Kenneth D. West Paper

The Equilibrium Real Funds Rate: Past, Present and
Future

James D. Hamilton
University of California at San Diego and NBER

Ethan S. Harris
Bank of America Merrill Lynch

Jan Hatzius
Goldman Sachs

Kenneth D. West
University of Wisconsin and NBER

February 2015
Revised August 2015

This paper was written for the U.S. Monetary Policy Forum, New York City, February 27, 2015. We thank Jari Stehn and David Mericle for extensive help wit h the modeling work in Section 6. We also thank Chris Mischaikow, Alex Verbny, Alex Lin and Lisa Berli n for assistance with data and charts and for helpful comments and discussions. We also benefited fro m comments on an earlier draft of this paper by Mike Feroli, Peter Hooper, Anil Kashyap, Rick Mish kin, Kim Schoenholtz, and Amir Sufi. West thanks the National Science Foundation for financial suppor t.

ABSTRACT

We examine the behavior, determinants, and implicati ons of the equilibrium level of the real federal funds rate, defined as the rate consistent wit h full employment and stable inflation in the medium term. We draw three main conclusions. First, the uncertainty around the equilibrium rate is large, and its relationship with trend GDP growth muc h more tenuous than widely believed. Our narrative and econometric analysis using cross-countr y data and going back to the 19th Century supports a wide range of plausible central estimates fo r the current level of the equilibrium rate, from a little over 0% to the pre-crisis consensus of 2%. Seco nd, despite this uncertainty, we are skeptical of the “secular stagnation” view that the equilibrium rate w ill remain near zero for many years to come. The evidence for secular stagnation before the 2008 cris is is weak, and the disappointing post-2008 recovery is better explained by protracted but ultimately tem porary headwinds from the housing supply overhang, household and bank deleveraging, and fiscal retrenchment. Once these headwinds had abated by early 2014, US growth did in fact acceler ate to a pace well above potential. Third, the uncertainty around the equilibrium rate implies that a monetary policy rule with more inertia than implied by standard versions of the Taylor rule coul d be associated with smaller deviations of output and inflation from the Fed’s objectives. Our simula tions using the Fed staff’s FRB/US model show that explicit recognition of this uncertainty results in a later but steeper normalization path for the funds rate compared with the median “dot” in the FOMC’s Summary of Economic Projections.

1. Introduction

What is the steady-state value of the real federal funds rate? Is there a new neutral, with a low equilibrium value for the foreseeable future? By the beginning of 2015, a consensus seemed to be buil ding that the answer to the second question is yes. Starting in 2012 FOMC members have been releasing their own estimates of the “longer run” nominal rate in the now somewhat infamous “dot p lot.” As Exhibit 1.1 shows, the longer run projection for PCE inflation has remained steady at 2.0%, but longer run projections for both the GDP and the nominal funds rate projections have dropped 2 5 bp. The implied equilibrium real rate has fallen from 2.0% to 1.75% and the current range among memb ers extends from 1.25 to 2.25%. Indeed, going back to January 2012, the first FOMC projections for the longer run funds rate had a median of 4.25%, suggesting an equilibrium real rate of 2.25%. Foreca sters at the CBO, OMB, Social Security Administration and other longer term official forec asts show a similar cut in the assumed equilibrium rate, typically from 2% to 1.5%.

The consensus outside official circles points to an ev en lower equilibrium rate. A hot topic of discussion in the past year or so is whether the U.S. ha s drifted into “secular stagnation,” a period of chronically low equilibrium rates due to a persisten t weak demand for capital, rising propensity to save and lower trend growth in the economy (see Summers ( 2013b,2014)). A similar view holds that there is a “new neutral” for the funds rate of close to zero in real terms (see McCulley (2003) and Clarida (2014)). The markets seem to agree. As of February 20 15, the bond market was pricing in a peak nominal funds rate of less than 2½% (see Misra (2015)).

The view that the equilibrium rate is related to tr end growth is long standing. For example, in Taylor’s (1993) seminal paper the equilibrium rate-t he real funds rate consistent with full employment and stable inflation-was assumed to be 2%. Why 2%? Bec ause it was “close to the assumed steady state growth rate of 2.2%” which, as Taylor noted at the time, was the average growth rate from 1984:1 to 1992:3. Perhaps the best known paper to formally estimate a time-varying equilibrium rate is Laubach and Williams (2003), which makes trend grow th the central determinant of the equilibrium rate.

A tight link between the equilibrium rate and grow th is common in theoretical models. The Ramsey model relates the safe real rate to a represen tative consumer’s discount factor and expected consumption growth. So, too, does the baseline New Ke ynesian model, whose generalization is central to much policy and academic work. Thus these famili ar models tie the equilibrium rate to the trend rate of growth in consumption and thus the economy. In th ose models, shifts in trend growth will shift the equilibrium rate. In more elaborate models, shifts in the level of uncertainty or other model forces can also shift the equilibrium rate. Empirical estimate s of the New Keynesian models such as Barsky et al. (2014) and Curdia et al. (2014) find considerable va riation in the natural rate of interest.

In other words, the equilibrium rate may be time var ying. Such time variation is very important for much of the discussion of current monetary policy .

In this paper, we address the question of a “new neut ral” by examining the experience from a large number of countries, though focusing on the U.S . In Section 2 we describe the data and procedures that we will use to construct the ex-ante real rates used in our analysis. These go back as far as two centuries for some countries, and also include more detailed data on the more recent experience of OECD economies. We also note the strategy we oft en use to make empirical statements about the equilibrium rate: for the most part we will look to averages or moving averages of our measures of real rates; at no point will we estimate a structural model .

Section 3 summarizes and interprets some of the exist ing theoretical and empirical work and highlights the theoretical basis for anticipating a r elation between the equilibrium real rate and the trend growth rate. In this and the next section, we look to moving averages as (noisy) measures of the equilibrium rate and the trend growth rate. Using both long time-series observations for the United States as well as the experience across OECD countries s ince 1970, we investigate the relation between safe real rates and trend output growth. We uncover some evidence that higher trend growth rates are associated with higher average real rates. However, that finding is sensitive to the particular sample of data that is used. And even for the samples with a p ositive relation, the correlation between growth and average rates is modest. We conclude that fact ors in addition to changes in the trend growth rate are central to explaining why the equilibrium real rate changes over time.

In Section 4 we provide a narrative history of deter minants of the real rate in the U.S. trying to identify the main factors that may have moved the e quilibrium rate over time. We conclude that changes over time in personal discount rates, financia l regulation, trends in inflation, bubbles and cyclical headwinds have had important effects on the real rate observed on average over any given decade. We discuss the secular stagnation hypothesis i n detail. On balance, we find it unpersuasive, arguing that it probably confuses a delayed recovery with chronically weak aggregate demand. Our analysis suggests that the current cycle could be simi lar to the last two, with a delayed “normalization” of both the economy and the funds rate. Our narrat ive approach suggests the equilibrium rate may have fallen, but probably only slightly. Presumpt ively lower trend growth implies an equilibrium rate below the 2% average that has recently prevailed, pe rhaps somewhere in the 1% to 2% range.

