Optimistic Take on Unemployment

Here is an optimistic take on unemployment from Jeff Stibel at the Harvard Business Review.  (HT: Tyler Cowen)  He forecasts an unemployment rate of 5% by July 2015.  His reason is that small business expansion has been very laggardly in this cycle, and is just now entering the acceleration phase that we would normally see earlier.

This recession was marked by an overall decline in small businesses (typically we see small business starts accelerate), decrease in mean employment size of small businesses, and a lack of turnover for the most tenured employees. All of this led to high unemployment rates. Optimism indexes show a similar trend: bigger businesses have gained in optimism at a faster pace than their smaller counterparts, contrary to past recoveries.Contrast these trends with what has happened historically and it is clear that these anomalies are critical; any projection that relies too heavily on historical patterns is likely to be imprecise when the historical account materially differs from present events.
Moreover, the trends we’ve seen since the beginning of the recession are beginning to shift. Our data is finally showing that the smallest of businesses are growing  more optimistic about their prospects, which will eventually lead to the increased hiring that typically comes at the start of a recovery. If the trend holds, it means that the typical post-recession jobs growth will be inverted during the current economic recovery. Thus, we should begin to see an acceleration in new jobs and rapidly decreasing unemployment.

There are a large number of factors that could be in play here.  One factor could be the influence of real estate equity in small business and start up funding.  Possibly the delayed recovery of housing and of small business employment are related.

In any case, the thesis appears to be built on some of the uncontroversially peculiar trends in this cycle.  I would add that the commenters on the article have created an almost museum-quality demonstration of all the biases and "mood affiliation" positions that can create a profitable tradable position if they are held universally enough.

May 2014 Employment

It's hard to know what kind of movement we will see in the unemployment rate this month, after such a sharp decline last month from 6.7% down to 6.3%.  Unemployment insurance claims continue to signal optimism.  Here are the weekly figures in initial and continued claims:

The second graph is my comparison of continued claims to the unemployment rate.  As with last month, there are two trends working in the favor of good news.  One is that continued claims have been declining dramatically, which should coincide over time with a general decline in unemployment.  The other trend is the convergence we should expect to see between the actual unemployment rate and the unemployment rate we have historically seen relative to the insured unemployment rate.

Of course, there is a lot of noise, month to month, with all of these indicators, but the trends look positive.  I believe that the divergence from historical unemployment levels was related to the generous level of Emergency Unemployment Insurance (EUI), which ended at the end of 2013.

The new level of continued claims would correspond to an unemployment rate of 6.1% without any additional convergence to the historical unemployment level. (edit: this estimated May level is the last point on the blue series in the graph.)  If the end of EUI is creating a new trend with a more steeply declining unemployment rate, then this month could see another gap down, with an expected range of, say, 5.9% to 6.3%.  The decline in continued claims may be a result of generally faster unemployment exit rates across unemployment durations, related to the end of EUI.  If that is the case, then we should expect there to be a convergence to historical trends along with the decline in UI, since there should also be an increase in unemployment exit rates for unemployment of durations slightly over 26 weeks, in addition to the decline in unemployed workers who are still eligible for regular UI.  So far, however, there appears to be a population of very long term unemployed whose exit rates remain very slow and, lacking a change in their own trend of employment behavior, will slow some of the convergence to historical levels until well into 2015.

If I am wrong about this new trend, and last month was mostly a noise event, we might be looking at an expected range of more like 6.1% to 6.5% in May.

Another Look at Minimum Wage Labor Force

The other day, I looked at this relationship.

In that post I looked at the annual change in the number of minimum wage workers compared to the annual change in the relative minimum wage:

I also looked at the historical levels of minimum wage employment to historical relative minimum wage levels, compared to the EPI estimates:

In this post, I thought I would compare the scatterplot of annual changes to the trendline that would be implied by the EPI estimate:

Also, I have extended the linear trend of the EPI estimate to the minimum wage levels that were in place back to 1979 (about $11.90 in current dollars, as a proportion of average wages):

It simply seems implausible to me that this relationship has shifted to this degree.  Assuming no job losses and a linear behavior (which is probably conservative compared to EPI's accelerating curvilinear trend), at a minimum wage of $11.90, the EPI trend would imply that 20% of the labor force is currently working at that wage level or less.

