Prices During the Great Depression: Was the Deflation of 1930-1932 Really
Unanticipated?
Stephen G. Cecchetti
The American Economic Review, Vol. 82, No. 1. (Mar., 1992), pp. 141-156.
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Prices During the Great Depression: Was the Deflation of 1 930-1 932 Really Unanticipated? This paper examines inflationary expectations in order to investigate whether the
deflation of 1930-1932 could have been anticipated. The major conclusion is
that beginning in late 1930, and possibly as early as late 1929, deflation could
have been anticipated at horizons of 3-6 months. This implies, in turn, that
short-run ex ante real interest rates were very high during the initial phases of
the Great Depression. These results provide further support for the proposition
that monetary contraction was the driving force behind the economic decline.
(JEL E31, N11)
A consensus on the causes of the Great
Depression has not yet emerged. The purpose of this paper is to establish some simple empirical facts that must be accounted
for by any explanation of the length and
depth of the contraction from 1930 to 1933.
In particular, I will show that beginning in
late 1930, and possibly as early as late 1929,
deflation could have been anticipated at
horizons of 3-6 months. This implies, in
turn, that short-run ex ante real interest
rates were very high during this period.
At least three general theories have been
proposed to explain this historical episode.
They are (i) the monetary hypothesis of
Milton Friedman and Anna Schwartz (1963),
in which a reduction in the quantity of
money is blamed for the 1930-1933 contraction; (ii) theories based on exogenous de-
clines in real consumption or investment,
such as the one described in Peter Temin
(1976); and (iii) the debt-deflation theories
based on Irving Fisher's original (1933) paper and more recently formalized by Ben
Bernanke and Mark Gertler (1989, 1990).
As Schwartz (1981) points out, a high real
interest rate is one of the key features that
differentiates the monetary hypothesis from
theories based on exogenous declines in real
consumption or investment.
The debt-deflation hypothesis is based on
the notion that the nearly 30-percent cumulative deflation of 1930-1932 was primarily
responsible for the depth of the Great Depression. The argument proceeds as follows.
Since unanticipated deflation increases the
burden of nominal debt, it caused debtors
to default on loans, which led to bank failures and the collapse of the financial system. Bernanke and Gertler (1989, 1990) examine a formal model in which deflation
lowers borrower net worth, thereby increasing leverage and the desire of entrepreneurs
to take
on risk.
~
~ This ~raises the
~ possibility
~ of
bankruptcy, lowers the level of investment,
and causes a reduction in both aggregate
Supply and aggregate demand. ~h~ debtis based On the assumption that the 1930-1933 deflation was
unanticipated when agents entered into
rnedium-term debt contracts during the preceding five years. I provide no evidence in
this paper regarding medium-tem expectstions during this period of debt accumula-
*De~artmentof Economics, Ohio State University,
1945 North High Street, ~ o l u m b u s ,O H 43210, aid
NBER. This is a revised version of NBER Working
Paper No. 3174 (November 1989), which was previously
~
section 2 of a ~ e f l a t i o nand the G~~~~D
(March 1988). Thanks are due to Laurence Ball, Robert
Barsky, Ben Bernanke, Michael Bordo, Robert Cumby,
Paul Evans, James Hamilton, Pok-sang Lam, Frederic
Mishkin, Anna Schwartz, Peter Temin, Alan Viard,
Paul Wachtel, the referees, and seminar participants at
the University of South Carolina and at the April 1988
NBER Workshop on Macroeconomic History for comments and helpful discussions; to John Campbell for
sharing his computer software; and to Jeff Miron for
providing his data. Support of the National Science
Foundation Grant No. SES-8821796 is gratefully acknowledged. The usual disclaimer applies.
141
~
~
142
THE AMERICAN ECONOMIC REVIEW
tion, so my results are not directly relevant
to what many people might view as the
central thesis of the debt-deflation hypothesis.
Instead, this paper investigates whether
the deflation of the early 1930's, when prices
fell at an average of 8.7 percent per year for
three years, might have been anticipated at
short-term horizons of 3-6 months. Data on
both prices and interest rates provide empirical support for the proposition that the
deflation could have been anticipated. This
calls into question theories of the Great
Depression that rely on contemporary
agents' belief in reflation-and low ex ante
short-term real interest rates-prior to 1933.
Three separate types of evidence suggest
the conclusion that the deflation could have
been anticipated. First, deflation was within
the recent experience of the people living in
1929. In fact, in the 64 years between the
Civil War and the Great Depression, there
were four episodes in which the price level
fell for two consecutive years or more. Second, changes in the price level were positively autocorrelated during the intenvar
years. This implies that simple rules of
thumb would have led to the expectation of
continued deflation during the period. Finally, the information contained in data on
interest rates can be used to extract estimates of both ex ante real interest rates and
expected inflation. While nominal interest
rates were low, the data suggest that real
interest rates were very high from 1927 to
early 1933. This implies that people expected the deflation to continue.
This econometric evidence complements
the direct historical evidence reported in a
recent paper by Daniel Nelson (1990) and
challenges the results reported in previous
work, particularly that of James Hamilton
(1987). Nelson examines articles in the contemporary business and financial press to
argue that in 1929 and 1930 many analysts
expected the price level to decline by as
much as 50 percent to its pre-World War I
level. Hamilton (1987) measures inflationary
expectations from data on commodity futures prices.
