Indy Telecom & Industrial Media

I rarely recommend textbooks as good reads. Not that they aren’t, of course, but they often tend to be academic in nature and therefore of little interest to anyone other than academics (and unfortunate students).

However, I’m taking a class by Professor Stephen P. Marks on World Poverty & Human Rights this Spring, and one of the textbooks is Amartya Sen’s rather excellent book Development as Freedom.

The book was such an engaging read that I finished reading it even before the start of my semester. Sen’s writing is very humanist in nature, peppered with a wry sense of humor in parts, all the while maintaining a tone that is at once both philosophical and pragmatic to the world’s problems.

Sen starts out addressing the question of whether or not freedom is conducive to development. He feels that such a question is at best defectively formulated, for reasons given below.

Sen ponders over how freedom is often dissociated from development, and considered a pleasant consequence thereof. However, Sen counters that freedom in itself should be the goal of development, and it is both constitutive and instrumental to development. He makes the argument that freedom (political, economic or societal) is central to achieving development; while freedom may result from such development, it would be unwise to ignore the inverse relationship, and true development will only happen through the proliferation of such freedoms. Furthermore, if the definition of development is to move beyond GNP and include freedom, unfree societies aren’t really quite developed.

Sen also argues against the “Lee Hypothesis”, named after the first Prime Minister of Singapore, Lee Kuan Yew. The idea behind the “Lee Hypothesis” is that democracy and freedom are luxuries that only developed societies can afford, and to become developed, less-developed societies will need to push forth agendas that may be at odds with democracy and freedom. Furthermore, a more ardent view would be that “non-democratic systems are better in bringing about economic development” for such societies.

In the same vein, he also takes to task the interpretation that “Asian Values” are inherently unsuitable and unfit for democracy, where Asia is defined not by region but through culture. The argument goes that discipline and obedience are critical traits to the Asian cultural psyche and as such, democracy is at odds with such a principle. This particular notion has had the unfortunate reputation of being exploited by authoritarian governments across Asia.

Sen counters both the “Lee Hypothesis” and the “Asian Values” argument by offering the example of the biggest democracy in Asia — India. While India has made several economic mistakes through the years, the fact that it continues to be free democracy hsa helped its economy grow while preserving the freedoms of its citizens. Sen also counters that the “Asian Values” argument isn’t necessarily unique to Asia, and that even within Asia, there have been differing schools of thought, including those that question blind allegiance to the state.

And of course, this book also touches upon Sen’s (now-famous) insight on famines and democracies.  He argues that famines are not necessarily caused by lack of  declines in food production but rather due to instability in the political, economic, or societal structures that leaves sections of the population unable to fend for themselves. Sen further proposes that countries that are “free” in the economic sense would have citizenry with a consistent income flow, and this income can be used to borrow or import basic necessities in times of need.

But at the end of the day, Sen concludes that true development cannot be measured through mere tangibles (e.g. GNP). Freedom remains the only true measure of development, and when there is freedom, development will follow.

(Cross posted from my International Relations blog.)

The topic and abstract for my IPE term paper that I had originally planned turned out to be a little too broad in its scope. As a result, my final paper had a much tighter focus.

Fluctuation & Flexibility: A Case Study of Exchange Rate Regimes from the 1997-1998 East Asian Crisis

The choice between fixed and flexible exchange rate regimes has long-lasting impacts on a nation’s economic security, and consequently, its political outlook. However, such a freedom of choice is almost always limited by the fiscal and monetary health of the nation. This paper evaluates the extent of such a freedom, and how choices in exchange rate regimes affect a country’s economic performance. Specifically, this paper uses the East Asian economic crisis as a case study to examine the effects of exchange rate policies.

The case study was performed on the basis of an exchange rate regime model by Patrick Osakwe, and was built using data before and after the Asian Crisis. The data and the results from the model were then utilized to review the original assumptions, and this laid the foundation for the conclusions drawn from the case study.

You can find my paper and the referenced Patrick Osakwe’s paper on choice of exchange rate regimes in emerging markets.

Finally, a quick caveat that this was a class term paper that’s effectively going to be a working paper to extend and validate Osakwe’s model. So, please treat it as such.

(Cross posted from my International Relations blog.)

On the same note as the previous post, here are some Scilab renderings of the slightly more interesting Plücker’s conoid.

And of course, here’s the code. Substitute N with the number of folds in the surface, where (quite obviously) the period of oscillation around the Z axis is given by 2π/n.

