Was there a Liquidity Trap during the Great Depression?
Draft version (please do not quote)
Olivier Damette1 and Antoine Parent2
Abstract : Using CSTR methodology in line with Choi and Saikkonen (2004, 2010), we
revisit the existence of a liquidity trap in the thirties. We consider the link between different
interest rates and the money supply M2 in low and high speculation regimes and find that
both variables are cointegrated in a nonlinear environment. When the stock index is below a
threshold value, the link between certain different interest rates (corporate, US bonds) and the
money supply is significantly negative. However, when the threshold surpasses an estimated
value, that is over the period 1926-1930, the interest rate turns to be insensitive to a move in
money supply. This result suggests the presence of a liquidity trap, in the sense of Keynes,
over the period 1926-1930 due to speculative behaviours.
JEL codes: N12, N22, G01, E52, E58, C22.
Keywords: liquidity trap, Crisis of 1929, monetary cliometrics, central banks reaction
function, non-linear cointegration, CSTR models.
1
Université de Lorraine, 34 cours Léopold CS 25233, 54052 Nancy Cedex, BETA-CNRS, LEF-INRA and
CAC,IXXI – “ComplexSystems Institute” – ENS Lyon; email : [email protected]
2
Sciences Po Lyon, 14 avenue Berthelot, 69365 LYON Cedex 07, France ; LAET UMR CNRS 5593 ; CACIXXI – “ComplexSystems Institute” – ENS Lyon; email: [email protected]
1
Introduction
Section 1. Approaches to Liquidity trap over the thirties: A survey
In the literature, two kinds of definition of the “liquidity trap” can be found. In The New
Palgrave Dictionary of Economics, Eggertsson (2008) recalls the standard definition: “A
liquidity trap is defined as a situation in which the short-term nominal interest rate is zero”.
But, in its original meaning (Keynes, GT, 1936), a liquidity trap situation is characterized as
an episode when the interest rate is insensitive to a move in the money supply.
Debates on the existence of a Liquidity Trap over the thirties fail to get out of these
contradictions. According to one view, the evidence of a liquidity trap is a zero or near zero
rate. Since short term rates were around zero in the 1930s, some conclude that the
USeconomy was in a liquidity trap (Hansen, 1953). The existence of a liquidity trap in the
thirties was strongly combatted by the monetarist school (Milton Friedman, Anna Schwartz,
Karl Brunner, Allan Meltzer, most notably),from a definition of the trap as a zero interest rate
applied to a wide range of interest rates: in fact, in their view, a “true” liquidity trap requires a
zero (or near zero) interest rate for the whole spectrum of interest rates(short and long-term
government and private debts). In this view, it comes that identifying aninterest rate different
from zero along the yield curve is a sufficient condition to condemn the presence of a
liquidity trap over the period.
The debate is rendered more complex because Keynes himself never said there had been a
liquidity trap during the Great Depression in the US. To make matters worse, Hansen (1953,
p. 132) introduced a confusion, qualifying this assertion by Keynes as “strange and
inconsistent”. On the contrary, Hansen contended that “In fact, the United States during the
thirties was a good example [of a liquidity trap]”. Indeed, rates on U.S. Treasury bonds fell
below one percent in May 1931 and remained below one percent for the remainder of the
decade. If Treasury bonds rates were close to the “zero bound,” was it a sufficient condition to
constitute a liquidity trap in the sense of Keynes? The answer is no, because the definition
Keynes gives of the liquidity trap is not simply equivalent to a zero or near zero interest rate.
Indeed, in a situation of liquidity trap, he argues, monetary policy would be ineffective, which
can occur at any rate, not necessarily zero.A sufficient condition for a liquidity trap to emerge
is the form of agents‟ expectations: whatever the level of the current interest rate (even it is
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more likely as rates approach zero),if speculators anticipate for any reason that the interest
rate will necessarily increase, then they will sell any bond to avoid capital losses and prefer to
hoard money than invest. This characterizes a situation of liquidity trap in Keynes definition;
this liquidity trap will persist as long as investors do not revise their expectations of rising
rates.
In his writings (GT, 1936), it is clear that Keynes stands out from the definition of the
liquidity trap as a mere zero interest rate. Does the monetarist criticism miss its target? In this
section, we first recall these controversies, before reviewing empirical tests of liquidity trap
occurrence in the thirties.
Keynes and the liquidity trap (GT, 1936)
In this section, we develop the following idea: Keynes in the GT (1936) defines the Liquidity
Trap as a pure hypothetical and theoretical case, which in turn facilitated the monetarists‟
criticism of its relevance and existence.
Keynes turns to an explanation of the liquidity trap as a specific feature, related to a „new‟
theory of the interest rate (a central point of the debate with Friedman is the evaluation of
Keynes‟s own contribution: had he really presented a new theory of the interest rate? See
below). A liquidity trap situation is characterized as an episode when the interest rate is
insensitive to a move in the money supply. His views are developed at chapters 13 and 15 of
the GT (1936). Below we present several quotes taken from these chapters.
In chapter 13 (GT, 1936), “The general theory of the rate of interest”, the interest rate is
defined as follows: “The rate of interest at any time, being the reward for parting with
liquidity, is a measure of the unwillingness of those who possess money to part with their
liquid control over it” (p. 167).
The willingness to part with the tradition of the Treatise is obvious in the following citation:
“Whilst liquidity preference due to the speculative motive corresponds to what in my Treatise
on Money I called „the state of bearishness‟, it is by no means the same thing. For
„bearishness‟ is there defined as the functional relationship, not between the rate of interest (or
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price of debts) and the quantity of money, but between the price of assets and debts, taken
together, and the quantity of money” (p. 173-174).