The approach of this paper is to use
contemporary econometric tools to examine
M R C H 1992
data on prices, interest rates, and money in
order to measure implied expectations. Section I describes the history of past deflations. This is followed by a study of the
univariate time-series properties of the price
level in Section 11, beginning with a discussion of whether the price level contained a
unit root. The remainder of the section
identifies and estimates ARMA models of
inflation and examines the properties of the
forecasts implied by the estimated models.
Section I11 describes a method for estimating expected inflation from data on interest
rates. Section IV contrasts the methods used
here with those used by Hamilton (1987) in
order to assess the relative validity of the
different techniques.' The final section contains concluding remarks and suggests directions for future research.
I. The History of Previous Deflations
While any broad-based nominal-price decline would take virtually everyone by surprise if it happened today, this was not true
in 1930. Deflation was within the experience
of contemporary economic agents. This
point is made clear by Table 1, where information is presented on the deflations of the
late 19th and early 20th century.
Between the Civil War and the Great
Depression, there were four periods of sustained deflation, when consumer prices fell
for two consecutive years or more. The
1920-1922 deflation following World War I
was clearly the most severe. In fact, the
cumulative price decline during these two
years was roughly the same as the decline
during the Great Depression.
While the experience of the four episodes
prior to the 1930's provides no reason to
believe that in 1929 a 3-5-year deflation of
20-30 percent was widely anticipated, it
suggests that people should have been aware
of the possibility of price declines and had
'1n a reply to an earlier version of this paper,
Hamilton (1992) has taken another look at futuresmarket data and come to a conclusion that is at least
partially in agreement with the thesis of this paper.
Specifically, he finds evidence of anticipated deflation
beginning in late 1930.
143
CECCHETTI: PRICES DURING THE GREAT DEPRESSION
VOL. 82 NO. I
TABLE
1-DEFLATIONSFROM 1869 TO 1932
Measure
1872-1877
Length of deflation (years)
Consumer price index (percentage)
Wholesale price index (percentage)
GNP deflator (percentage)
Cumulative real GNP growth (~ercentage)
5
- 12.3 - 22.1 - 12.9 + 22.4 1882-1885
3
- 13.8
- 15.8
- 12.2
+ 5.0
1892-1894
1920-1922
2
2
- 17.8
- 37.8
- 19.4
+ 3.4
- 3.6
- 8.2
- 4,2
- 3.1
1930-1933
3
- 27.9
- 31.6
- 23.3
- 29.3
Sources: See Appendix.
some notion of how to cope with them. In
light of that experience, the subjective probability assigned to a decline in the price
level could have been fairly high.
11. The Time-Series Properties
of the Price Level
A. Overview
The first step in studying the data on
inflation is to examine the univariate properties of consumer prices. The major purpose of this section is to formulate ARMA
forecasts of inflation for the 1930-1932 period. The conclusion is that there was substantial persistence in the inflation in the
192OYs,and so it is reasonable to believe
that, once it started, deflation would have
been expected to continue.
I begin with a simple plot of the data on
the level of consumer prices, monthly from
1913 to 1940.~Figure 1 plots the natural
logarithm of the index. The figure includes
vertical lines drawn at the beginning of 1919
and the beginning of 1929, delimiting the
period that will be examined more closely in
this paper. The data show a pattern that is
consistent with a nonstationary time series.
ZAs described in the Appendix, the data on consumer prices are mainly the cost-of-living indexes (CLI)
constructed from monthly surveys by the National Industrial Conference Board. These data are based on
contemporaneous monthly surveys and were made
available through publications of the period. Prior to
1919, the consumer price data are drawn from the
current Bureau of Labor Statistics Consumer Price
Index series (CPI). The CLI series is preferred to the
CPI, since the latter appears to have been constructed
by interpolating data at a frequency of approximately
six months.
Prices do not appear to revert to any sort of
absolute level or deterministic trend. Instead, movements seem to reflect a stochastic trend.3
The remainder of this section begins with
a series of preliminary steps and then reports the results of a univariate ARMA
forecasting exercise. Section 11-B establishes the plausibility of assuming that the
log of the price level is a first-order integrated process, implying that inflation is a
stationary series. This is done by discussing
both theoretical arguments in favor of the
hypothesis of a unit root and examining
some empirical evidence.
The following section presents the results
of a simple exercise to determine the univariate ARMA process for inflation. Using
quarterly data from 1919 to 1928 only, inflation is modeled by an MA(2). When data
through 1940 are added to the sample period, the resulting identification is that inflation follows an AR(1). The estimated coefficients for both of these processes imply
persistence.
Finally, results on univariate forecasts of
inflation are presented using both the MA(2)
estimated over the 1919-1928 period, and
the AR(1) model for the 1919-1940 data
set. The forecasts clearly suggest that the
deflation of 1930-1932 could have been anticipated.
B. Unit Roots: Theoretical Arguments
and Empirical Tests
There are both theoretical and empirical
reasons for believing that the price level
3 ~ hw
e holesale price series, which is also used in
the following analysis, has the same broad profile.
THE AMERICAN ECONOMIC REVIEW
MARCH I992
Date
should contain a unit root. It is well recognized that, in the presence of a paper money
standard, inflation exhibits stochastic properties similar to those of money growth. The
data on the post-World War I1 period suggest that it is the second difference of the
money stock, and therefore the second difference of the price level, that is stationary
under the current institutional arrangement.4
It is less clear what the time-series properties of the price level should be in the
presence of a gold or commodity money
standard. However, the same reasoning that
leads one to suspect that the price level is
nonstationary when there is fiat money holds
when a gold standard is operating. In fact,
the price level would be stationary only by
chance.
