Andy talks too much.

Entries tagged as ‘economics’

Economics and Horror Movie Exuberance

September 21, 2009 · Leave a Comment

Every horror movie has that moment. It usually takes place right as some beautiful girl hides in a closet, the killer tearing away at the door while she screams for help. But suddenly the violent pounding stops and goes away. Everything goes silent, and the background score fades. All you can hear as labored and fearful breathing and soon everything goes quiet and softens as you think the killer’s left the house. This pause is something I like to call horror movie exuberance. And it usually gets you killed.

Obviously the killer’s still there. The pounding suddenly continues, the door breaks in because our unfortunate victim wasn’t bracing it when they started relaxing, and a group of college students takes another round of tequila shots for their drinking game as one of the protagonists meets their end in a stupidly gory fashion.

Horror movie exuberance isn’t just for movies like Scream and I Know What You Did Last Summer. I think there’s a lot of horror movie exuberance going on in business right now. Across the United States, the recession has toppled industries and left scores of families unemployed (or worse) as a result of the credit markets freezing and businesses being unable to grow. Everyone wants this to end: businesses want the credit market to thaw so they can get access to capital for growth, customers want business growth so they can see increased quality of service, and familities want economic growth so that they can get jobs and increase their income again.  The world eagerly awaits a turn in the winds of economic change and fortune.

The sails of the nation’s economy seem to be picking up something. Indicators of growth such as lay-offs and earnings reductions seem to have plateaued. And for many, this is a good reason as any to crack open the champagne bottles and start the party. Already, Wall-Street IB firms are getting into the habit of monetizing bad debt again with the introduction of “fixed” CDOs that have a higher expected value (thanks to introducing goods with low risk into absurdly “duh-they’re-going-to-f*cking-default” bundled assets such as sub-prime mortgages). Tech firms have turned off hiring freezes. Even consumer spending is up. It seems like good times have returned.

Well, no they haven’t. In fact, this is no different than relaxing because the killer’s not pounding at the closet door anymore. These secondary proxy indicators of economic success aren’t 1:1 with the end of the recession. The recession’s still raging hard, and even if we might have hit an inflection point we’re still locked into it for the time being.

Horror movie exuberance usually comes as a result of two things: wanting the bad experience to be over and being able to rationalize it being over (e.g.: thinking the evidence supports the killer leaving because there’s no more pounding). Business is no different. We want the recession over. And we’re able to rationalize the recession being over by looking at our proxies for indicators of growth. But this isn’t how it works.

There’s a few reasons why we’re still in a recession, even though the indicator lights are green for recovery:

  • The second derivative is not the first derivative. The popular sentiment of a recession being two quarters of negative growth isn’t spot-on for the economic definition of recession. But it is a deciding factor in how we determine if we’re in a recession. These indicators aren’t referring to the rate of change of GDP though (the so-called first derivative of GDP with respect of time). This is more about how the rate of our rate of change of GDP is changing, the second derivative. If these indicators were about the first derivative, we’d see GDP rising and not “slowing down” in its decline. Sure, it may start rising soon. But right now slowing to an end in dropping is not the same as going positive; the second derivative is not the first derivative.
  • The indicators could mean nothing. This isn’t the first time where we’ve used indicators such as unemployment and inflation rates to determine the economy’s growth incorrectly. The Phillips Curve is a great example of getting it wrong. Originally, we believed that there was a concrete inverse relationship between inflation and unemployment. Then along came the 1970s and stagflation, a period of stagnant economic growth with high inflation and high unemployment.  While recent amendments to this theory such as the NARU (Natural Rate of Unemployment) work to revise the Phillips Curve model in the face of such problems, the fact remains that macroeconomics still has a long way to go until it gets the same level of concrete mathematical understanding as microeconomics.
  • Total Profits = Total Revenue – Total Cost. We see business profits rising right now and point to a proportional increase in business opportunity. This makes sense, right? Well, not necessarily. Especially in technology, huge layoffs are common to drop the total cost of a firm to ensure that lower revenue keeps a company in the green. If costs are decreasing more than revenue is decreasing, you can still have positive profits (albeit reduced compared to the previous period). This little bit of algebra shows that maybe everything’s not right in the world yet; maybe our costs are just very, very low. It’s important to note that firms like Intel and Apple who’ve reported excellent profits also posted massive layoffs during the last few years.