In Section 5 we perform some statistical analysis of t he long-run U.S. data and find, consistent with our narrative history as well as with empirical r esults found by other researchers in postwar datasets, that we can reject the hypothesis that the r eal interest rate converges over time to some fixed constant. We do find a relation that appears to be s table. The U.S. real rate is cointegrated with a measure that is similar to the median of a 30-year-av erage of real rates around the world. When the U.S. rate is below that long-run world rate (as it i s as of the beginning of 2015), we could have some confidence that the U.S. rate is going to rise, cons istent with the conclusion from our narrative analysi s in Section 4. The model forecasts the U.S. and worl d long-run real rate settling down at a value aroun d a half a percent within about three years. However, because the world rate itself is also nonstationary with no clear tendency to revert to a fixed mean, t he uncertainty associated with this forecast grows larger the farther we try to look into the future.

Indeed, the confidence interval two years ahead is wi de, from 1 to 2 percentage points wide depending how far out one forecasts. This confiden ce interval only partially overlaps with Section 4’s narrative range of 1%-2%. Both ranges include the F OMC forecast implied by the numbers in Exhibit 1.1. We do not attempt to formally reconcile our two ran ges. Rather, we conclude that the U.S. real rate wi ll rise but that it is very hard for anyone to predict what the average value might turn out to be over t he next decade.

More generally, the picture that emerges from our an alysis is that the determinants of the equilibrium rate are manifold and time varying. We are skeptical of analysis that puts growth of actual or potential output at the center of real interest r ate determination. The link with growth is weak. Historically, that link seems to have been buried by effects from factors listed above such as regulation and bubbles. We conclude from both formal and descr iptive analysis that reasonable forecasts for the equilibrium rate will come with large confidence in tervals.

We close the paper in Section 6 by considering the i mplications of uncertainty about the equilibrium rate for the conduct of monetary policy . Orphanides and Williams (2002, 2006, 2007) have noted that if the Fed does not have a good estimate o f what the equilibrium real rate should be, it may be better able to achieve its objectives by putting m ore inertia into its decisions than otherwise. We us e simulations of the FRB/US model to gauge the relevanc e of this concern in the current setting. We evaluate a range of policies using an objective func tion that has often been applied for this kind of analysis, and consider how greater uncertainty about the equilibrium rate affects policy performance. Our results suggest that relative to the “shallow glid e path” for the funds rate that has featured prominently in recent Fed communications, when there is greater uncertainty about the equilibrium rate, a policy of raising rates later but-provided th e recovery does gather pace and inflation picks up- somewhat more steeply, may deliver a higher value of the objective function.

To conclude, the evidence suggests to us that the secul ar stagnationists are overly pessimistic. We think the long-run equilibrium U.S. real interes t rate remains significantly positive, and forecasts t hat the real rate will remain stuck at or below zero for the next decade appear unwarranted. But we find little basis in the data for stating with confidence exactly what the value of the equilibrium real rate is going to be. In this respect our conclusion shares s ome common ground with the stagnationists. When the equilibrium real rate is not known, a policy of initially raising rates more slowly achieves a high er value for the objective function in our simulations compared to a policy that incorrectly assumes that the equilibrium real rate is known with certainty.


2. The real interest rate across countries and acro ss time

Our focus is on the behavior of the real interest rat e, defined as the nominal short-term policy rate minus expected inflation. The latter is of cour se not measured directly, and we follow the common approach in the literature of inferring expected in flation from the forecast of an autoregressive model f it to inflation. However, we differ from most previous studies in that we allow the coefficients of our inflation-forecasting relations to vary over time. W e will be making use of both a very long annual data set going back up to two centuries as well as a quarte rly data set available for more recent data. The countries we will be examining are listed in Exhibit 2.1. In this section we describe these data and our estimates of real interest rates.

2A. A very long-run annual data set

Our long-run analysis is based on annual data going as far back as 1800 for 17 different countries. Where available we used the discount rat e set by the central bank as of the end of each year. For the Bank of England this gives us a series going all the way back to 1801, while for the U.S. we spliced together values for commercial paper rates ov er 1857-1913, the Federal Reserve discount rate over 1914-1953, and the average fed funds rate durin g the last month of the year from 1954 to present.1 Our interest rate series for these two countries are p lotted in the top row of Exhibit 2.2 and for 15 oth er countries in the panels of Exhibit 2.3.2 The U.S. nominal rate shows a broad tendency to de cline through World War II, rise sharply until 1980, and de cline again since. The same broad trends are also seen in most other countries. However, there are als o dramatic differences across countries as well, such as the sharp spike in rates in Finland and Germany following World War I.

We also assembled estimates of the overall price level for each country. For the U.S., we felt the best measure for recent data is the GDP deflator which is available since 1929. We used an estimate of consumer prices for earlier U.S. data and all other c ountries. The annual inflation rates are plotted in the second row of Exhibit 2.2 for the U.S. and U.K. and for 15 other countries in the panels of Exhibit 2.4 . There is no clear trend in inflation for any countr y prior to World War I, suggesting that the downward trend in nominal rates prior to that should be interp reted as a downward trend in the real rate. Inflati on rose sharply in most countries after both world wars, w ith hyperinflations in Germany and Finland following World War I and Japan and Italy after Wor ld War II. But the postwar spike in inflation was in every case much bigger than the rise in nominal inter est rates.

How much of the variation in inflation would have b een reasonable to anticipate ex ante? Barsky (1987) argued that U.S. inflation was much les s predictable in the 19th century than it became later in the 20th century. Consider for example using a first-order a utoregression to predict the inflation rate in country n for year t :

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Dennis (2009, equations (6), (7), (11) and (12)) supplies the first order analogues to (3.3) when utility is (a) of the form (3.11), or (b) when habitis multiplicative rather than additive. It follows from Dennis’s expressions that neither internal nor externalhabit substantially affects the mean level of the safe rate when parameters are varied within the plausible range. Specifically, for additive habit, suchas in (3.11) above, it follows analytically from Dennis’s (11) and (12) that variation in habit has no effect on the mean safe rate. For multiplicative habit we have solved numerically for a range of plausible parameters and find habit has little effect on the mean rate. (Dennis’s expressions are log linearized around a zero growth steady state. We have derived the log linearization in the presence of nonzero growth in one case (additive external habit), and the conclusion still holds.)

Campbell and Cochrane (1999) let conditional secondmoments vary over time. They assume that the conditional variance of what they call “surplus consumption” rises as consumption Ct approaches habit Xt. They parameterize this in a way that delivers an equilibrium real rate that is indeed plausibly low on average. The model, however, implies counterfactual relations between nominal and real rates (Canzoneri et al. (2007)).

Hence our review of existing literature leads us to conclude that it is unlikely to be productive to focus on consumption when modeling the real rate, despite the strong theoretical presumption of a link between consumption growth and the real rate. The remaining parts of this section focus on GDP growth instead.

3C. Output growth and the real rate in the U.S.

