The first article by Donohue and Levitt is the same concept that we read about in Freakonomics. They discuss the idea that the legalization of abortion was the major cause of the reduction in all types of crime in America in the 1990s. Although abortion was legalized by Roe v. Wade in 1973, the effects on crime rates were not seen until the 1990s when the cohort of the would-be teenagers would be committing the most crime. The argument is twofold in that it is shown that people from the age of 15-20 are the most likely to commit crimes. So, if abortion is legal, it reduces the number of teenagers, thus reducing crime. And also, it reduces the amount of unwanted children that grow up in unhealthy environments which makes them more susceptible to crime. With a smaller population of unwanted children due to legalized abortion, crime will decrease. Since there was a large jump in the number of abortions after they were legalized, it would make sense to see these predicted effects some 15-20 years later (since that's the age at which those teens would have been committing crimes).
Donohue and Levitt make a convincing argument and point to a lot of other research and literature that has been done and written on this subject. They provide data and regression models to help support their notion that legalized abortions caused a reduction in crime rates. They do mention other factors that may have helped reduce crime, however, they argue that those factors were always around and did not seem to reduce crime rates as abruptly as they propose legal abortion did. Foote and Goetz write a comment on the paper by Donohue and Levitt pointing out what they see as flaws in their work and findings.
Foote and Goetz state that Donohue and Levitt made errors in their regressions and analysis of data which caused a skewed perspective of what was going on. They do say that Donohue and Levitt made some convincing arguments however, they also point out that their method of cross-state rather than within-state comparisons of crime data were a misrepresentation of the facts. They point out that the crime and reasons for it in New York and Idaho are much different. Therefore, they should be comparing crime trends over time in just New York and in just Idaho rather than making a sweeping generalization about crime in all parts of the country.
Another thing that Foote and Goetz point out is the coding problem in the final regression that Donohue and Levitt run. One of the flaws they point out is the fact that the regression included total arrests rather than per capita arrests as had all the other regressions in the paper. Foote and Goetz find that when they use the appropriate measure of per capita arrests they find that the significance in the model disappears.
Essentially the second paper discounts a lot of the information that we read in the first. However, I still do think that there is something to learn from the first paper. Aside from it being an interesting concept that abortions have reduced crime rates, I do think that Donohue and Levitt provide a lot of good information and evidence that it is true. Even Foote and Goetz say that there is some strong evidence to support their hypothesis. So, after reading each I do not completely discount what we have read both in Freakonomics and the paper by Donohue and Levitt. It makes you think critically about things that you read and pay attention to detail, but I mostly think that the notion of legalized abortions reducing crime rates years later has some factual backing to it. It is at least theoretically sound even if it is not definitely a causal truth.
Tuesday, May 1, 2012
Thursday, April 26, 2012
Freakonomics Chapter 4
In this chapter the author discusses the trend in criminal activity in the United States and what the possible causes are for it's decrease in the early 1990's. They discuss several theories of why the crime rates have decreased including, increased numbers of policeman, stricter gun laws, changes in drug markets, and abortion laws. The chapter does a good job of evaluating the various theories that economists and others have about why the crime rates decreases. The author brings up some interesting points that make you think differently about something that may seem obvious. He also discusses at length how abortion has an effect on crime rates. Most people would not think that there would be a relationship between crime and abortion however he brings up a good theoretical point that makes us think that it could be possible.
The author states that babies that a mother would have aborted but didn't receive less attention and care than a wanted baby. Therefore, they grow up in worse conditions and may be more prone to criminal activity than a baby growing up in a loving and healthy environment. Something that I thought was interesting was his critique on whether or not Rudy Giuliani really had the huge impact that people thought he did on crime in New York City. He points out that the man that was mayor before him actually implemented a lot of things at the same time as crime rates were decreasing. He says that crime rates started to go down before Giuliani was even in office. I would argue that although this may be true, there could have been other factors that cause crime rates to go down. Possibly his strong leadership presence, initiative, knowledge, and dedication played a large role in reducing crime as well. I think the author may be looking too strongly into the numbers and concrete facts of these scenarios rather than immeasurable aspects such as the ones I just listed that can also have effects on certain things like the crime rate.
