ImageI chose this regression because of the interesting collinearity that is shown.  When regressing GNP change on Unemployment change, I found a very large correlation with a t-value of -14.91.  After adding the dummy variable for recession years in, there was a significant drop in the coefficient of change in GNP which seemed to be directly connected to a high coefficient of recession years of .474 and a t-value of 9.33.  Because Okun’s law, by itself, is a very nice fit, it seems that adding variables only decreases from the f-score, but due to the large initial f-score, this is ok.  There are clearly things missing from this regression.  In my actual regression, I found that labor participation rates also have a significant effect on unemployment.  I think I will look further into other labor statistics to find more statistically significant variables.

 

          Bibliography

 

Knotek, Edward S., II. “How Useful Is Okun’s Law?.” Federal Reserve Bank Of Kansas City Economic Review 92.4 (2007): 73-103. EconLit. Web. 28 Feb. 2013.

 

Kurosaka, Yoshio. “Okun’s Law And Employment Adjustment.” Japanese Economy 39.2 (2012): 87-107. EconLit. Web. 28 Feb. 2013.

 

Moffatt, Mike. “Quarterly Economic Data.” About.com. N.p., n.d. Web. 28 Feb. 2013.

 

Sogner, Leopold, and Alfred Stiassny. “An Analysis On The Structural Stability Of Okun’s Law–A Cross-Country Study.”Applied Economics 34.14 (2002): 1775-1787. EconLit. Web. 28 Feb. 2013.

 

Since the establishment of the economic theory known as “Okun’s Law” in the 1960’s, economists have been examining the relevance and accuracy of Okun’s law.  Because of this discrepancy of the reliability of Okun’s Law, many economists have started using terms such as Okun’s rule of thumb because of the variability of the accuracy of the law.  I am curious to find out just how accurate or inaccurate Okun’s Law is and why the law is proven sometimes but not others.  In this paper I will use fifty years of United States data to test the accuracy of Okun’s law.  Based on my results I will look at sections of data, which show inaccuracies in Okun’s Law and try to figure out what factors may be responsible for such variability. I will then add in variables to account of other causes of GDP change to isolate more precisely the overall effect of Okun’s Law. 

 

The main thesis of this chapter is that the image of crack dealers living in mansions with one of the most profitable jobs in the country is a complete and utter myth.  While drug gangs can be extremely organized and operate in the similar style as corporations, the main  bulk of work is done by foot soldiers, or the “interns” of the crack game.

pg 102 Each of the top bosses stood to make $500,000 per year

pg 103 The top 120 men in the Black Disciples gang represented just 2.2 percent of the full-fledged gang membership but took home well more than half the money

pg 103 The foot soldiers earned just $3.30 an hour, less than minimum wage.

pg 104 The most dangerous legal job according to the Bureau of Labor Statistics is a timber cutter with a chance of death of 1/200.  The chance of death for a crack dealer is 1/4.

I thought the author presented these statistics in an interesting way.  For the main bulk of the chapter, the mood was that of surprise for the shear organization and level of education the higher-ups in the gang had and how impressive the corporation of crack dealing was from an insider view.  I think the statistics I presented in earlier in the blog are in fact true due to the level of commitment shown by Venkatesh.  I believe his background in mathematics and his devotion to the study definitely should show honest results.

The answer which the author was trying to solve was, “Why do Drug Dealers Still Live with their Moms?”.  I believe that the author answered this question partially.  Because they need the money to scrape by.  I do believe, however, that this does not fully explain the answer.  What about drug dealing in suburbs.  I know of a few kids in their 20’s in my town who deal drugs and live with their parents but there is no clear evidence observed from the reading to explain this phenomenon.  This is just something to think about.  It may be a question better suited for a psychologist however. 

I originally was curious to find out what kind of effect rapid increases in industry and growth of an economy can have on the environment.  Unfortunately, even after emailing EPA, I was not able to acquire any valid data to run a regression with.  While there may be other countries worth looking at, China was my main topic of concern due to their recent industrialization and horrible air quality.  China has, unfortunately, been trying to cover up this data which made the acquisition of a dataset difficult.  I have decided to move onto a new topic in which i will use quarterly data from the last ten years to test Okun’s Law of the affect of unemployment on GDP.  I have quarterly real GNP and GDP data, as well as percent change from quarter to quarter and unemployment numbers to match.  I am interested to see if Okun’s law is a relavant economic theory to the actual results in the United States over the last ten years.