There are theoretical reasons to expect a long-run relation between the real rate and GDP growth. In a model with balanced growth, consumption will, in the long run, grow at the same rate as output and potential output. Thus the combination of the intertemporal condition (3.4) and balanced growth means that over long periods of time, the average short real rate will be higher when the growth rate of output is higher and lower when output growth is lower. Perhaps there is a clear long-run relationship between output and the real rate, despite the weak evidence of such a relationship between consumption and the real rate. In this section we use our long-run U.S. dataset to investigate the correlation, over business cycles or over 10 yearaverages, between GDP growth and real rates. Our focus is on the sign of the correlation between average GDP growth and average real rates. We do not attempt to rationalize or interpret magnitudes. We generally refer to “average real rate” rather than equilibrium real rate. But of course our view is that we are taking averages over a long enough period that the average rate will closely track the equilibrium rate.

Real rate data were described in Section 2. We nowdescribe our output data. Our U.S. GDP data runs from 1869 to the present. Balke and Gordon (1989) is the source for 1869-1929, FRED the source for 1929-present. Quarterly dates of business cycle peaks are from NBER. When we analyze annual data, quarterly turning points given by NBER were assigned to calendar years using Zarnowitz (1997, pp732-33). Zarnowitz’s work precedes the 2001 and 2007 peaks so we assigned those annual dates ourselves. When, for robustness, we briefly experiment with potential output instead of GDP, the CBO is our source.

As just noted, we focus on the sign of the correlationbetween average GDP growth and average real rates. We find that this sign is sensitive to sample, changing sign when one or two data points are removed. We did not decide ex-ante which data points to remove. Rather, we inspected plots presented below and noted outliers whose removal might change the sign of the correlation. Ex-post, one might be able to present arguments for focusingon samples that yield a positive correlation, and thus are consistent with the positive relation suggestedby theory. But one who does not come to the data with a prior of such a relation could instead conclude that there is little evidence of a positiverelation.

Peak to peak results

Peak to peak results are in Exhibits 3.1-3.4. Our baseline set of data points for the peak to peak analysis are the 7 (quarterly) or 29 (annual) pairs of (GDP growth, r) averages presented in Exhibit 3.1. Here is an illustration of how we calculated peak topeak numbers. In our quarterly data, the last twopeaks are 2001:1 and 2007:4. Our 2007:4 values are 2.52 for GDP growth and 0.45 for the real interest rate. Here, 2.52 is average GDP growth over the 27 quarters from 2001:2 (that is, beginning with the quarter following the previous peak) through 2007:4,with 0.45 the corresponding value for the real rate.

Let us begin with quarterly data (Exhibit 3.2, and rows (1)-(4) in Exhibit 3.4). A glance at the scatterplot Exhibit 3.2 suggests the following. First,the correlation between average GDP growth and the average real rate is negative, at -0.40 it so happens. (See line (1), column (6) of Exhibit 3.4. That exhibit reports this and other peak-to-peak correlations that we present here in the text.) Second, the negative correlation is driven by 1981:3. If we drop that observation-which, after all, reflects a cyclelasting barely more than a year (1980:2-1981:3), andis sometimes considered part of one long downturn (e.g., Mulligan (2009) and Angry Bear (2009), and our own Exhibit 4.9 below)-the correlationacross the remaining six peak to peak averages is indeed positive, at +0.32 (line (2) of Exhibit 3.4)). If we continue to omit the 1981:3 peak, but substitute CBO potential output for GDP (line (3)) or ex-post interest rates for our real rate series (line (4)), the correlation falls to -0.01 or 0.17.

Of course, such sensitivity to sample or data may not surprising when there are only six or seven data points. But that sensitivity remains even when we turn to the much longer time series available with annual data, although the baseline correlation is now positive.

The averages computed from annual data in columns (5) and (6) in Exhibit 3.1 are plotted in Exhibit 3.3. A glance at the scatterplot in that exhibit reveals the positive correlation noted in the previous paragraph, at 0.23 it so happens (line (5) of Exhibit 3.4). That correlation stays positive, with a value of 0.30 (line (6) of Exhibit 3.4) if we drop 1981, the peak found anomalous in the analysis of quarterly data.

However, for annual data, one’s eyes are drawn not only to 1981 but also to points such as 1918, 1920, 1944 and 1948. One can guess that the correlation may be sensitive to those points. To illustrate: Let us restore 1981, but remove the postwar1920 and 1948 peaks, the correlation across the remaining 27 peak to peak averages is now negative, at -0.23 (line (7)). If we instead drop the three peaks that reflect the Great Depression or World War II, the correlation is again positive at 0.29 (line (8)).

The remaining rows of Exhibit 3.4 indicate that the annual data give results congruent with the quarterly data when the sample period is restricted (lines (9) and (10)) and that the annual results are not sensitive to the measure or timing aggregate output (Romer (1989) and year ahead data in lines (11) and (12)).

We defer interpretation of sensitivity until we havealso looked at backward moving averages of U.S. data, and cross-country results.

Ten-yearaverages

We consider 40-quarter (quarterly data) or 10-year (annual data) backwards moving averages. Ten years is an arbitrary window intended to be longenough to average out transient factors and presumably will lead to reasonable alignment between output. Using annual data, we also experimented with a 20-year window, finding results similar to those about to be presented.

Numerical values of correlations are given in column(6) of Exhibit 3.5, with scatterplots presented in Exhibits 3.6 and 3.7. In Exhibit 3.6, the fourth quarter of each year is labeled with the last two digits of the year. We see in Exhibit 3.6 that for quarterly data, the correlation between the 40-quarter averages is positive, at 0.39 it so happens (line (1) in Exhibit 3.5). This is consistent with the quarterly peak-to-peak correlation of 0.32 when 1981:3 is removed (line (2) of Exhibit 3.4)). The result is robust to use of ex-post real rates (line (3)). But, as is obvious from Exhibit 3.6, if we remove the post-2007 points, which trace a path to the southwest, the correlation becomes negative, at -0.19 (line (2)). We see in Exhibit 3.7 that for annual data, the correlation between 10-year averages is negative,at -0.25 it so happens (line (4) in Exhibit 3.5). The postwar sample yields a positive correlation (line (5)). Omitting 1930-1950, so that the Depression years fall out of the sample, turns the correlation positive (line (6)). The value of 0.31 is consistent with 0.29 figure in line (8) of peak-to-peak results in Exhibit 3.4, which also removed Depression and post-World War II years.

3D. Cross-country results

Our GDP data come from the OECD. The source data were real, quarterly and seasonally adjusted. Sample coverage is dictated by our real rate series that were described in Section 2. Our real rate series for all countries had a shorter span than our GDP data. Our longest sample runs from 1971:2-2014:2.

We compute average values of GDP growth and of the real interest rate over samples of increasing size, beginning with roughly one decade (2004:1-2014:2, to be precise) and then move the start date backwards. The sample for averaging increases to approximately two (1994:1-2014:2), then three (1984:1-2014:2), and finally four (1971:2-2014:2) decades. Some countries drop out of the sample as the start of the period for averaging moves back from 2004 to 1971.

Exhibit 3.8 presents the resulting values. Exhibit 3.9 presents scatterplots of the data in Exhibit 3.9. Note that the scale of the 2004:1-2014:2 scatterplot is a little different than that of the other three scatterplots.