The argument follows directly from considering the equilibrium condition for the
money market in the presence of a gold
standard. Following Robert Barro (1979),
where P is the price of goods, Y is the level
of real output, and k is the ratio of money
demand to income and may be a function of
the rates of return on alternative assets (i.e.,
inflation and interest rates). Using the fact
that PG is fixed by definition and that A is
assumed to be ~ o n s t a n t equilibrium
,~
in the
4 ~ o t hRobert Barsky (1987), in his examination of
U.S. quarterly inflation from 1960 to 1979, and Laurence Ball and Cecchetti (19901, in their study of
inflation in 40 countries from 1960 to 1989, find that
inflation is well approximated as an IMA(1,l).
'AS Barro (1979) notes, if money is defined to include commercial bank deposits, then changes in the
ratio of currency to demand deposits would change the
level of A. However, one would expect h to be constant
in a steady state.
assume that the supply of money is a roughly
constant multiple of the size of the monetary gold stock,
where P, is the money price of gold, Gm is
the monetary gold stock, and A is a multiplier relating the sum of currency and deposits to the value of the monetary gold
stock. Assume that the demand for money
can be written as
VOL. 82 NO. I
CECCHETTI: PRICES DURING THE GREAT DEPRESSION
money market implies that
(3)
A log P, = A log G,m -
The stochastic properties of the price level
depend on the time-series characteristics of
the three variables on the right-hand side of
equation (3). There are two natural possibilities: (i) the three variables are all trendstationary, and (ii) some subset of the variables is integrated.6 In the first case, the
price level will be stationary about a trend,
except in the extremely unlikely circumstance that the trends in the three variables
exactly cancel. Equating the supply and demand for money implies that, unless the
rate of growth of the gold stock happens to
match the rate of growth of real output, or
the ratio of the demand for money to income happens to be changing to exactly
offset the difference between the base
money and output growth rates, the price
level has some secular m ~ v e m e n t . ~
However, it seems plausible that at least
one of these variables will be integrated. In
this case, log P, will be stationary if and
only if A - I o ~ G , "kt,
~ , and A l o g y are cointegrated with exactly the right cointegrating
vector. For example, if all three variables
are I(l), then the cointegrating vector would
have to be equal to (1, - 1, - 1).
Statistical evidence also suggests that it is
sensible to model the price level as containing a unit root. For example, the autocorrelations of the time series for both the CPI
and the WPI die out very slowly. In the case
of quarterly inflation from 1919 to 1940, the
6 ~ h e t h e output
r
is I(1) is an unsettled matter. The
growth rate of monetary gold depends on the supply
and demand for gold, which depend in turn on the real
price of gold, on improvements in the gold-extraction
technology, and on the demand for nonmonetary gold.
Any deflationary tendency in the price of goods, caused
by output growth, is at least partially offset by reductions in k together with increased gold production.
' ~ a r r o(1979 p. 20) suggests that the price level will
exhibit a secular decline. Michael Bordo and Richard
Ellson (1985) demonstrate that, as a result of resource
constraints and in the presence of depletion, one should
actually expect long-run deflation under a classical gold
standard.
145
autocorrelations of the CPI and WPI both
exceed 0.20 at a horizon of 20 quarters,
implying that the series may be well approximated as having a unit root. Unfortunately,
specific statistical tests, such as the ones
suggested by David Dickey and Wayne
Fuller (1981), have notoriously low power
against alternatives in which the time series
has an autoregressive root only slightly less
than 1. Nevertheless, use of the DickeyFuller test shows that the null hypothesis of
a unit root is generally not rejected for
either the CPI or the WPI, at a monthly or
quarterly frequency, using samples for
1919-1928 and for 1919-1940.8
These arguments suggest that it is reasonable to study the implications of assuming
that inflation is a stationary series. The following section proceeds by examining
ARMA models of i n f l a t i ~ n . ~
C. A R M Models: Identification, Estimation, and Forecasting The next natural step is to identify the
appropriate ARMA model for inflation. As
Campbell and Mankiw (1987) describe, there
' ~ h e s e results, which are reported in a workingpaper version of this paper (Cecchetti, 1989) are based
on examining the coefficient on the lagged price level
in the regression given by Apt = a + bpt-, +
Ci(,,c, Apt-, + u,, where p is the log of the price level,
Ap is the first difference in the log of the price (inflation), u is a random error, and the remaining terms are
parameters. The null hypothesis is that the log of the
price level (p,) has a unit root, namely that b = 0.
Using quarterly data on consumer prices from 1919 to
1940 the random-walk null is never rejected at the
10-percent level.
91t is imwrtant to note that differencing the data in
no way biases the conclusions about persistence of
inflation or deflation. As John Campbell and N. Gregory Mankiw (1987) discuss in detail, modeling the first
difference of a time series as stationary leaves open the
question of whether the level is a stationary process.
This is not to say that the results would necessarily be
the same if the ARMA models were estimated in
levels. The assumption that the log of the price level is
an AR(2) without a trend, for example, would imply
that the price level is reverting to some mean level.
