Monday, December 18, 2017

Festivus 2017 Airing of Grievances -- I Gotta a Lot of Problems with You, Taylor Rule

December 19, 2017

Festivus 2017 Airing of Grievances: I Gotta a Lot of Problems with You, Taylor Rule

December 23rd is almost upon us. You know what that means. It’s time for me to work up my annual airing of grievances for Festivus 2017. Although I have myriad political-economic grievances for 2017, I am going to concentrate on only one in this annual Festivus epistle – the Taylor Rule. For decades, there has been a debate as to whether central bank monetary policies should be guided by some clearly-defined rule or should central banks be free to operate with discretion, i.e., by the seat of their collective pants. I come down on the side of a rule vs. discretion. But not on the side of the rule most often mentioned, the Taylor Rule.

In 1993, John Taylor, a Stanford University economics professor, published a research paper in which he purported to describe how the Federal Reserve had conducted monetary policy in terms of its movement of the federal funds interest rate from 1987 through 1992. Essentially what Taylor did was estimate a Fed reaction function to consumer goods/service price inflation above or below a perceived Fed inflation target and to real GDP growth above or below a perceived Fed real GDP target. In his 1993 research paper, Taylor suggested that his description of past Fed monetary policy decisions in terms of movement of the federal funds rate could be useful as a guideline as to how the Fed should operate in the future. Although Taylor did not suggest in his 1993 research paper that the Fed should adhere rigidly to his estimated reaction function, subsequently he has implicitly criticized Fed policy for not hueing to his rule (see “A Monetary Policy for the Future”, April 16, 2015)

In its basic form, the Taylor reaction function is:

i = r*+ p + 0.5 (p-p*) + 0.5 (y as a % of y*)
where:
i = nominal fed funds rate
r = real equilibrium federal funds rate (usually 2%)
p = actual inflation rate (yr/yr % chg)
p*= target inflation rate (usually 2%)
y = actual real output
y* = potential real output

So, this formula states that for every 1% rise in inflation above its target, the Fed would raise the federal funds rate by 0.5% and similarly for every 1% increase in the output gap (actual real GDP as a percent of potential real GDP, the Fed would raise the federal funds rate by 0.5%. If actual inflation rate were equal to the Fed’s target inflation rate and if actual real GDP were equal to potential real GDP (i.e., the output gap were zero) then the nominal, or observed, federal funds rate would equal the unobservable real equilibrium federal funds rate, assumed by Taylor to be 2%, plus the inflation rate.

My grievances with the Taylor Rule arise out of the old saw, it’s not what you don’t know that will hurt you, but what you think you know but don’t. There are two elements in the Taylor Rule that are assumed to be known but are not, in fact known. The first of these elements is “r”, the equilibrium real federal funds rate. Just as the price of wheat varies over time because of changes in the supply and demand for wheat, so does the real equilibrium federal funds rate vary over time. Changes in fiscal policy, changes in business “animal spirits”, changes in the age distribution of the population, to name just a few factors, can change the equilibrium level of the real federal funds rate. If the actual equilibrium real federal funds rate has risen to 3% from the assumed level of 2% in the Taylor Rule, then the Fed would persistently be keeping the nominal federal funds rate too low for an extended period of time, which would result in persistently accelerating inflation rate. This was why Milton Friedman, may he rest in peace, argued against the Fed using an interest rate as its policy instrument. No one knows what is the equilibrium level of the nominal interest rate, much less the real interest rate, which would also require knowledge of what inflation expectations are.  In some instances, a 3% federal funds rate might represent an accommodative monetary policy. In other instances it might represent a restrictive monetary policy. If the Fed persistently keeps the level of the federal funds rate low compared to its equilibrium level, an inflationary spiral will result. If the Fed persistently keeps the federal funds rate high compared to its equilibrium, a deflationary spiral will result.

