Roubini and the Egyptian Counterfactual

Nouriel Roubini, a well-known economics professor at New York University, commented in the video above that "...what's happening in Tunisia and Egypt is in part being driven exactly by rises in food prices." Dr. Roubini is well-known in part because, as early as September 7, 2006, he was predicting the Subprime mortgage crisis in front of the International Monetary Fund (here). Dr. Roubini's predictions were dismissed because he did not make use of mathematical models.

I'm not sure whether the criticism extends to statistical models (which are mathematical) but Dr. Roubini's assertions about Egypt can be tested with time series models. First, it is important to understand that Roubini's assertion (that protest in Tunisia and Egypt is the result of commodity price rises) is essentially a counterfactual historical statement. That is, had world commodity prices remained constant, Egyptians would not have gone to the street.

Without getting into all the details, we can test the counterfactual by using the WL20 world systems model to predict unemployment in Egypt (assuming that a large unemployed urban population is a precursor to protest). One of the cyclical state variables in the WL20 model captures world commodity prices (oil and wheat). Since Egypt is a peripheral economy in the world system, any effects of world commodity prices should affect the Egyptian economy (and thus employment) through the state of the world system.

The figure above displays the predicted dynamic attractor for unemployment in the Egyptian economy. It shows that through most of the late 20th century, unemployment has been cyclically increasing. What is interesting is that from 2007-2008 (the start of the world food crisis which did result in Egyptian protests) until the present, unemployment has actually been decreasing.

When we eliminate the commodity price state variable from the WL20 model and reconstruct the attractor (run a "free" counterfactual simulation of the model starting in 1960), we see that without the current increase in commodity prices, unemployment would have increased.

What is happening here is that Dr. Roubini and other commentators may be confusing correlation with causation. Yes, increases in food prices have appeared with increases in unemployment and conflict. And, increased commodity prices do squeeze the consumer (see a causal version of Roubini's theory here). Economic theory, however, suggests that there may be second round feedback effects.

Increasing world commodity should bring forth an economic and political response from the country being affected. Higher commodity prices should induce farmers to increase output (maybe with a year lag) and should induce governments to respond with agricultural programs, subsidies and price controls to offset any shocks from world markets.

Given the existing distortions in the Egyptian economy (read an overview of the economy here), there is plenty of room for negative feedback responses. And, any economic response to increases in world commodity prices would have some positive effect on employment. Still, the WL20 model attractor for Egyptian unemployment shows that the Egyptian economy is one of the "immiserizing" economies that produce growth without improving employment. And, immiserizing growth by itself might be enough to create protest (read more about immiserating growth in Mexico and Argentina, here).

Causality and The Financial Crisis Inquiry Commission

The Financial Crisis Inquiry Commission released its official report today (here). The Commission was created to "examine the causes, domestic and global, of the current financial and economic crisis in the United States." How effectively the Commission executed its charge and what the causes of the financial crisis were will be debated for many years to come (the causes of the Great Depression are still being debated after 82 years).

My interest is in developing a causal model of the financial crisis. In future posts, I will try to read the Commission's report and see what kinds of causal theories (if any) are embedded in the verbiage.

I have read one interesting causal explanation of the financial crisis by Alan Schwartz, the last CEO and chairman of Bear Stearns. An account of Bear Stearns' role in the financial crisis can be found in the excellent book "House of Cards" by William D. Cohan (you can read an excerpt of Schwartz's description from the book here).

I've worked out Schwartz's causal model at right (click to enlarge). Without getting into details, Schwartz traces the rise of Wholesale Banking and collateral financing to the repeal of the Glass-Stegall Act in 1999 and the increase in excess wealth seeking high returns as a result of globalization.

Now, let's see how the Financial Crisis Inquiry Commission does with their causal analysis.

AmeriQuest, the Subprime Mortgage Crisis and the Ten Not-Really-So-Hilarious Ads

At first I though this would be funny, but it actually made me sick to my stomach. AmeriQuest was one of the most notorious subprime mortgage lenders (read about it here). In the Report of the Financial Crisis Inquiry Commission (here), AmeriQuest was described by Lisa Madigan, the attorney general of Illinois as:

"...engaged in the kinds of fraudulent practices that other predatory lenders subsequently emulated on a wide scale: inflating home appraisals; increasing the interest rates on borrowers' loans or switching their loans from fixed to adjustable interest rates at closing; and promising borrowers that they could refinance their costly loans into loans with better terms in just a few months or a year, even when borrowers had no equity to absorb another refinance."