This has the rather dramatic implication that the more
unanticipated deflation there is, the more inflation is
expected. This is the result obtained by Kathryn
Dominguez et al. (1988) in their study of the forecasts
obtained from a vector-autoregressive system containing the price level.
146
THE AMERICAN ECONOMIC REVIEW
is a difficulty in estimating the parameters
of ARMA processes with moving-average
roots close to unity. Following their recommendation, a set of ARMA models has been
estimated using the Kalman filtering algorithm described in Andrew Harvey (1981).
All of these models are of the form
where T is inflation, A(L) and B(L) are
lag polynomials of order p and q, respectively, and E is a Guassian white-noise error
term.
Model selection was carried out by estimating all ARMA(p, q ) models up to order
(2,2) using quarterly consumer price data
over sample periods beginning in 1919 and
ending either in 1928 or in 1940. The likelihood values from these two sets of estimates were then compared using the criteria proposed by both H. Akaike (1974) and
Gideon Schwarz (1978), as well as simple
likelihood-ratio tests for nested models.
This exercise yielded unambiguous results. For the sample ending in 1928, the
MA(2) model is not rejected by any more
general model at the 5-percent level using a
likelihood-ratio test. Furthermore, the
MA(2) is chosen by both the Schwarz and
the Akaike criteria. The AR(1) model is
dominant when the long sample is used.
The MA(2) model estimated over the
1919-1928 period is (inflation is measured
in percent per quarter at an annual rate):
(numbers in parentheses are asymptotic
standard errors; mean of T = 0.263; estimated standard deviation of E , = 7.89; standard deviation of T,= 10.55), and the AR(1)
model estimated over the 1919-1940 period
is
(numbers in parentheses are asymptotic
standard errors; mean of T = - 0.586; esti-
MARCH I992
mated standard deviation of E , = 7.93; standard deviation of T,= 9.25).
Both of these models imply persistence in
price changes at horizons of two quarters.
Once a deflation begins, it is expected to
continue at least briefly. The MA(2) model
suggests that, if a deflation were to begin
unexpectedly, as it must since the constant
in (5) is positive, it would be forecast to
continue for two quarters at between onehalf and three-quarters the initial rate. The
AR(1) estimates imply that, beginning with
a 10-percent annual deflation, prices would
still be forecast to fall by 1 percent (at an
annual rate) one year later. The conclusion
is that inflation during the entire interwar
period was substantially serially correlated
and that, once a deflation started, it should
have been expected to continue for at least
3-6 months.
It is possible to use the ARMA estimates
in (5) and (6) to generate forecasts of inflation from 1929 through 1933." The results
of this exercise yield out-of-sample forecasts
for the MA(2) model, which is estimated
using the 1919-1928 data set. By contrast,
the AR(1) model forecasts are withinsample fitted values, since the model parameters are estimated using the entire
1919-1940 data set."
Figures 2 and 3 report the forecasts (the
solid lines), with 95-percent confidence intervals (the two dashed lines).'* I have also
' O ~ o rthe AR model, constructing the forecasts is
straightforward. For the MA model, there are a number of options. The reported forecasts use the prediction errors from the Kalman filter at the end of the
estimation period. Other alternatives, such as using the
full-sample smoothed residuals or the backcasting technique described in chapter 5 of George Box and Gwilym
Jenkins (19761, yield virtually identical results.
"1t is also possible to construct expanding-sample
forecasts in which the ARMA model is reestimated
using all data up to the date prior to the date of the
forecast. These are reported in the following section.
fo he confidence bounds are constructed in a manner analogous to the one suggested by Frederic Mishkin
(1981) and used in the next section. For the AR(l), for
example, it is assumed that the model is the true model
of expectations formation, and so fitted value is an
estimate of expected inflation. The uncertainty about
this estimate is due to the variance of the coefficient
estimates only.
VOL. 82 NO. 1
CECCHETTI: PRICES DURING THE GREAT DEPRESSION
FIGURE
2. EXPECTED
AND ACl7JAL INFLATION,1929-1933 (QUARTERLY
AT
AN ANNUAL
RATE,MA(2) OUT-OF-SAMPLE
FORECASTS)
1929
1930
1931
1932
1933
1934
Year
FIGURE
3. EXPECTED
AND ACTUAL INFLATION,1929-1933 (QUARTERLY
AT
AN ANNUAL
RATE,AR(1) IN-SAMPLE
FITTED
VALUES)
I48
THE A M E R U N ECONOMIC REMEW
plotted actual inflation, as indicated by the
" x " symbols connected by a solid line.
As is to be expected, the AR(1) model
generates smoother forecasts and forecasts
deflation more consistently. The MA(2)
model shows larger, more erratic jumps. In
both cases, however, there is a clear tendency for the forecasts to be significantly
less than zero. While the forecasts imply
that there was still some unanticipated deflation, the univariate models come quite a
bit closer to the actual values than one
might have thought.13
111. Measuring Expected Inflation from
Interest Rates
In addition to studying the expectations
implied by the univariate inflation process,
it is also possible to obtain measures of
anticipated price changes from data on interest rates. This section employs a procedure first suggested by Mishkin (1981) for
dividing information in the nominal interest
rate into the component that represents the
ex ante real interest rate and the component
that represents expected inflation.