The second unknown element in the Taylor Rule is the level of potential real GDP. Potential real GDP is a function of the size of the potential labor force, the productivity of that potential labor as well as the productivity of other production factors and the rate of technological advances. The easiest of these variables to estimate with a high degree of accuracy is the potential labor force. Demography actually is a science.

Alright, even if we did know with a high degree of certainty what was the equilibrium level of the real federal funds rate and the level of potential real GDP, how do we know that 0.5 is the correct value of the reaction coefficients to the inflation and output “gaps”? Why should the coefficients be of the same value for each gap? Is the lag between a change in the nominal federal funds rate and the inflation rate the same as it is for real GDP?

Lastly, even if we did know with a high degree of certainty what was the equilibrium level of the real federal funds rate, the level of potential real GDP and the correct reaction coefficients of the “gaps”, there are time lags with respect to the availability of inflation and real GDP data. Currently, the Commerce Department releases the Personal Consumption Expenditures (PCE) chain price index monthly with about a one-month lag. For example, the November 2017 PCE price index will be released on December 22, 2017. And of course, it is subject to revisions.  Perhaps the Fed could use the consumer price index that is updated daily from MIT’s The Billion Prices Project. The Commerce Department’s first estimate of Q3:2017 GDP was released on October 27, 2017, the second estimate on November 29, and its third estimate on December 21. Then in 2018, 2017 GDP data will be revised still more. Talk about navigating in the fog without a GPS!

Now, let’s look at how the Taylor Rule would have guided the level of the federal funds rate vs. the actual level of the funds rate and comparing that with reported nominal GDP growth with implicit Taylor Rule “targeted” nominal GDP growth. The blue line plotted in Chart 1 is the four-quarter moving average of percentage-point differences between the prescribed Taylor Rule level of the federal funds rate (calculated by Haver Analytics using the PCE price index and the Congressional Budget Office estimate of the real GDP output gap) and the actual level of the federal funds rate. Implicit in the Taylor Rule is that nominal GDP growth is equal to the growth in potential real GDP plus 2% inflation. The red bars in Chart 1 are percentage point differences between year-over-year percent changes in reported nominal GDP and the implicit Taylor Rule “targeted” nominal GDP. The GDP data and the inflation data incorporate the latest revisions, which, of course would not have been available to the Fed in real time. The data start in Q1:1987, when Taylor started estimating his reaction function, and end in Q3:2017.




Chart 1

From Q1:1987 through Q3:1992, the Taylor Rule fed funds rate was below the actual fed funds rate (i.e., the blue line in Chart 1 is below zero). Yet, over most of this period nominal GDP growth was above the implicit Taylor Rule targeted nominal GDP growth (i.e., the red bars are predominantly above zero).  This means that the Taylor Rule would have performed worse than the actual discretionary Fed policy in terms of achieving the Taylor Rule targeted nominal GDP growth. The Taylor Rule’s finest hour, so to speak, was from Q4:2002 through Q4:2006 when the Taylor Rule fed funds rate was above the actual fed funds rate and nominal GDP growth was above Taylor Rule targeted nominal GDP growth. Yes, the Taylor Rule was superior to Greenspan’s discretion – a pretty low bar in my opinion. All of the economic masochists out there would have loved it if Taylor had “ruled” during the Great Recession. During most of the last recession, the Taylor Rule fed funds rate was above the actual fed funds rate. Had the Fed followed the Taylor Rule then, the Great Recession might have turned into the second Great Depression. From Q3:2010 through Q3:2017, the Taylor Rule fed funds rate has been above the actual fed funds rate. All else the same, then, this current economic recovery/expansion would have been even more anemic than it has been if the Taylor Rule had been followed. Call me mean-spirited and self-centered, but I was disappointed when John Taylor was not nominated for Fed chairman by President Trump. I wanted to see how much damage the Taylor Rule would inflict on the U.S. economy.

