Assignment 11

 Reading Freakonomics for the second time I was rather surprised at the lack of statistical evidence I missed during my first reading.  The authors Levitt and Dubner merely present a continues stream of anecdotal numbers they introduce as fake statistics, for any actual statistics related to their models they merely mention studies (often which they themselves did).  With that in mind I was rather looking forward to reading their actual research and not a watered down version.  However this was disappointing, DL used the same technique of presenting a multitude of numbers (not statistics and mostly trends) in establishing not just a correlation between crime and abortion but a casual relation.  I was quite glad to read Foote and Goetz rework DL’s regression work; most apparent to me was the omitted variable biases both regressions DL used and also the discontinuity between DL’s regressions that FG only mentioned.

            Without doing any regressions myself I would side with FG and the other literature they site as agreeing with them (Sailer, Joyce, Lott and Whitley) that DL’s work is flawed and only shows signs of correlation and in no way causality.  DL overlooking the obvious correlation between high crime and high abortion rates, while only looking at a lack of relationship in the trends of crime and abortion rates.  They base their causality claims on this.  However I find it odd that one would check for a correlation in rates before averages (and not in averages at all), it is merely counter intuitive especially given the plethora of numbers they use in claiming causality.  I am much more inclined to believe that they checked for a correlation in average rates of abortion and crime and then neglected the high and significant coefficient because it didn’t fit within their theory of causality.  This makes them potential frauds, although no explicit evidence of this exists.

            Additionally, I thought the blatant contradiction of the results from their two regressions indicative of fraudulently presenting their findings as significant and casual.  The first cross-state regression showed evidence of correlation between abortion and crime rates, while the second regression only shows that states with more abortions (and also more crime to begin with) experienced a sharper relative drop compared to average states.  However there was not a significant correlation between crime rates and abortion rates in the regressions done on individual states, this more than anything should have altered DL to potential problems in their regressions.

            That said about FG’s and the other literatures critique of DL I had some additional critiques of DL’s work.  I felt the critiques of DL operate within the framework DL set out to stringently, mostly be using the same effective abortion measure, a simple summation of all previous abortion rates times a measure of arrest rate for that age group.  What this does is potentially introduce a bias for a particular cohort being more violent that another in addition to assuming that the effect of abortion is constant in the propensity to commit a crime over the entire life of a criminal.  This might be why DL and FG didn’t run any regressions with data past 1997.  What I really want see, in establishing causality is stabilization in the crime rate after 1998, the abortion rate stabilizing in 1980, this follows directly from DL’s theory that abortion has a lagged effect on crime rates of roughly 18 years.  In order to demonstrate this and the establishment of a steady state crime rate influenced by abortion rates a new effective abortion term needs to be established; one that demonstrates a constant correlation between criminality and age (this term will need to be raised to a power because of the drop off in criminality rates as age increases) and one that corrects for estimated coefficient between crime and lagged abortion rates.  Replacing the summation used by DL and others with an integral yields a differential equation able to find a steady state component in the crime rate if it is truly related to the abortion rate, producing a test for causality.  Figure 1 in DL’s paper indicates a very stable steady state in the abortion rate between 1980 and 1990 making this test possible.

ImageWhere ai is the population of cohort i, X(i,t) is a measure of the criminality of age group i at time t and A(i,t) is a measure of the abortion rate of age group i at time i (time of birth).  A(i,t) is also a function of time since the abortion rate is not constant over 1973-1980 (although this could be inputted directly into a similar model assuming like DL that abortions and criminality have no common factors across time).

 

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Assignment 10

Poor Economics Chapter 7

 

            Chapter seven of Poor Economics was much less statistics based than the previous chapters, the few numbers used are more anecdotal than statistical.  The main purpose of the numeric figures used in chapter seven is to compare western debt markets to those in the developing world.  However the real underwriting theme throughout the chapter is the misinterpretation, willful or unwilling, of credit reality in the third world.  This lack of understanding stems from ether an inherent lack of data on informal moneylenders or self-inflicted resistance to the true costs/benefits of microfinance.

