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Final Post

The link between abortion and crime is an extremely interesting viewpoint brought up by the authors.  After reading the two papers and the chapter, it is difficult to determine how much of a role Roe vs. Wade played, although I believe there is no doubt played a role. 

The research provided strike me as very thorough.  They compare different sets of individuals.  They compare the group of individuals born before Roe v. Wade in 1973 and the set of individuals that came to be after the court’s decision.  They find that those born after were much less likely to commit violent crime on average than those born before.  Also interesting is the comparison between states, which already had legal abortion and states where abortion become legal after the court’s decision.  Those states, the ones with abortion legal prior to Roe v. Wade, experienced crime drops sooner than those states that did not have it legalized

Foote and Goetz, in there article, do bring up interesting counterpoints.  First and foremost, in my opinion, is the possibility of a coding error in Donahue and Levitt’s regression.  If this is true, then the accuracy and validity of the results cannot be taken seriously.  Also is their discussion of different demographics.  They argue you cannot compare cross sectional data from different states.  As states have entirely different demographic compositions and institutions.  Those different compositions and institutions have the potential to alter crime rates in ways that Donahue and Levitt’s model did not control for.  However, they are not to prove this claim beyond concluding the functional form of cross sectional data may have resulted in the positive correlations.  This means that Donahue and Levitt’s model is efficient and accurate, boosting their argument.

Donahue and Levitt provide ample evidence to prove their point.  The dramatic fall in crime during the 1990s has a connection to Roe vs. Wade.  It is a logical and empirical connection.  Obviously the true portion of credit it deserves will most likely never be determined, but there is credit due.

E.C. Senator Feingold’s Lecture

Despite the fact that Senator Feingold’s lecture was not heavily influenced by economics, rather it was mostly based on politics and terrorism, it was still interesting.  He made many informative points and I found his knowledge about “inside the beltway” especially interesting.  Trying to relate back to economics, and to add a dash of speculation, did George W. Bush’s administration push the Iraq War to help revive the economy?  The years following the Tech Bubble in the United States, 2001 and 2002, were not great years for the economy.  While by no means bad years, comparatively to the most recent recession, they certainly were not like the late 1990s.  In America, voters have a habit of praising or blaming the President for the economic conditions, usually the later.  However, as any economist will tell you, the President has very little influence over the economy.  At the same time, as any political scientist will tell you, a great indicator of how an incumbent President will fair in a re-election campaign is how well the economy is doing.  However, that same economist will also tell you war spending is good for the economy.  It creates a lot of jobs and promotes growth.  Is it feasible that President Bush’s Administration, using the War on Terror as a guise, pushed the War in Iraq to jumpstart the economy?  That will most likely never be answered.  There are numerous speculations as to why the Bush Administration pushed the war on Congress so hard.  They range from oil security to President Bush was really the war monger Dick Cheney’s puppet to faulty intelligence.  Rarely have I heard that poor economic growth prospects may have been a contributing factor.  War spending estimates vary from $1 trillion to over $6 trillion.  Obviously not all that money was spent in America, but regardless that is a lot of money and a healthy global economy only benefits the American economy.  It is an interesting line of research that would not only require a lot of data digging, but also a lot of political dredge work, but maybe someday we’ll get answer. 

Assignment #10 Spring 2013

Chapter 10 deals with the process of micro-finance in developing countries.  The authors present statistics, in this chapter in particular, in an easy to understand way.  This is best seen with the way they present interest rates.  Off the bat they list the interest rate per day and it does not seem that high, somewhere around 4% a day.  An average reader might see that as somewhat high, but not outlandish.  The authors then bring the rates out to a year and it becomes much clearer that those interest rates are outrageous, as in 800% a year in some cases.  By doing this, it allows the authors to really show the reader what it is like to be a borrower in a poor area.  In addition, the authors’ analysis of why the interest rates are so high takes some of the “evil” veal of moneylenders to come off.

I actually have personal experience with micro-finance, as I started a micro-finance club in my high school.  I absolutely was under the belief that it would dramatically reduce poverty around the world.  It is interesting to see that many times it does not work and actually hurts in some cases.  However, it is good to see that most of the time, if run correctly; it can be beneficial to communities in developing nations.

Assignment #9 Spring 2013

One paper I found particularly interesting is State Education Spending: Current Pressures and Future Trends published by the Tax Journal in 2007.  It’s main point is that changing age demographics in the United States is going to put significant pressure on education spending in the future.  As baby-boomers retire more funds will need to be directed towards retirees as they will be living longer and thus will be voters for longer.  Retirees see little benefit from education spending and thus are going to put pressure on governments to curb it.  It didn’t bring in any new data, however it brought in a different perspective.  I had been thinking of demographics in more of an income and location mindset, but this paper made me realize age will play a huge role as well.  It may affect my model.  I have yet to decide if I am going to attempt to project future spending, if so then this paper definitely has suggested an issue I need to take into consideration.  It would not be an easy fix, but using current trends I believe I will be able to formulate an assumption.  Education spending increases have seen two big jumps in the past decade, one from No Child Left Behind and the other from the stimulus.  However, year over year increases for the other years are very small, actually negative in some cases.  I believe I will be able to work with that.