Mishkin's technique has several advantages over the univariate procedure of Section 11. Principally, it allows the use of additional information. Estimates of expected
inflation are based not only on the behavior
of the price level, but also on movements in
interest rates and other macroeconomic
variables such as money growth. Furthermore, estimates of expected inflation (or
deflation) that are constructed from data on
interest rates are not sensitive to assumptions about whether or not the price level is
stationary. All that is required for valid inference is the extremely plausible assump-
13
Estimation of the model under the constraint that
one MA root is - 1 (the case in which the series has
been overdifferenced) suggests that the data are well
approximated by an AR(2) in levels, with a negative
drift. This model yields results similar to that of the
AR(1) model in first differences reported above. Using
either within-sample fitted values or out-of-sample
forecasts leads one to conclude that deflation was
anticipated in every quarter from 1930:l through
1933:3, except for 1931:4.
MARCH 1992
tion that the real interest rate is stationary.14
Given the difficulty inherent in establishing
whether the price level has a unit root, this
technique provides results that are complementary to those reported in Section 11.
To understand how Mishkin's procedure
works, define r,,i to be the expectation at
time t of the J-period real return on a
nominally riskless bond held from t to t + j,
and define it,, to be the corresponding jperiod nominal return at t . If r: . is expected inflation from t to t + j, then the
ex ante real rate of interest on a j-period
bond held to maturity is defined by the
Fisher identity
While r,,, is unobservable, the ex post or
realized real return can be measured directly from the data. Define eprr,,, and rt,,
as the ex post real return and the realized
inflation from t to t + j, respectively, so
eprr,,, = it, - r,,,.Combining this with (7),
it is clear that r,,, -eprr,,,, the difference
between the ex ante and ex post real interest rate, is unanticipated inflation, ( T , , ~r;,). Rational expectations imply that
unanticipated inflation is always expected to
be zero. Therefore, if 0, is information
available at time t , then E(r,,., - r;,)lR,)
= 0. The econometrician, being less informed than agents in the economy, observes only a subset of 0,. Using this reduced information set, X,, an estimate of
the ex ante real rate of interest can be
obtained by projecting r,,, on X,, P(r,,,(X,)
= X,S. This will entail a projection error
u,,, that is orthogonal to X,. Making appropriate substitutions yields the regression
equation
,
Since unanticipated inflation and the pro1 4 ~ i s h k i n(1991 appendix 11) provides a discussion
of this point in the context of estimating regressions for
the real interest rate of the type examined here. James
Stock and Kenneth West (1988) discuss issues of this
type in the context of testing the permanent-income
hypothesis.
VOL. 82 NO. I
CECCHETTI: PRICES DURING THE GREAT DEPRESSION
149
jection error for the real rate are both orinformation set was assumed to contain the
thogonal to the components of the informamost recently available value of the growth
tion set X, equation (8) can be estimated
rate in x over the previous year, as well as
using ordinary least squares.15 It is clear
the growth rate lagged one and two years.
from the above discussion thai the fitted
After estimating the projection equation invalues from this regression, Xtf3, are esticluding these variables, a Wald test was
mates of the ex ante real rate.16
performed for the null hypothesis that the
Applying Mishkin's technique to Mankiw
three coefficients on the new variable were
and Jeffrey Miron's (1985) data on threejointly different from zero. If the null was
month and six-month time loans at New
rejected, the variable was included; if it was
York banks, I have constructed estimates of
not, the variable was dropped. Because the
the real interest rate for the interwar pedata on interest rates are at a monthly freriod. Since the results for both maturities
quency (except for three-month yields), the
are virtually identical, only the three-month
error term in (8) is a second-order moving
average." This means that a robust covariestimates are reported below.
ance-matrix estimator must be used.'' VariChoice of the variables included in the
ables were examined in the following order:
information set X, was dictated by several
inflation, industrial production, M2, MB,
considerations discussed at length in
and MI." The resulting tests yielded the
Mishkin's (1981) work. First, the nominal
specification that included inflation, M2, and
interest rate was included. Then, five addithe monetary base.20
tional variables were considered. These were
the level of inflation (T),growth in the
Figure 4 plots the estimates of r,,,, the
one-quarter-ahead ex ante real interest rate
monetary base (MB), growth in two measures of the stock of money (MI and M2, as
from 1919 to 1940, along with 95-percent
defined by Friedman and Schwartz [1963]),
and growth in the new industrial production
series recently constructed by Miron and
Christina ~ o m e (1989).
r
The ~ ~ ~ e nind i x ' h s is discussed in John Huizinga and Mishkin
'ludes a
description of the
(1986), when the holding-period j is larger than 1, and
All data are seasonally unadjusted. For each
overlapping data are used, the error in this regression
will be a moving average of order j- 1. This implies
of these five variables, I began by constructthat a robust procedure must be used to estimate the
ing 12-month log differences. For a variable
Standard
error of consistently.
x, define Ax, = log(x, /x,-,,). Then, for a
he estimates here employ the simple moment
given variable, Ax,- 1, Axt - 13, and
-25
estimator suggested by Lars Hansen and Robert Howere all added to regression (8). That is, the
drick (19801, unless it is not positive definite, in which
quati ti on (8) can be thought of as a simplified
linear form of the expression for the interest rate that
would arise in the model developed by John Cox et al.
(1985). In their scheme, the bond yield is a linear
function of the state variables, or factors. The weights
on the factors depend on the parameters of the vector
stochastic process that describes the state. If one assumes that this process is stable, so that the weights
are time-invariant, and that X, is a set of variables
describing the state at time t , then the p's are the
weights. Since the purpose here is to recover the real
interest rate without explicitly specifying the set of
factors and their stochastic process, it is unnecessary
to do more than examine the simple projection equation (8).