As suggested by the scatterplots and confirmed by the numbers presented in the “corr” row of Exhibit 3.8, the correlation between average GDP growth and average real rates is positive in all four samples, and especially so in the 20 year sample. However, the sign of the correlation is sensitive to inclusion of one or two data points. For example, in the 1984-2014 sample, if Australia is omitted, the correlation turns negative.

3E. Summary and interpretation

Both our U.S. and our international data yield a sign for the correlation between average GDP growth and the average real interest rate that is sensitive to sample, with correlations that are numerically small in almost all samples.However, the theoretical presumption that there is a link between aggregate growth and real rates is very strong. One could make an argument to pay more attention to the samples that yield a positive correlation-for example, dropping 1980-81 from the set of full U.S. expansions or dropping 1930-1950 from the 10-year U.S. averages-and deduce that there is modest evidence of a modestly positive relationship between the two. For our purposes, we do not need to finely dice the results to lean either towards or against such an argument. Rather, we have two conclusions. First, if, indeed, we are headed for stagnation for supply side reasons (Gordon (2012, 2014)), any such slowdown should not be counted on to translate to a lower equilibrium rate over periods as short as a cycle or two or a decade. Second, the relation between average output growth and average real rates is so noisy that other factors playa large, indeed dominant, role in determination ofaverage real rates. In the next section we take a narrative approach to sorting out some of these factors.


4. A narrative interpretation of historical real rates

Much of the recent discussion of the equilibrium real rate has relied on a framework similar to the simple one sketched in equation (3.5) above inwhich the major factor responsible for shifts in the IS curve is changes in the trend growth of the economy.Although this is a very common assumption, we found at best a weak link between trend growth and the equilibrium rate.

More generally, theoretical models suggest trend growth is not the only factor that can shift the equilibrium rate. We noted above that the literature has considered varying the discount factor, the utility function and dropping the representative agent / complete markets paradigm. In connection with the last, we note that much research assumes that the interest rate that governs consumption decisions in equation (3.5) and its generalizations for other utility functions is the risk-free real rate. However, as noted for example by Wieland (2014), in an economy with financial frictions the rate at which households and firms borrow can differ substantially from the risk-free rate. The literature on the monetary transmission mechanism suggests the equilibrium real funds rate will also be sensitive to changes in the way monetary policy is transmitted through long term rates, credit availability, the exchange rate and other asset prices. The equilibrium rate will also be sensitive to sustained changes in regulatory or fiscal policy. Finally the typical models assume that changes in the trend inflation rate have no effect on the real interest rate, an assumption that again turns out to be hard to reconcile with the observed data.

In this section we provide a narrative review of the history of the U.S. real interest rate to call attention to the important role of factors like the ones referenced in the preceding paragraph in determining changes in real rates over time. Since our focus is on the equilibrium rate we look at averages over various time periods, taking into account forces that may have shifted the equilibrium rate or caused the average to deviate from equilibrium at the time. Our ultimate goal is to understand

6This is consistent with the formal econometric work of Clark and Kozicki (2005,p403), who conclude that the link between trend growth and the equilibrium real rate is “quantitatively weak.”

whether similar forces are at play today. We take a particularly close look at one of the most popular narrative interpretations of recent developments. This is the view that the US economy is suffering from “secular stagnation”-persistent weak demand and a nearzero equilibrium rate. Our tentative conclusion from this exercise is that the equilibrium rate currently is between 1 and 2%, but there is considerable uncertainty about how quickly rates willreturn to equilibrium and the degree of likely overshooting at the end of the business cycle.

In this analysis we will be referring to two different measures of the real rate. The “ex-ante real rate”” is the estimate of the ex-ante real rate developed in Section 2, which proxies inflation expectations using an autoregressive model for the GDPdeflator for data after 1930 or a CPI for data before 1930 that is estimated over rolling windows. The “static-expectations real rate” is the measure that people in the markets and the Fed look at most often, calculated as the nominal interest rate minus the change in the core PCE deflator over the previous 12 months. Exhibit 4.1 repeats Exhibit 2.7, with the static-expectations real rate added on. As the Exhibit shows, the two real rate series align very closely. Over the 1960 to 2014 period, the GDP-based ex-ante real rate and the PCE-based static-expectations real rate both average 2.01%.

4A. The real interest rate before World War II

Exhibit 4.2 reproduces our long history ex-ante realrate series for the United States from the lower left panel of Exhibit 2.2. The first thing that stands out in the real rate data is the notable downward shift in the real rate starting in the 1930s. U.S. real rates averaged 4.2% before World War Iand only 1.3% since World War II. We found a similar drop for virtually every other country we looked at.

Three factors may account for the secular decline in real rates. First, in the earliest periods the short rate may have not been truly risk free. As Reinhart and Rogoff (2009) and others have documented, the period before World War II is laden with sovereign debt defaults. Almost all the defaults occurred when countries were in an emergingstage of development. In their data set, only Australia, New Zealand, Canada, Denmark, Thailand and the U.S. never had an external debt default. In the U.S. case, however, bouts of high inflation in the American Revolution and Civil War and the exit from the gold standard in 1933 had an effect similar to default.

Second, before the Great Depression financial markets were much less regulated. Interest rates, rather than credit and capital constraints did the work of equilibrating supply and demand.

Third, and perhaps the most important explanation in the economic history literature is low life expectancy. From 1850 to 2000 the average life expectancy for a 20 year old American male rose from 58 to 76.. Shorter life expectancies in the past created two kinds of risks. First, absent a strong bequest

7 Source: http://mappinghistory.uoregon.edu/english/US/US39-01.html

motive, a short life expectancy should mean a high time value of money. You can’t take it with you. Second, shorter life expectancy increases the risk of nonpayment.

Regardless of the cause of the shift, this suggests a gooddeal of caution in trying to extrapolate from these early years to the current economy.

History lesson #1

: The equilibrium rate is sensitive to time preference and perceptions about the riskiness of government debt.

History lesson #2

: Judging the equilibrium rate using long historical averages can be misleading.

4B. Financial repression (1948-1980)

Reinhart and Sbrancia (2015) define financial repression as a regulatory effort to manage sovereign debt burdens that may include “directed lending to government by captive domestic audiences (such as pension funds), explicit or implicit caps on interest rates, regulation of cross-border capital movements, and (generally) a tighter connection between government and banks.” The period immediately following World War II was one of financial repression in many countries, including the U.S. If there are limited savings vehicles outside of regulated institutions and if those institutions are encouraged to lend to the government, this can lower the cost of funding government debt and the equilibrium rate. As noted by Reinhart and Rogoff (2009, p. 106),

During the post-World War II era, many governments repressed their financial markets, with low ceilings on deposit rates and high requirements for bank reserves, among other devices, such as directed credit and minimum requirements for holdinggovernment debt in pension and commercial bank portfolios.)

Not surprisingly, real policy rates were very low for most of this period. Before the Fed Treasury Accord of 1951, interest rates were capped at 3/8% for 90 day bills, 7/8 to 1 ¼% for 12-month certificates of indebtedness and 2 ½% for Treasury bonds (Exhibit 4.3). The caps were maintained despite wild swings in inflation to as high as 25%. In the 1930s and 1940s the Fed also frequently used changes in reserve requirements as an instrument of monetary control.