//Plücker’s conoid
stacksize (10000000);
num_points = 50;
u = linspace (0, 2*(%pi), num_points);
v= linspace (0, (1/2)*(%pi), num_points);
[U, V] = meshgrid (u, v);
x = V.*cos(U);
y = V.*sin(U);
z = sin(N.*U);
mesh (x, y , z);
surf(x, y, z,'edgecol','blu');

It’s been a while since I did something interesting with math on my blog, so I figured I’d go back to some old favorites. I’ve done the Cross Cap before, so here’s a variation — the Pseudo Cross Cap.

And of course, as always, here’s the code code to render them in Scilab. The code has been tested on Scilab 4.0. Enjoy!

//Pseudo Cross Cap
stacksize (10000000);
num_points = 50;
u = linspace (0, 2*(%pi), num_points);
v= linspace (0, (1/2)*(%pi), num_points);
[U, V] = meshgrid (u, v);
x = (1 .- (U.*U)).*sin(V);
y = (1 .- (U.*U)).*sin(2.*V);
z = U;
mesh (x, y , z);
surf(x, y, z,'edgecol','red');

I was rather intrigued and quite delighted to read about Minnesota introducing the world’s first Carbon tariff.

The target of this (much maligned, if I might add) tariff is North Dakota, which exports electricity produced primarily through the use of coal power plants. This is in stark contrast with Minnesota, which is ranked 4th in the nation for sustainable and non-polluting wind power generation.

The irony of this, of course, is that the world had always expected such a tariff to be imposed by one of the developed nations on the developing world, particularly China.

However, whether or not Minnesota can succeed in imposing such a tariff remains to be seen. One particularly significant hurdle is Article I Section 10 of the U.S. Constitution — the commerce clause — that specifically forbids states from imposing tariffs on interstate commerce:

“No State shall enter into any Treaty, Alliance, or Confederation; grant Letters of Marque and Reprisal; coin Money; emit Bills of Credit; make any Thing but gold and silver Coin a Tender in Payment of Debts; pass any Bill of Attainder, ex post facto Law, or Law impairing the Obligation of Contracts, or grant any Title of Nobility.

No State shall, without the Consent of the Congress, lay any Imposts or Duties on Imports or Exports, except what may be absolutely necessary for executing it’s inspection Laws: and the net Produce of all Duties and Imposts, laid by any State on Imports or Exports, shall be for the Use of the Treasury of the United States; and all such Laws shall be subject to the Revision and Controul of the Congress.

No State shall, without the Consent of Congress, lay any duty of Tonnage, keep Troops, or Ships of War in time of Peace, enter into any Agreement or Compact with another State, or with a foreign Power, or engage in War, unless actually invaded, or in such imminent Danger as will not admit of delay.”

While there are several arguments regarding the interpretation of the Commerce Clause, it is quite likely that this argument would entirely be at the mercy of the Supreme Court. After all, the Federal government has time and again demonstrated that what constitutes “interstate commerce” could be something completely arbitrary to suit an agenda.

However, what is more likely to work (in my opinion) is the argument of public good (in the Adam Smith sense of the term). In that context, it is the prerogative of Minnesota to tariff, tax, or otherwise hinder what it considers harmful to the inhabitants of the state. Also, the Commerce Clause specifically applies to states regulating commerce through the use of taxes and tariffs on interstate commerce — however, pollution is hindering the public good (air, water, health) and Minnesota is not just taxing those from other states, but also those from within Minnesota.

After all, if I pollute a river whose water is consumed downstream, the folks downstream are well within their rights to tariff all providers of water who do not conform to a standard of purity. It’s unfortunate if the majority of those live upstream — but that in no way means that the polluters  downstream do not have to pay a price. They are taxed/tariff-ed just the same.

Secondly, the fact Minnesota has been pushing for wind power over time (as evidenced by the great animation below) is a point further in their favor –

It could be argued that they are moving towards a source that is less polluting and more sustainable in the interest of public good. Of course, the reverse could also be argued in that they are exploiting that which they’re abundant in. However, that’s a facetious argument simply because there are other states better positioned to use their natural resources (e.g. solar energy) that don’t (e.g. Texas).

No matter which way this goes, it is bound to be an interesting debate — and one in the right direction.

After all, as an adherent of Keynesianism, I am of the firm belief that inefficiencies in the market are endemic to private enterprises, and a “correction” mechanism in the form of public intervention is often necessary (as little as possible, however). I will also add that public good is one such inefficiency that’s often ignored by the private sector, and it falls within the purview of governments to ensure that the interests of the people and the environment are maintained over the interests of the greenback.

Go Vikings!

Excellent and fascinating video by National Geographic on Dean S. Potter – climber, rope-walker and BASE jumper.

Fascinating visualization of US bank failures by the folks at Computational Legal Studies.