Just to clarify, the notion that MW causes some job loss only proposes that some portion of this huge difference is due to job loss.

The notion that MW causes no job loss would depend on this entire shift being due to an exogenous shift in wage distribution.  It would have to depend on an average increase in minimum wage workers as the MW increased that is incrementally steeper than it has ever been in any single annual data point in the last 35 years, including the most recent MW increases.

Creative Destruction, thankfully, applies to human capital

Tyler Cowen linked to two recent stories:

National Nurses United has an ad warning about the dangers of replacing nurses with data.

And here is a story of the battle between farmers and "big data".

The nurse ad is pretty funny, but probably not in the way the union intended.  It reminds me of these wonderful old ads from musician's unions in the 1930's campaigning against recorded music (ht: KPC).

These conflicts are an example of how difficult progress can be when it causes obsolescence of something we consider dear or sacred.  Is there a more quintessential image of human character than a farmer's intimate relationship with the sight, smell, and feel of his dirt?  Monsanto has technology that makes this knowledge increasingly obsolete.  Likewise, AI diagnosticians are becoming more dependable than doctors and nurses.

Our reaction to this is much different than our reaction to the obsolescence of technology.  Or, even think of cars replacing horses.  Stable keepers' unions probably had ads against those infernal new machines, but with distance, we recognize these advances as boons to human opportunity.  (Auto repair diagnosis has also become highly automated.  I think it is an interesting exercise to compare this to medical automation.  There was relatively little despair over this development in auto repair.  How does this relate to our feelings toward this service, and toward auto mechanics versus doctors and nurses?)

It seems compassionate and pro-human - pro-community - to support the skilled farmers and professionals in these matters.  The sentiments being prodded in the nurse and musician ads are universally sensitive.  And, come on, are you really going to side with Monsanto over farmers?  Is it outrageous and mean spirited of me to feel disappointment that our educational institutions are shielding teachers from these same pressures?

But, the irony is that these easy sentimental biases are wholly anti-progress.  If we apply them in these contexts, we are allowing our subconscious knack for social signaling to overbear progress in the very society we are signaling to.  We have a bias for supporting obsolete human capital because it shows our loyalty and support for people doing good in our communities.  It shows our sophistication - that we can recognize talent and skill.

But, what are the consequences?  In the end, the most powerful force for improvement of the most poor, the most egalitarian tool in the history of humanity, is automation.  Canned music means that paupers can now enjoy the same entertainment previously only available to the elite.  AI medical tools will mean that the triage office in rural Appalachia or the Kenyan savannah will offer the same quality of diagnosis as the Mayo Clinic.  Farming automation means that basic foodstuffs are abundant for many poor people across the globe.  Imagine the possibilities for marginalized kids if teaching were largely automated.  Not only would the poorest kids have access to the same sources of knowledge as middle class kids, but resources would be freed to provide them with even more services.

A central dilemma of political advocacy:  Being truly pro-progress sometimes necessarily means taking postures that make you look like an ass.  ("Don't you see?  We're all better off because the skills you built over a lifetime in a widely honored craft are no longer needed!  Huzzah!")  Of course, also being human means that if you commit to this discipline, sometimes you will bravely be defending progress at your own social cost, and sometimes, you will just be being an ass.  Since these matters can never be universally determined with certainty, not looking like an ass is probably the smart choice most of the time.  Thus, I would humbly suggest that, if your economics or politics don't frequently put you in the unavoidable position of supporting positions only an ass would support, you might just be a cog in a giant collective action problem.  But, I suppose I could just be saying that because I'm an ass.

Revisiting Minimum Wage Workers as a Portion of the Labor Force

Here was my last post on this issue.  The post included this graph:

My point was that this historical relationship seemed pretty linear and stable, and for the number of workers at $10.10 or less without a binding minimum wage to be twice the number that there are with a binding minimum wage, there would have to be significant distortions in the labor force, probably including measurable disemployment.