Subsequently, liquidity preference refers to a specific economic behavior: “The concept of
hoarding may be regarded as a first approximation to the concept of liquidity preference…
The habit of overlooking the relation of the rate of interest to hoarding may be a part of the
explanation why interest has been usually regarded as the reward of not-spending, whereas in
fact it is the reward of not hoarding” (p. 174).
From this, Keynes develops the well-known rationale of the liquidity trap: “Given that the rate
of interest is never negative, why should anyone prefer to hold his wealth in a form which
yields little or no interest to holding it in a form which yields interest? There is a necessary
condition failing which the existence of a liquidity preference for money as a means of
holding wealth could not exist… This necessary condition is the existence of uncertainty as to
the future of the rate of interest”. (p. 168).
“The individual who believes that future rates of interest will be above the rates assumed by
the market, has a reason for keeping actual liquid cash, whilst the individual who differs from
the market in the other direction will have a motive for borrowing money for short periods in
order to purchase debts of longer term. The market price will be fixed at the point at which the
sales of the „bears‟ and the purchases of the „bulls‟ are balanced” (p. 170).
“Circumstances can develop in which even a large increase in the quantity of money may
exert a comparatively small influence on the rate of interest (p. 172)”.
Ultimately, “Liquidity preference is defined as the relationship between the rate of interest
and the quantity of money (GT, p. 173)”… “For whilst an increase in the quantity of money
may be expected to reduce the rate of interest, this will not happen if the liquidity preferences
of the public are increasing more than the quantity of money (p. 173)”.
In chapter 15, “The psychological and business incentives to liquidity”, Keynes defined more
precisely the aggregate and variables to take into consideration to assess the liquidity trap:
“The speculative motive is particularly important in transmitting the effects of a change in the
quantity of money (p. 196)”… “Let the amount of cash held to satisfy the transaction and
precautionary-motives be M1 and the amount held to satisfy the speculative-motive be M2 (p.
199)”… “Finally, is the question of the relation between M2 and r (p. 201)”.
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However, at the same time, Keynes did not carry out the statistical analysis of the correlation
between these variables. The analysis of the liquidity trap is briefly concluded by evoking the
case for „absolute liquidity preference‟. The famous quote reported below will be repeatedly
cited by Friedman and other monetarist scholars in order to lessen the contribution of Keynes
to the renewal of the analysis of the interest rate:
“There is the possibility that after the rate of interest has fallen to a certain level, liquidity
preference may become virtually absolute in the sense that almost everyone prefers cash to
holding a debt which yields such a low rate of interest. In this event, the monetary authority
would have lost effective control over the rate of interest. But whilst this limiting case might
become important in the future, I know of no example of it hitherto… The most striking
examples of a complete breakdown of stability in the rate of interest have occurred in very
abnormal circumstances (p. 207)… In the US at certain dates in 1932 there was a financial
crisis or crisis of liquidation, when scarcely anyone could be induced to part with holdings of
money on any reasonable terms” (pp. 207-208)… “There is finally the difficulty in the way of
bringing the effective rate of interest below a certain figure, which may prove important in an
era of low-interest rates” (p. 208)…”Thus, the rate of interest may be incapable of being
brought, by the method of existing banking and financial organization, below a certain figure”
(p. 208)… “In a society in which for any other reason no one feels any uncertainty about the
future rates of interest, the propensity to hoard will always be zero in equilibrium… which is
much the same as the quantity theory of money in its traditional form” (pp. 208, 209).
Obviously, this passage is fodder for the Monetarists. Keynes himself lessens the importance
of the liquidity trap and recognizes the universality of the quantity theory of money. More
generally, we can say of the entire passage quoted above, that Keynes invites criticism and
that Monetarist scholars after him will drive the point home. Indeed, Keynes considered here
the „absolute trap‟ as a pure case study and following Keynes (p. 208), all monetarists will
deal with the liquidity trap as a purely theoretical case and attempt to demonstrate, within a
monetarist framework, its theoretical impossibility and logical inconsistency.
Friedman’ s appraisal of Keynes definition
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Friedman (1987), in his “Keynesian challenge to the quantity theory” (New Palgrave
Dictionary of Economics, pp. 11-14), correctly pointed out some limits to the assessment of
the Liquidity Trap by Keynes in the GT (1936):
“The depression of the 1930s produced a wave of scepticism about the relevance and validity
of the quantity theory of money… The scepticism about the quantity theory was further
heightened by the publication of JMK‟s GT (1936)…“Keynes did not deny the validity of the
quantity equation, in any of its forms – after all he had been a major contributor to the
quantity theory (Keynes, 1923). What he did was something very different. He argued that the
demand for money, which he termed the liquidity-preference function, had a special form
such that under conditions of underemployment the V and the k would be highly unstable…
Under such conditions, these equations, though entirely valid, were largely useless for policy
or prediction.” (p11).
“In his analysis of the demand for money, Keynes treated the stock of money as if it were
divided into two parts, one part M1, „held to satisfy the transactions – and precautionary
motives‟ (GT, p199). He regarded M1 as roughly constant fraction of income. He regarded
the demand for M2 as arising from „uncertainty as to the future course of the rate of interest‟
(GT, p. 168) and the amount demanded as depending on the relation between current rates of
interest and the rates of interest expected to prevail in the future… „In a given state of
expectations‟, the higher the current rate of interest, the lower would be the (real) amount of
money that people would want to hold for speculative motives for two reasons: first, the
greater would be the cost in terms of current earnings sacrificed by holding money instead of
securities, and second, the more likely it would be that interest rates would fall, and hence
bond price rise, and so the greater would be the cost in terms of capital gains sacrificed by
holding money instead of securities” (p. 12).