Murray, Sheila E., Kim Rueben, and Rosenberg Carol. “State Education Spending: Current Pressures And Future Trends.” National Tax Journal 60.2 (2007): 325-345. Business Source Elite. Web. 29 Mar. 2013.

http://search.ebscohost.com/login.aspx?direct=true&db=bsh&AN=25977868&site=eds-live 

Assignment #8 Spring 2013

 

 

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This is currently my most advanced and significant regression.  However, it is not my final product.

The primary relationship of interest is education spending, in per pupil form, and a respective state’s GDP per capita.  My thesis is that the two should be positively correlated.

The t-value for the estimated coefficient of my variable of interest is -2.51, which is well past the 99% confidence interval.  This means the variable is clearly affected by the included variables. 

From this regression I can draw the conclusion that there is definitely a correlation between instruction spending and GDP per capita.  Instruction spending does not include all spending.  When using total spending no significant conclusion can be drawn as there is no strong correlation.  However, instruction spending which includes materials directly related to classroom instruction, such as teacher salaries.  This is interesting as clearly different forms of spending have different results.  Urbanization is also an interesting component.  It makes sense, however. When people are closer together, economies of scale are easier to take advantage of, bringing down costs.

The short answer is yes, there are always things missing, as no one will ever come across a “perfect” regression.  One aspect that would be very useful is how teachers are paid, say performance vs, tenure.  However, reliable data on this is downright impossible to find.

Yes, a casual link can be obtained for all of the variables.  The t-values are all past the 95% confidence interval.   

 

 

Assignment #7 Spring 2013

Chapter 4 of Poor Economics deals primarily with the notion of an education based poverty trap.  The chapter talks about how education levels vary widely across the world, with emphasis on the developing world.  A particular point it makes is that quality is significantly more important that quantity.  The authors use Africa to prove their point.  Many African nations have attempted to improve their national education systems in the hopes that those improvements will result in better jobs and life quality.  However, the education reforms are often “swallow.”  Meaning high quality teachers and new schools were not a priority, rather mass education is and that has not proven to work.

An article in the New York Times by John Tierney deals with prison and poverty traps (http://www.nytimes.com/2013/02/19/science/long-prison-terms-eyed-as-contributing-to-poverty.html?pagewanted=all&_r=0).  However, he devotes a good portion of the article of how education plays a critical role in the cycle.  More often than not people convicted of crimes have not achieved a high level of education.  When they are incarcerated they are not able to help their families with expenses.  This contributes to a vicious cycle of inmates’ children and spouses having  a higher felony rate than those who do not have a family member imprisoned.  This leads to lower education attainment levels.  This in turn leads to severely decreased job opportunities owing to low education levels and the criminal record obtained from severing their sentences.  The author advocates for training programs for released inmates and improved after school programs for children in general, but specifically those with an incarcerated family member.  

Assignment #6 Spring 2013

Introduction (Tentative)

Education spending is a hot topic issue.  There are opposing views as to how spending more or less actually impacts student performance.  In my report, I will examine how a state’s spending on education affects their students performance.  I will specifically look at per pupil expenditure.  I expect to find that higher per pupil spending does result in higher performance.  However, the result may not be cost efficient.

Bibliography (Also tentative)

“BEA News Release (GDP by State).” Bureau of Economic Research. N.p., 5 June 2012. Web. 28 Feb. 2013.

“In Ranking, U.S. Students Trail Global Leaders.” USAToday. The Associated Press, 7 Dec. 2010. Web. 5 Dec. 2012. <http://usatoday30.usatoday.com/news/education/2010-12-07-us-students-international-ranking_N.htm&gt;.

Madland, David, Nick Bunker, and Progress Center for American. “Middle-Class Societies Invest More In Public Education: A Stronger Middle Class Is Associated With Higher Levels Of Spending On Education.” Center For American Progress (2011): ERIC. Web. 1 Mar. 2013.

“National Economic Accounts.” Bureau of Economic Analysis. U.S Department of Commerce, 29 Nov. 2012. Web. 1 Dec. 2012. <http://www.bea.gov/national/index.htm&gt;.

U.S. Department of Education. Institute of Education Sciences, National Center for Education Statistics.***

Yamamura, Eiji. “Public Education Spending And Outcomes: Puzzle Of Skipping And Completing School.” IUP Journal Of Public Finance 9.3 (2011): 34-40. Business Source Elite. Web. 1 Mar. 2013.

***This is a generic citation for now.  It will become more specific when I decided exactly what data I will be using.