Menzie Chinn, at www.econbrowser.com looked at the relationship here.  Using Durbin-Watson and other tests, he found that the correlation could be spurious because of a lack of stationarity.  There is a trend break at Minimum Wage levels below about 27% of the Average Wage (MW/AW), which I think is because the legal minimum begins to fall below the natural minimum wage in that range.  But, cutting the data off before 2001 doesn't seem to help much on the Durbin-Watson test.

So, clearly, there is a positive relationship between these ratios, but the coefficient (shown as .30 in the graph) may be suspect.  Because of Dr. Chinn's input, I also looked again at the EPI data that I had originally referenced, and realized that there was updated data as well as a couple of additional data points that I could add to the graph.

I looked at the same data from my original post, but as annual changes instead of as levels over time.  Residual autocorrelation and stationarity aren't issues in this data if we use yearly changes instead of levels.  Here are graphs of the annual changes over time and scatter plots of the annual change in the ratios.  The first scatter plot is of the entire period.  The second scatter plot is of the period 1981-2001.  This cuts out the period after 2001 during which the legal MW was too low to exert typical influence and 1980, which is an outlier.  Culling the data down to this period pulls the slope coefficient up to .378.

The final, large graph below compares historical MW employment with (1) the estimated level of MW employment using the coefficient from the yearly changes, (2) the estimated total number of MW workers plus workers not employed due to the MW (based on my estimate of a loss of 0.26% in total employment for each 1% increase in the MW/AW ratio), and (3) three EPI estimates of the number of workers at or below their proposed MW levels in 2014, 2015, and 2016.

EPI assumes no job loss (and, in fact, some job gains), so I would interpret the difference between the EPI estimates of MW workers and my estimate of the number of workers as a combination of:
(1) Job losers captured by my estimate.
(2) Job losers not captured by my estimate.
(3) Workers currently under the EPI proposed MW levels who would have new wage levels slightly above the MW after implementation.
(4) Job gains incorrectly assumed by EPI.

This is not an exhaustive list, but these seem like an obvious starting point.  Of course, there is a possibility that I have over-estimated the job losers, and there are other explanations for the gap.

If I understand him correctly, Dr. Chinn believes that there has been a shift in the distribution of low wage workers, so that, even though the coefficient of the slope of this relationship appears to have been below 0.5 in the past, it is currently much higher.  In other words, an increasing MW level will sweep up many more workers than it had in the past.  So, he sees the relationship implied from the EPI estimates of an increase of about 1% in the MW workers/Total Labor Force ratio as a reasonable possibility of the number of workers who would be working at a minimum wage for each 1% rise in the ratio of MW/AW.

It seems possible that this thesis could be tested now, if there is a set of data somewhere that compares the distribution of wages today with the distribution of wages in about 1989.  The minimum wage was in the same ballpark then as it is today, as a percentage of the average wage, so if there had been an exogenous shift in wage distribution, a comparison of those two sets would be informative.

But, what I think might be the most interesting aspect of this is how our priors feed into our interpretations of events in complex ways that prevent the data itself from creating an agreed upon measure.

To me, this graph is predictable.  I would expect MW legislation to create disemployment.  So, if we are measuring the number of workers earning less than 35% of the average wage, I would expect to see many more of them when the MW/AW ratio is only 25% than when the MW/AW ratio is 35%.  So, the EPI estimates seem fairly predictable to me, and the question comes down to how much will employment at the new MW level decrease as we raise the MW to that level - a question which this basic analysis might begin to crawl toward.

To someone who doesn't think that MW legislation creates disemployment, the number of workers earning 35% or less of the average wage should be relatively unchanged in any context where the MW/AW ratio is at or below 35%.  So, a large increase in low wage workers that just happened to coincide with a decreasing MW/AW level would appear to be an exogenous change to the labor market.  Since the decreasing MW level wouldn't seem like an explanation for increasing low wage employment, this increase in low wage employment would be bad news.  It would signal that wages are becoming more inequitable, divided between upper and lower classes.  It would signal an economy only creating low-wage, low-quality working opportunities.  These exogenous changes in the labor market would mean that many more workers would be affected by an increase in the minimum wage, and since the minimum wage would, on net, be beneficial to low wage workers, this would be a compassionate policy to implement, as a response to the shifting distribution of wages.