“Although expectations are given great prominence in developing the liquidity function
expressing the demand for M2, Keynes and his followers generally did not explicitly
introduce an expected interest rate into that function. For the most part, in practice they
treated the amount of M2 demanded as a function simply of the current interest rate, the
emphasis on expectations serving only as a reason for attributing instability to the liquidity
function. Except for somewhat different language, the analysis up to this point differs from
that of earlier quantity theorists, such as Fisher, only by a subtle analysis of the role of
expectations about future interest rates, its greater emphasis on current interest rates…” (p12).
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“Keynes special twist concerned the empirical form of the liquidity-preference function at the
low interest rates that he believed would prevail under conditions of underemployment
equilibrium. Let the interest rate fall sufficiently low, he argued, and money and bonds would
become perfect substitutes for one another; liquidity preference, as he put it, would become
absolute.” (p. 12).
“Even the slightest lowering would lead speculators with firm expectations to absorb the
additional money balances by selling any bonds demanded by the initial holders of the
additional money. The result would simply be that the community as a whole would hold the
increased quantity of money without any change in the interest rate”. (p. 12).
“Keynes regarded absolute liquidity preference as a strictly „limiting case‟ of which, „though
it might become practically important in the future‟, he knew „of no example … hitherto‟
(GT, p. 207)”. (p. 12). Obviously, on this last point no one can disagree with Friedman‟s
analysis: the weakness of Keynes‟s arguments in the GT (1936) notably derives from the fact
that he did not rely on – though he must have known them - the empirical arguments
developed amongst the Fed‟s Board which would, on an empirical basis, have strengthened
his own analysis of the phenomenon.
Given these legitimate doubts about the theoretical foundations of the liquidity trap definition
by Keynes, the monetarist tradition tried to demonstrate that this „limiting case‟ was a mere
“illusion”3. Gandolfi (1974) and Brunner and Meltzer (1968) are the emblematic examples of
this literature denying the existence and relevancy of the liquidity trap.
Monetarist refutations of a Liquidity trap over the thirties
Gandolfi (1974) in his article entitled “Stability of the demand for money during the great
contraction: 1929-1933” estimated the demand for deposit function (D) deriving from the
permanent income theory by Friedman. The following log linear relationship is tested:
3
Orphanides (2004) characterizes the liquidity trap as an “illusion”. He mentions “the popularity of the liquidity
trap tale”. Focusing on the 1937-1938 period when short term nominal interest rates remained close to zero, he
considered that the economy was not “caught in a liquidity trap”: “Close examination of the historical policy
record for the period indicates that the evidence does not support such assertions. The incomplete and erratic
recovery from the Great Depression can be traced to a failure to consistently pursue an expansionary policy,
resulting from an incorrect understanding of monetary policy in a context of very low short term nominal interest
rates”. His view echoes Meltzer (1968, 2003), see further. Meltzer (1999) reasserted the case against a full
spectrum liquidity trap in the 1930s in the United States talking of “Liquidity Claptrap”.
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Log (D/P) = logβ0 + β1 log (Yp/P) + β2 log (Cd),
Where D is per capita total bank deposits, Yp is permanent per capita nominal personal
income, 1+ Cd is the opportunity cost of holding bank deposits, and P the permanent price
level variable.
Cd is defined as the ratio of net value (in the next period) of a dollar invested in the national
asset market (Rn) to the net value (in the next period) of a dollar held as deposits (Rd):
Cd = (1 + Rn)/[(1+Rd)(1-Le)]
Le is the present value of the expected loss rate on deposits from bank failures and
suspensions. It is assumed that Le is a function of the current and lagged bank failures rates.
This formulation assumes that the opportunity cost of holding deposits is reflected in Rd.
Gandolfi (1974) defends the view that there was “no evidence of any substantial change in the
relationship between income and deposit holdings due to economic contraction”. His main
finding is that the behavior of interest rate coefficients show that they did not substantially
increase in size over the 1929-33 period “as would happen if the economy were in, or moving
toward, a liquidity trap” (p. 974). He considers that “the demand function for total deposits
was stable during the period” (p. 975)… “These results suggest that, for the period under
examination, the demand for deposits is a function of permanent income and that there is no
stable or significant positive relationship between deposit holdings and transient income” (p.
980)… “Our results show that there was no breakdown in the relationship between money and
income from 1929 to 1933 and that the contraction did not destroy the foundation (a stable
money-demand function) for an effective contracyclical monetary policy” (p. 981).
Gandolfi concludes that “in fact, we cannot help but be impressed by how little the massive
economic dislocations of the Great Depression seem to have affected the demand for money”
(p. 981).
The most thorough criticism of the relevancy of the liquidity trap in the literature is
given by Brunner and Meltzer (1968). Their article “Liquidity traps for money, bank credit
and interest rates” aims at being a theoretical and empirical refutation of the existence of
liquidity trap. First, the authors split up the trap issue into several components: traps are
supposed to affect interest rates, the bank demand for excess reserves, the public‟s demand for
money. Each of these traps is said to prevent monetary policy from affecting output,
employment and prices. Arguing that analysis has not hitherto proceeded “beyond the
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statement of an assumption that one or another elasticity is at an extreme value (zero or
infinity)” (p.2), the purpose of the authors is to “derive necessary and sufficient conditions for
most of the liquidity traps and separate them into those (1) incompatible with the theory and
that must be rejected on a theoretical point of view, (2) those that depend on the sign or size
of particular parameters” (p.3).
