Abortion and crime rates

4 May

The common theme between these two papers and the chapter from Freakonomics is that they both focus on the relationship between the legality of abortion relative to crime rates and how they decreased. In the first paper, by Donohue and Levitt, they focus on why crime rates dropped in America in the 1990s and how abortion influenced if not caused the dramatic decrease. Both Freakonomics and the first paper focus on this area and look at the time when abortion was made legal, in 1973 as a result from Roe v. Wade. Basically what they find is fairly straight forward; legal abortion caused a drastic decrease, as much as 50%,  in crime rates; however, not immediately after it became legal. Since people do not start committing crimes when they are babies or young children, there was a period of time that passed before observing these dramatic drops in the crime rates. Thus, in addition to studying how abortion affects crime rates, they also discovered that crime rates are highest amongst teenagers, from about fifteen to twenty years of age. This is because there was about an seventeen year lag from when abortion became legal and when crime rates started dropping. They also provide convincing arguments for why this is the case, and evidence with regressions. In addition, Levitt and Donohue account for several other possible causes of the sudden reason for the reduction of crime. However, they find that they did not have much of an impact upon crime rates relative to what they had been doing before 1990. This is primarily due to the fact that most of the regulations, laws, and other contributing factors to crime reduction had been in place before and after the drop, thus being fairly unimportant.

Although Donohue and Levitt do present a good argument for abortion and crime rates, the critique by Foote and Goetz offers some interesting points that they say Donohue and Levitt seemed to miss. The primary thing that they talk about is the way in which Donohue and Levitt ran their regression model and how they incorporated the data. They say that in order to look at something like crime rates, one cannot collect data from different states, cross-state data, and in this case different cities and then compare them. They suggest that collect data from each state individually, in-state data, and then analyze crime rates in cities amongst themselves. Then you can compare city to city rather than making larger, less accurate assumptions. In addition to this critique of their work, they also look at the variables in their regressions and find that by changing some of them, it makes the regression no longer significant. They reason that in all the regressions that Donohue and Levitt run, they use the amount of arrests per capita to prove their point, however, in one regression, they stray from this logic and simply use the total amount of arrests, which would completely change the output from the data. Thus, Foote and Goetz run the regression using per capita assets and find that the regression becomes insignificant, consequently nullifying the conclusions made by Donohue and Levitt.

Although after reading the first paper and comparing it to Freakonomics and then reading the second paper and finding out that it was mostly based off false conclusions was kind of annoying, however nonetheless interesting. Despite the fact that Donohue and Levitt’s point is technically based on a poor regression, they still do provide a very valid point; that the legalization of abortion do in fact decrease crime rates due to the basic principle of reducing the amount of people that could commit crimes several years down the road.

Cyclical Trends in Macroeconomic Predictors and related fatalities

13 Apr

In my paper, I am focusing on finding out whether or not there is any correlation between the quarterly and annual Gross domestic product and construction related injuries and fatalities, and additionally how strong that correlation might be. The reason I am focusing on this is to see if you are able to predict levels of construction safety spending and insurance policy costs based on the cyclical trends in the gross domestic product. I will carry this out by looking at the GDP and running regressions with construction incidence rates based on the size of the firms. I include the size of the firm to see whether there are higher incidence rates amongst larger firms, relative to the smaller ones. This is important because it relates back to my hypothesis because I predicted that as the economy grows, so do construction companies and once they begin to spread them selves too thin over too many projects, more injuries begin to occur. I found that there is a correlation between GDP fluctuations construction related fatalities and injuries, therefore, it is possible to predict, with some accuracy, the relative amount of incidents that will occur based on cyclical trends in the economy

Post #7

9 Mar

The Article that I have read, related to my topic was an article titled “Construction Accidents and Injuries Both Declined in 2011, While Construction Permits Increased 7.7 Percent” at http://www.nyc.gov/portal/site/nycgov/menuitem. The main point of the article is that due to the increased insurance costs and more serious construction precautions, construction related accidents have decreased in the last two years.

Mayor Bloomberg is quoted in the article, for saying that he “announced an 18 percent decrease in construction-related accidents in New York City for 201.” This raised an interesting idea for what I was focusing on. Originally, I was looking at simply the impact of economic cycles on construction fatalities, but I didn’t think to include the policies that the mayor would have initiated related to construction safety.

Fatal Construction Accident

1 Mar

A recent article that I found pertaining to construction fatalities in New York City was an article about a crane collapse trial. http://newyork.construction.com/yb/ny/article.aspx?story_id=169745949. The main focus of the article is that James Lomma, the manager of a construction company has been accused of manslaughter for intentionally dodging regulations on a crane repair. 

The article, although short provides a very interesting and important detail to the research that I am doing because I am focusing on why the economy effects fatalities in New York construction workers. I am analyzing the deaths and when they occur relative to economic cycles to see if there is a correlation between construction companies and deaths. The idea being that the companies try to take on more jobs by buying cheaper unskilled labor and cutting corners in areas such as safety in economic boom periods, thus putting their workers at a higher risk. 