At the outset of the commentary, I said that I was in favor of the Fed monetary policy being guided by a rule rather than by discretion – just not the Taylor Rule. The rule I would prefer is what I’ll call the modified Milton Friedman monetary quantity rule. Friedman advocated that the Fed target a steady rate of growth in some definition of the money supply. Friedman was against discretion when it came to conducting monetary policy because he recognized that there is a lot we really don’t know but think we know when it comes to the macro behavior of the economy. You can conceive of a Friedmanesque monetary quantity rule as kind of Hippocratic Oath for central bankers – first, do no harm. Friedman did not expect his rule to enable monetary policy to prevent the occurrence of business cycles. Rather, he believed that his rule could reduce the amplitudes of business cycles. As important, Friedman realized that if his monetary-quantity growth target were too high or too low, it would not result in inflationary or deflationary spirals. In other words, inflation might rise if the target were set too high, but it would stabilize at some higher level. In contrast, if an interest rate target were set too low, there was no mechanism to keep the rate of inflation from continuing to rise except an increase in the interest rate target to some unknown higher level.

Okay, let’s get to the modified Friedman monetary quantity rule. I know that by now you have guessed it involves the Fed targeting a steady rate of growth in thin-air credit, thin-air credit being the sum of the credit created by depository institutions (commercial banks, S&Ls and credit unions) plus Fed-created cash reserves of these depository institutions and currency in circulation, or the monetary base. Plotted in Chart 2 are the quarterly observations of the year-over-year percent changes in nominal GDP along with the quarterly observations of the year-over-year percent changes in the sum of depository institution credit plus the monetary base (i.e., thin-air credit).
Chart 2

The two series appear to move in close tandem. When thin-air credit growth rises, so does nominal GDP growth and vice versa. One glaring exception to this “rule” occurs in 2008, when thin-air credit growth went up but nominal GDP contracted. During this period of financial crisis, households, nonfinancial institutions as well as financial institutions dramatically increased their demands for liquidity. The Fed extended massive amounts of credit to financial institutions to satisfy their increased demand for liquidity. Businesses tapped their lines of credit at financial institutions to enhance their liquidity positions, not to purchase new equipment or build inventories of goods. Cross -correlation tests demonstrate that growth in thin-air credit tends to affect growth in nominal GDP, not the other way around. When the subperiod from Q1:2008 through Q4:2009 is omitted, the contemporaneous correlation coefficient between the two series from Q1:1953 through Q3:2017 is 0.61. When thin-air credit growth is lagged by one quarter to test whether thin-air credit growth last quarter affects nominal GDP growth this current quarter, the correlation coefficient rises to 0.63.
However, when nominal GDP growth is lagged by one quarter to test whether nominal GDP growth last quarter affects thin-air credit growth this current quarter, the correlation coefficient falls to 0.56. Oh, and by the way, the Fed publishes weekly the level of “narrow” thin-air credit – commercial bank credit, the bulk of depository institution credit, and the monetary base.

What might a modified Friedman monetary quantity growth rule look like? Both the median and average year-over-year percent change in quarterly observations of real GDP was 3.1% from Q1:1953 through Q3:2017. Let’s round it off to 3%. I don’t quite know why 2% is a magic number for an annualized inflation target. Why not zero or even minus 2%? Whatever the argument, let’s accept a 2% inflation target. That gives us a 5% annualized nominal GDP growth target to shoot for. I ran an ordinary least-squares regression with the year-over-year percent change in nominal GDP as the dependent variable, year-over-year growth in thin-air credit lagged one quarter as the explanatory variable along with a constant term. Based on the results of this regression, in order to achieve 5% annualized growth in nominal GDP, thin-air credit would have to grow at an annualized rate of 4.6%. (There is evidence of a lot of serial correlation in nominal GDP growth. That is, this quarter’s growth in nominal GDP is highly correlated with the previous quarter’s growth. The estimate of target thin-air growth was made without correcting for the serial correlation. When I did correct for it, the coefficient on thin-air credit growth decreased, but remained statistically significant with a 99% probability.) As an aside, in Q3:2017, thin-air credit was up 4.0% vs. Q3:2016.