The author states that babies that a mother would have aborted but didn't receive less attention and care than a wanted baby. Therefore, they grow up in worse conditions and may be more prone to criminal activity than a baby growing up in a loving and healthy environment. Something that I thought was interesting was his critique on whether or not Rudy Giuliani really had the huge impact that people thought he did on crime in New York City. He points out that the man that was mayor before him actually implemented a lot of things at the same time as crime rates were decreasing. He says that crime rates started to go down before Giuliani was even in office. I would argue that although this may be true, there could have been other factors that cause crime rates to go down. Possibly his strong leadership presence, initiative, knowledge, and dedication played a large role in reducing crime as well. I think the author may be looking too strongly into the numbers and concrete facts of these scenarios rather than immeasurable aspects such as the ones I just listed that can also have effects on certain things like the crime rate.
Thursday, April 12, 2012
Research Paper Summary
The research that I did for my paper looked at the link between poverty and population size in urban settings. My hypothesis was that as cities grow, so too do their poverty rates. I collected data from 17 different cities over a 30 year period. Other factors that I thought would effect poverty rates outside of population were level of education by citizens of those populations and median family income. My two measures of education were the number of people that completed high school and the number of people that completed college or more. I also included the years to see if there was a relationship over time between population and poverty.
The results that I got were somewhat what I had expected. I did find a very statistically significant relationship between poverty rates and population though there was not a very large coefficient on the variable population, the t-stat was highly significant. I was also pleased to find that my measure of education, specifically the college or more variable, effected poverty rates in a negative way. There was a negative correlation between whether a person gets a college degree and poverty rates, which was nice to see because that's what I expected to happen. The same was true for median family income. The coefficient was negative, meaning it decreased poverty rates as it increased and it was very statistically significant. However, the opposite was true for those people who received less than a high school education. As the number of people with this level of education increases, so too did poverty rates. Though it was not statistically significant at a high level, it did suggest an upward trend between the two variables.
Overall, the findings were interesting to see and I was pleased because it was what I was expecting to happen. After writing a rough draft, I think there are still some things I can change around a little and look at more closely to try to get a better model.
The results that I got were somewhat what I had expected. I did find a very statistically significant relationship between poverty rates and population though there was not a very large coefficient on the variable population, the t-stat was highly significant. I was also pleased to find that my measure of education, specifically the college or more variable, effected poverty rates in a negative way. There was a negative correlation between whether a person gets a college degree and poverty rates, which was nice to see because that's what I expected to happen. The same was true for median family income. The coefficient was negative, meaning it decreased poverty rates as it increased and it was very statistically significant. However, the opposite was true for those people who received less than a high school education. As the number of people with this level of education increases, so too did poverty rates. Though it was not statistically significant at a high level, it did suggest an upward trend between the two variables.
Overall, the findings were interesting to see and I was pleased because it was what I was expecting to happen. After writing a rough draft, I think there are still some things I can change around a little and look at more closely to try to get a better model.
Wednesday, March 28, 2012
Assignment #8
In chapter 5 of Poor Economics, the authors discuss family size in the under developed countries that they have studied. They ask the question whether families want to have large families or if there are out side sources that cause family size to be much larger in these countries. They also look at the effects of having large families in these areas. They discuss fertility decisions among the poor in these countries, contraception in those areas, family dynamics, and the economics of large families and how children can be of financial use to the parents.
The chapter talks about areas with family-planning clinics versus areas without them and how it affected fertility rates in those areas. The book states that though the areas with clinics did have lower fertility rates, it was not due to the clinics themselves. The clinics were most abundant where people wanted them to be. In other words, people demanded these clinics and therefore they were built in those areas. However, the clinics had no direct effect on fertility. Despite what the book concludes, my hypothesis about fertility rates and family-planning clinics would be: the more family-planning clinics, the lower the fertility rates. I would test this by collecting data on the number of family-planning clinics in different areas and the related fertility rates in those areas.