            The few statistics used contrast the lending to the third world poor with that of first world developed countries.  In the third world informal relationships between creditor and borrower, replace the credit scores and due diligence used in developed economies.  As indicated by the orders of magnitude higher borrowing costs to the third world poor, theses relationships are much harder to cultivate and maintain; when combined with the associated higher default risks there is little wonder why the poor must pay such high borrowing costs.

            On the subject of microfinance, the proponents thereof use a blatant substitution of statistical inference with anecdotal evidence, to inflate the relative benefits thereof.  Banerjee and Duflo reference a study they carried out on microfinance but site few statistics other than the percent of loan recipients that are actually entrepreneurs, a very small 5-7% (Poor Economics, 170).  The marginal amount of entrepreneuring negates the main argument for microfinance the notion that it promotes economic development while simultaneously empowering individuals.

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Assignment 9

Litvak brought to light the idea that Sarbanes Oxley (SOX) changed the relative risk reward ratio of public companies.  This means I should be looking for SOX induced adjustments in both market risk correlation β and in expected returns.

 

Litvak, Kate. 2007. “Sarbanes-Oxley and the Cross-Listing Premium.” Michigan Law Review 105 (8, The Louis & Myrtle Moskowitz Conference on the Impact of Sarbanes-Oxley on Doing Business): 1857-1898.

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Assignment 6

            I found an article titled “Teacher Absences as a Leading Indicator of Student Performance” the article examines the relationship between student performance and teacher absenteeism in the United States.  I found the article very interesting because it related the educational phenomena discussed by Banerjee and Duflo in the third world to my world, the USA.  Of note is that teacher absenteeism rates differ greatly across the US with rates in locals like Camden New Jersey around 40 percent a day, similar to those in the third world (Center for American Progress, 2012).  Both the American Progress article and Poor Economics found private (The Center for American Progress also included charter schools) had lower rates of teacher absenteeism, I am interested in further study here because Banerjee and Duflo didn’t discuss the tenure/compensation systems in the third world schools.  The American Progress reported cited statistics for the large number of absences according adjacent to weekends and in blocks just under the requisite number of days requiring a doctor’s note.  Banerjee and Duflo using third world data and much higher absenteeism rates never had to justify the point that teachers nefariously report time. 

            Both agree that there is an absenteeism problem in their separate educational system of study; in addition I think Banerjee and Duflo would agree that the problem is worse in education systems with lower performance.  I should note that there is probably a feedback loop between the two variables of student performance and teacher absenteeism.  However I think both these studies miss the major point and that is both teacher absenteeism and low student performance are probably just separate manifestations of similar causes.

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Introduction and Bibliography

Introduction 

          In recent years the number of market listings has declined sharply, initial public offerings are now bellow replacement rates.  Current research has proved that new forms of corporate structure, venture capitalism and new regulations have affected the incentives for companies, especially smaller ones to list publically.  IPO activity and total equity listings fell sharply in the early to mid 2000’s, following the dot-com bubble, in 2000, and the passage of Sarbanes-Oxley Act (SOX) of 2002.  SOX placed additional accounting requirements on publically traded US based companies raising average costs encouraging them to defer listing (Kamar, Karaca-Mandic and Talley, 2013).  Fitting into this literature, my research will analyzes the effect that SOX has had on the profitability of different sized firms witch have recently listed stocks.  Comparing the profitability of different sized firms against the market average allows me to directly test the common assumption (that SOX negatively affects firms particularly smaller ones) used in measuring the affect SOX had the probability that companies will list publically or be bought by venture capital.

 

Bibliography

Chhaochharia, Vidhi, Clemens A. Otto, and Vikrant Vig. 2011. “The Unintended Effects of the Sarbanes—Oxley Act.” Journal of Institutional and Theoretical Economics (JITE) / Zeitschrift Für Die Gesamte Staatswissenschaft 167 (1, 28th International Seminar on the New Institutional Economics — Business-to-Consumer Transactions): 149-164.