So, the Fed has a read on the growth in narrow thin-air credit on a weekly basis. If narrow thin-air credit is growing above its target growth rate, the Fed would drain a sufficient amount of reserves from the financial system so as to get thin-air credit growth back to target. If narrow thin-air credit were growing below target, the Fed would add a sufficient amount of reserves to get thin-air credit growth back to target. The guys and gals in the Chicago interest rate futures pits would love this because short-maturity interest rates would be much more variable, similar to the price of wheat.

Now that I have aired my 2017 grievances, it is time to gather around the aluminum Festivus pole (aluminum is best, according to Frank Costanza, because of its high strength-to-weight ratio) and join me in singing the only Festivus carol I know:





A Festivus Carol
(Lyrics by Katy Kasriel to the melody of O’ Tannenbaum)

O’ Festivus, O’ Festivus,
This one’s for all the rest of us.
The worst of us, the best of us,
The shabby and well-dressed of us.
We gather ‘round the ‘luminum pole,
Air grievances that bare the soul.
No slights too small to be expressed,
It’s good to get things off our chests.
It’s time now for the wrestling tests,
Feel free to pin both kin and guests,
Festivus, O’ Festivus,
The holiday for the rest of us.
Paul L. Kasriel
Founder, Econtrarian LLC
Senior Economic and Investment Advisor
1-920-818-0236
“For most of human history, it made good adaptive sense to be fearful and emphasize the negative; any mistake could be fatal”, Joost Swarte

∆ + 6 = A Good Life


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Saturday, December 9, 2017

Don't Expect an Investment Boom if the Corporate Tax Rate Is Cut

December 11, 2017
Don’t Expect an Investment Boom if the Corporate Tax Rate Is Cut

It appears as though the rate on U.S. federal corporate profits is going to be reduced. Although U.S. corporations may be considered “people” in terms of the First Amendment, they are not “people” when it comes to paying taxes. Corporations are de facto tax collectors, not tax payers. Real people ultimately pay the taxes in one way or another on the profits that corporations earn. So, why don’t we relieve corporations of their tax-collecting duties and tax their shareholders directly on the accrued profits of corporations in which they own shares as Laurence Kotlikoff, Boston U. econ professor and 2016 write-in presidential candidate, has suggested? If this were done, the tax on dividends and, thus, the double taxation of corporate profits would be eliminated. Alas, this kind of tax reform is not in the cards, but a cut in the corporate profits tax would be a step in the right direction.

One of the arguments being made in favor of the cut in the corporate profits tax rate is that it would unleash a torrent of investment on the part of corporations. In turn, this increase in business investment would enhance the potential real growth in the economy and would increase the capital-to-labor ratio. An increase in the capital-to-labor ratio would raise the productivity of labor, which eventually would lead to an increase in real wages.

Whoa, Nellie! There are some ugly facts that counter this beautiful hypothesis.  For starters, profits from domestic corporate operations after federal tax as a percent of GDP are relatively high in an historic context, as shown in Chart 1. From 1955 through 2016, the high in nominal after-tax corporate profits from domestic operations as a percent of nominal GDP occurred in 2012 at 7.6%. In 2016, after-tax profits relative to GDP stood at 6.9% vs. a median value of 5.5%. Despite corporate after-tax profits being relatively high, real business fixed investment (structures, equipment and intellectual property products) as a percent of real after-tax corporate profits is not exceptionally high, as shown in Chart 2. In 2016, real business fixed investment was 191.5% of real after-tax corporate profits. Although this was above the median of 174.5%, it was well below the record high of 323.7% of 2000 or the near-record high of 300.7% in 2008. So, despite U.S. corporate after-tax profits currently being high absolutely and relatively, real business fixed investment currently is not particularly high compared to real after-tax profits. Although a decrease in the corporate profits tax rate would, all else the same, increase after-tax corporate profits, it is not clear from the data presented in Charts 1 and 2 that an increase in after-tax corporate profits would result in a big increase in business fixed-investment spending.
  