Solutions for interest rates, money and bank credit derive from a discussion of the elasticities
conducted within a model “expressing the quantity of money supplied (M1 = currency and
demand deposits) and the quantity of earning assets demanded by banks (Eb) as the product of
the adjusted base (Ba) and a multipliar, m1 or a. The multipliars are assumed to depend on an
index of interest rates (ie) representing yields on loans, government securities, other assets
included in the banks‟ portfolios and on the reserve requirement ratios (rd)”. (p. 4).
M1 = m1(ie,rd, …) Ba
Eb = a(ie,rd, …) Ba
This model represents the equilibrium on the bank-credit market and permits to assess
the effect of monetary policy changes on the stocks of money and bank credit.
Then, the authors consider conditions for various liquidity traps: If a critical value (0 or
infinite) is reached, the trap is defined as „absolute‟. If some elasticity is assumed to approach
but not reach a critical value, the trap is called „asymptotic‟. „Partial‟ traps occur if some
policy actions become ineffective while others remain capable of inducing changes in the
monetary variables. Various combinations are possible: “for example a complete or partial
trap may be either absolute or asymptotic”. (p12). Then, derived from their theoretical
framework the authors draw necessary and sufficient conditions for the existence of „absolute‟
liquidity traps: They find that “some sets of conditions that imply these traps conflict with the
theory (while others require empirical evidence)” (p. 13).
Their core outcome is that “The theory of the money-bank credit process precludes the
possibility of absolute traps for interest rates and money” (p. 18): “A trap for interest rates
determined on the bank-credit market cannot be absolute” (p.13)… “The denial of a trap for
interest rates on bank earning assets shows that some interest rate can always be reduced by
expansive policy action.Rejection of this trap denies that interest rates reached an absolute
floor in the thirties” ( p. 14)… “An absolute trap in the demand for money is impossible… The
implications of such a case have no economic meaning, the conditions that imply them can be
safely disregarded. It follows that there is always some policy action that reduces the interest
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rate. Since interest rates can always be reduced and the money supply can always be
increased, there cannot be an absolute liquidity trap in the demand for money” (p.
18)…“Monetary policy remains capable of creating an excess supply of money, lowering
interest rates and thereby inducing changes in output, employment and prices”. (p. 19).
Further, Brunner and Meltzer (1968) attempt to demonstrate, within a monetarist
framework, its theoretical impossibility: “A bank-credit trap is impossible within our
framework (p. 15)… A necessary and sufficient condition for a money-demand trap … is
impossible” (p17, 18)… “This evidence suggests that a money-demand trap did not occur (p.
17)”.
Studying the case for asymptotic and partial trap, Brunner and Meltzer (1968) deliver an
empirical denial of these various forms of the liquidity trap. The authors found elasticities to
be “inconsistent with available evidence” (p. 23) and hence reject the possibility of
„asymptotic or partial traps‟: “the estimated interest elasticity of the demand for money in the
thirties is smaller in absolute value than the estimate for the period 1900-1958. These
findings are incompatible with the conditions required for the various traps” (p. 24) … “The
data cast substantial doubt on the likely occurrence of those traps that require a particular
elasticity to reach or approach a critical value. The results suggest that the estimated values
and the critical values are far apart (pp. 24-25)”… “The public held a slightly smaller quantity
of money than would be expected from their behavior in other periods. This finding provides
no support for the notion of a trap in the demand for money (p. 27)”.
Three objections can be made to this refutation of both absolute and asymptotic traps.
First, the demonstration is driven within a framework that a priori excludes the trap; this leads
the authors to sustain, as illustrated above, that the reality of the trap would be anyway a
falsification of their model, which is supposed to dismiss the relevancy of liquidity trap.
Secondly, what is tested in this model is not the appropriate definition of the trap by Keynes
(GT, 1936): notably, there is a confusion between the interest elasticity of money demand
(which is high as compared with the elasticity of income to investment according to Keynes
(GT, 1936) independently from any situation of liquidity trap) and the definition of the trap by
Keynes (GT, 1936), which refers to the insensitivity of the interest rate to a move in the
money supply: indeed, the interest elasticity of money demand refers to the speculative
money demand motive, which is different from the liquidity trap itself, which refers to the
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direct link between the money stock and the interest rate. Ultimately, the authors as other
monetarists do, consider M1 as the relevant indicator for the money stock whereas Keynes
(GT, 1936) explicitly refers to M2.
Empirical tests of Liquidity Trap occurrence in the Thirties
Empirical tests of Liquidity Trap occurrence in the Thirties are very rare with the exception of
the study by Peter F. Basile, John Landon-Lane, and Hugh Rockoff (2010) entitled “Money
And Interest Rates In The United States During The Great Depression”, (WPNBER N°16204,
July). These authors reexamine the debate on the existence of a liquidity trap in the thirties by
exploring a whole battery of interest rates (yields on corporate debtfrom low risk to junk,
bank lending rates, and mortgage rates). Thus, they envision a liquidity trap on the whole
spectrum of maturities to cope with Friedman‟s argument (1971, p. 28) who regarded “the
market rates stressed by the Keynesians as only a small part of the spectrum of rates that are
relevant.” Considering that “Only when the full spectrum, including long-term private and
public securities, have reached low sticking points and have become insensitive to monetary
policy can we conclude that the economy is in a liquidity trap” (p.10). To fill a gap in the
literature, these authors “test the no-full-spectrum liquidity trap view by examining an array
of interest rates that have been bypassed in earlier discussions”. By this standard, Basile,
Landon-Lane, Rockoff, (2010, p. 10) conclude: “according to this school of thought, the U.S.
economy had not fallen into a liquidity trap in the late 1930s... In general, our results reinforce
the conclusion of Friedman and Schwartz, Brunner and Meltzer, Orphanides, Hanes and
others, including Keynes, that there was no full-spectrum liquidity trap”. They contend that
“In general our evidence adds further support to the view that many segments of the spectrum
of interest rates were flexible in the 1930s and were responsive to monetary policy” (p. 3).