Just like horror movies too, the exuberance of thinking the recession’s over can be very dangerous. If a company tries to increase head-count and hire staff to deal with an increase in consumer demand that isn’t coming, you’re bound to have layoffs. In general, people that increase their cost curves significantly to try and grab market share improperly during this period aren’t going to find things radically turned around next quarter.

You could very easily get yourself killed right now by not leaning on that closet door hard enough for the next inevitable blow.

Categories: Business · economics
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Using the Tools of the Enemy

August 10, 2009 · Leave a Comment

For the last year I’ve been working on a CS research paper on how certain types of algorithms can be applied to solve pertinent problems (Ha! Alliteration!) in business and economics. Finding ways of hacking Bellman-Ford, Min-Cost Max Flow, and Dijkstra to address critical business intelligence issues is a lot of extremely nerdy fun for me. It’s also been getting me thinking about examining the issue from the other side of things:

How can we use the math from economics to solve problems in technology and software engineering?
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Categories: Algorithms and Computer Science · Computer Software · Computer Technology · economics
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Theory Courses that Apply in Tech Companies.

June 10, 2009 · Leave a Comment

Edit: For some reason this post got malformed when I last edited it and chopped off a section on computer architecture. I’ve fixed the post and the title, but lost the comment that my K posted on Facebook. K, you’re absolutely right in regards to Theory of Computation.  That slight should be better directed at Formal Languages…

As of this semester, I’m done with both my major and minor in college. This semester also marks my second full year of substantial industry work experience – an ancillary benefit of needing money to pay for things like food and shelter.

Between the two worlds of poor college student and poor entry-level tech company employee, I’ve had ample opportunity to see how the things I learn from school translate into solving very real problems in the real world. Sure – unless you’re getting into academia there are a score of subjects that have no applicability whatsoever (**cough** theory of computation **cough**) in the workplace. But even theoretical classes are necessary elements of success in a tech company.
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Categories: Algorithms and Computer Science · Information Security and Crypto · economics
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The Netbook and the Demand Function: How Technological Development Can Thrive in a Recession

February 28, 2009 · Leave a Comment

For economists in Microeconomics and Consumer Choice, the demand function (or demand schedule) is one of the most powerful analysis tools at their disposal. The market demand function is a powerful information machine that processes an extraordinary amount of data about market variables and returns them in a legible and quantitative analysis-ready format. From the demand for another competitor’s good to the expectations of the market, the results of a demand function reflect not only upon what consumers in the market want. They also reflect on the market itself.

As of the time of this writing, the United States (and much of the developed world) is in a significant economic recession. According to the Department of Labor, the United States’ unemployment rate rose to 7.8% in January 2009 and U.S. imports are down 1.1%[1]. Both are signs of a weakened domestic economy, as the unemployment rate continues to be a salient variable in determining the overall health of the economy and the import rate is an indicator of how willing and able US companies and households are to invest and purchase foreign goods. Here in California, home to Silicon Valley – the home of powerful software and hardware names such as Intel, Google and Yahoo!, the situation is particularly dire. California reported an unemployment rate of 10.1% in January, 29% higher than the national average[2] . Major tech firms such as Google, Microsoft, and Yahoo! have engaged with massive layoffs in an effort to cut costs as banks and investment firms have turned gun-shy at helping them finance their operations in the downfall of major investment banking companies such as Lehman Brothers. In this environment of scarce resources, it seems nearly suicidal for technology companies to dare to innovate and produce new technology through demanding and potentially fruitless research and development investment when so much is on the line.

And then came the Netbook.
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Categories: Computer Technology
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