My guess is that there would be other factors that effect fertility rates outside of whether or not family-planning clinics exist. They may be population, family income, marital status of the mother, and perhaps whether there was access to good education (people may not start families in areas where they cannot send their children to school). My model would look something like this:
Fertility Rate = B#family-planning clinics + Bpopulation + BMedian family income + B#of schools + E
The dummy variable in this equation could be the marital status of the mother. If she was married she would be a 1 and if she were not married she would be a 0. If I believe that being married causes a woman to have more children I would expect the coefficient of my dummy variable to be a positive number. I wouldn't expect it to be very high numerically because I don't think that being married increases fertility rates by a huge number, but I would expect it to be positive. If it were positive it would tell me the married women, on average, have more babies than do unmarried women. To tell whether or not this variable is significant I would look at the t-statistic that I get from running a t-test. After seeing that value I could determine whether or not this dummy variable of being married or not were significant.
The chapter talks about areas with family-planning clinics versus areas without them and how it affected fertility rates in those areas. The book states that though the areas with clinics did have lower fertility rates, it was not due to the clinics themselves. The clinics were most abundant where people wanted them to be. In other words, people demanded these clinics and therefore they were built in those areas. However, the clinics had no direct effect on fertility. Despite what the book concludes, my hypothesis about fertility rates and family-planning clinics would be: the more family-planning clinics, the lower the fertility rates. I would test this by collecting data on the number of family-planning clinics in different areas and the related fertility rates in those areas.
My guess is that there would be other factors that effect fertility rates outside of whether or not family-planning clinics exist. They may be population, family income, marital status of the mother, and perhaps whether there was access to good education (people may not start families in areas where they cannot send their children to school). My model would look something like this:
Fertility Rate = B#family-planning clinics + Bpopulation + BMedian family income + B#of schools + E
The dummy variable in this equation could be the marital status of the mother. If she was married she would be a 1 and if she were not married she would be a 0. If I believe that being married causes a woman to have more children I would expect the coefficient of my dummy variable to be a positive number. I wouldn't expect it to be very high numerically because I don't think that being married increases fertility rates by a huge number, but I would expect it to be positive. If it were positive it would tell me the married women, on average, have more babies than do unmarried women. To tell whether or not this variable is significant I would look at the t-statistic that I get from running a t-test. After seeing that value I could determine whether or not this dummy variable of being married or not were significant.
Friday, March 9, 2012
Assignment #7
The article that I read was one from the New York Daily News from September of this past year. It discusses how poverty rates in New York City rose according to the 2010 census. They state that the economy is to blame for the rise in poverty rates and that there is concern of how poverty is spread throughout the city. There is a lot of disparity in poverty among different demographics of people. The article also states that every borough except for Manhattan experienced an increase in poverty rates which is also concerning to government officials in the City.
The article made me realize that something that I may need to keep in mind are years in which there are recessions and how it may affect the poverty rate. Obviously, if the economy is not doing well then poverty rates are more likely to go up in those years. Therefore, I could possibly create a dummy variable for years that are and are not recession years. This way I could hopefully control for the economy and get a better measure of how population is effecting poverty rates.
Another thing the article talks about is poverty among different racial groups. This is something that I could maybe think about as well. I am not exactly sure how I would take that into account or whether it would skew my data at all if I don't consider it, but it would definitely be something interesting to explore. I don't think that any of these new variables would violate any of the assumptions of the linear model however, it is possible that there may be correlation among variables that I choose to use. There is likely correlation between recession years and the poverty rates which implies co-linearity among my explanatory variables. However, I think including information about the economy, specifically the recession years as dummy variables will help to give me a stronger regression.