We now discuss their strong conclusion that monetary policy continued to influence interest
rates throughout the thirties,which dismisses the case for a liquidity trap in the thirties.
This study is definitely a contribution to the empirical assessment of the liquidity trap over the
thirties, but some reservations apply. Mainly, the conclusion remains fragile since it relies too
exclusively on the use of a questionable variable, namely the junk bonds yield. The choice of
this indicator sounds improper since it may primarily reflect the risk premium on that kind of
asset. Two factors are supposed to compose the yield of any security in the yield-curve: the
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“pure” price of time and the “risk premium”. It remains clear that, in times of Great
Depression, when uncertainty was very high, each junk bond could obviously incorporate a
high risk premium. In these circumstances, the risk premium should explain most of the
expected return on this kind of security. The high returns on these assets had probably little to
do with monetary policy, since they likely reflected their specific risk. Well aware of this
limit, the authors admit that during the recession that ran from May 1937 to June 1938
“Investors were afraid that 1929-1933 had returned, and the perceived probability of defaults
rose. It is conceivable that non-monetary forces produced the recession, which in turn
produced the increases in Baa and junk bond yields(p. 17)”.
Another strong limit to the use of junk bond series is that financial markets at that time could
have been segmented so that long term assets (the most distant from money) could not reacted
to a move in liquidity. Higher yields on the long term assets may simply reflect this
segmentation of financial markets4. If this is the case, high yields responded to other factors
than a general change in liquidity. This makes the study of the impact of a change in monetary
policy on long-term risky assets less relevant.
For these reasons, the choice of the indicator “junk bonds”remains very questionable. Some
assertions of the authors deserve to be qualified: “In any case, M2 growth, which was
normally positive, declined and turned negative on an annual basis in November 1937. What
happened in financial markets? If one looks at the rate on Baa bonds one does see, as Meltzer
(2003, 519-20) points out, an increase in rates, although an increase of only a few basis
points. But if one looks at the yield on junk bonds, one sees a dramatic rise. The data, in
short, is consistent with the continued effectiveness of monetary policy.”(Basile, Landon-Lane
and Rockoff, 2010, p. 17). Such a statement ought to be corroborated by an accurate study of
the risk premium on that kind of asset coupled with a study of the microstructure of financial
markets. It might be that high yields reflectedfirst the high risk premium on these specific
assets, not the incidence of monetary policy. Moreover, yields on junk bonds may be biased
4
In a section entitled “A pebble in a pond or a tsunami in the sea?”, Basile, Landon-Lane and Rockoff (2010)
want to challenge the view expressed by Temin (1976, 96-103) of the “pebble in the pond” theory of the
monetary transmission mechanism, by which a change in the stock of money would have a larger impact on
short term assets (the closest to money) than on long term assets (more distant from money). These authors
imagine another adjustment path by which monetary shocks would have a greater impact on long term assets
than on short term assets. They propose to call this effect “Tsunami theory of the transmission of monetary
shocks”. We leave aside this discussion considering that the underlying theoretical framework of this suggestion
is unclear.
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by the segmentation of financial markets. Thus, it seems dubious to take junk bonds for
granted to deal with the liquidity trap issue.
Ultimately, the conclusions drawn from the VAR simulation and Impulse Response Function
analysis should be taken cautiously. Basile, Landon-Lane and Rockoff (2010) propose “to
shed some additional light on the relationship between monetary policy and bond yields by
estimating a simple vector autoregression (VAR) that includes a bond yield, an indicator of
monetary policy, and an indicator of general economic conditions (p. 18)”.They found that:
“The impact on the Aaa bond rate is very small and not statistically significant at the 5%
level. The impact on the Baa bond rate is somewhat larger, but also not statistically
significant. The impact on the junk bond rate is still larger and does reach conventional levels
of statistical significance. The results, in other words, provide additional support for the claim
advanced above that monetary stimulation remained effective. (p. 20)”. This conclusion
seems highly questionable in light of IRF tests. Indeed, the response of the junk bond yield to
a one standard deviation innovation in M2 is erratic and does not provide any clear cut
evidence of the effectiveness and direction of the monetary stimulation on the term structure
of interest rates. From this, one may find the conclusion drawn by the authors a little bit
overstated: “In the end we were persuaded that the evidence is consistent with the idea that
changes in money produced changes in corporate yields in the late 1930s, and that the effects,
especially in the junk bond market, were large enough to be taken seriously (p. 22)”.
Nevertheless, beyond this limitation on the misuse of one indicator (and the fact that the
outcomes of this study rely exclusively on it), this paper represents a real breakthrough in the
understanding and analysis of the Liquidity Tap in that it is one of the very few 5 in the
literature which assess the liquidity trap using the monetary aggregate that Keynes (GT, 1936)
claimed, namely M2 instead of M1. Indeed, this is the only monetary aggregate that enables
to address correctly the issue of the liquidity trap and to cope with Keynes rationale. Actually,
M2 is needed to measure whether the interest rate remained insensitive to a move in the
money aggregate during the Great Depression, since the speculative motive of money demand
refers to liquid assets yielding interest rate (included in M2, not in M1). As reported by the
5
See also, Diebolt, C., Parent, A., Trabelsi, J. (2012), “Revisiting the 1929 Crisis: Was the Fed Pre-Keynesian?
New Lessons From the Past”, Historical Social Research, Vol. 37, N° 2, pp. 280-97.
13
authors “M2 has the merit that it reflects changes in monetary conditions brought about by
open market purchases and sales, discount loans, and reserve ratio changes” (p. 18).
