The topics being discussed throughout these papers are shocking to me. The fact that they found a correlation between crime rates directly linked with abortion is unbelievable. After thoroughly reading Chapter 4 in Freakonomics, it makes sense as to how this relationship could be true. From a socioeconomic standpoint, it makes perfect sense as to why an abortion that is outlawed could result with a troubled child. A child that is born from a mother who wanted an abortion is at a high risk for being resented, raised by one parent, and grow up in poverty. All of these characteristics tend to lead to a higher rate for an individual to become a criminal. Abortions were not the only topic discussed which happened to have an influence on the crime rate during the 90’s. Another topic mentioned was the gun laws as well as capital punishment. Gun laws are another factor influencing the crime rate at which I completely would never think to have an impact. Gun laws allow licensed individuals to carry a firearm in public which to a certain degree puts everyone at risk. Simple scenarios were presented where an individual could act rashly and harm another person. The gun laws absolutely could have a major impact on the acts of violence in society. This in my opinion is a very valid argument that is presented well in the chapter. Individual statistics used in the reading left a lasting impression in my mind for the validity of these arguments. For example: states with high abortion rates take responsibility for a 30% drop in crime relative to states with low abortion rates. These statistics help to prove the point they are making and are presented in a logical order which I believe give even better results. More compelling statistics regarding abortions relevance to how it influences the crime rate were: the typical child that went unborn when abortion was legal, was 50% more likely to live in poverty. Also that child would have a 60% chance of growing up in a one parent household. Overall capital punishment wasn’t seen to have a huge impact on the murder and crime rate but the numbers were found to decrease. The topics discussed in this chapter were absolutely my favorite topics that were presented in the entire book. The authors do a great job of making what seems to be a crazy relationship between things people would not think about, but then back up their points with statistics in a logical, clear order. This book was an overall great read with very interesting but also surprising topics.
In chapter 7 “The Men from Kabul and the Eunuchs of India: The (Not So) Simple Economics of Lending to the Poor” different types of money lending are discussed in developing countries. For example banks, informal moneylenders, and traders. A main issue brought to the reader’s attention is that in these developing countries banks neglect the poor by not lending to them. As a result of the bank refusing to lend to the poor, moneylenders and traders often will make deals with them. The problem with the informal moneylenders and traders is that they will charge astronomical interest rates along with using unethical ways to retrieve their payments. Because of my living situation I never thought of how hard it must be to get a loan especially being poor in a developing country. This chapter offers a very interesting as well as alarming perspective highlighting the struggle that goes on. The authors present their statistics in a great way of showing the significance of the points they are trying to make. For instance early on in the chapter they mention the interest rates the moneylenders give to the poor and show how much their interest rates are in comparison to Bank of America. They then go on even farther to display how high the interest rates are in comparison to the low wage these families earn. They do a great job of painting a picture of just how bad of a situation it is. Throughout this chapter I’ve learned the overall benefits to microfinance and how it is pivotal in helping the poor. Although microfinance is not flawless, which the authors pointed out as well. My only question after reading this chapter is how the government can make microfinance more accessible for quick money to keep the poor from reaching out to moneylenders and traders?
The main question I am investigating is how unemployment affects the housing market prices. This article discusses the catastrophe we have experienced with regards to housing prices since 2008. A combination of a rise in unemployment and declining house prices resulted in a substantial increase in mortgage defaults. This article highlights three key factors affecting the housing market in a negative way.
1) The healthcare law and uncertainty over tax increases
2) Lack of credit for mortgages
3) Further unemployment
It states that to have a recovery, job creation must increase. The article also notes that economic growth above 1 percent would be very helpful for the recovery process. Also with a rising GDP, a correlation has been found with increasing job creation.
