The views expressed in this commentary are those of Hoisington Investment Management Company, the sub-advisor to the Fund, and may differ from the views of Wasatch Advisors.
In the first calendar quarter of 2014, the 30-year Treasury bond yield decreased 0.42 of a percentage point, more than reversing the 0.28 percentage point gain of the prior quarter. The Wasatch Hoisington Treasury Fund registered a return of 8.99% in the first quarter, compared to 1.84% for the Barclays Capital U.S. Aggregate Bond Index. The 30-year U.S. Treasury bond yield closed at 3.97% on December 31.
Over the past six months, yields were extremely volatile in the Treasury market, rising in the final quarter of 2013 but falling in the first quarter of 2014. This is reminder that investors in this Fund should be patient and allow our well established discipline to key on long-term economic fundamentals that we believe will eventually determine the value of the assets held in the Fund. In the face of this volatility over the last six months the Fund returned 4.72% compared to 1.70% for the Index.
For the last three years, the Fund’s average annual return was 10.44% versus 3.75% for the Index. Since inception, the Fund’s average annual total return was 7.82%, or 1.10 percentage points per annum higher than the Barclays.
Outlook for the Year
Since the last recession ended in 2009 the Federal Open Market Committee (FOMC)*** has continuously been overly optimistic regarding its expectations for economic growth in the United States. If the FOMC’s annual forecasts had been realized over the past four years, then at the end of 2013 the U.S. economy should have been approximately $1 trillion, or 6%, larger. The preponderance of research suggests that the FOMC has been incorrect in its presumption of the effectiveness of quantitative easing (QE)† on boosting economic growth since QE has had little or no positive impact. This faulty track record calls into question the latest prediction of 2.9% real gross domestic product (GDP)†† growth for 2014 and 3.4% for 2015.
A major reason for the FOMC’s overly optimistic forecast for economic growth and its incorrect view of the effectiveness of quantitative easing is reliance on the so-called “wealth effect”—this is described as a change in consumer wealth which results in a change in consumer spending. In an opinion column for The Washington Post on November 5, 2010, then chairman Ben Bernanke, wrote, “…higher stock prices will boost consumer wealth and help increase confidence, which can also spur spending. Increased spending will lead to higher incomes and profits that, in a virtuous circle, will further support economic expansion.” Former FOMC chairman Alan Greenspan in a CNBC interview on February 15, 2013 said, “The stock market is the key player in the game of economic growth.” This year, in the January 20th issue of Time Magazine, current FOMC chair, Janet Yellen, said, “And part of the [economic stimulus] comes through higher house and stock prices, which causes people with homes and stocks to spend more, which causes jobs to be created throughout the economy and income to go up throughout the economy.” (The chair of the Federal Reserve is also the chair of the FOMC.)
FOMC leaders may feel justified in taking such a position based upon the FRB/US, a large-scale econometric model. In part of this model, employed by the FOMC in their decision-making, household consumption behavior is expressed as a function of total wealth as well as other variables. The model predicts that an increase in wealth of one dollar will boost consumer spending by five to 10 cents (see pages 8-9, Housing Wealth and Consumption by Matteo Iacoviello, International Finance Discussion Papers, Number 1027, Board of Governors of the Federal Reserve System, August 2011). Even at the lower end of their range this wealth effect, if it were valid, would be a powerful factor in spurring economic growth.
After examining much of the latest scholarly research, and conducting in house research on the link between household wealth and spending, we found the wealth effect to be much weaker than the FOMC presumes. In fact, it is difficult to document any consistent impact with most of the research pointing to a spending increase of only one cent per one dollar rise in wealth at best. Some studies even indicate that the wealth effect is only an interesting theory and cannot be observed in practice.
The wealth effect has been both a justification for quantitative easing and a root cause of consistent overly optimistic growth expectations by the FOMC. The research cited below suggests that the concept of a wealth effect is in fact deeply flawed. It is unfortunate that the FOMC has relied on this flawed concept to experiment with over $3 trillion in asset purchases, and continues to use it as the basis for what we believe are overly optimistic growth expectations.