The Accord gave the Fed the freedom to raise interest rates, but a variety of interest rate caps and other restrictions continued to hold down the equilibrium rate into the 1970s. When monetary policy was loose, rates fell; but when monetary policytightened, a variety of ceilings became binding and the main restraint from monetary policy came from the quantity of credit rather than the price of credit. As Exhibit 4.4 shows, three-month T-bill rates rose above the Regulation Q deposit rate ceiling several times during this period. Indeed, many models of real activity at the time used dummy variables to capture a series of credit crunches during this period-in particular, 1966, and 1969-70. By the late

8 Clark (2005) argued that these developments account for a decline in interest rates beginning with the industrial revolution.

1970s the constraints had become less binding and interest rate ceilings were phased out from 1980 to 1986.

History lesson #3

: The equilibrium real rate is sensitive to the degree of financial constraint imposed by regulations and by the degree to which policy relies on quantity rather than price (interest rates) to manage aggregate demand.

4C. The inflation boom and bust (1965-1998)

The era of financial repression overlapped with the Great Inflation. Inflation was very low and stable in the early 1960s, but started to move higherin 1965. Exhibit 4.5 shows the history of headline and core PCE inflation. In 1966 the Fed tried to put on the brakes by hiking rates. This caused disintermediation out of the mortgage market and a collapse in the housing sector. The Fed then backed off, marking the beginning of a dramatic surge in inflation. From 1971 to 1977 the ex-ante real funds rate averaged just 0.3%, reflecting both persistently easy policy and a series of inflation surprises for investors.

From 1980 to 1998 the inflation upcycle was completely reversed. PCE inflation fell back to 1%. Starting with Volcker the Fed created persistently high rates. During this period the “bond vigilantes” extracted their revenge, demanding persistently highreal returns. Survey measures of inflation expectations also showed a persistent upward bias. Over the period the ex-ante real funds rate averaged 4.1%. With the Fed pushing inflation lower,interest rates probably were above their long-run equilibrium level during this period.

Both inflation and real interest rates have been verylow over the past two business cycles. Since 1998, year-over-year core PCE inflation has fluctuated in a narrow band of 1% to 2.4%. Consumer surveys of inflation expectations dropped to about 3%in the mid-1990s and have stayed there ever since (Exhibit 4.6). Surveys of economists, such as the Survey of Professional Forecasters have settled in right on top of the Fed’s 2% PCE inflation target (also Exhibit 4.6).

History lesson #4

: Trends up or down in inflation can influence the real interest rate for prolonged periods. Real rate averages that do not take this into account are poor proxies for the equilibrium rate.

4D. Real rates in delayed recoveries (1991-2007)

Both the 1991-2001 and 2002-2007 cycles differed significantly from past recoveries. Historically, the economy comes roaring out of a recession and the bigger the recession the faster the bounce back. Exhibit 4.7 shows a simple “spider” chartof payroll employment indexed to
the trough of the last 7 business cycles.Note the slow initial rebound in 1991, 2002 (and in the current cycle). This initially weak recovery prompted considerable speculation about permanent damage to growth and permanently lower rates. In 1991 Greenspan argued that heavy debt, bad loans, and lending caution by

9For expository purposes we have excluded the brief1980 cycle. Also note that earlier cycles look similar to the 1970s and 1980s cycles.

banks were creating “50 mile-per-hour” headwinds for the economy. But by 1993 Greenspan was changing his tune: “The 50-miles-per-hour headwinds a re probably down to 30 miles per hour.” The same thing happened in the 2001-2007 cycle: fear of terrorism, corporate governance scandals, the tech overhang and fear of war in the Middle East all app eared to weigh on growth. When the Iraq War ended without a major oil shock or terrorist event, GDP gro wth surged at a 5.8% annual rate in the second half of 2003 and by 2005 the unemployment rate had dropp ed below 5%.

These delayed recoveries had a major impact on funds rate expectations. When the Fed first started hiking rates in February 1994 the market loo ked for the funds rate to rise about 100 bp over the next 24 months; in the event, the Fed hiked the fund s rate by 300 bp in 13 months (Exhibit 4.8) The ex- ante real rate averaged 2.9% over the full business cy cle, but at 4.7% at the end of the cycle as the Fed fought inflation (Exhibit 4.9). In the next cycle, when the Fed finally started to hike in June 2004, m any analysts thought a normal hiking cycle was not possible . 11 When the Fed started to move, the markets were pricing in 170 bp in rate hikes over the next 2 4 months; in the event, the Fed hiked by 425 bp over a 24 month period. The real funds rate averaged just 0.5% over the full business cycle, but again peaked at a much higher 3.1%. The PCE-based measure yields n umbers that are about two tenths higher than these averages of the ex-ante real rate.

History lesson #5:

Persistent headwinds can create a persistently low real rate, but when headwinds abate rates have tended to rise back to t heir historic average or higher.

4E. Real rates, gluts, conundrums and shortages (20 01-2007)

While for most of this paper we have ignored the broa der global backdrop, a big story in the 2000 cycle was the unusual behavior of bond yields glo bally. From 2004 to 2006 the Fed hiked the funds rate by 425 bp and yet 10-year yields only rose about 40 bps. Greenspan (2005) called this the “bond conundrum,” pointing to an even bigger drop in yiel ds outside the US, pension demand as population ages, reserve accumulation by EM central banks, and perhaps most important, a growing pool of global savings. Bernanke (2005) described this as a “glut of g lobal savings,” noting that after a series of crises many emerging market economies were building up massi ve currency reserves. He also pointed to rising savings by aging populations in Germany, Japan and oth er developed economies and to the attractiveness of US capital markets. Caballero (2006 ) and others make a related argument that there is a “safe asset shortage” caused by a rapid growth in inco mes and savings in emerging markets and a shortage of safe local saving vehicles due to undevelop ed capital markets.

It is not entirely clear whether the “glut”, “conun drum,” or “shortage” lowers or raises the equilibrium real funds rate. All else equal, lower U S bond yields and compressed term premia stimulate the economy, forcing the Fed to hike more to achiev e the same degree of financial restraint. However, not all else is equal. For example, central bank buyi ng of US treasuries presumably put some upward

11 For example McCulley (2003) argued that the equilib rium real funds rate was close to zero. He argued t hat “overnight money, carrying zero price risk, zero cred it risk and zero liquidity risk should not yield a real after-tax return.”

pressure on the dollar, contributing to the sharp wide ning of the trade deficit. Indeed, as Exhibit 4.10 shows, from the peak of the previous business cycle (200 0:1) to the peak of the construction boom (2005:3), housing as a share of GDP rose by 2pp and ne t exports as a share of GDP fell by 2 pp. On net, the saving glut may have not changed overall financi al conditions, but instead made them imbalanced, contributing to both a surging trade deficit and a h ousing bubble. The upshot of all of this is that the glut did not prevent significant Fed rate hikes. As we n oted above, the static-expectations real rate peaked at 3.3% in 2006.

History lesson #6:

The global saving glut probably distorted overall US financial conditions, but did not have a clear impact on the equilibrium real funds rate.