This article made me consider several alternate sources of information that I could use in my paper. The primary thing that I thought of is to look outside New York City into other areas around the country for construction related accidents and see how common they are. Additionally I found that I could approach my paper from a broader angle, looking at how people have addressed the issues in other areas and then further relate it to New York City.

Poor Education

24 Feb

The whole point of this chapter was basically to show how there is a correlation between poverty and lack of education. They show how through several different programs that were implemented in India, Pakistan, Kenya, and several other countries, that if there was some type of economic stimulus, education would increase amongst children. Additionally they show that public schools, when they are in poor condition, push the local people to demand private schools. This in turn further promotes education for the children because they show a dramatic increase in the level of education from private school kids relative to public school kids. However, all in all, the education system in India and other countries alike is horrendous.


In a blog post online, located at http://www.africaw.com/forum/f2/education-is-the-most-neglected-sector-in-india-t2633/, there is a similar message described like the one in the chapter. Mainly, education is absolutely horrible in India. The author makes it clear that the education system is in shambles and nothing has really been done to re-direct it. One point that he brings up is that a major problem that has arisen from this detachment of education is that diplomas and degrees do not carry any weight in the job market which further deters individuals from pursuing education.


The blog and the chapter are very similar in the message that they address; however, the chapter in poor economics is obviously much more convincing. Banerjee and Duflo provide a plethora of accurate and comparative statistics to prove their several points about child education and its relation to the family situation and their economic standing. The primary statistics that they focus on are percentages of students being able to read a first grade level passage relative to the grade they may currently be in to show how poor the education system is. The primary difference between the two readings was that the blog addressed the issue of adult education as a separate issue, as opposed to the chapter which focused primarily on the lack of child education.

Economic Cycles and Construction Fatalities

24 Feb

The topic that I am focusing on is the correlation between the amount of construction dollars spent per annum and the construction fatalities during economic boom and bust periods in New York City. As economic cycles take place, construction spending tends to follow in a similar manor, increasing as the economy prosper and declining as the economy too, declines. However, construction related fatalities tend to follow the same trend as well. Using data from the Bureau of Labor Statistics (http://www.bls.gov/iif/oshsum.htm#10Summary%20News%20Release ) and from the New York Building Congress (http://www.buildingcongress.com/research/costs/01.html ), I will analyze the correlation between construction hard costs and construction fatalities in New York City.

This topic is important because it will show if there is a strong correlation or not between increased costs and fatalities, and it will additionally explain why there might be increased fatalities during times of economic prosperity. The primary reason for choosing my topic is because I am interested in insurance and my uncle’s company works with construction insurance.

The primary difficulty in this estimation will be finding the relevant data amongst all the other variables that could affect construction costs and also fatalities. Also because the Bureau of Labor Statistics does not just have construction fatalities for New York City alone per annum, it will be difficult to separate the data and account for any outside factors.

Who is joining the US Military and why?

17 Feb

The topic that I am focusing on for my paper is the United States military and the impact of various cultural and geographical elements upon individuals and their decision to join the military. The United States has long had a tradition of military power, but who exactly makes up the United States military. Is it an individual’s socio economic position, geographical location, religious association, or a combination of all three which dictate whether an individual joins the United States military? This question is the main idea that I am investigating, as stated in my thesis and I will be using data sets from the United States Census and several additional research projects conducted by military officers. This research data can be found at this link: http://www.civicyouth.org/PopUps/WorkingPapers/WP32Adamshik.pdf.

The reason that I decided to research this topic is because my Uncle and Grandfather were both in the military, as well as several other family members and I was interested if their reason for joining might have been for any specific reason, or just a sense of duty or patriotism. I feel that it is an important topic because national defense and the military are crucial to any country’s survival and strength. Additionally, I feel that it is important for the military to see who they are recruiting and for what purposes.

Since the question focuses on the United States military, which affects almost every citizen, there are several policy implications that will have to do with the data. Some examples of this are military spending to provide students with an education, or people on welfare being more likely to join the military. Additionally, in the south, gun laws tend to be more lackadaisical than in other parts of the country and may also impact a persons willingness to join the military.

Although the United States military is a powerful, well organized government body, there are several difficulties in obtaining data and making estimation difficult. The primary problem that I have already encountered is obtaining data sets that haven’t been shut down or controlled by the government. I have run into the problem already that a majority of the data providing information about members in the military and much of their religious, socio-economic, and geographical data is undisclosed. This makes it primarily difficult to find a large amount of observations for data and the accuracy of the data. Additionally, the United States military is an enormous institution, drawing from members of every social class and geographical location. Therefore, it will be important to pay very close attention to the detail of the data, because it may be difficult to find the specific observations that will answer my question.