Our purpose in this article is to extend the work of Basile, Landon-Lane and Rockoff (2010)
and renew the debate over whether there was a liquidity trap during the interwar period. These
authors estimated VARs for the aftermaths of the Great Depression (1934 – 1941). We shall
study a different period (1921 – 1933), using more sophisticated econometric techniques in a
non-linear analysis. Our subject focuses on whether a liquidity trap operated before and
during the Great Depression.
Section 2. Methodology and data
Our methodology consists in estimating the relationship between different market interest
rates and the money supply M2 in order to identify the possible existence of liquidity trap
episodes during the interwar period.
2.1 Data and dynamics of the series
The period under study covers 1921:8–1933:2 (monthly data). Indeed, from the 6th to the 9th
of March 1933, a „Banking holiday‟ closed all banks. It coincided with the climax of the
depression. We end our period for studying monetary policy at this date since under the
Roosevelt Administration, a change in policy goals occurred at this time: in the months that
followed, domestic expansion and employment replaced monetary policy as guides to
economic policymaking.
We take into account severalmain variables. At first, our interest variables are the money
supply, M2 and a smoothed and filtered money supply M2l and different interest rates:
commercial paper, treasury notes, call loans rates, US government bonds and corporate bond
rates. We also use the Dow Jones index and a proxy of the Dow Jones volatility to test the
nonlinearity of the interest rate/M2 link in relation with speculative behaviors. Some control
variables (not used in this draft version of the paper) will also be used to check the robustness
of the canonical relationship: the nominal industrial production index, IPPG (Index of
Production of Producers‟ Goods, NBER Series) considered as a proxy for economic activity,
the consumer price index, CPI (NBER Series) and deposits in suspended banks that is used by
Bernanke (1983) as a measure of bank failures.
14
Figures 1 to 4 show the different dynamics of these series. Since unit root dynamics are
expected regarding these figures, we perform several unit root tests to investigate the
stationarity of the variables. The table 1 shows that the interest rates and M2 money supply
are non-stationary. In the rest of the paper, we investigate the existence of a cointegration
relationship between these variables in a nonlinear framework.
FIGURE 1: Dynamics of the market interest rates
10
8
6
4
2
0
21
22
23
24
25
26
27
28
29
30
31
32
Short Term Interest Rate Three-Six Month Treasury Notes and Cert
Commercial Paper Rates New York
Average Rate on Stock Exchange Call Loans NY
FIGURE 2: Dynamics of the money supply
15
64
60
56
52
48
44
40
22
23
24
25
26
27
M2
28
29
30
31
32
33
M2LISSE
FIGURE 3: Dynamics of the Down Jones Index
400
360
320
280
240
200
160
120
80
40
21
22
23
24
25
26
27
28
29
30
31
32
Dow Jones Industrial Average (DJIA)
Industrial Stock price Index (Dow Jones)
FIGURE 4: Dynamics of the long interest rate
16
6.0
5.5
5.0
4.5
4.0
3.5
3.0
22
23
24
25
26
27
28
29
30
31
32
33
Long Term Interest Rate U.S. Government Bonds
Corporate Bonds
TABLE 1
UNIT ROOT TESTS CONCERNING THE DISCOUNT RATE AND ALL THE EXPLANATORY VARIABLES
Test
Variables
Lags k
Stat
Commercial paper
1
-1.829
Call loans
0
-1.680
Treasury
0
-1.469
1
-3.387
Corporate
3
-3.777
CPI
1
-2.665
IPPG
3
-1.239
Suspended Deposits
1
-4.428
M2
3
-1.13
Us government
Bonds
ADF
Tabulated value (10%)
-2.577
17
Commercial Paper
1
-0.210
Call loans
0
-1.180
Treasury
0
0.252
1
-0.294
Corporate
3
-0.060
CPI
1
-1.334
IPPG
3
-1.123
Suspended Deposits
1
-4.299
M2
3
-0.925
US government
Bonds
DF-GLS
-1.615
-3.146
Commercial Paper
1
(1928:09**)
Call loans
-
-
Treasury
-
-3.070
Us government
Bonds
1
(1932:03*
,1928:12**)
Lee and Strazicich
-3.915
Corporate
5
-3.21 (*)
-4.17 to -4.21 (**)
(1928:09**)
CPI
4
IPPG
3
-1.799
(1931:09**)
-2.156
(1929:10*)
-4.486
Suspended Deposits
4
(1930:11*)
18
-3.037
M2
3
(1928:09*,**)
NOTES: The comma separating the significance levels of the Lee and Strazicich test with one
break indicates the significant break dates: * denotes a model with a constant break, and **
denotes a model with an intercept and a trend break.
2.2 The CSTR methodology
2.2.1 Testing for non-linearity
There is a recent body of literature dealing with non-linear econometric models. One major
direction focused on modeling and testing non-linear adjustments in deviations from linear
long run equilibrium: see Balke and Fomby (1997), Hansen and Seo (2002). In this kind of
approach, the equilibrium relationship itself may be non-linear. In other words, equilibrium
among our interest rate variables depends on the state system as represented by one or several
transition variables.
We test the possibility that the relationship linking interest rate and money supply M2 (both
variables being I(1)) undergoes regime shifts. Indeed, if the assumption of linearity is invalid,
a re-examination of this relationship is needed. To this aim, the Choi and Saikkonen (2004)
smooth transition cointegrating regression model is used (CSTR). The major interest of this
approach is to identify the transition or threshold variable to capture the non-linearity of the
long run relationship between interest rates and M2 by explicitly considering the I(1)
processes of these variables. The general methodology consists in identifying a transition
value for an explanatory variable (exogeneous to the model or lagged endogeneous) to deal
with the dependence of the parameters to the dynamics of the relationship. Consequently, the
long-run equilibrium relationship might change smoothly depending on the transition (or
threshold) variable that is dependent on where the covariates x t are located relative to the
threshold parameter c.