1 6 ~ e n n e t hSingleton (1981) provides a detailed discussion of inference in the context of Mishkin's model.
case the Whitney Newey and Kenneth West (1987)
estimator is used.
l g ~ h actual
e
statistical properties of such a sequential testing procedure are not known. The order in
which the variables were tested does make a small
difference. For example, if M2 is entered before inflation, inflation will not have much added explanatory
power. Fortunately, the results for the estimated levels
of the real interest rate and expected inflation are
robust to these changes.
the presence of overlapping data, an additional
check on the specification is to see if the residual
autocorrelations beyond the second are equal to zero.
Robert Cumby and Huizinga (1989) have recently developed a test for this hypothesis. The value of their
statistic testing the null that the third through eighth
autocorrelations in the residual in the regression (8)
are zero is 7.79. This statistic is distributed as chi-square
with six degrees of freedom under the null. The 10-percent critical value for a
is 10.65, implying that the
model meets the desired criterion.
Xkl
UARCH 1992
THE AMERICAN ECONOMIC REVIEW
150
1919
1921
1923
1925
1927
1929
1931
1933
1935
1937
193s
1941
Year
FIGURE
4. EXANTEREALINTEREST
RATE,1919-1940 (MONTHLY
AT AN ANNUAL
RATE,
THREE-MONTH CONF~DENCE
BANDS)
HORIZON.WITH 95-PERCENT
TABLE2-CHRONOLOGYOF MONETARY
EVENTSDURING
THE DEPRESSION,
FROM FRIEDMAN
AND SCHWARTZ
(1963)
Month
Event
October 1929
October 1930
March 1932
September 1931
April 1932
January 1933
March 1933
January 1937
May 1937
Stock market crash
First banking crisis
Second bank crisis
Britain leaves the gold standard
Onset of open market purchases
Last banking crisis
Bank holiday
Announcement of final rise in reserve requirement
Effective date of increase in reserve requirement
Note: Numbers correspond to vertical lines in the figures.
confidence interval^.^' The vertical lines in
this figure, as well as those in Figures 2, 3,
and 5, correspond to the events described in
the chronology reproduced in Table 2.
The most striking feature of Figure 4 is
the height of the estimates of the real inter" ~ i s h k i n (1981) provides a detailed discussion of
the construction of these standard errors. I follow his
suggestion and plot the lower bound of the standard
error associated with (?,, - r,,j ) .
est rate throughout the latter half of the
1920's and the early 1930's. While it moves
substantially, the estimated real rate is consistently high. In fact, the estimates rise to
nearly 20 percent in late 1931 and early
1932 during the most severe phase of the
Great Depression. Then, immediately following the onset of open-market purchases
in April 1932, the real interest rate begins
to fall, never again rising to levels even
close to those at the beginning of 1932 and
VOL. 82 NO. 1
CECCHETTI: PRlCES DURING THE GREAT DEPRESSION
Year
rising above 5 percent only briefly in early
1934, mid-1937, and early 1938. Although
the real rate appears to have been quite
volatile following the bank holiday of March
1933 (the vertical line labeled 7), it was
consistently low.
Given that nominal interest rates declined steadily from October 1929 to February 1933, with only a brief rise in late 1931
and early 1932, this implies that deflation
was anticipated during 1930 and 1 9 3 1 . ~ ~
Figure 5 plots expected inflation implied by
the estimates of the real interest rate in
Figure 4. Once again, 95-percent confidence
intervals are included. The results are clear
support for the proposition that the
1930-1932 deflation was anticipated.
" ~ nalternative to the specification developed later
in this paper is to use the log of the price level in place
of lags of inflation in X,. This can be done simply by
adding log P I - , to the regressions used here. As one
would expect, this makes little difference. Adding an
additional variable to the information set can only
make the model track the high ex post real interest
rates more closely and, therefore, continue to imply
expected deflation.
It is useful to compare the results from
the univariate models of Section 11, the
MA(2) and AR(l), with those obtained from
the interest-rate data. Table 3 presents expanding out-of-sample forecasts of inflation
based on each of the three models.23All the
estimates are for three-month periods, measured at annual rates. In addition, the table
reports the actual, expost level of inflation.
2 3 ~ h expanding-sample estimates all have an advantage w e r the within-sample fitted values presented
in Figures 3 and 5. Any procedure that relies on least
squares, including the Mishkin technique and simple
estimates of autoregressive models, has major shortcomings that might lead one to be skeptical of the
results based on full-sample estimation. In particular,
the fitted values from any ordinary least-squares regression tend to follow the raw data rather closely:
estimates of ex ante values will look very much like
ex post realizations. This makes inferences about expectations from within-sample fitted values suspect. In
essence, the agents in the economy have to know the
true model before the data have been produced for an
econometrician to estimate it. During a period like the
1930's, this seems like a rather large leap of faith.
Out-of-sample forecasting is a natural way to address
this concern.