Many episodes of rising and falling financial and housing asset wealth have occurred throughout history. The question is whether these periods of wealth changes are associated in a consistent and reliable way with changes in consumer spending. We examined, separately, percent changes in real consumption expenditures per capita against percent changes in the real S&P 500 Index††† (financial wealth) and against percent changes in Robert Shiller’s real home price index (housing wealth). If economic relationships are valid they should work for all time periods, regardless of highly different idiosyncratic conditions, as opposed to an isolated subset of historical experience. As such, we conducted our analysis from 1930 through 2013—the entire time period for which all variables were available.
We made a scatter diagram of these 84 current percent changes in both real per capita consumption (the preferred measure of spending) and the real S&P 500 stock price index. Such is a very robust sample. Over our sample period, as with most extremely long periods, time will tend to link economic variables to each other; population is a key factor that can cause such an association. By expressing consumption in per capita terms, trending has been reduced, and in turn, an artificially overstated degree of correlation‡ has been avoided.
If financial wealth drives consumer spending, an unambiguous positively sloped line should be evident on this scatter diagram. The trend line through the dots is positive, but only barely so. Many of the observations were negatively correlated. The goodness of fit (coefficient of determination) of 0.27 is statistically significant; however, the slope of the line is minimally positive. This means that an approximate one-dollar increase in wealth will boost real per capita personal expenditures by less than one cent, far less than even the lower band of the effect in the Fed’s model.
Theoretically, lagged changes are preferred because when current or coincidental changes in economic variables are correlated the coefficients may be biased due to some other factor not covered by the empirical estimation. Also lags give households time to adjust to their change in wealth. As such, we correlated the current percent change in real per capita personal consumption against current changes as well as one- and two-year lagged changes (expressed as a three-year moving average) in the S&P 500. The lags did not improve the goodness of fit as the coefficient of determination fell to 0.21. An increased dollar of wealth, however, still resulted in a one cent increase in consumption. We then correlated current percent change in real per capita personal consumption with only lagged changes in the real S&P 500 for the two prior years (expressed as a two-year moving average), and the relationship completely fell apart as the goodness of fit fell to a statistically insignificant 0.06.
We made a second scatter diagram, relating current percent changes in real home prices to current percent changes in real per capita consumer spending. Once again, the trend line does have a small positive slope, but there are many negatively correlated observations.
As with the analysis on financial wealth, when current changes in consumption were correlated against the lagged changes in home prices (both the three-year moving average and the two-year moving average), the goodness of fit deteriorated significantly and was not statistically significant in either case.
Correlations, or the lack thereof, indicated by scatter diagrams do not prove causation. Nevertheless, economic theory offers an explanation for the poor correlation. If a person has an appreciated asset and wishes to increase spending, one option is to sell the asset, capture the gain and buy something else. However, the funds to make the new purchase come from the buyer of the asset. Thus, when a financial asset is sold, the money balance increases for the seller but falls for the buyer. A person with an appreciated asset could choose to borrow against that asset. Since new debt is current spending in lieu of lower future spending, the debt option may only provide a temporary boost to economic activity. To avoid an accentuated business cycle, debt must generate an income stream to repay principal and interest. Otherwise any increase in debt to convert wealth gains into consumer spending may merely add to cyclical volatility without producing any lasting benefit.
Scholarly research has debated the impact of financial and housing wealth on consumer spending as well. The academic research on financial wealth is relatively consistent; it has very little impact on consumption. In Financial Wealth Effect: Evidence from Threshold Estimation (Applied Economic Letters, 2011), Sherif Khalifa, Ousmane Seck and Elwin Tobing found “a threshold income level of almost $130,000, below which the financial wealth effect is insignificant, and above which the effect is 0.004.” This means a one-dollar rise in wealth would, in time, boost consumption by less than one-half of a penny. Similarly, in Wealth Effects Revisited 1975 - 2012, Karl E. Case, John M. Quigley and Robert J. Shiller (Cowles Foundation Discussion Paper Number 1884, December 2012) write, “The numerical results vary somewhat with different econometric specifications, and so any numerical conclusion must be tentative. We find at best weak evidence of a link between stock market wealth and consumption.” This team looked at quarterly observations during the 17-year period, 1982 through 1999 and the 37-year period, 1975 through the spring quarter of 2012.