This article helps to clearly define the role GDP will have in my experiment. It gives me a better understanding of how it impacts the housing market. Also, this article strengthens my thoughts and hypothesis made that an increased unemployment rate leads to a decrease in the value of homes along with the overall housing market. As for variables that can be introduced to my project, I believe after reading this article research on previous years treasury and mortgage rates before and after 2008 could be very useful. These two variables could be very valuable to the project and I believe will display a strong correlation with the housing market. I will need to continue to research the housing market to find a couple other variables which will help to show and paint the picture I am trying to make. As for now current news and previous experiments will be my best options to help better my research project.
The research paper I read was taking a look at all of the effects unemployment has on one’s satisfaction and health. It examines unemployment’s effects on five different categories: vocational activities, income, housing, leisure time, and health. In respect to each of these categories housing was shown to display the smallest variance in overall satisfaction as one became unemployed.
This research paper takes another look at housing as one of the variables of unemployments effects on an individual. This shows the effects of unemployment on housing situations in a different perspective. The research in this particular research paper does not show a classical linear regression model. The correlation in this case would not be linear. The data in this research paper does not match up or display the same relationship as the data I gathered, it would take finding new data to fix this problem.
The movie Barbarians at the Gate was a movie based on the greed and selfishness of top level corporate executives. It was a well thought out and interesting movie showing the complexity of leverage buyouts. I found it very interesting the cat and mouse game played in the buying of the company. It was funny to see how information was disclosed to one another and publicly. It turned out that the New York Times played a huge role in the final decision made on who would take over. The fall of RJR Nabisco was actually the biggest in history in the year 1988. After President Johnson discovered the news that the cigarettes were a disaster that they sunk over $350 million into, it was interesting to see how he reacted to that. An attempt to purchase the company was something that I never saw coming. I left the movie wondering why the board would accept a lower price offered? I am aware the management team plays a huge role along with other factors, but the chairman distinctly said in one scene that it had become strictly a numbers game. Also I can’t quite understand why President Johnson would want to buy the company knowing the hit it would be taking with the new smokeless cigarette. I felt that this one a scheme that President Johnson was taking part in the whole movie but at the end I changed my thought. Smokeless cigarettes were anticipated to drive the market price up, based off the test results and consumers reactions they were only going to hurt the company. This is very unclear to me. Overall this movie was very interesting to see the perspective of what goes on with corporate management during a leverage buyout negotiation.
Unemployment’s Influence On Housing Market Outline
- What impact does the unemployment rate have on the housing market prices?
i. This is the focal point of the paper which motivates everything else.
ii. Briefly state main reasons for why the unemployment rate impacts the housing market in the direction it does.
iii. Briefly mention other factors that can be brought up and be used as variables for influencing the housing market.
- Examples: inflation, GDP
- Closing Introduction
i. Present sequentially the layout of the rest of the paper without giving much detail about each section.
- Literature Review
- Data findings
- Literature Review
- Present the specific articles which are directly tied in with: What impact does the unemployment rate have on the housing market prices?
i. Summarize the questions, hypothesis, and findings of the analyzed articles.
ii. Discuss how my question is different.
iii. Determine the significance of answering the main question.
- Critique of the literature
i. Mention how the papers were presented and their method of trying to find their answer.
ii. Analyze what they did well and what could have been improved.
- Closing Statement
i. What will my research will improve upon the previous experiments.
i. What impact does the unemployment rate have on the housing market prices?
- Hypothesis: If the unemployment rate increases, the housing market prices will decrease. If the unemployment rate decreases, the housing market will increase.
- An inverse relationship will be discovered.
ii. Methodology for testing hypothesis
iii. Mention counter arguments from previous experimenters
- Discuss what type of data validates the point being made
i. Description of the data used
iii. Detailed description of what the found data means in words.
- Explain each variable and the data representing them.
iv. Compare the found data with the hypothesis
- Mention in sequential order, everything that was found within the research.
i. Key findings
iv. How the data matched with the proposed hypothesis
- Potential errors skewing the data in a certain direction
i. Ways to improve the findings
- Closing statements of how this ties into the real estate industry
i. Benefits of knowledge gained
Blitzer, David. “House Prices and the Unemployent Rate.” Housing Views. Standard and Poors, 01/04/2012. Web. 4 Oct 2012. <http://www.housingviews.com/2012/01/04/house-prices-and-the-unemployment-rate/>.