The article made me realize that something that I may need to keep in mind are years in which there are recessions and how it may affect the poverty rate. Obviously, if the economy is not doing well then poverty rates are more likely to go up in those years. Therefore, I could possibly create a dummy variable for years that are and are not recession years. This way I could hopefully control for the economy and get a better measure of how population is effecting poverty rates.
Another thing the article talks about is poverty among different racial groups. This is something that I could maybe think about as well. I am not exactly sure how I would take that into account or whether it would skew my data at all if I don't consider it, but it would definitely be something interesting to explore. I don't think that any of these new variables would violate any of the assumptions of the linear model however, it is possible that there may be correlation among variables that I choose to use. There is likely correlation between recession years and the poverty rates which implies co-linearity among my explanatory variables. However, I think including information about the economy, specifically the recession years as dummy variables will help to give me a stronger regression.
Thursday, March 1, 2012
Poverty Among Urban Youth
I found an article that was posted a few days ago on the recent report by UNICEF on "The State of the World's Children 2012". The article discusses how millions of children around the world are growing up in urban poverty. Despite having greater access to modern services and facilities than their rural counterparts, children in urban areas still lack access to clean water, electricity, and education. Also, due to overcrowding in cities and the often unsanitary environments they reside in, children tend to suffer from deadly diseases. So, as cities continue to grow, people in those areas, particularly children, continue to suffer because they are often not able to afford the aid or medicine that they need. The article also points out that people often say that those in urban areas are better off than those in rural areas. However, the authors say that the relative wealth of those living in cities offsets those living in poverty making it look like urban areas are less poor when, in reality, that is not always the case.
Although this article is summarizing a report of urban areas in other, poorer parts of the world, it still brings up factors that I will need to think about in my research. The article stresses that children who are poverty stricken are often held back later in life because they grew up in an environment where they did not have the opportunities to receive a good education, eat nourishing foods, and receive good health care. All of these factors lead to children not being as healthy and productive as they can possibly be. This is related to what we read in Poor Economics where the authors found that malnourished workers could not be as productive as possible and therefore were not able to get good jobs and therefore lift themselves out of poverty. The report states that because the children growing up in these parts of the world suffer from under nutrition and lack of education they are not able to bring themselves out of poverty later in life.
These factors are things that I think are also true for the urban poor in America as well. If children in urban America are unable to afford a sufficient amount of food or afford to go to college and receive a good education it is unlikely that they will be able to receive a good job and bring themselves out of poverty. So these are some of the factors that I will need to try and account for in doing my research. I will probably need to find some data on schooling systems in poor areas of American cities and whether or not the people who live there receive some sort of financial aid for food and other necessities. These will be very important in whether or not people will remain poor or not and also whether or not they will be able to move out of these areas.
http://www.newsroomamerica.com/story/220341/millions_of_children_in_cities_face_poverty_and_exclusion:_report_.html
Although this article is summarizing a report of urban areas in other, poorer parts of the world, it still brings up factors that I will need to think about in my research. The article stresses that children who are poverty stricken are often held back later in life because they grew up in an environment where they did not have the opportunities to receive a good education, eat nourishing foods, and receive good health care. All of these factors lead to children not being as healthy and productive as they can possibly be. This is related to what we read in Poor Economics where the authors found that malnourished workers could not be as productive as possible and therefore were not able to get good jobs and therefore lift themselves out of poverty. The report states that because the children growing up in these parts of the world suffer from under nutrition and lack of education they are not able to bring themselves out of poverty later in life.