The research on housing wealth is more divided. In the same paper referenced above, Karl E. Case, John M. Quigley and Robert J. Shiller write, “In contrast, we do find strong evidence that variations in housing market wealth have important effects upon consumption.” These findings differ from the findings of various other economists. In The (Mythical?) Housing Wealth Effect (NBER‡‡ Working Paper Number 15075, June 2009), Charles W. Calomiris, Stanley D. Longhofer and William Miles write, “Models used to guide policy, as well as some empirical studies, suggest that the effect of housing wealth on consumption is large and greater than the wealth effect on consumption from stock holdings. Recent theoretical work, in contrast, argues that changes in housing wealth are offset by changes in housing consumption, meaning that unexpected shocks in housing wealth should have little effect on non-housing consumption.”
Furthermore, R. Glenn Hubbard and Anthony Patrick O’Brien (Macroeconomics, Fourth edition, 2013, page 381) provide a highly cogent summary of the aforementioned research by Charles W. Calomiris, Stanley D. Longhofer and William Miles. They argue that consumers “own houses primarily so they can consume the housing services a home provides. Only consumers who intend to sell their current house and buy a smaller one—for example, ‘empty nesters’ whose children have left home—will benefit from an increase in housing prices. But taking the population as a whole, the number of empty nesters may be smaller than the number of first time home buyers plus the number of homeowners who want to buy larger houses. These two groups are hurt by rising home prices.”
Amir Sufi, Professor of Finance at the University of Chicago, also indicates that the effect of housing wealth is much smaller than assumed in the policy models and earlier empirical research. Dr. Sufi calculates that an increase of one dollar of housing wealth may yield as little as one cent of extra spending (Will Housing Save the U.S. Economy?, April 2013, Chicago Booth Economic Outlook event). This is in line with a 2013 study by Sherif Khalifa, Ousmane Seck and Elwin Tobing (Housing Wealth Effect: Evidence from Threshold Estimation, The Journal of Housing Economics). These economists found that a threshold income level of $74,046 had a wealth coefficient that rounded to one cent. Income levels between $74,046 and $501,000 had a two-cent coefficient, and incomes above $501,000 had a statistically insignificant coefficient.
In total, the majority of the research is seemingly unequivocal in its conclusion. The wealth effect (financial and housing) is barely operative. As such, it is interesting to note its actual impact in 2013.
If the wealth effect was as powerful as the FOMC believes, consumer spending should have turned in a stellar performance last year. In 2013 equities and housing posted strong gains. On a yearly average basis, the real S&P 500 stock market index increase was 17.7%, and the real S&P/Case-Shiller U.S. National Home Price Index‡‡‡ increase was 9.1%. The combined gain of these wealth proxies was 26.8%, the eighth largest in the 84 years of data. The real per capita personal consumption expenditures (PCE)§ gain of just 1.2% ranked 58th of 84. The difference between the two was the fifth largest in the 84 cases. Such a huge discrepancy in relative performance in 2013, occurring as it did in the fourth year of an economic expansion, raises serious doubts about the efficacy of the wealth effect.
In econometrics, theoretical propositions must be empirically verifiable. Researchers using numerous statistical procedures examining various sample periods should be able to identify at least some consistent patterns. This is not the case with the wealth effect. Regardless, whether examining a simple scatter diagram or something far more sophisticated, the wealth effect is a weak and inconsistent relationship. The powerful wealth coefficients imbedded in the FRB/US model have not been supported by independent research. To quote Chris Low, Chief Economist of FTN (FTN Financial, Economic Weekly, March 21, 2014), “There may not be a wealth effect at all. If there is a wealth effect, it is very difficult to pin down …” Since the FOMC began quantitative easing in 2009, there has been an increase of over $3 trillion in assets on the FOMC’s balance sheet. This may have boosted wealth, but the U.S. economy received no meaningful benefit. Furthermore, the FOMC has no idea what the ultimate outcome of such an increase or a return to a “normal” balance sheet will be. Given all of this, we do not see any evidence for economic growth as robust as the FOMC predicts.
