Lessons from Leamer: Part 2

Continuing from previous post.

1. Housing shows up in the GDP accounting via employment generation. Price appreciation of houses is not part of GDP; and more importantly, increased land prices today if booked as an asset, a liability has to be entered. Where? Liabilities for future buyers. This is transfer of wealth from future generations to present generations!
2. The stickiness of housing prices downwards means, most importantly, price cycles follow sales volume cycle. Also, the volatility of the housing volumes is much higher than the price.
3. Sellers develop their expectations of prices from a backward perspective (“what did I pay for it compared to the offer price?”). Buyers have forward looking price expectations (“what will I get for the house 5 years from now”). So, sales only happen when there is a high bid price by sellers.
4. In a housing boom, the fastest appreciation happens for small houses with low-income zip codes (and smaller square footage = condos and small homes). Predictably, during a bust – they get hit the most.
5. To avoid business cycle fluctuations – one must avoid housing cycle fluctuations and job-losses in consumer durables.
6. Monetary policy that acknowledges the two factors – must face up to the fact that if real interest rates fall temporarily, then for equilibrium level of housing stock will return to “normal”, only if production and sales fall and allow a return to the mean. In contrast, if real interest rates fall permanently, then equilibrium levels of housing stock will rise.
7. Monetary policy that accounts for housing investment is a difficult inter-temporal resource allocation issue.
8. Today, one observes the presence of weak housing starts (new houses being built) and increased inflation – resulting in a conflict for what the “right” policy prescription ought to be.
9. In case of policy choices to be made between housing starts and inflation – there is no real conflict.
10. The best predictor for Fed Funds rate is the 10-year Treasury bond yields.
11. Its the Housing Cycle!
    

Lessons from Leamer (Part 1)

Professor Edward Leamer has written a very interesting paper; and was presented at the Jackson Hole conference. I have been going through it in detail -- and I must admit it is a remarkable piece of analytical detective work. Following two posts are dedicated to his work. Although the original is nearly 70+ pages -- it is written in a very reader friendly style. So, worth the effort. For the rest, here is a quick summary. Caveat Lector!

1. Conclusions can be drawn of effects of policy X, if there are control and treatment groups. In macroeconomics, we only have non-experimental data. So, we rely on “story-telling”.
2. Monetary policy affects economy via housing-related decisions. Tempering business cycles means figuring out how housing-related choices are affected.
3. Inflation is a “daily” phenomenon, while housing is reinforced by a “wave”.
4. Monetary policy at different stages of the housing cycle – can exacerbate or diminish the extent of hurt that happens when a boom declines.
5. Housing booms are very susceptible to interest rate changes at the end of the boom, rather than in the early and middle stages.
6. Historically, the US economy has been growing at 3% over the past 30 years – despite all kinds of real, monetary and technological shocks. Monetary and fiscal policy must restrict itself to smoothening out the cycles (the amplitude and the frequency).
7. Contributions to long run growth are led by, in order of importance from a 2005 perspective, Consumer services, Non Durable Consumer Spending, Durable Consumer Spending, Equipment, State and Local Expenditure, Defense expenditure, Residences etc., i.e., Residences do not contribute substantively in long term growth.
8. For business-cycle fluctuations, Residences are very important. Typically, Residences contribute to the weakness in GDP growth before the “recession” starts and contribute above normal before the “recession” ends. This is in contrast to equipment and software sales. i.e., Residential spending is a pro-cyclical predictor of GDP growth. Equipment sales just mirrors GDP growth rate.
9. To address decline in GDP growth, one must address the “consumer” side of the equation and not the business side. So, Monetary policy must explicitly take into account Residential and Durables levels and volatilities.
10. There have been 10 U.S. recessions. Only two were driven by “production” side (i.e., by lack of demand on the business side) – post-Korean war and 2000/01 internet bubble collapse. Rest of the recessions have been caused by lack of consumer demand.
11. Housing prices are sticky downwards – i.e., prices don’t fall all that much. So, the natural way the market clears is by massive reduction in demand. This reduction is demand affects GDP/employment.

Predicting the Fed

The problem with best estimates is two fold.
One, the 'best-ness' criterion is contingent on the information available. So, new information can cause a previous “best” estimate to be a second best or worst estimate. (An extreme example would be, in a non-financial context, American foreign policy on September 10’2001. The next day’s events – led to wildly different prescriptions than most academics/policy wonks had anticipated.) So, the quanta, quality and timing of information is the key.

Second, the estimate itself is a result of some estimating method – an algorithm, a formulae – that econometricians call “estimators”. In essence, it is not just information that is relevant – but the method in which you process the information. It is entirely feasible, and relatively easy to show, that even with the most recent information using a wrong estimator can result in (a) biased estimates (b) unbiased but highly inefficient (c) biased and highly inefficient estimates. By inefficient, one means estimators that contain within itself the possibility of generating widely variant results as the underlying sample increases in size.

As you can imagine, getting oneself tied up in some subtleties is something that many participants on Wall Street have little time for, or worse, just find it plain useless. One of the biggest games is undoubtedly, inspired no doubt by Whack-a-Mole journalism in American media, is watching the Fed’s decisions on rate cuts. (Things are sometimes so absurd that, as Alan Greenspan writes, there are guys dedicated to watching the size of Greenspan’s briefcase!)

One of the well observed predicting markets is the Fed Fund Futures (FFF) market. The FFF is a futures contract written on the “average of the daily effective FF rate”. The FF rate is the rate that the Federal Bank of New York charges to federal fund brokers. The “effective” part in the earlier definition arrives from the fact, for any given day, different brokers who deal with differing transactional sizes, might be charged differently. So, the “effective” is the same as ‘weighted average’. A heuristic reason is that the Fed Funds market participants are likely to take into account all the factors that might affect the path of the interest rates that the fed sets. The rates implied by this market can be thought of as a first-order prediction. There are various issues – as of yesterday, the one month rates are given as below.

7-Oct 95.255
7-Nov 95.495
7-Dec 96.61
8-Jan 95.665
8-Feb 95.785
8-Mar 95.82
8-Apr 95.895
8-May 95.925
8-Jun 95.92

The implied 1-Month rates are given above.

The critical aspect is that the generic expectation is that the Fed will continue to accommodate and allow for a 4% rate over the next six months. i.e., 3/4 of a decrease in rates. Implicit in this expectation is

• Inflation, core or otherwise, will not be a problem. This, despite the clear trends to a 100$ barrel.
  
• The housing conditions will worsen -- i.e., when over 800billion USD worth mortgages are to be reset over the next two months -- expect a lot more defaults.
  
• The weakening dollar is not really something the Fed worries about. (How to reconcile rising import costs with its inflation hawkishness is a tricky question!)

I think, this will be a very difficult time for Bernanke and Co., primarily because with rising inflation (via oil, via imports, via China, via protectionist lobbies) and worsening labor markets -- the short end of the curve will have substantive volatility.

Again, my thoughts are that the demand for non-USD denominated assets will continue.