Chart 1
Chart 2
It’s just a hunch on my part, but I suspect one of the most important factors driving business capital spending is actual evidence of demand for the products produced by businesses. The world might beat a path to my doorstep if I build a better mousetrap, but I’m taking a big risk if I scale up my better-mousetrap production capability by purchasing a lot of new equipment and the world, in fact, does not beat a path to my doorstep. This hunch on my part might explain why there is a high positive correlation, 0.70, between prior changes in real consumer spending and current changes in real business fixed-investment spending (see Chart 3).
Chart 3

Before betting that a cut in the corporate profits tax will result in an investment boom, it might be instructive to see what nonfinancial corporations have been using their after-tax profits for in recent decades. The data in Chart 4 show that starting in the mid 1980s, nonfinancial corporations stepped up their dividend payments and equity retirement (share buybacks) relative to their after tax profits. How could the sum of dividend payments and equity retirement be more than 100% of after-tax corporate profits in some cases? Corporate borrowing.
  


Chart 4
In sum, by all means, cut the tax rate on corporate profits. But don’t expect the tax-rate cut to unleash a torrent of business investment spending. Currently, corporate after-tax profits already are high relative to GDP, yet business fixed-investment spending relative to after-tax profits is not exceptionally high. Moreover, in recent decades, corporations have shown a preference for using after-tax profits to pay out dividends and buy back shares rather than make capital investments.

Paul L. Kasriel
Founder, Econtrarian LLC
Senior Economic and Investment Advisor
1-920-818-0236
“For most of human history, it made good adaptive sense to be fearful and emphasize the negative; any mistake could be fatal”, Joost Swarte

∆ + 6 = A Good Life



Tuesday, November 28, 2017

The S&P 500 Is Not Expensive According to the Kasriel Valuation Model

November 29, 2017

The S&P 500 Is Not Expensive According to the Kasriel Valuation Model

In each of the first three quarters of 2017, there have been double-digit year-over-year percentage increases in the quarterly average level of the S&P 500 stock-price index – 19.3% in Q1, 15.5% in Q2 and 14.2% in Q3. Although there were year-over-year contractions in the S&P 500 index of 5.6% in Q1:2016 and 1.3% in Q2:2016, there has not been a year-over-year contraction of 10% or more since Q3:2009. With the S&P 500 stock-price index hitting record highs in recent weeks and no contraction of 10% or more in it in eight years, one could reasonably wonder if large cap stocks have gotten expensive. In terms of the Kasriel stock market valuation model, the S&P 500 stock price index was not expensive in an historical context as of this past third quarter.

The essence of the Kasriel stock market valuation model is a calculated theoretical market capitalization of a group of stocks compared with the actual market capitalization. If the actual market cap is larger than the theoretical market cap, then the stock market group is overvalued. If the actual market cap is less than the theoretical market cap, then the stock market group is undervalued.

The theoretical market cap is calculated by discounting corporate earnings by a corporate bond yield. Thus, the theoretical market cap varies positively with the level of earnings and negatively with the level of bond yields. For corporate earnings, I have used quarterly observations of aggregate S&P 500 reported earnings, starting in 1964:Q1. (I would have preferred to use operating earnings, earnings adjusted for one-time special events. But in my database, operating earnings data do not begin until 1988:Q1.) I smooth the earnings series with some highfalutin econometric technique called the Hodrick-Prescott filter. The Hodrick-Prescott filter is supposed to remove the cyclical component of a series. Think of it as less arbitrary technique than a moving average, such as Shiller’s use of a 10-year moving average. Why 10 years? Why not 9 or 11 years? So, my theoretical S&P 500 market cap is Hodrick-Prescott filtered quarterly aggregate S&P earnings discounted by the quarterly average level of the corporate BAA bond yield. After calculating the theoretical market cap of the S&P 500 stocks, I calculate the percentage that the actual S&P market cap is over or under the theoretical S&P 500 market cap.