Keep Your Eye on the Ball

Last night, President Obama gave his State of the Union speech (full video below). The speech marked the end of President Obama's Keynesian phase and his rebirth as a neoclassical growth economist. In his Keynesian phase, it was all deficit spending and employment. In his neoclassical growth phase, it will be all technology, capital investment and competitiveness.

The graphic above shows a causal diagram of neoclassical economic growth theory. Everybody that can work is fully employed. Production involves the combination of capital, labor and technology within a free market system. But wait, how does that work? Neoclassical growth theory is about the long-run. Unemployment is still above 9% (here). Is neoclassical growth theory really applicable? And, doesn't more production mean more greenhouse gas (GHG) emissions (what ever happened to cap-and-trade and Carol Browner)?

If the Financial crisis of 2007-2011 is over, maybe it's time to forget bailouts and stimulus packages and think about the long run (take our eye off the ball?). A lot of people are more than happy to forget Keynesian economics. Whether you agree or not with John Maynard Keynes, however, he did produce some great quotes:

"The ideas of economists and political philosophers, both when they are right and when they are wrong are more powerful than is commonly understood. Indeed, the world is ruled by little else. Practical men, who believe themselves to be quite exempt from any intellectual influences, are usually slaves of some defunct economist."
— John Maynard Keynes

"The long run is a misleading guide to current affairs. In the long run we are all dead"
— John Maynard Keynes

Paul Ryan, R-WI: Conservative Philosopher

Representative Paul Ryan, R-WI, gave the Republican response to the State of the Union message. As some responders have found (e.g., Bobby Jindal, here), this can be a tough assignment. Representative Ryan chose to give us a primer on Conservative philosophy while at the same time coming off as a reasonable person. Quite an achievement!

I love counterfactuals, for example, "What if Paul Ryan would have made some specific proposals?" Had Rep. Ryan chosen to do so, he probably would have drawn on his ROADMAP FOR AMERICA'S FUTURE (here): (1) Health Care: repeal the current bill (which is a mess) and allow people to buy health insurance across State lines. People in Wisconsin can then enjoy trying to make claims on insurance companies in Nevada or use their refundable tax credit to play on-line poker. (2) Medicare and Medicaid: Fully fund Medical Savings accounts so that poor people with no money can put some of it aside for medical expenses. (3) Social Security: Allow people under 55 to take part of their Social Security taxes (it's my money and I need it now) and invest it in the stock market or add it to their refundable health care tax credit to play on-line poker. And, (4) Simplify the Tax code so that the wealthy and the large corporations don't have to pay taxes and don't have to hire expensive Democratic tax lawyers to find loopholes that they should just be getting anyway.

For any of my international readers who think Wisconsin is in Canada, Rep. Ryan's political philosophy and ROADMAP FOR AMERICA'S FUTURE should help correct your geography.

Integrated Assessment Models: PNNL GCAM

The IPCC is in the process of developing the next generation of emission scenarios. The scenarios are used to generate anthropogenic radiative forcings that drive Global Circulation Models. The so-called Integrated Assessment Models (IAMs) are being developed by government agencies and research laboratories in the U.S., the Netherlands, Japan and Austria. It is worth trying to understand and simplify these models because they are critical to conclusions the IPCC is drawing about climate change.

In the U.S., the Pacific Northwest National Laboratory (one of US DOE's ten national laboratories) has developed the Global Change Assessment Model (PNNL GCAM) which will be used to generate scenarios for the next release of IPCC documentation.

The PNL GCAM model is essentially the same partial equilibrium model you saw in introductory economics textbooks. Basically what these models (and their big brothers, general equilibrium models) do is compute long-run equilibrium prices. Partial equilibrium models look at one market (energy) while general equilibrium models look at all prices. Actual prices are assumed to be deviations from rationally determined long-run prices.

