy as gas prices rise.
2. Literature Review
- It is important to address other research done in this field.
- I have found articles about how gas prices affect product choice in the automotive industries.
- Other useful articles focus on the why the industry reacts to rising gas prices.
- There are other articles that look at the automotive industry as a whole and analyze its sales in a generic sense.
- The automotive industry has an ample supply of information. The main source for car sale data is from the National Automotive Dealers Association (nada), they provide useful information on used and new car sales.
b) Other data can be found at motor trend and other places that show safety improvements in cars.
- Gas prices can be found any number of sites some of which correlate it to car sales or usage. The data is simply showing the increase in barrel pricing as opposed to individual prices at the pump which vary dramatically state to state, which is not my interest.
i) Although state variation may be something to consider. Perhaps it would more clearly illustrate the effect of gas prices by showing different sales based on those gas prices.
- At this point I will know if gas price is the driving force behind a consumers decision when it comes to buying a car. This would also be a place to apply other research to my findings.
In Poor Economics one of the issues the authors bring up is returns to education. The authors explain that although education is free in many places and affordable in the rest people still chose not to force kids to go through school. Instead they tend to focus on one child in hopes of a big payout. Although not the same scenario, the blog post “College, Still Worth It”, the link is assignment 5 in blog roll, addresses the same issue of returns to education. Even though education is a safe investment people still chose not to make it for many reasons. The issue addressed in the chapter is that people see school as a lottery and either the child will have an extremely good job at the end or he or she will drop out. The blogs focus was that people see the debt that college students accrue as an offset to the gains of education. The answer is in the fact that a college educated person will make more over their lifetime. Also, it is highly unlikely for a person to earn more than seventy thousand dollars a year without at least some college education. This is numerically arguing the point in the book which is saying that education seemed to help people do better even when they did not get the government jobs the parent had hoped for.
One of the big differences is that the chapter is focused on early education and secondary school, college is not really a focus or consideration in the chapter. While the article is specifically about the college investment and it only has data for those that have at least gone to high school. The article assumes that the reader is considering college and is trying to tell the reader it is worth it. The book is more a presentation of people’s beliefs about secondary school. It is arguing from the point of view that education is necessary and that people should defiantly be going to school. The assumption is that parents are not considering education and so have to be convinced to send their kids. Conversely the article is assuming that the reader is only lightly debating if he or she should go to college and the author is saying that it might not payout, but it really helps your chances. The deference is that the book is trying to convince people to educate their children while the article is more of a bump in the right direction.
Neither story is particularly convincing. The book seems to be lacking data about how education helps and the article says college is not a guaranteed payout but it does have the highest returns to investment. To me the book would be more convincing because it is telling something slightly different than the article. The point of the chapter is that there should not be a poverty trap which in that light the chapter is more convincing.
The question why do drug dealers still live with their moms may seem like it has a simple answer. However, the authors of Freakonomics would have you believe that it is much more complicated or simpler than you would really think. The main argument of this chapter is that one cannot simple take conventional wisdom at face value, or perhaps at any value. This is shown in the number of homeless reported and the police underreporting crime. The main focus of disproving conventional wisdom is found through the example of a millionaire crack dealer. Conventional wisdom would have you believe that crack dealers live this unfairly glamourous life style while pumping destructive drugs into a neighborhood. The reality is that a drug gang operates very similarly to an average McDonald’s. The big wigs make a large profit while the local level employees work for minimal wage under subprime conditions. In many foot soldiers case the average pay came out to be $3.30 an hour and for the officers $7.00 and hour (100). Both of those jobs pay less than most minimum wages and have significantly higher incidents of death. What this shows is that most people involved with drug deals are not living glamourous lifestyles. THe importance of this is that the entire drug story shows that conventional wisdom proves faulty in many cases. The chapter paints a bleak picture for low level drug dealers and continues to make the picture bleaker once these stats were introduced.
The next key statistic is the list of risks located on page 101. Including the chances of being arrested at 5.9, number of nonfatal wounds 2.4, and 1 in 4 chance of being killed. This statistic is used to question why anyone would actually become a drug dealer. The answer is the same as why anyone would do what they do, because at the top there is money to be made. Surviving the low ranks leads to promotions and promotions lead to the top, and in any corporation the profits are at the top. J.T. the gang leader was by no means struggling for money, just as most CEOs make far more than their employees ever will. The gang big wigs made upwards of $500,000 a year and J.T. made at least $100,000 a year (99). In this sense the low level jobs weed out the people that could make it to the top. This is all being used to show that dealing drugs is actually worse than working at the counter of a McDonald’s, which, although it may be a great opportunity, is by no means glamourous.
Lastly a key illustrative statistic is found on 112, and it is the quadrupling of homicide rate. Being killed is not glamourous, and a large percent of crack dealers die. Although crime did fall it shows that drugs bring violence. Violence ensures that drug dealers have a quick turnover rate. Most cannot stay long enough to reap the rewards.