The results of these calculations are plotted in Chart 1. According to the Kasriel model, S&P 500 stocks in the aggregate were overvalued by 4.4% in 2017:Q3. Compared to the average overvaluation of 36.1% over the entire sample period, a 4.4% overvaluation is small potatoes. The level of the corporate bond yield used to discount smoothed annualized earnings of $899.1 billion in this past third quarter was 4.35%. Given the same level of annualized earnings, a 100 basis point increase in the corporate bond yield would put third-quarter S&P 500 stocks 28.4% overvalued, still short of the sample average of 36.1% overvaluation.












Chart 1

Testing the lead/lag relationship between the Kasriel valuation model and the year-over-year percent change in the S&P 500 stock price index shows that the highest negative correlation (-.20) between the two series is obtained when the over/under valuation measure is lagged by five quarters. So, the current quarter’s over/under valuation estimate has its greatest effect on the year-over-change in the S&P 500 stock price index five quarters in the future. Let’s plot the year-over-year percent change in the quarterly average of the S&P 500 stock price index against the Kasriel model of over/under valuation estimates lagged five quarters to see how the Kasriel model comports with the behavior of stock prices. These data are plotted in Chart 2.

Given the low absolute value of the correlation coefficient between the two series, 0.20, you would be correct in assuming that the Kasriel over/under valuation model does not do a stellar job in predicting the year-over-year percent changes in the S&P 500 stock price index. (Gosh, and I thought it would be easy to accurately predict stock prices!) But the Kasriel model does catch some big moves. In terms of stock price rallies, the Kasriel model does show stocks were undervalued preceding the stock price rallies of the mid 1960s, mid 1970s, early 1980s and early 2010s. And the Kasriel model also shows that stocks were extremely overvalued preceding the stock price declines of the late 1980s, early 2000s and late 2000s. However, significant stock price rallies in the early 1970s, in the early to mid 1980s, in the early 1990s and in the late 1990s were preceded by Kasriel model overvaluations near or above the average overvaluation reading of 36.1%, which again shows that the stock market can stay overvalued longer than you can meet the margin calls on your short positions! 




Chart 2

2017:Q3 marks the 34th quarter in which the S&P 500 stock price index has gone without a quarter-to-quarter decline of 10% or more. In the past 34 quarters, the S&P 500 stock price index has increased at a compound annual rate of 14.0%. The average 34-quarter compound annual rate of change in the S&P price index has been 6.6% in the period from Q1:1964 through Q3:2017. Despite this bull-market run, S&P 500 stocks in the aggregate do not appear to be overvalued in an historical context. Hodrick-Prescott filtered S&P 500 aggregate earnings grew at a compound annual rate of 6.55% in the 34 quarters ended 2017:Q3, which is less than the average 34-quarter compound annual growth in these earning of 7.75% in the period from 1972:Q3 through 2017:Q3. So, the key driver of the theoretical S&P 500 market cap and thus undervaluation or relatively low overvaluation of the S&P 500 in the past 34 quarters has been the low level of the discount factor, the yield on corporate BAA bonds.

Given the low correlation coefficient of -0.20 between percentage changes in the S&P 500 stock price index and the Kasriel model over/under valuation estimates, there obviously are other factors that have significant effects on the behavior of S&P 500 stock prices such as expected government tax and regulatory policies, as well as geopolitical events. Thus, if the S&P 500 stock price index were to plunge 10% or more in the next four quarters or so, it would likely be the result of some factor other than stocks currently being overvalued. (Of course, by writing this, I probably have put the “kiss of death” on the U.S. stock market!)

Paul L. Kasriel
Founder, Econtrarian LLC
Senior Economic and Investment Advisor
1-920-818-0236
“For most of human history, it made good adaptive sense to be fearful and emphasize the negative; any mistake could be fatal”, Joost Swarte

∆ + 10 = A Good Life