This seems like an issue that could finally be settled empirically, but previous federal increases in the minimum wage have, unfortunately, coincided with apparently exogenous labor crises.  This has happened with such regularity that we can't rule out the fact that Congress' motivation to increase the minimum wage is somehow correlated with some third variable that correlates both with Congress' motivation for raising MW and with labor crises.  After 60 years of this pattern, it seems unlikely to change, whether the minimum wage is the cause of job losses or not.  Of course, if I thought MW hikes were defensible, I would still recommend them as a policy prescription.  I would feel a duty to support positive policies, and Congress' knack for bad timing would be a problem for someone else to solve separately.

Bonds and Real Estate as Giffen Goods

Chart 1

My last post discussed trends in Commercial and Industrial Loans as a proportion of total bank credit (chart 1).  One obvious issue in that graph is the tremendous drop in C&I Loans over time.

Interestingly, the level of C&I Loans as a proportion of GDP is pretty level over many decades (chart 2).

Chart 2

So, the change isn't so much a product of decreasing C&I Loans as it is of Increasing Bank Credit in general.  Chart 3 shows securities in bank credit (treasuries and federal agency bonds) as a proportion of GDP (inverted), compared to inflation rates.  These proportions seem to move with inflation and nominal rates.  As rates decrease, securities in bank credit increase.



Chart 3

Here is an old article, by Frank Steindl, discussing how cash and bonds could interact as Giffen goods.  Alternatively, Scott Sumner frequently discusses how the opportunity cost of holding cash is higher when rates are high, so as rates go up, central banks can actually reduce their asset bases, counterintuitively.  I don't know if this is precisely the description of a Giffen good, but it does mean that the more money a central bank produces, the less of it the market will demand.  Recently, there has been mention of treasuries as Giffen goods, with regard to default risk.  Here is an Economist article that suggests the flight from risk is so strong that high public debt and sovereign default risk can actually increase demand for U.S. Treasuries.  Treasuries would be a Giffen good.



Chart 4

I believe all of these explanations of Treasury bonds as Giffen goods have some merit.  But, looking at C&I Loans got me thinking about bonds as a Giffen good from a slightly different perspective.  Chart 4 shows the relative change in the level of C&I Loans, real estate loans, securities in bank credit, and currency in circulation, over time, as proportions of GDP.  (Real estate loans are slightly complicated by a long term positive trend.)  Currency, securities, and real estate all show an inverse relationship to inflation & nominal rates.

Currency can be explained by Scott Sumner's point, that the market is more indifferent about holding cash when rates are low.

Chart 5

But, I think what real estate and bank securities have in common is that they are low risk long term cash flow instruments.  Their nominal rate levels are relatively low because of low credit risk, but they do have duration risk.  The longer the duration of a bond, the more vulnerable it is to changes in interest rates.  Prices and yields are inversely proportional, which means that as yields get lower, the price becomes more sensitive to yield changes (chart 5).  In other words, as rates decrease, bonds get riskier.  But, since real estate and government bonds are the least risky parts of bank balance sheets, banks might react to this higher risk by accumulating more of these assets.  When the price of these low risk bonds goes up, their risk goes up, and when their risk goes up, banks want more low-risk assets.  We can intuit how the hierarchy of risk in a bank's or a household's balance sheet would begin with low risk assets and add higher risk assets as conditions allow.  These assets aren't exactly what we would call an inferior good, yet their place in balance sheet construction would be parallel.

I have discussed how the Price to Rent ratio for homes should increase as real interest rates decrease.  This can happen through an increase in price or a decrease in rents.  In practice, it appears to have come entirely from increases in real estate prices.  Could it be because low risk long term securities are Giffen goods?  As their values increase, the economy's propensity to hold them also increases, whether in terms of ownership of properties or bank ownership of securities.