We consider two possible transition variables:
1. Dow Jones Index. The Dow Jones index is a good proxy to capture speculation behaviors
that are expected to generate nonlinearity in the interest rate/M2 relationship.
2. The Volatility of the Dow Jones Index.
19
Following the approach recently developed by Choi and Saikkonnen (2004), we test linearity
against non-linearity of the STR form. The non-linear model is given by6:
K
Interest t     x t   x t g ( s t ,  , c ) 

j K
 j  xt  j  u t
'
(1)
t  K  1, ..., T  K
where u t is a zero mean stationary error term, the function g is a logistic function bounded
between 0 to 1 that only affects the regressor x t , c is a threshold (or location) parameter and 
denotes the smoothness i.e. the slope of the change. It should be noted that y t may be
substituted by the different interest rate we test here and that x t is a vector of explanatory
variables that may contain both w t'  1, y t 1 , ..., y t  p  and z t   z1t , ..., z kt  exogenous or weakly
'
'
exogenous variables. The last term of the equation (1) allows us to resolve the serial
correlation between regressors and error terms by adding K leads and lags. The logistic
transition function makes the regression coefficient for x t (which includes at least M2 in our
context) vary smoothly between  and 
function of order one: g 

. In this paper, we assume a standard logistic
1
1 e
   ( zt  c ) 
.
When the value of the transition function exceeds the threshold value, the coefficient of the
regressor x t takes a value close to  but when the value of the density decreases and is far
below the threshold value, the coefficient for elasticity changes and approaches 
Furthermore, if 
0

.
, the non-linear STR becomes a conventional linear model.
Thus, in line with Choi and Saikkonen (2004), we test for linearity in equation (1) by
assuming the null hypothesis: H 0 :   0 or   0 . However, conventional hypothesis testing
is complicated because the cointegrating STR model contains unidentified nuisance
parameters under the null corresponding to the transition value c and the slope parameter  .
Hence, a possible solution is to employ the first-order (T1) and the second order (T2) in order
to replace the transition function g. The Choi and Saikkonen statistic follows a Chi Square
distribution under the null with p degrees of freedom where p is the number of covariates
related to the transition function.
6
Five econometric restrictions are needed for the transition variable g, see Choi and Saikkonen (2004) for more
details.
20
Since the null of non-linearity can be rejected for at least one transition variable, a
cointegrating STR model has to be estimated. We have
'
'
V t    x t  k , ...,  x t  k 
'
and
'
'
p t   K ( x t ) V t 
with
1



x
 t

 x t g  s t ,  , c  


K ( x t ) 
 g (.)  .

x
 t 



 g (.) 

x
 t  c

Finally, the two-step Gauss-Newton estimator is also computed considering the first-step
estimator as the initial estimator instead of the NLLS one.
All in all, the Saikkonen and Choi (2004) procedure has two advantages: in large samples, the
Gauss-Newton estimator is more efficient than NLLS estimators and eliminates NLLS bias
and the t-test follows a conventional standard normal distribution in the limit. Simulations
conducted by the authors show that when the sample size grows, the RMSEs (Root Mean
Squared Error) of one-step and two-step Gauss-Newton estimators decrease. In our paper, the
sample is, however, somewhat small and so we compute bootstrap t-stats. Note in addition
that we will report both one-step and two-step estimators; the two-step tends to improve the
RMSE of the one-step Gauss-Newton estimator in terms of RMSE when the errors are serially
and contemporaneously correlated but on occasions, the two-step estimator may be more
biased than the one-step.
As in Saikkonen and Choi (2004), we did not estimate the smooth parameter but instead
tested different values of  . Indeed, it is difficult to accurately estimate the parameter by the
NLSS (see Saikkonen and Choi, 2004) estimator unless either sample sizes are very large or
the location parameter is located close to the median of the explanatory variable. In addition,
the choice of the initial values is crucial to avoid multiple local maxima issues. Note also that
the other parameters are adversely affected by a poor estimate of  . Consequently, we set
some values of  and only report results yielding the least sum of squared errors for the twostep Gauss-Newton estimator. Finally, we choose different values of gamma to check the
robustness of our results (0.5 to 3). The results of the two-step Gauss-Newton estimation of
model (1) with the Dow Jones index as a transition variable are reported in following section.
21
Section 3. Preliminary results
3.1 Linearity tests
The results of the LM linearity tests are illustrated in tables 2 and 3. Two specifications
(denoted by (1) and (2)) are distinguished: in the first, the DJ index as a transition variable is
considered; in the second, we test the DJ volatility to check the robustness of our results. Choi
and Saikkonen (2004) consider that we may reject the null hypothesis of linearity if the LM
test leads to rejection for at least one value of K. As outlined in tables 2 and 3, we can
conclude that the evidence supports non-linearity when the Dow Jones index is considered,
especially when only one lag is considered. The results concerning the Dow Jones volatility
are in the same line: non-linearity is supported especially when one lag and one lead are
included in the DOLS. All in all, our results are also robust in the specification of the long-run
relationship.In other words, the different interest rates (short and long run) are cointegrated
with the money supply M2 but this cointegration relationship is nonlinear regarding the
dynamics of the Dow Jones and the Dow Jones volatility. We can expect that speculative
behaviors have impacted on this relationship and thus created situations of liquidity trap. The
next subsection investigates this assumption by estimating the CSTR model.