“Databases, Tables & Calculators by Subject .” Bureau of Labor Statistics. U.S. Bureau of Labor Statistics, 10/04/2012. Web. 4 Oct 2012. <http://data.bls.gov/timeseries/LNS14000000>.
“House Price Indexes.” Federal Finance Housing Industry. N.p., 10/04/2012. Web. 4 Oct 2012. <http://www.fhfa.gov/Default.aspx?Page=87>.
Gordon Hughes, Barry McCormick. Housing Markets, Unemployment and Labour Market Flexibility in the U.K. Volatility and Economic Growth: The First Ten, 1991 http://www.nber.org/chapters/c11677
The argument of the chapter is what appears to be a very glamorous and lucrative business of selling crack cocaine turns out to be no different from any other firm or organization. This industry (if you can call it that) is a hard nose, competitive and demanding business. The author tells the story of a student going into a gang in Chicago and befriending the leader of a specif crew. He then stays with them for years learning and observing the lifestyle and way of business transactions. The author argues that selling crack cocaine just like anything else is a process of starting at the bottom and working your way up. Not everyone is cut out for it and the wealth is distributed heavily among the top leaders leaving very little for the sellers at the bottom of the chain. It turns out that selling crack cocaine is much more organized as well, with complex levels of hierarchy modeling companies like McDonalds.
The first key statistic I would like to mention is that the crack dealers actually distributing the crack only make roughly $3.30 an hour. This is powerful because that is less than half of minimum wage and is a clear reason why one would still live with their mom. My problem with this stat listed on page 102 is how can you measure dealing drugs on a per hour basis? When is a drug dealer working and not working, being that a drug dealer spends a lot of time on a street corner waiting for potential customers to find them? I feel that this stat can be skewed saying the drug dealer works more hours than they actually do.
On page 101 there were some amazing statistics presented showing the craziness of these crack dealers working for $3.30 per hour. It was stated that if you worked for J.T.’s gang for four years, you would have a 1 in 4 chance of being killed. This compared to what the Bureau of Labor Statistics calls the most dangerous job which is being a timber cutter, trumps it. Being a timber cutter over four years you run the risk of dying 1 out of 200. In Texas, the leading state for the death penalty, in 2003 24 inmates were killed out of 500. Both of these examples show just how high 1 out of 4 is. This helps to show the astonishing number as well as set itself up for the impact of that low wage earned by the dealers.
On page 104 crack dealing along with other extremely competitive professions was referred to as a tournament. One must work their way up the ranks and pay scale will increase each round. The comparison between an editorial assistant earning $22,000 in a Manhattan publishing house and a crack dealer earning $3.30 an hour was made. This is yet another impactful stat because it represents a low paying bottom of the food chain job, but it leaves the door open for the possiblity that if one can separate themselves fame, wealth, and accolades are achievable. Being able to make a valid comparision between movies, sports, music, fashion, and crack dealing is interesting as well as impressive to relate.
Lastly, listing J.T. and the other high position members of the black disciples wages was very statistically relevant as well as impactful. J.T. for example was said to make $100,000 annually and $8,500 monthly. The combined wages of all three officers under him was $2,100 and all foot soldiers $7,400. (split between 20) Clearly J.T. is making a distinctly higher portion of the profits than his inferiors. (pg. 100) The reasoning was said to be that whoever in charge must get his before everyone else, this will show their power along with there being so many people under the foot soldiers who want work, J.T. can afford to pay at a low wage being that the supply of foot soldiers is so high and the demand is so low. Each foot solier is very replaceable. All of four of these statistics tie in together nicely with one another and make the message even stronger.