MARCH 1992
THE AMERICAN ECONOMIC REVIEW
Expected inflation
Quarter
Actual
inflation
MA(2) model
AR(1) model
Interest-rate
model
1929:l
1929:2
1929:3
1929:4
-3.60
0.80
6.75
-3.16
- 0.81
- 6.30
2.27
7.03
- 2.73
- 2.09
0.55
4.17
- 0.43
- 4.20
- 8.37
0.10
1933:l
1933:2
1933:3
1933:4
- 16.83
7.15
26.96
-4.10
- 4.68
- 10.48
7.07
22.97
- 6.48
- 11.75
3.51
16.62
22.07
12.39
- 4.04
4.47
Notes: All estimates are for one quarter at annual rates. The MA(2) and AR(1)
estimates use the procedures described in Section 11. The "interest-rate" estimates
are constructed from equation (8).
The expanding-sample estimates compute
forecasts using data available at the time
the forecast needed to be made. For example, in each case, the estimate for the first
quarter of 1930 was obtained by estimating
the model through the end of 1929 and then
forecasting the beginning of 1930.24
The important feature of Table 3 is that
all the estimates have the same basic properties. The conclusion that the deflation was
anticipated is robust to changes in the estimation procedure. By the end of 1929,
deflation was anticipated, although expectations were that it would be a fairly moderate 2-3 percent. However, as the 1930's
began, the price declines were expected to
2 4 ~ist important to note that the model selection
criteria described above yield virtually the same specification if the exercise is performed on data ending in
1928.
persist, and the absolute size of the anticipated deflation increased. For the first three
quarters of 1931, these methods all generated expectations of deflation that exceed 5
percent.
IV. Comparison with Previous Work
The results using both univariate prices
and interest rates differ dramatically from
those reported by Hamilton (1987). It is
worth commenting on the reasons for these
differences.
Using data from commodity futures markets, Hamilton (1987) concludes that the
deflation of 1930-1932 was unanticipated.
Hamilton measures expectations of future
inflation by looking at the difference between the current spot price and the futures
price, six months ahead, for a number of
storable commodities, including cotton,
wheat, corn, and oats.
VOL. 82 NO. 1
CECCHETTZ:PRICES DURING THE GREAT DEPRESSION
There are several reasons to be skeptical
of his results. First, when considering commodity futures markets, it is important to
keep in mind the existence of physical
stocks. These stocks are assets whose riskadjusted nominal return must equal that of
other assets. A bond is in this set of alternatives, and since the nominal interest rate
can never be negative (except in unusual
circumstances described in Cecchetti [19881),
the price of the stored commodity can never
be expected to fall.
There are several caveats to this simple
argument. First, the price can be expected
to drop at the harvest date, when the stock
from the previous year will be nearly exhausted. Furthermore, in the presence of a
convenience yield (the return to holding a
stock that is a necessary factor of production) the commodity price can fall at that
rate. However, Robert Pindyck (1990) shows
that the marginal convenience yield net of
storage is nearly zero, except when inventories are very low. Since physical stocks were
actually quite high during the Great Dep r e ~ s i o n price
, ~ ~ declines are implausible.
A second reason to doubt Hamilton's
conclusions emerges from a study of the
nature of government intervention in the
futures markets during the early 1930's.
Anne Peck (1976) describes how from 1929
to 1933 the Federal Farm Board, in an
attempt to stabilize agricultural commodities prices, traded futures contracts. Peck
documents that, during 1930 and 1931, the
Farm Board, through the Grain Stabilization Corporation, held large open positions
in the wheat futures market that often comprised over half the open interest in wheat
futures in the Chicago, Kansas City, and
Minneapolis markets. In fact, in Minneapolis, the Farm Board owned 93 percent of the
open interest in wheat futures during March
1931. Furthermore, by the end of the
25
Consider the case of cotton, one of the commodities Hamilton (1987) studies, which is harvested beginning in mid-September. The total stock of cotton available on August 1 of 1930, 1931, and 1932 averaged
nearly half of production for those three years (see
Historical Statistics of the United States, Colonial Times
to 1970 [Series K-554 and 556, p. 5171.
153
1930-1931 crop year, the government owned
outright more than 250 million bushels of
wheat, or nearly three quarters of the 344
million bushels produced during that year.
Peck's study focuses on wheat futures held
by the Federal Farm Board through the
Grain Stabilization Corporation, but she
notes that other federal agencies were participating in other futures markets at the
same time. The clear goal of government
policy was to keep the prices of agricultural
commodities from falling, and one of the
main methods for doing so was to participate in the futures market. Given the nature and magnitude of government intervention in the commodity futures markets
between 1929 and 1933, it is difficult to see
how prices in these markets can be used to
infer the beliefs of private agents in the
economy at the time.
V. Conclusion
The purpose of this paper has been to
show that the deflation of 1930-1932 could
have been anticipated. Simple models of
price expectations, based on either univariate time-series representations or on the
information contained in interest rates, suggest that the persistence in the inflation
process could have led agents to believe
that the deflation would continue once it
began. These conclusions imply that theories for the propagation of the Great Depression must be consistent with very high
short-term real interest rates beginning possibly as early as 1927, and certainly from
late 1930 onward.
The finding that the deflation could have
been anticipated is relevant to two ongoing
debates about the nature of the Great Depression. The first pertains to the Robert
Lucas and Leonard Rapping (1969) claim
that unanticipated deflation led to intertemporal substitution, which then explains the
low level of employment during the 1930's.
Clearly, the results in this paper do not
support their position.