These factors are things that I think are also true for the urban poor in America as well. If children in urban America are unable to afford a sufficient amount of food or afford to go to college and receive a good education it is unlikely that they will be able to receive a good job and bring themselves out of poverty. So these are some of the factors that I will need to try and account for in doing my research. I will probably need to find some data on schooling systems in poor areas of American cities and whether or not the people who live there receive some sort of financial aid for food and other necessities. These will be very important in whether or not people will remain poor or not and also whether or not they will be able to move out of these areas.
http://www.newsroomamerica.com/story/220341/millions_of_children_in_cities_face_poverty_and_exclusion:_report_.html
Friday, February 24, 2012
Top of the Class
In chapter 4 of poor economics, the authors discuss the educational systems in the developing countries that they are studying. There are two theories about the poor quality of the education in these places. One is a supply-side theory of tackling the problem with the education system and the other is demand-side oriented. The supply-siders say that government needs to regulate and make sure that there are good teachers in the classroom actually teaching the students. One of the big problems they find is that the teachers are often absent or when they are there they aren't teaching the students. The demand-siders say that since there is a high rate of absenteeism and many parents don't send their children to school, why bother trying to intervene and regulate. If people want education then a good system will come about through a strong demand. If the public schooling isn't good enough for the parents then a demand for private schooling will emerge and the system will essentially remedy itself.
The article that I found was about schooling in Africa in the after math of a long civil war. The authors state that both attendance among students and the quality of the education provided have fallen drastically since the war ended. Though the reasons for the low quality of education that the book talks about are different than that of the article, they each raise some interesting concepts. For example, the book talks about how in the United States education is something that is highly valued and the government forces parents to send their children to school. In the book the authors state that in some places parents keep their children home to help them work around the house or in their shops. In the article it says that only 10% of students were in attendance during the first week of school. Although the reasons for low attendance is different (one cause by a war and the other by a need for additional help at home), it makes you think about how people in different parts of the world value education and how it is regarded in society. It is hard to imagine in America a child just not attending schooling because their parents need them to go to work on their farm or in their business. However, this is what happens in many parts of the world. And, although we haven't experienced a war in our own country in a long time, even after something as tragic as 9/11 did not really cause us to miss much school. These examples may not be comparable but I did find it interesting to read and think about how people view education and how important attendance in school is in different parts of the world.
Another thing that both the book and the article bring up is low quality of education. The article states that pass rates dropped as much as 13% following the end of the civil war. In the book the authors state that the teachers in school are not performing as well as they should be and as a result students do not know how to do simple mathematics or read simple paragraphs. The reading levels of the students in the countries the authors studied was very low. Though the article and the book provide the same issues but in very different contexts, they raise the same fundamental issues of education quality and attendance which I found interesting to think about especially in relation to our own educational system.
Here is the article that I read: http://blogs.cfr.org/campbell/2011/11/03/low-school-attendance-marks-slow-recovery-for-ivory-coast/
The article that I found was about schooling in Africa in the after math of a long civil war. The authors state that both attendance among students and the quality of the education provided have fallen drastically since the war ended. Though the reasons for the low quality of education that the book talks about are different than that of the article, they each raise some interesting concepts. For example, the book talks about how in the United States education is something that is highly valued and the government forces parents to send their children to school. In the book the authors state that in some places parents keep their children home to help them work around the house or in their shops. In the article it says that only 10% of students were in attendance during the first week of school. Although the reasons for low attendance is different (one cause by a war and the other by a need for additional help at home), it makes you think about how people in different parts of the world value education and how it is regarded in society. It is hard to imagine in America a child just not attending schooling because their parents need them to go to work on their farm or in their business. However, this is what happens in many parts of the world. And, although we haven't experienced a war in our own country in a long time, even after something as tragic as 9/11 did not really cause us to miss much school. These examples may not be comparable but I did find it interesting to read and think about how people view education and how important attendance in school is in different parts of the world.
Another thing that both the book and the article bring up is low quality of education. The article states that pass rates dropped as much as 13% following the end of the civil war. In the book the authors state that the teachers in school are not performing as well as they should be and as a result students do not know how to do simple mathematics or read simple paragraphs. The reading levels of the students in the countries the authors studied was very low. Though the article and the book provide the same issues but in very different contexts, they raise the same fundamental issues of education quality and attendance which I found interesting to think about especially in relation to our own educational system.
Here is the article that I read: http://blogs.cfr.org/campbell/2011/11/03/low-school-attendance-marks-slow-recovery-for-ivory-coast/
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