Table 2: LM Linearity tests from Choi and Saikkonen: Dow Jones index as a transition
variable and smoothed M2
Interest rate
Commercial paper
Call loans
Treasury notes
US bonds
Corporate
K=1
10.64***
9.26***
7.91***
10.95***
4.83**
T1
K=2
8.02***
16.13***
10.46***
7.42***
2.99*
K=3
10.04***
19.12***
7.99***
8.93***
2.01
K=1
11.20***
9.34***
8.84**
11.18***
4.93*
T2
K=2
8.56**
16.34***
11.99***
7.97**
3.42
K=3
10.67***
19.34***
9.28***
10.40***
3.12
Notes: K denotes the leads and lags in the auxiliary regression model (1). T1 (first order expansion) and T2
(second order expansion) are distributed as asymptotic Chi2 statistic under the null with one and two degrees of
freedom respectively (specification (1)) and with two and three degrees of freedom respectively (specification
(2)). ***, ** and *: significant at 10%, 5% and 1% level respectively.
22
Table 3: LM Linearity tests from Choi and Saikkonen: Dow Jones volatility as a
transition variable and smoothed M2
Interest rate
Commercial paper
Call loans
Treasury notes
US bonds
Corporate
K=1
6.73***
6.50**
4.48**
10.03***
4.29**
T1
K=2
4.02**
9.67***
4.86**
5.65**
1.68
K=3
5.11**
10.90***
3.60**
7.42***
1.15
K=1
7.42**
7.06**
4.95*
10.92***
4.61*
T2
K=2
4.36
10.66***
5.47*
5.77*
1.83
K=3
5.26*
11.66**
3.82
7.44**
2.56
Notes: K denotes the leads and lags in the auxiliary regression model (1). T1 (first order expansion) and T2
(second order expansion) are distributed as asymptotic Chi2 statistic under the null with one and two degrees of
freedom respectively (specification (1)) and with two and three degrees of freedom respectively (specification
(2)). ***, ** and *: significant at 10%, 5% and 1% level respectively.
3.2 CSTR estimates
Since the null of non-linearity can be rejected for two different transition variables (Dow
Jones index and Dow Jones volatility), a cointegrating STR model has to be estimated. We
now report the results of the two-step Gauss-Newton estimation of model (1) with the Dow
Jones index as a transition variable. In this preliminary version, the set of explanatory variable
is reduced to the money supply M2. Note however that our further work will integrate other
control variables (IPPG, CPI, Deposits) in the cointegration vector. In addition, though DOLS
specification is able to control endogeneity, threshold VAR models may be an alternative
method to investigate the liquidity trap.
The preliminary results (see Table 4)are not in favor of the existence of a liquidity trap
concerning short term interest rates commercial paper, call loans and treasury notes rate. The
coefficients are negative in both regimes in most of the cases. This result might be caused by
the absence of control variables in the cointegration vector. Robustness checks are needed to
make a clear-cut conclusion.
However, the results are much more robust concerning the US Bonds and Corporate rates and
lead to interesting results. When the Down Jones index is below a threshold value (132.41) as
shown by the Figure 5 and last column of Table 4, the coefficientalpha of money supply is
negative and significant (at only 10% level). Regarding the Figure 5, this regime takes place
between 1921 and 1925 and between 1931 and 1933. In contrary, when the Down Jones index
surpasses a threshold value, the models turns to its nonlinear regime and the coefficient
23
betaturns to be insignificant. This insensitivity is due to the sharp increase in the Dow Jones
index reflecting speculative behaviours.This outcome supports that a liquidity trap situation
occurredduring this period, which lessens the view expressed by Basile, Lane and Rockoff
(2010).
Table 4: Two-Step Gauss-Newton estimation results
Interest rate:
Corporate
Gamma=2
K=1
2-step
Interest rate:
US Bonds
Gamma=3.5 K=1
1-step



c
7.5977
(1.7753)
(4.0878;11.1077)
-0.0517
(0.0318)
(-0.1145;0.0111)
0.0011
(0.0062)
(-0.0112;0.0134)
132.41



c
7.7071
(2.1668)
(3.4233;11.9910)
-0.0748
(0.0388)
(-0.2130;0.635)
0.0021
(0.0076)
(-0.0129;0.0170)
132.41
Notes: K denotes the leads and lags in the auxiliary regression model (1). The number in the first parentheses
denotes the standard error and the numbers in the second parentheses denote the 95% confidence interval using
the long-run variance estimated through Andrews‟s (1991) method with an AR(4) approximation for the
prefilter. We used the prcg as the solution algorithm as in Saikkonen and Choi (2004).
FIGURE 5: Dynamics of the Dow Jones and threshold value
24
400
360
320
280
240
200
160
120
80
40
22
23
24
25
26
27
28
29
30
31
32
33
Industrial Stock price Index (Dow Jones)
THRESHOLD
Section 4. Conclusion
Using CSTR methodology in line with Choi and Saikkonen (2004, 2010), we revisit the
existence of a liquidity trap in the thirties. We consider the link between different interest
rates and the money supply M2 in low and high speculation regimes and find that both
variables are cointegrated in a nonlinear environment. When the stock index is below a
threshold value, the link between certain different interest rates (corporate, US bonds) and the
money supply is significantly negative. However, when the threshold surpasses an estimated
value, that is over the period 1926-1930, the interest rate turns to be insensitive to a move in
money supply. This result reveals the presence of a liquidity trap over the period 1926-1930
due to speculative behaviours.
25
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Hypothesis”, The Review of Economics and Statistics, 79(2), 212-218.
SAIKKONEN, P., CHOI, I., (2004), “Cointegrating smooth transition Regressions,”
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26