4F. Secular stagnation and the equilibrium rate (19 82-? )

Our narrative approach to the history of the equilib rium rate is particularly useful in addressing a competing “narrative theory” of the last several bu siness cycles: the idea that the economy suffers from secular stagnation. The idea goes back to the 19 30s when Alvin Hansen asked whether the economy would ever be able to achieve satisfactory gr owth. He was concerned both about chronic deficient demand and a lower trend growth in the ec onomy and hence a low equilibrium real rate.

The secular stagnation hypothesis.

Krugman, Dominguez, and Rogoff (1998) revived Han sen’s concerns, suggesting that when the equilibrium real interest rate is negative, an econo my could get stuck at suboptimal growth and deflation as a result of the zero lower bound on nomi nal interest rates. Summers (2013b) expressed the hypothesis this way:

Suppose that the short-term real interest rate that wa s consistent with full employment had fallen to negative two or negative three percent in the middle of the last decade. Then … we may well need, in the years ahead, to think about h ow we manage an economy in which the zero nominal interest rate is a chronic and systemic i nhibitor of economy activity, holding our economies back below their potential.

Summers (2014) suggested that secular stagnation in the U.S. goes back to the 1990s, arguing that the strong performance in the 1990s “was associated with a substantial stock market bubble.” Again in 2007 the economy did “achieve satisfactory levels of capac ity utilization and employment”, but this was due to the housing bubble and “an unsustainable upward mov ement in the share of GDP devoted to residential investment.” He queried “in the last 15 y ears: can we identify any sustained stretch during which the economy grew satisfactorily with conditio ns that were financially sustainable?” Finally Summers extended this argument to the rest of the indu strial world, pointing to even worse performance in Japan and Europe.

12 Summers is basically restating the “serial bubbles ” view of recent business cycles popularized by Ste phen Roach and many others, See for example, http://delong.type pad.com/sdj/2005/06/stephen_roach_o.html

Krugman (2013) also argued that bubbles have been nec essary to achieve economic growth:

We now know that the economic expansion of 2003-2007 was driven by a bubble. You can say the same about the latter part of the 90s expansion; a nd you can in fact say the same about the later years of the Reagan expansion, which was drive n at that point by runaway thrift institutions and a large bubble in commercial real est ate….So how can you reconcile repeated bubbles with an economy showing no sign of inflation ary pressures? Summers’s answer is that we may be in an economy that needs bubbles just to ac hieve something near full employment – that in the absence of bubbles, the economy has a ne gative equilibrium rate of interest. And this hasn’t just been true since the 2008 financial c risis; it has arguably been true, although perhaps with increasing severity, since the 1980s.

Were near zero rates and/or asset bubbles essential to a chieving full employment in the 1982, 1990 and 2000 business cycles? Is underlying demand so weak that it is impossible to create inflation pressure even with super easy policy? A close look at t hese cycles shows little support for either of these propositions.

Unemployment, inflation, and the real interest rate over the last 3 cycles.

The US economy has not been suffering chronic under-e mployment. The economy not only reached full employment in each of the last three bu siness cycles, it actually significantly overshot full employment. This is true whether one uses typical estim ates of the NAIRU from the CBO, IMF or OECD or if one takes an agnostic approach and simply use th e historic average unemployment rate (5.8% in the post-war period). For example using CBO estimates, the US overshot the NAIRU rate by between 0.6 to 1.1 pp in each cycle and these periods of tight la bor markets lasted between 8 and 18 quarters (Exhibit 4.11). CBO estimates of the output gap show si milar results: GDP was above potential in 1988- 1989, 1997-2001 and 2005-2006. Note that this success i n achieving a full recovery is not an artifact of assuming low potential growth or a high NAIRU: during this period CBO estimates of potential growth rose and the estimated NAIRU fell. These extended peri ods where aggregate demand exceeded aggregate supply are hardly a sign of secular stagnat ion.

Exhibit 4.12 shows furthermore that each of the last t hree cycles ended with incipient inflation pressure. In the 1980s cycle, the Fed pushed inflation down to below 4%, but by 1988, it was trending up again. In the 1990s, inflation also picked up at the end of the business cycle, although core PCE inflatio n only briefly pierced 2%. Presumably, this was related to the unexpected surge in productivity during this period. On a 5-year basis, growth in nonfarm busine ss productivity peaked at 3% at the end of the 1990s expansion, up from just 2% over the previous 20 years or so. Core inflation was persistently above 2% in the second half of the 2000 expansion and headline i nflation was above 3% other than a brief interruption in 2006. This seems inconsistent with the idea that the Fed had trouble sustaining normal inflation.

Of course, the rise in inflation at the end of recen t economic expansions has been milder than in the 1960s and 1970s. However, in our view, this is not a sign that the Fed cannot create inflation; instead, it shows that they have learned when to apply the brakes, gaining credibility along the way. The 1970s experience has taught the Fed about the risks o f trying to exploit the short-run Phillips Curve and the importance of finishing the job in eradicating u nwanted inflation. A good measure of their success in restoring credibility is that both survey and market m easures of inflation expectations have become very stable. In Exhibit 4.13, we show the standard 10-year inflation breakeven, along with a measure from the Federal Reserve Bank of Cleveland that attempts to remove term and risk premia. The recent weak response of inflation to tight labor markets probably also reflects the unexpected productivity boom in the 1990s; increased global integration, making the US sensitive to global as well as domestic slack; the weakening of union power and low minimum wages; and host of other factors. In our view these conventional arguments for a flatter Phillips Curve are more compelling than the secular stagnation thesis.

History lesson #7:

During the period of alleged secular stagnation, t he unemployment rate was below its postwar average and inflation pressures e merged at the end of each cycle.

Over the 1982 to 2007 period as a whole the ex-ante real rate averaged 3.0% (and the static- expectations measure averaged 2.9%). This was above the 2.0% post-war average, but since the Fed was trying to lower inflation in the first half of this p eriod, we believe the average rate was higher than its equilibrium level during this period. The 1980s cycl e had the normal strong start and quick funds rate normalization. However, for both the 1990 and 2000 cycle, the economic recovery was initially weak and the funds rate was persistently low. As headwinds fa ded, however, eventually the funds rate surged above its long-run average. Looking at the individu al cycles, the economy reached full employment with an ex-ante real rate of 3.3, 4.0 and 0.25% respecti vely (again see Exhibit 4.9). In each cycle, the r eal rate eventually peaked well above its historic average (la st column of Exhibit 4.9).

History lesson #8:

During the first part of the period of alleged sec ular stagnation (1982-2007) the real rate averaged 3%, a percentage point highe r than its post-war average.

The role of asset bubbles in the last three recover ies

What about asset bubbles? Were they essential to achiev ing full employment and normal inflation? The evidence is mixed, but a close look a t the three cycles offers little support for the secula r stagnation thesis. As we will show, the timing of the alleged bubbles doesn’t really fit the stagnation story.