The interesting thing to note, of course, are the three key takeaways:

1. Acceleration: There were four failures in the first six months of 2008, followed by another 22 failures in the next six months. By January of 2009, there were 21 failures in the first three months of the year, followed by 138 from April to last Friday.
3. Magnitude: Failures in the past two years have cost the Depositors Insurance Fund an estimated $57B. The IndyMac failure of July 2008 accounted for $10B alone, followed by BankUnited at $4.9B and Guaranty Banks at $3B.
4. Spatial Correlation: There is a significant amount of spatial correlation in California, Georgia, Florida, Texas, and Illinois. These states account for 77% of the total costs to the Depositors Insurance Fund. Furthermore, most of the losses in California and Georgia were concentrated highly around a few urban centers.

(Link du jour Paul Kedrosky)

Following Berkshire Hathaway’s SEC filing last Friday, I received the ballot to vote on the splitting of Berkshire Hathaway Class B stock.

To me, it is an unfortunate sign because this would effectively invite every option trader to speculate on Berkshire Hathaway — and BRK will move away from being one of the few remaining investment equities and go towards being a speculative equity (although, one may argue that all equities are by definition speculative).

Doing some rough math, the number of Class B shares would go up from ~47 million to potentially ~2.33+ billion.  And that would also raise the issuing maximum from the current 57.7 million to 3.23 billion.

Cheap options and easier buy = higher noise and higher volatility.

We should all rejoice, for it signifies the return of Gen Braham, the rather Unintelligent Speculator.

(Created from Nobel Lecture by Barack H. Obama, Oslo, 10 December 2009.)

Excellent (and controversial) summary chart of the global macro-economic history of the past ~50 years by David Beckworth.

Of course, the chart has sparked some interesting takes by Paul Krugman and Alex Tabarrok, amongst others.

From Instapundit:

CONSTANT-DOLLAR DOW: Today’s 10,000 is really 7,537. Or, in another metric: “It cost about 30 ounces to buy the 10,000 Dow last time. Now it costs less than 10.”

And here’s an interesting Bloomberg screen cap of the Dow over CPI –

(Link du jour Prasenjeet)

I’ve been meaning to post this for a while now.

Some time ago, the WSJ had an excellent interactive graphic that chronicled the timeline of credit crisis by stacking the 6 key financial indicators through these two years.

The key indicators were DJIA, Treasury Yields, Libor, Commercial Paper Yields, CDS Spreads & Mortgage Backed-Securities Spreads.

An excellent piece by Robert J. Moore of RJ Metrics called Twitter Data Analysis: An Investor’s Perspective that goes into how a potential investor would perform analytics on a platform like Twitter before investing.

With the use of some very basic statistics that’s easily available through Twitter’s API, he performs a very interesting cohort analysis of user activity and engagement activity.

Fascinating stuff. A few thoughts from my end –

• How could this be monetized based on user preferences, demographics (those of users & followers) etc?
• What will be needed to encouraged people to tweet more?  I’ve been on Twitter for a long time, but I’ve less than 10 tweets. Surprisingly, I’ve 45 followers.
• What could be done about bots? More importantly, how could user credibility be built (ratings, karma, community moderation etc)?
• On the same note, how about differentiating corporate users? E.g. Google’s official Twitter channel vs. that of their fans (and detractors, of course).

So, turns out that the US trade deficit went down to $30.7 billion in August 2009 from $31.9 billion in July 2009.

What is particularly interesting is the strong correlation between the imports and the exports.

The worst percentage loss were for Northwest, United & American. The ones that did well with minimal loss were JetBlue, SkyWest & Southwest.

The data was sourced from the Airline Data & Statistics section of the Bureau of Transportation Services.

Here’s a slightly better attempt at creating a heat map, this time with the Google Gadgets API.

The heat map below is that of the Average Gross Yield (Nominal) of MFI institutions from various countries in the world. The yield is in percentage (i.e. .06=6% and .85=85%).

Data was sourced from MIX Market.

Here’s a fun visualization created using Google’s Visualization API.

The data was queried from International Monetary Fund’s World Economic Outlook Database, October 2009.

Lately, I’ve been playing around with some fun MFI data from around the world. In particular, I was curious to see what the Gross Loan Portfolio across various microfinance institutions were, and how they aggregated within each country of operation.

Luckily, I was able to source some rather excellent data from MIX Market.

Given this (and the fact that I’ve been playing around with Google’s Chart API for a while), I went ahead and created a little heat map of the global MFI rankings by Gross Loan Portfolio:

If you look at the above map, those countries with higher portfolios are in a darker shade of green and those with lower portfolios are in a lighter shade of green.

The list of the top all countries with more than 1% of the global MFI Gross Loan Portfolio is also listed below.