Category Archives: Economics

An economics tutorial on oil prices

In today’s Wall Street Journal, Martin Feldstein provides a simple economics tutorial on oil prices entitled “We Can Lower Oil Prices Now”. Once you read this, you’ll understand why “Any steps that can be taken now to increase the future supply of oil, or reduce the future demand for oil in the U.S. or elsewhere, can therefore lead both to lower prices and increased consumption today.”

Of course, Professor Feldstein’s conjecture directly contradicts claims made recently by certain members of the political class who simply assert (without benefit of any corroborative economic theory and/or evidence) that increased drilling cannot possibly have any such effects; e.g., see “Obama and The Don’t Drill Democrats To America: Don’t Drive. Just Shut Up and Sweat In Your Dark House.”

Drill! Drill! Drill!

I would like to nominate Daniel Henninger, editorial writer for the Wall Street Journal, for president. His article in today’s WSJ, entitled “Drill! Drill! Drill!” provides a very clear analysis of the predicament that the U.S. faces as a result of its longstanding (30 years plus) policy of not developing domestic energy sources. Click on the video play button below to see an interview with Mr. Henninger about today’s column.

moral hazard and public policy

Harvard finance professor Josh Lerner is quoted today in the Austin American Statesman: “It’s sort of like, heads you win, tails the Fed picks up the pieces”. Professor Lerner made these comments in reference to the historically unprecedented and controversial Fed-engineered rescue of Bear Stearns (cf. “Bear Stearns fetches a better price, shoring up deal” to see this quote in its original context).

Clearly the motivation for the Fed to intervene in this fashion was to prevent a severe and pervasive “credit crunch” in the U.S. economy from going from bad to even worse. A couple of weeks ago, Bear Stearns suffered a classic “run-on-the-bank” scenario; its short-term creditors refused to lend the firm any more money via the extension of overnight loans, and simultaneously demanded repayment of outstanding debt. The net effect completely overwhelmed Bear’s cash position, which in turn forced the investment bank to seek help from JPMorgan Chase and the Fed. Since then, the Fed has opened its so-called “discount window” to investment banks as well as commercial banks. The last (and only other) time that this occurred was during the Great Depression.

From a risk management perspective, the decision by the Fed to take this action involves trading off the benefit of preventing a financial contagion in the short run against longer run moral hazard effects such as Professor Lerner has described. At this point in time, it is impossible to determine whether our economy will be better off as a result of this policy action. The most important asset that any organization, including the government, can have is the trust of its constituents. The problem with ad hoc regulatory interventions like this is that it raises the bar in terms of people’s expectations regarding future public policy; specifically, it encourages the notion that the government will bail you out if you are big enough and manage to mess up badly enough. Economists refer to this as “time-inconsistent” behavior on the part of government. The concern that many have about this action by the Fed is that it may make matters worse by effectively increasing systemic risk going forward. The issue here is whether the long run moral hazard consequences can be reigned in prospectively, or whether the action will effectively “up the ante” and encourage even more risk prone behavior on the part of investors, as suggested by Professor Lerner’s quote.

Nobel Prize in Economics

It is worth noting that the Nobel Prize in Economics was announced on Monday. The winners are Leonid Hurwicz (University of Minnesota), Eric Maskin (Institute for Advanced Study at Princeton University) and Roger Myerson (University of Chicago). They are famous for their seminal work in the field of “Mechanism Design Theory”. NPR provides a good (audio) explanation on their website. Still don’t understand what these Nobel winners developed? Here’s an explanation for non-economists from the "Marginal Revolution" blog.

 

The Tort Tax

Apparently, the total cost of the US tort system continues to grow. Relative to GDP, the “direct” or “static” costs of litigation — including damage awards, plaintiff attorneys’ fees, defense costs, administrative costs and deadweight costs from torts such as product liability cases, medical malpractice litigation and class action lawsuits, grew from 2.04% of GDP in 2001 to 2.44% of GDP in 2006. However, the total cost of tort is quite a bit higher than this because of the manner in which the tort system creates incentives for economically unproductive behavior. Yesterday’s Wall Street Journal article entitled “The Tort Tax” outlines various “dynamic” or “indirect” costs related to tort, and concludes that once these costs are taken into consideration, the actual total costs of tort are more like 6.4% of GDP; in 2006 dollars this comes to $865 billion (2006 GDP is estimated to be $13.45 trillion). This amount is equivalent to the total annual output of all six New England states, or the yearly sales of the entire U.S. restaurant industry. On a per capita basis, this comes out to $2,883 per year per American (note that the population of the United States is approximately 300 million).

It would be interesting to see what total tort costs (including both the direct and indirect costs as described above) are in countries other than the United States. The direct costs of tort are already very well documented. For example, the 2004 Economic Report of the President, notes that the direct costs of the U.S. tort system (as a percent of GDP) are more than 3 times greater than tort costs in the United Kingdom, and are also significantly higher than tort costs in most other industrialized countries.

Confusion about the "Law of Large Numbers"

An important concept in the theory of risk that seems to confuse a lot of people (journalists in particular) is the law of large numbers. The law of large numbers is a statistical law which implies that the average value of a randomly selected sample is likely to be close to the average value of the population from which the sample is drawn. The law of large numbers makes important risk pooling mechanisms such as insurance economically feasible. For more information on the law of large numbers, see the Wikipedia entry on this topic, entitled “Law of large numbers”.

Lately in the media, I have heard numerous (incorrect) references to examples of the “law of large numbers” at work. For example, this morning on Bloomberg Radio, an analyst was droning on about how the “law of large numbers” works to the “disadvantage” of large companies like Walmart. This analyst correctly observed that as large firms such as Walmart grow even larger, their opportunities for further growth in the future diminishes. This is an example of the “law of diminishing returns”, not the law of large numbers.

Confusion about the "Law of Large Numbers"

An important concept in the theory of risk that seems to confuse a lot of people (journalists in particular) is the law of large numbers. The law of large numbers is a statistical law which implies that the average value of a randomly selected sample is likely to be close to the average value of the population from which the sample is drawn. The law of large numbers makes important risk pooling mechanisms such as insurance economically feasible. For more information on the law of large numbers, see the Wikipedia entry on this topic, entitled “Law of large numbers”.

Lately in the media, I have heard numerous (incorrect) references to examples of the “law of large numbers” at work. For example, this morning on Bloomberg Radio, an analyst was droning on about how the “law of large numbers” works to the “disadvantage” of large companies like Walmart. This analyst correctly observed that as large firms such as Walmart grow even larger, their opportunities for further growth in the future diminishes. This is an example of the “law of diminishing returns”, not the law of large numbers.

]]>