In partial equilibrium models, population growth, technology and gross domestic product are given exogenously. All the model does is calculate energy prices. The existing capital stock is assumed fixed.

It's hard to understand how a partial equilibrium model would be of much use in studying global climate change. Wouldn't there be impacts on food prices from oil prices and fertilizer prices? Wouldn't food prices have an impact on population and production? Wouldn't energy prices have an impact on technology and the existing capital stock e.g., replacing gasoline with electric vehicles?

These models were originally used to help the DOE study energy demand. They were recruited by the IPCC for the study of climate change.

PNNL also has a computable general equilibrium (CGE) model or Second Generation Model (SGM) that is described here. I'll talk about that model in a future post. CGE models are not necessarily an improvement.

Economic Outlook for 2011: Bernanke, Bair, Warner and Bell

Top regulators talk to the Small (Weak?) Business Forum. Some interesting points:

Bernanke (FED): The problem with the economy currently is weak demand (not excessive taxes?).

Bair (FDIC): One-fourth of small business finance themselves with home equity loans and home equity values are in the tank.

Warner (D-VA): The American consumer can't carry the entire recovery on their back. We need exports.

Bell (US Chamber of Commerce): Business uncertainty, too much government, blah, blah, blah.

Markets and Climate Change: One Analyst's View

Top Energy Fund Manager Questions Global Warming @ Yahoo! Video This analyst thinks that global temperature has been "cooling" over the last decade even though 2005 and 2010 were supposedly the hottest years on record (see my last post here). Is all this confusing enough or what?

Interesting Quotes:

"What we're looking at is alternative energy's economic at the present time and ... the only thing that makes sense is wind."

"The question is, are we going to get some kind of carbon tax that levels the playing field ... The cap-and-trade system we currently have doesn't do anything."

Hottest Years on Record: 2005 and 2010

Yesterday, the NY Times reported (here) that new data shows that 2010 was tied with 2005 as the two hottest years on record. It's useful to compare the new data to the revised forecasts from the IPCC "Climate Change 2007: Synthesis Report" (here) and to my own forecasts presented below.

The IPCC projections (forecasts) are based on emission scenarios. There are four basic scenarios generated from assumptions about globalization and economic growth. The A1 scenario is high globalization and high economic growth. The B1 scenario is high globalization and sustainable development. The A2 scenario is based on low globalization and high economic growth. Finally, the B2 scenario is based on low globalization and sustainable development. The scenarios produce different GHG emissions (left panel above, click to enlarged) and different global warming paths (right panel). The global warming projections range from about 1 degree C to over 3 degrees C with error bars over 6 degrees C (the error bars for the scenarios are on the far right of the graphic).
There are a number of alternative global temperature forecasts on the web (here and here, for example). The projections are typically based on single-equation statistical approaches. The basic equation is T = sF +V where T is global temperature, F is radiative forcing from GHG emissions or natural sources, V is natural variability and s is the climate sensitivity parameter. The increase in temperature is a direct result of forcing and climate sensitivity with some natural or cyclical variability thrown in.

My approach is based on state-space models that treat the environment and the economy as two interacting complex systems. The state of the environment is affected by the state of the economy and vice versa. Since the two systems can and do have negative impacts on each other, growth and global temperature peak over time. Notice that although the confidence intervals look wide, the top 98% confidence interval never hits the 2 degree C warming threshold considered critical by the IPCC.

The difference in projections is basically the result of the assumptions underlying the IPCC emission scenarios (the left graphic above). I'll go into more detail about and criticism of the emission scenarios (which are based on neoclassical economic growth theory) in a future post. My projections should not be taken as support for global warming denial. The models predict warming. What the world will look like after peak global warming, the models cannot predict.

The Financial Crisis Could Reduce U.S. Income Inequality

The role of income inequality in the Financial Crisis of 2007-2010 will be analyzed and debated for many years in the future. The time series above plots the percent of income being received by the top 99-100% of income earners in the US (the data are from Emmanuel Saez, here, and are controversial--read both sides here). What is very interesting is that income inequality peaked right before the Great Depression and right before the Great Recession. The coincidence (?) suggests a number of hypothesis about income inequality and financial speculation (here).