Without a wealth effect, the stock market is not the “key player” in the economy and no “virtuous circle” runs through the stock market. We reiterate our view that nominal GDP will rise just 3% this year, down from 3.4% in 2013. Such an environment is conducive to lower inflation and lower long-term Treasury bond yields and would provide a favorable backdrop for the securities held by the U.S. Treasury Fund.
The inflation rate should continue to move irregularly lower in 2014. M2§§ growth in the latest 12 months was 5.8%, but velocity§§§ should decline by at least 3% and limit nominal GDP to 3%. Such weak top line growth will further diminish inflationary pressures as well as gains in real economic activity. Due to poor growing conditions, the USDA projects food prices may rise 4% this year, compared with only a 1% increase in 2013. Also energy prices have risen sharply thus far in 2014. These price increases will tend to force funds away from discretionary spending. The latest yearly increase in the core personal consumption expenditures deflator§ was one of the lowest for the entire series. Such inflation dynamics suggest that the 30-year bond yield should move lower this year, providing the potential to reward patient investors in long-term Treasury securities.
Thank you for the opportunity to manage your assets.
**The Barclays Capital U.S. Aggregate Bond Index covers the U.S. investment grade fixed rate bond market, including government and corporate securities, agency mortgage pass-through securities, and asset-backed securities. To be included in the index the security must meet the following criteria: must have at least one year to final maturity, regardless of call features; must have at least $100 million par amount outstanding; must be rated investment grade or better by Moody’s Investors Service, Standard & Poor’s, or Fitch Investor’s Service; must be fixed rate, although it can carry a coupon that steps up or changes to a predetermined schedule; must be dollar-denominated and must be nonconvertible. All corporate and asset-backed securities must be registered with the SEC; and must be publicly issued. You cannot invest directly in this or any index.
***The Federal Open Market Committee (FOMC), a component of the Federal Reserve System, is charged under United States law with overseeing the nation’s open market operations. Open market operations are the means of implementing monetary policy by which a central bank controls the short term interest rate and the supply of base money in an economy, and thus indirectly the total money supply.
†Quantitative easing, also known as Large Scale Asset Purchases (LSAP), is a government monetary policy used to increase the money supply by buying government securities or other securities from the market. Quantitative easing increases the money supply by flooding financial institutions with capital in an effort to promote increased lending and liquidity.
††Gross domestic product (GDP) is a basic measure of a country’s economic performance and is the market value of all final goods and services made within the borders of a country in a year. Debt-to-GDP ratio is a measure of a country’s federal debt in relation to its gross domestic product (GDP). The higher the debt-to-GDP ratio, the less likely the country will be to pay back its debt, and the higher its risk of default.
†††The S&P 500 Index includes 500 of the United States’ largest stocks from a broad variety of industries. The Index is unmanaged but is a commonly used measure of common stock total return performance. You cannot invest in this or any index.
‡Correlation, in the financial world, is a statistical measure of how asset classes, securities, markets, or countries move in relation to each other.
‡‡The National Bureau of Economic Research (NBER) is a research organization dedicated to promoting a greater understanding of how the economy works.
‡‡‡The S&P/Case-Shiller U.S. National Home Price Index measures the change in value of the U.S. residential housing market.
§The Personal Consumption Expenditure (PCE) price index, also referred to as the PCE deflator, is a United States-wide indicator of the average increase in prices for all domestic personal consumption using a variety of data including U.S. Consumer Price Index and Producer Price Index prices. It is derived from personal consumption expenditures, the largest component of Gross Domestic Product in the National Income and Product Accounts of the Bureau of Economic Analysis (BEA). The less volatile measure of the PCE price index is the core PCE price index, which excludes the more volatile and seasonal food and energy prices.
§§M2 money supply consists of currency and checking accounts, consumer-type time and savings accounts and equivalent near monies, while M3 money supply consists of M2 plus business-type time deposits and less liquid near monies. Both M2 and M3 exclude monies and near monies owned by the Treasury, depository institutions and foreign banks and official institutions and IRA and Keogh balances owned by consumers.
§§§The velocity of money (V) is defined as the rate at which money circulates, changes hands or turns over in an economy.