1982-1990. Asset bubbles may have had some impact on the 1982-90 e conomic recovery, with a boom in commercial real estate and related easy len ding from savings and loans. However, the economy hit full employment in 1987 and stayed there even as the tax reform in 1986 had already undercut the real estate boom and even as the stock m arket crashed in 1987. Thus, while nonresidential investment did surge in the early 1980s, it collapsed a fter tax reform in 1986. As seen in Exhibit 4.14 over the course of the recovery structures investment plunged as a share of GDP. The Savings and Loan industry followed a similar pattern. The heyday of e asy S&L lending was in the early 1980s. From 1986 t o 1989 the Federal Savings and Loan Corporation (FSLIC ) had already closed or otherwise resolved 296 institutions. Then the Resolution Trust Corporation (RT C) took over and shuttered another 747 institutions. The boom and bust in these two sectors cau sed shifts in aggregate demand, but it is hard to see their role in achieving and maintaining a low un employment rate after 1986.

History Lesson #9 : The economy reached full employment in the 1980s despite high real interest rates and retrenchment in the real estate and S&L i ndustry in the second half of the recovery.

1990-2000. The asset bubble story is even less convincing in the 19 90s recovery. The NASDAQ started to disconnect from the economy and the rest of the stock market in late 1998 and surged out of control in 1999 (Exhibit 4.15). However, before the bubble started, the unemployment rate had already dropped to 4.7% in 1997, well below both its histori c average and CBO’s ex post estimate of full employment. Hence the NASDAQ bubble may have contri buted to the subsequent overheating at the end of the economic recovery but it is putting the c art before the horse to argue that it was necessary for achieving full employment.

History Lesson #10

: The NASDAQ bubble came after the economy reached full employment and therefore was not a precondition for achieving full employment.

2000-2008. Of the three recent business cycles, the 2000 cycle provides the best support for the argument that monetary policy is only stimulative if it creates asset bubbles. Data from Core Logic shows national home prices rising very slowly in the e arly 1990s, but then accelerating to double digit rates and peaking in 2005. The Case-Shiller measure o f national home prices shows a slow acceleration in the early 1990s, and then an acceleration to dou ble digit rates, peaking in 2005. Bank of America Merrill Lynch’s model of the Case-Shiller data sugges ts home prices began to diverge from their fair value in 2001 (Exhibit 4.16). Lending standards eased during this period with a surge in exotic lending starting in the second half of 2004. Meanwhile, lever age ratios and off balance sheet asset expansion surged.

Was the recovery in the economy unusually weak given the credit bubble during this period? Would the economy have reached full employment with out the bubble? Getting a definitive answer on this is difficult, but at a minimum it requires look ing not only at the biggest tailwind in this period- the housing bubble-but also the biggest headwinds-the sharp increase in the trade deficit and the relentless rise in energy prices. Here we compare the positives and the negatives using some simple metrics. Note that for each chart we draw a vertic al line in 2005 when the unemployment rate had dropped to 5%, the CBOs estimate of NAIRU.

First, the boosts: easy credit stimulated a boom in b oth construction and consumer spending. As Exhibit 4.17 shows, residential investment has historic ally averaged 4.7% of GDP, with a typical peak of about 6%. However, in the 2000s cycle residential i nvestment rose from 4.9% at the end of the 2001 recession in 2001Q4 to 6.6% at the housing market pe ak in 2006Q1. This boom occurred despite weak

13 Summers (2014) also argues that “fiscal policy was excessively expansive” during this period. Note, how ever, that official estimates of the cyclically adjusted budget deficit show fiscal policy tightening from 200 4 to 2007. For example, OECD estimates show cyclically adjusted ne t government borrowing falling from 6.1% of potential GDP in 2004 to 4.7% in 2007. Indeed, by this metric fiscal policy tightened in the second half of each of the last three cycles with a particular big tightening in the 1992-2 000 period.

demographics: the peak in first home buying is in the 30 to 39 age range, but this group shrunk about 0.9% per year in the 2000 cycle. It therefore seems quite reasonable to attribute the gain mostly to easy credit, which would imply a boost of 1.7 percentage points directly through higher homebuilding, or 0.4 percentage point at an annual rate. However, it is worth noting that at the start of the Great Recession in 2007Q4 residential construction had already falle n back to just 4.8% of GDP.

At the same time, surging home prices boosted consumer spending through both a classic wealth effect and a liquidity channel related to th e surge in “mortgage equity withdrawal” (MEW) illustrated in Exhibit 4.18 and discussed in Feroli et al. (2012). To get a sense of the magnitude of thes e effects, we go back to the analysis in Hatzius (2006) which presented a simple model of consumer spending with separate housing wealth and MEW effects . In this analysis, the coefficient on (housing) wealth was estimated at 3.4 cents/dollar and that on ” active MEW”-cash-out refinancing proceeds and home equity borrowing-at 62 cents/dollar; “passive M EW” i.e. home equity extracted in the housing turnover process was not significantly related to co nsumer spending. Using these estimates, the increases in the housing wealth/GDP ratio and active MEW from 2001Q4 to 2006Q1 added a total of 2.3% to the level of GDP, which implies a boost to gr owth of about 0.5 percentage point at an annual rate.

Second, the drags: the increase in the trade deficit and rising energy prices were important counterweights.

Regarding trade, the trade deficit increased by 2.4% of GDP from 2001Q4 to 2006Q1, subtracting 0.5 percentage point per year from growt h. In our view, much of this increase was due to two forces: the direct impact of the housing and cred it boom on import demand and the entry of a highly mercantilist China into the global economy po st WTO accession. In our view, both need to be taken into account when evaluating how quickly the economy “should” have grown during the housing and credit bubble.

Regarding oil prices, we believe the price increase i n the 2000s mostly reflected a combination of constrained supply and surging demand from emergin g markets. Hence, from a US perspective, much of it was an exogenous supply shock. A simple app roach for estimating the size of the shock is to look at the “tax” on household incomes from energy pr ices rising faster than nonenergy prices. In Exhibit 4.19 we compare the growth in the overall PCE defla tor to the PCE excluding energy. Based on this metric, rising energy prices imposed a tax increase of about ½ percentage point of disposable income per year on the consumer between 2001Q4 and 2006Q1. Recognizing that consumption is about 70% of GDP and assuming a marginal propensity to spend of 70% , this number suggests a GDP hit of about ¼ percentage point per year over this period. After 2 006, the energy hit to GDP growth increased further as oil prices rose even faster through mid-2008.

Putting the shock variables together, we estimate tha t rising home construction and the housing wealth/MEW effect were adding just under 1 percentag e point per year to growth from 2001Q4 to 2006Q1. Against this, the increase in the trade defi cit and the surge in energy prices were subtracting about ¾ percentage point. In other words, the negat ive forces probably canceled out most of the stimulative impact of the housing bubble. By the pea k of the business cycle, the winds had already shifted as construction and home prices started to slide and the energy tax surged. Nonetheless, the unemployment rate fell below NAIRU, bottoming at 4. 4%.

Would the economy have achieved and sustained full em ployment in the absence of all of these shocks, positive and negative? It is impossible to do f ull justice to this period in a short narrative, but if we are right that a sizable portion of the obvious b ubble-induced boosts were canceled out by equally obvious drags, the fact that the unemployment rate fe ll below NAIRU despite a 3% real funds rate suggests that the answer may well be yes.

History lesson #11

: Taking into account the offsetting headwind from the rising trade deficit and higher oil prices as well as the tailwinds from the housing bubble, it is not clear whether the economy suffered secular stagnation in the 2000s.