PS.  Here is a chart from this Economist article.  At that site the chart is interactive.  Note that house prices across the Anglosphere have followed similar trajectories for the last 40 years, until 2008.  Since then, the US is the outlier.  It is tempting to think that the US has reverted back to a normal valuation level, but I think this is a product of mental accounting biases.  If US home prices recover to pre-crisis levels, they will be catching back up to these foreign markets.

Interest Rates and Commercial & Industrial Loans

There is a remarkably regular pattern between the Fed Funds rate and Commercial & Industrial Loans as a proportion of total bank credit:

Recovery in C&I Loans has always coincided with recovery in the effective Fed Funds rate.  In fact, the Fed Funds rate tends to precede C&I Loans, slightly.  So, this recovery is unique.

Corporate spreads are still a half point higher than typical recovery lows, and banks don't seem to be excessively profitable.  There are plenty of reasons why rates would still be low.  And, the natural short term rate was probably significantly below the zero lower bound, so there was no way to measure a recovery in short term rates.  And, the banks were so hobbled, this might be a recovery that is unusually supply based, whereas previous recoveries were generally demand based.

But, this does make me wonder about the shape of interest rate movements to come.  I wonder if demand for C&I Loans will be fairly inelastic even if rates go up a couple percent.  If the limit to bank asset growth has been the product of some discrete risk management, capital, or regulatory limits instead of some continuous function of supply and demand of credit, maybe rates are well below their functional equilibrium levels, but it just hasn't made much difference in credit markets because of other factors.

Intrinsic Value of Homes & Mortgage Payments

Here is a table of intrinsic home values, based on the present value of 50 years of rent payments.  All homes are based on $12,000 in net implied rent per year.  (edit - By net rent, I mean rent minus costs of ownership, like taxes & maintenance.) I am assuming that rent inflation equals the expected inflation portion of the discount rate, so the intrinsic value is completely dependent on the real portion of the discount rate.  (edit - expected rent inflation should differ from location to location.  In locations with higher expected rent inflation, we should see higher home prices, relative to net rents.)

The total nominal rates in these tables is a combination of the real and the inflation rates, so the nominal discount rate where inflation is 3% and the real rate is 5% is the same as the discount rate where inflation is 5% and the real rate is 3% (approx. 8% in both scenarios).

Here are the monthly mortgage payments for the same home.  (I have assumed, for simplicity, that the mortgage interest rate is equal to the discount rate applied to future rent payments.)

The intrinsic value of the home is only a product of the real rate, but the mortgage payment is a product of the total nominal rate.  Since the mortgage payments happen sooner, on average, than the rent payments that create the home's intrinsic value, real rates affect the value of the home more intensively than they affect the size of the mortgage payments.  This has the odd effect of causing real rates and inflation premiums to have the comparatively opposite effect on mortgage payments.  Higher inflation causes higher mortgage payments, but higher real rates cause lower payments.

So, the most expensive home, in terms of mortgage payments, is the home that has a 10% mortgage rate that is entirely an inflation premium.  But, the home with the lowest mortgage payment is also a home with a 10% mortgage rate - the home with no inflation and 10% real rates.

This is why viewing the housing market through the lens of nominal rates is incoherent.  It seemed coherent when inflation rates were high and volatile in the 1970's & 1980's, and inflation was the most influential element.  Then, other factors like cyclical and demographic demand factors would have been noticeable, and since inflation was very high in the 1970's when real rates were very low, the mitigating effect of those high mortgage payments on demand masked the valuation effects of real rates.

But, the taming of inflation has exposed the effect of real rates.  Over the past 20 years or so, we have gone from 8% rates (4% real + 4% inflation) to 4% rates (2% real + 2% inflation).  This would lead to an intrinsic value moving from $258,000 to $377,000, with mortgage payments staying roughly the same.

Here's an example of the kinds of problems that crop up when we set public policies based on imperfect models (and they are all imperfect).  If the Fed managed to push inflation expectations up to 3%, which would probably be beneficial in the current low rate context, the positive effect this would have on markets in general and home markets specifically would probably move home prices up.  (I believe they are below intrinsic value now, due to the damaged credit market.)  In addition, the higher inflation premium would cause the average mortgage payment to go up another 12%.  If that happened, the standard "home affordability" indexes that compare mortgage payments to household incomes would trigger red flags, everyone would start yelling "bubble" and "housing inflation", and the Fed will be obliged to sucker punch us again.