I don’t think that the findings found by Shafir and Mullainathan change my perspective on the poverty trap at all, I think it backs it.  The only perspective that changes in my eyes is the poverty trap close to home instead of far away in the poorest places on earth.  The survey which is cited by Shafir really put that into perspective for me.  I can actually remember getting lunch money for school and being in similar situation.  In middle school, when there were times when I didn’t bring lunch my father would give me money to buy cafeteria lunch with.  Due to my short term goals of eating as much as I could with my given lunch money, I spent all my money on as much food as I could get while I could have easily been stashing away half the un-needed money to eventually accumulate a decent chunk of money.  With people spending so much time worrying about where there money is going each day it is hard to imagine ever “wasting” the days money for savings.  It is much easily to understand now in those terms.  

I would have liked to see the statistics on foreclosures on paycheck to paycheck mortgage payments to really have a grasp for why living day to day is such a burden on someone’s life.  There are so many exogenous effects that can occur to throw someone living in that lifestyle off their “track” completely (the example of the sick man in India in Poor Economics).  

I think an interesting experiment would be to offer 10 dollars a day to people living paycheck to paycheck in exchange for each person to record their daily income and expenses.  Coming from a college student, when there is a relatively easy ten dollars on the table, you should take it.  While I am a college student, the people in the study would be in much worse shape than I am (no meal plan) and would be sure to jump at the opportunity.  With this data at a larger scale, it would be more obvious to see trends and proof of a real, true poverty trap for many people.  

While instant gratification is, obviously, gratifying, sometimes it is better to just suffer a little bit in the present to provide a happier and less stressful future.

I enjoy reading the findings of the authors of Poor Economics.  They present many issues in which I was not all ready aware and have never really even considered.  The arguments presented are enjoyable due to both the evidence given in support, and the evidence that contradicts.  This presentation leaves thought and interpretation up to the reader.  I would really like to see more graphs to show their finding more visually as I can more easily understand data in that fashion although I do realize this is a book, not a paper.  

2.  The hunger-based poverty trap is a phenomenon which is seen in hunger stricken countries all over the world.  The basis of this hunger trap is that extremely poor people can not make enough money to purchase enough food to sustain a energy filled workday.  Due to this fact, malnourished people can not make any extra money because they simply do not have enough energy to work enough.  The authors make this claim by looking at the poorest people in the world and comparing their calorie intake.  The thought is that if there is not enough food to provide a well nourished diet, the person will make less and less money, become poorer and hungrier while nourished people have the opportunity to make more and more increasing the income gap.  The authors made many points that argued with this phenomenon by pointing out the percentages of income used towards food.  They found that only about 50-75 percent of income went towards food.  

I believe that the poverty-hunger trap does exist even thought the income spent on food is so low. I believe this because while not all of their money is spent on food, people must have a reason for living.  It is easy for us back in the US to look at these people, baffled, as to why they don’t buy more food, but the thing is, if they spent every cent of their hard-earned salary on food, just to immediately consume it all, what is the point of living?  These people live in some of the worst conditions worldwide and it is easy for me to see why the spend some of their money on things that can, temporarily at least, make them happy.

Blogging is a relatively new, but also rapidly growing form of sharing ideas and opinions.  Because of blogs, it is possible for those who normally do not have a public voice or opinion to express their views in a public and open forum for anyone who is interested to view.  Blogging can also be used as a journal type area for public viewing where people may update a blog daily or weekly.  

 

Three interesting blogs that I found are: the economic journals Calculated Risk (http://www.calculatedriskblog.com), Real Time Economics (http://blogs.wsj.com/economics), and The Big Picture (http://www.ritholtz.com/blog).

Calculated Risk is a blog authored by Bill McBride which looks at economic subjects in a very statistical matter showing many numbers and percentages to explain points.  There are posts added several times daily.  This blog is interesting because of the analytical quantitative view.

Real Time Economics is a blog authored by various economists which analyzes economic issues and subjects at a more qualitative theoretical point of view.  This blog, like the previous, updates several times daily.

The Big Picture is an interesting blog authored by Barry Ritholtz. This blog, which is updated multiple times daily, lists daily economic reads for the day which he deems important/interesting.  Ritholtz posts many interesting graphs as well.