Gao, Feng, Joanna Shuang Wu, and Jerold Zimmerman. 2009. “Unintended Consequences of Granting Small Firms Exemptions from Securities Regulation: Evidence from the Sarbanes-Oxley Act.” Journal of Accounting Research 47 (2, Regulation of Securities Markets: Perspectives from Accounting, Law, and Financial Economies): 459-506.

IV, John C. Coates. 2007. “The Goals and Promise of the Sarbanes-Oxley Act.” The Journal of Economic Perspectives 21 (1): 91-116.

Kamar, Ehud, Pinar Karaca-Mandic, and Eric Talley. 2009. “Going-Private Decisions and the Sarbanes-Oxley Act of 2002: A Cross-Country Analysis.” Journal of Law, Economics, & Organization 25 (1): 107-133.

Litvak, Kate. 2007. “Sarbanes-Oxley and the Cross-Listing Premium.” Michigan Law Review 105 (8, The Louis & Myrtle Moskowitz Conference on the Impact of Sarbanes-Oxley on Doing Business): 1857-1898.

Ritter, Jay R. and Ivo Welch. 2002. “A Review of IPO Activity, Pricing, and Allocations.” The Journal of Finance 57 (4, Papers and Proceedings of the Sixty-Second Annual Meeting of the American Finance Association, Atlanta, Georgia, January 4-6, 2002): 1795-1828. 

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Drug Dealers and their Moms

1. Levitt and Dubner make the economic argument that drug dealers live with their mothers because their average income is very low and people becomes drug dealers because they dream about having high earnings and respect.

2.

            a. The first statistic they reference (in a rather ad hoc manner) is the comparison of a “Black Disciples” organizational chart and that of McDonalds (89).  While no statistical analysis was done on this piece of information, it is used as a justification why there is an economic viewpoint to the research question and why there is data that they can use.  This is done largely because their audience is not micro-economists, who would naturally assume that people respond to the incentives they face.

            b. The second statistic used is a cost breakdown for the Black Disciples Chicago Branch (90-92). The authors use this statistic to demonstrate the cost structure and revenue sources for the gang, to help explaining some gang decisions like wages (later in the chapter).  This will be very important for why some in a gang organization are paid a lot while others are not.

            c. The third statistic used by the authors is an actuarial table of the risks faced by drug dealers (94).  The authors use this table to demonstrate the disincentives (or risks) to being a drug dealer.  This table shows, what the lay audience typically thinks on the subject, the likely very poor quality of life outcomes for the majority of gang members.

            d. The forth statistic used is earning potentials for the upper tier of drug dealing compared to other potential income streams, Black Disciples Chicago Branch (94-95).  The authors use it to demonstrate the microeconomics incentives that drive people to become drug dealers.  That is primarily the dream of having people look up to them and making lots of money, upwards of 500,000$ a year.

            e. The final statistic I will talk about is the comparison of hourly pay for a high school quarterback and a drug dealer (96).  This statistic is used to concluded the message of the chapter and present it in a form easily related to and attainable by the non-economist audience.  By relating the dream of a drug dealer to the dream of a high school quarterback, the authors show a similarity in dreams and the motivations of people across different demographic groups.

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Assignment 4: Research Paper

In recent years the number of market listings has declined sharply, initial public offerings are now bellow replacement rates.  Current research has proved that new forms of corporate structure, venture capitalism and new regulations have affected the incentives for companies, especially smaller ones to list publically.  Fitting into this literature I want to research the effect the Sarbanes-Oxley Act has had on the decision of corporations to list in the US or Britain.  I will be using two sets of cross-panel data and a difference-in-difference model to estimate the likelihood of a company to go public in the US or in Britain.

 

My research will analyzes if the passage of the Sarbanes-Oxley Act (SOX) of 2002 encouraged initial public offerings (IPO) activity to move from the United States to Britain.  IPO activity and total equity listings fell sharply in the early to mid 2000’s, following the dot-com bubble, in 2000, and the passage of SOX.  SOX placed additional accounting requirements on publically traded US based companies raising average costs encouraging them to defer listing (Kamar, Karaca-Mandic and Talley, 2013).  At the same time, starting in 2004, IPO activity in Britain exceeded that of the US and would so until 2006  (The economist, 2012).

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