Since low real rates are probably going to be around for another cycle or two, we will continue to have this phantom housing "inflation", along with high nominal levels of capital, high nominal levels of household debt, and low nominal rates.  All of these artifacts of low real rates are false signals of loose monetary policy and over-expansion, and are important reasons why I expect the Fed to continue to be erroneously hawkish.  Fed members even refer to their recent policy stance as loose or accommodative.

Home Price Forecasts

I have been forecasting a continuing recovery in home prices, arising out of my point of view that home prices in the 2000's weren't actually out of line with other assets, even though, at the time, I considered them to be crazy.

A Digression

I live in a neighborhood with many young families, and we would laugh back then about how none of us would have been able to afford the homes that we had all purchased a few years before.  That seemed like an obvious sign at the time that the homes were overpriced.  Now, I believe that it was perfectly reasonable for our homes to be too expensive for us to buy.  Long term real risk-free interest rates were about 2% at the time.  Baby boomers and investors who needed long-term fixed income should have owned our homes, and we should have been renting the homes from them.

This whole issue is similar to the difference between owning a AAA-rated bond and buying a bond-holding mutual fund.  The bond fund is marked to market each day, so the volatility of the present value of the investment is made very clear.  Individual bonds are sometimes marketed to individual investors as a source of safe, fixed income.  But, the difference is mainly a matter of framing.  If the investor marked that bond to market each day, it would be just as volatile as the fund.  But, if the investor doesn't mark to market, then they simply see a $100 investment that pays them $4 per year every year until maturity.  The cash flows are very stable.

There is a similar situation going on in real estate, except that real estate prices aren't only a mathematical product of a stated yield, so the risk factors are stated differently.  I imagine my statement about real estate investments in the 2000's eliciting a reaction of incredulity - that even though I might argue that they could have been good investments, that theory clearly didn't pan out.  But, that theory only didn't pan out for homeowners who were marking to market.  Rent levels are fairly stable.  If an investor bought a home with cash in 2005 and continued renting it throughout this period, their cash flows would have been, more or less, in line with their original expectations - much like the owner of that AAA-rated bond.  And, if they had originally planned to sell that house in 2030, there is no reason to think that its eventual value will be such that their investment won't have earned some small real return over that time.  (Homes don't promise a set maturity value like bonds, and so they tend to provide higher returns to compensate for that risk.  In fact, I have been modeling homes as a low-risk bond holding, but maybe I should envision them more as a high dividend equity.)  In any case, my point is that, eventually, in hindsight, even after all that has happened, if in 2005 you had needed a long-term inflation-hedged asset, a house will probably have suited that purpose just fine.


Home Price Forecasts

I have been looking at price to rent ratios from the various home price indexes, and it is interesting how much variation there is.  Here is a graph of some price indexes, indexed to the top of the market at the end of 2005.  In addition to those shown here, there is the CoreLogic series, which I believe shows similar behavior to the Case-Shiller series shown here.  These series seem like the outliers, although they do seem, anecdotally, like they reflected existing home prices in major cities.  To the extent that Case-Shiller is accurate, then homes seem undervalued by 40% in a functioning credit market, given expected long-term real interest rates.  This might be relevant to a new speculative position that involves straightforward exposure to real estate assets.

But, if a position is going to be established by exposure to homebuilders, then the Median Sales Price of New Houses series is probably more relevant.  This series was much less volatile than Case-Shiller during the boom, and was also slightly less volatile than the All-Transaction and Purchase Only home indexes from FHFA.

Oddly, the New Houses series has been much more positive since the crisis than the other series.  I believe that some of this difference comes from two factors:

1) All of the home-tracking indexes (Case-Shiller and the two FHFA series) are affected by short sales and foreclosure sales that tend to be priced below the normal market level.  This probably accounts for a measurable decline in stated prices throughout the crisis, currently probably amounting to less than 5% of the level that would be reported if foreclosures were not unusual.