In this post, I'm going to beg the obvious question "If there is too much income inequality in the U.S., how much income should the upper 1% of income earners be making?" One approach to answering this question is to assume that the earnings of the top 1%, like the earnings of every other worker, should be tied to growth in the U.S. economy. If the economy grows by 4%, however, how much of that 4% growth premium should be captured by the upper 1%? All of it? Some of it? None of it?
What turns out to be a better model and one that fits the data better is that, regardless of growth in the U.S. economy, the share of income to the upper 1% should remain at about 13%, about where it is right now in 2010 after the Financial Crisis. Interestingly, from 1950 to about 1990, the upper 1% weren't getting their share! Something changed after 1990 (a nice topic for analysis and speculation) and that innovation, whatever it was, created a huge inequality bubble--a bubble that was popped by the Subprime Mortgage Crisis.
For the future, the model predicts that we will return to the level of income inequality that marked the U.S. economy from WWI to the 1990s. What new innovation might come along to create the next inequality bubble? We can't know the future but the model predicts that without shocks, the income of the top 1% would stabilized around 13%--something I probably won't see in my lifetime.

BMI and All-Cause Mortality: New Results

A paper on the relationship between Body-Mass Index (BMI) and health hazards appeared in the recent New England Journal of Medicine (NEJM, here). The study re-analyzed 19 prospective studies of 1.46M white adults from 19-84 years of age. All-cause mortality was adjusted to age, study, physical activity, alcohol consumption, education and marital status.

The results (displayed in the graphic on the right as hazard ratios--click the graphic to enlarge) confirm the conventional wisdom that a BMI of between 22.5 and 24.9 had the lowest all-cause mortality hazard ratio and seems to refute some early evidence that healthy people were a little fatter.

The graphic confuses me a little since healthy subjects who never smoked had a faster rising hazard curve as compared to all subjects (I would have thought that healthy people would have a flatter hazard curve) but the result may be due to sample size issues or some misunderstanding I have about the study. If anyone has any ideas, let me know.

What's also interesting is that underweight (BMI less than 22.5) is associated with an elevated hazard ratio. There are lots of problems with the BMI, but it seems to work well at least in population studies. The median BMI for the study was 26.2, suggesting people need to loose a little weight.

Top Performing Companies Welcome Environmental Regulation

Yesterday on CNBC (video here), Tim Solso, CEO of Cummins, Inc. (CMI) was interviewed on Fast Money. Cummins is one of the year's top S&P performers. Mr. Solso had some very interesting things to say about environmental regulation.

"In the 1990's, we saw regulation as a challenge and a problem. But [...now...] we think we're the technical leaders. We invest in key technologies... The tougher the emissions standards and the faster they're implemented, [sic] gives us an advantage. It's a barrier to entry for other engine manufacturers ... Emission regulations are going all over the world ... We're already starting to get ready for the 2014 CO2 regulations with better fuel economy which will benefit consumers. Regulations are a good thing for us and it's a good thing for clean air and a clean environment."

The quote demonstrates that the top performing companies welcome regulation. It's their weaker rivals that are the first to seek regulatory relief. And, the purpose of Capitalism is to sort out and eliminate the weak competitors. Smart environmental regulation is an essential part of the process. Next time you hear politicians complaining about the effects of regulation on "small business," remember that they really mean "weak" businesses.

Back to Cummins, they're stock price history is displayed in the first image (above) along with step-ahead model predictions. The predictions are based on a best-fit model and, in this case, the best fit model is based on secular and cyclical trends in the US economy (the USL20E model). Unlike GM (here), the Cummins stock price is not a random walk.
Over time, there have been periods where Cummins stock was both over- or under-valued. The graph above plots the USL20E model predictions without external shocks, that is, the equilibrium position for Cummins stock price. Right now, at the end of 2010, Cummins stock is about at its equilibrium value.
For the future, the model predicts (above) that Cummins will have a pretty good run at least until 2015. However, there is a lot of variability in the prediction (the dotted lines are the upper and lower 98% prediction intervals), so there is plenty of both potential upside gain and downside loss if you're interested.