4G. Outlook for the current cycle

With this historical narrative as our guide, what are the implications for the equilibrium rate today?

First, the obvious: using historical averages from so me periods of history as a gauge of equilibrium today can be quite misleading. The whol e period before the Fed-Treasury Accord seems of very limited value. Real rates before WW I were chr onically higher, presumably reflecting higher risk premiums and discount rates. Real rates fluctuated wild ly during the Depression and war years. And the period of interest rate pegging is clearly not releva nt today. On a similar vein, clearly average real r ates during a period when inflation is trending in one di rection are a poor measure of the equilibrium rate.

Second, changes in the monetary transmission mechani sm due to regulatory and developments are clearly very important to determining equilibri um. Before financial deregulation, credit crunches d id most of the “dirty work” in fighting overheating in the economy. This tended to cap the upside for real interest rates, lowering the average rate for the per iod. Today the long period of deregulation is over and regulatory limits are growing.

Rather than dig into the deep weeds here, we would make the following observations. First, capital markets remain much less regulated than in the 1960s and 1970s. Today there is a big, active corporate debt market, global capital markets are wi de open and banks play a much smaller role in the financial system. Bank capital and liquidity require ments have gone up; but restrictions on banks do not approach historic levels. Two areas may face chronica lly tight credit: residential mortgage lending and small business lending. But even here the constraint i s tighter credit standards, not dramatic disintermediation episodes. Recall that even in the heavily regulated 1960s real rates averaged well above zero. For example, from 1960 to 1965, a perio d of stable 1% inflation, the real rate also average d about 1% (recall Exhibit 4. 1) for both ex-ante and static-expectations real rates.

Third, as in the last business cycle, global forces seem to be having a big impact on the US bond market. The current negative real interest rates are a global phenomenon. Of the countries represented in Exhibit 2.1, 17 of the 20 estimated quarterly ex- ante real rates are negative as of the end of 2014, with 15 out of 17 the comparable figures for annual data. In the past 12 months US 10-year bond yields have plunged by more than 100 bp, despite the end of QE3, stable core inflation, the end of the Fed’s balance sheet expansion and a looming rate hike cycl e. It appears that a combination of weak global growth, falling core inflation (particularly in Eur ope) and expectations of further central bank balanc e sheet expansion is putting downward pressure on global rates. In the two years ahead, we expect the combined balance sheet of the “big four” central ban ks-the Fed, ECB, BOJ and BOE-to expand their balance sheets at almost double the pace of the last ye ar. As with the previous “glut” it is hard to know whether global developments are raising or lowering the equilibrium real funds rate.

Fourth, our look back at the last two economic reco veries underscores the danger of mistaking short-run headwinds for permanent weakness. Recall th at one of the great dangers in formal models of the equilibrium rate is the “end point problem”-esti mates of time-varying parameters tend to be skewed by the most recent data. This problem is also cri tical for the narrative approach: simply put, it is a lot easier to identify the equilibrium rate after the business cycle is over than in real time. In th e last two tightening cycles, the Fed started slow, but even tually pushed real rates well above their historic averages.

Last, but not least, we are skeptical about the secu lar stagnation argument. We see two problems as it relates to the current recovery. First, it does not distinguish between a medium-term post-crisis problem and permanent stagnation. Clearly this is not a normal business cycle where a big collapse is followed by a big recovery (Exhibit 4.20) . As Reinhart and Rogoff (2014) and many others note, when there is a systemic crisis both the recessio n and the recovery are different than in a normal business cycle. Summarizing 100 such episodes, they find that GDP typically falls by 10.3% and it typical takes 8.4 years to recover to pre-crisis levels. Their “severity index”-adding the absolute value of these numbers together-averages 19.6 for all 100 cases.

Is history repeating itself? Most of these cycles preda te the modern era of automatic stabilizers and countercyclical fiscal and monetary policy. They also ignore the special status of the US as the center of capital markets. And they don’t attempt t o gauge the relative strength of the policy response to each crisis. Nonetheless, these historic averages are a good starting point for analyzing the current period. Indeed, as the last line of the table shows, t he US has done much worse than following a normal recession, but measured in comparison to previous such c ycles, the US has done quite well, with a smaller recession, a quicker recovery and a much smal ler “severity index.”

These systemic crises unleash extended periods of delever aging and balance sheet repair. How long this impairs aggregate demand presumably depends o n the speed of the healing process. This also suggests that the effectiveness of monetary policy shoul d be judged by balance sheet repair as well as the speed of growth in the economy.

15 See Harris (2014).

Judging from a variety of metrics, easy policy seems to have accelerated the healing process:

-Banks are in better shape, with more capital, a lot l ess bad debt and with the ability to withstand serious stress tests.

– The housing market has worked off most of its bad loa ns and both price action and turnover rates are back to normal.

– There has a been a full recovery of the ratio of ho usehold net worth to income, the debt-to- income ratio has tumbled, and debt service has dropped to the lowest of its 34 year history (Exhibit 4.21).

– High-yield companies have been able to refinance an d avoid defaults despite a feeble recovery.

In our view, these metrics suggest the balance sheet re pair is well advanced.

A second problem with the secular stagnation argument is that it ignores the role of fiscal policy in driving aggregate demand. This economic recovery has seen major fiscal tightening, starting at the state and local level and then shifting to the federa l level. Despite the weak economic recovery, the 5.5 pp improvement in deficit to GDP ratio from 2011 to 2014 was by far the fastest consolidation in modern US history (Exhibit 4.22). A number of recen t studies suggest that fiscal policy is particularly potent when interest rates are stuck at the zero lowe r bound.

Adding to the headwinds, this consolidation has been ac companied with a series of confidence shaking budget battles, including a “fiscal cliff” an d repeated threats of default or shutdown. The result is a series of spikes in the “policy uncertainty index” developed by Baker, Bloom and Davis (2013) (Exhibit 4.23). It is a bit odd to have a Keynesian theory of inadequate demand such as “secular stagnation” that does not include a discussion of the r ole of contractionary fiscal policy in creating tha t shortfall.

4H. Summary: the new equilibrium

In some ways the received wisdom on the economy has co me full circle: the optimistic “Great Moderation” has been replaced with its near-opposite, “Secular Stagnation.” The truth seems to be somewhere in between. Some of the moderation was earn ed at the expense of asset bubbles. Some of the stagnation is cyclical. If our narrative is corre ct, the weak economic recovery of the past five year s is not evidence of secular stagnation, but is evidence o f severe medium-term headwinds. The real test is happening as we speak: with significant healing from the 2008-9 crisis, will the recent pick-up in growth continue, creating a full recovery in the economy? And will the economy withstand higher interest rates? Judging from the previous three business cycles (and recent growth data!), we think the answer to both questions is “yes.”

16 See Christiano, Eichenbaum, and Rebelo, (2011). O ne of the ironies of the secular stagnation debate i s that some of its strongest advocates are also strong suppo rters of more simulative fiscal policy. For example , Krugman (2014) argues that the recent actions in Washington h ave been like someone hitting themselves with a base ball bat and now that the beating is over the economy is doing better.

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