2) The median price of new homes is not based on tracking of individual properties, so my understanding of it is that it would be affected by changing home characteristics.  I have attempted to account for that by controlling for square footage, which is tracked, along with prices, by the Census Bureau.  Below is the measure for square footage of new homes, and in the Price Index graph above, the light blue line is the relative Price to Rent level for Median Sales Prices of New Houses Sold, after adjusting for changing square footage.  Since the end of the crisis, square footage has climbed significantly.  Adjusting for this pulls the relative New Home Price To Rent measure down somewhat, but not all the way to the price measures for existing homes.

But, these adjustments put all three of the less volatile price series at around 85% of the high Price To Rent levels of the 2000's.  That leaves about a 20% gain from today's prices to reach those levels again, according to each of these indexes.

In addition, the square footage adjustment to the new home price series makes that series even less volatile in the 2000's than the unadjusted measure.  If this is the product of greater price-stickiness among new homes, relative to existing homes, then the high point of prices in the 2000's might still have been below the equilibrium prices.  That could mean that new homes have more room to rise, relative to the other indexes.  The FHFA indexes include a lot of homes in parts of the country with stagnant real estate markets.  Homebuilders would tend to be in growing markets that should reflect more of the price growth that Case-Shiller is picking up.  Therefore, it might be reasonable to expect the New Home price series to come in somewhere between the FHFA series and the Case-Shiller series.

Of course, if prices in the 2000's were too high, then my targets here are wrong, but accepting my basic premise, it seems as though homes are capable of a 15-20% gain to meet pre-crisis levels, at a minimum, and potentially up to more of a 30-40% gain, if the Case-Shiller index is a more accurate portrayal of the position one takes.  However, treating homes as inflation-hedged cash flow instruments might only justify about a 50% gain from the mid-90's to the 2000's, which can account for the FHFA series and the new homes series, but doesn't fully justify the 100% gains in the Case-Shiller index, so it might be a bridge too far to use my premise to call for a return to the Case-Shiller highs.  On the other hand, if the gains take 2 or 3 years to play out, inflation would add another 10% or so, and interest rates could rise at least another 1% while still justifying the 2000's Price to Rent ratios.

At the other extreme, new home price-to-rents, adjusted for square footage, are back at 1990's levels, so by this measure, homes could possibly call for the full 50% increase in value coming from the decreased real interest rates, but this series appears to be much less volatile than the other series, so this probably isn't a reasonable expectation.  Additionally, my Price to Rent ratio for Case-Shiller seems more volatile than the ratio shown at calculatedrisk.com, although it looks he is using the same ratio.  If my measures aren't capturing changes in rents and prices accurately, then there could be drift over time in the expected price level.

It still looks to me like more home price appreciation should be coming, but I don't know if I can say how much with any precision.

CMT 2014 Q1

Core Molding Technology has been doing well.  It has almost doubled since the beginning of 2013 and it's up about 30% since last summer.  It is more or less proceeding as I had hoped.  My thesis on this position isn't complicated.  This is just a basic small cap that has been a little undervalued.  Here are quarterly income numbers for the past few periods and a chart of the stock price over the past 3 years.



from www.money.msn.com

My main thesis here was that as CMT established more revenue outside of Navistar and PACCAR, they would increase top and bottom line numbers, but that also the added diversification would lead to some multiple expansion.  I think we have already benefitted from this factor.  In the period of time coming out of the recession, Navistar and PACCAR had accounted for as much as more than 80% of CMT sales.  By 2014 Q1, other customers accounted for nearly 1/2 of revenues.  As of 2014 Q1, Yamaha now accounts for about 10% of revenues and Volvo 25%, with more than 10% coming from other customers.  After some fits and starts, they have performed well in this area.



from www.money.msn.com

Over the past year or so, revenues from PACCAR seem to have declined.  This appears to be a transitional issue, but this is the main issue to watch, going forward.  If their PACCAR business recovers, then all the pieces seem to be in place for a valuation in the high teens to $20 range.  If not, then it may be prudent to take profits in the current range.

This is a decent position, but it isn't going to provide any sort of moonshot return.