The primary debate over the causes of
the Great Depression is Friedman and
Schwartz (1963) versus Temin (1976). The
most recent version of this appears in the
154
THE AMERICAN ECONOMIC REVIEW
volume edited by Karl Brunner (1981). As
Schwartz (1981) points out, the monetary
hypothesis requires that real interest rates
be high from 1930 through 1932. This is
clearly supported by the estimated level of
the ex ante real interest rate on three-month
time loans, which exceeds 5 percent
throughout the period, reaching a peak in
excess of 20 percent in early 1932. Furthermore, the fact that real interest rates were
high beginning in 1927 confirms Hamilton's
(1987) conclusion that tight monetary policy
initiated the Great ~ e p r e s s i o n . ~ ~
Although the econometric evidence suggests that some deflation could have been
anticipated, actual price declines were even
greater. There was still unanticipated deflation between 1930 and 1933. The estimates
of Section IV suggest that at most threequarters of the deflation could have been
anticipated. Since prices fell nearly 30 percent, this means that the cumulative amount
of unanticipated inflation was at least 8-10
percent.
Finally, the observation that the deflation
of 1930-1932 could have been anticipated
indicates a possibly new interpretation of
the Great Depression which concentrates
on the consequences of anticipated deflation and high ex ante real interest rates.
Future research will examine the implications of a fully anticipated, severe temporary deflation. The importance of this
derives from the fact that, as deflation worsens, the nominal interest rate goes to zero,
driving up the real return on money, causing portfolio shifts and leading to negative
net investment. Under some circumstances,
the economy will become substantially impoverished as the capital stock shrinks.
2 6 ~mentioned
s
in the Introduction, it is important
to note that these results are not necessarily inconsistent with debt-deflation being an important factor affecting economic activity between 1929 and 1933. The
finding that deflation could have been anticipated at
horizons of 3-6 months does suggest that simple debtdeflation theories for the propagation of the Great
Depression must rely on the failure of agents to anticipate deflation several years in advance, not several
quarters in advance. To show that debt-deflation was
an important part of the contraction of the early 1930's
it is important to document the accumulation of substantial medium- and long-term debt prior to 1929.
MARCH 1992
This appendix describes the data used in the paper.
Consumer Prices.-The monthly consumer price series was constructed by splicing together two series.
From January 1913 to December 1919 the raw data are
from the U.S. Department of Labor, Bureau of Labor
Statistics (BLS) Consumer Price Index. From January
1920 to December 1940 the raw data are from the
National Industrial Conference Board all-items consumers' vrice index vublished in Robert A. Savre (1948
table 1): It appearsAthatthe BLS did not collect and
publish a monthly series on the prices of consumer
goods during the 1920's and 1930's. The all-items CPI
data that are currently available for this period seem to
have been created from data sampled at a lower frequency and then interpolated using some component
series. The quarterly consumer price series is then
constructed by taking the last observation of each
quarter of the monthly series.
The annual consumer price series is constructed by
splicing the annual Federal Reserve Bank of New York
"estimated cost of living" index to the BLS CPI.
Wholesale Prices.-Data on wholesale prices were
constructed by splicing data from George F. Warren
and Frank A. Pearson (1935 table 1) to the all-commodities wholesale price index published by the BLS
beginning in January 1913.
GNP Deflator.-Prior to 1929, data were taken from
Romer (1988). Beginning in 1929, the data are from
the Bureau of Economic Analysis, National Income
and Product Accounts.
Money Stock.-All data on money are from Friedman and Schwartz (1963 appendix A). Data on M1 and
M2 are taken from their table A-1, and data on the
monetary base are from their appendix A (table A-2).
interest Rates.-Interest-rate data are three-month
time-loan rates at New York banks. The data were
collected by Mankiw and Miron (1985).
Industrial Production.-The new series collected by
Miron and Romer (1989) was used. The data are
monthly, seasonally unadjusted, and they provide a
consistent monthly series beginning in January 1884.
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Prices During the Great Depression: Was the Deflation of 1930-1932 Really Unanticipated?
Stephen G. Cecchetti
The American Economic Review, Vol. 82, No. 1. (Mar., 1992), pp. 141-156.
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[Footnotes]
1
Was the Deflation During the Great Depression Anticipated? Evidence from the Commodity
Futures Market
James D. Hamilton
The American Economic Review, Vol. 82, No. 1. (Mar., 1992), pp. 157-178.
Stable URL:
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4
Inflation and Uncertainty at Short and Long Horizons
Laurence Ball; Stephen G. Cecchetti; Robert J. Gordon
Brookings Papers on Economic Activity, Vol. 1990, No. 1. (1990), pp. 215-254.
Stable URL:
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5
Money and the Price Level Under the Gold Standard
Robert J. Barro
The Economic Journal, Vol. 89, No. 353. (Mar., 1979), pp. 13-33.
Stable URL:
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7
Money and the Price Level Under the Gold Standard
Robert J. Barro
The Economic Journal, Vol. 89, No. 353. (Mar., 1979), pp. 13-33.
Stable URL:
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9
Are Output Fluctuations Transitory?
John Y. Campbell; N. Gregory Mankiw
The Quarterly Journal of Economics, Vol. 102, No. 4. (Nov., 1987), pp. 857-880.
Stable URL:
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9
Forecasting the Depression: Harvard versus Yale
Kathryn M. Dominguez; Ray C. Fair; Matthew D. Shapiro
The American Economic Review, Vol. 78, No. 4. (Sep., 1988), pp. 595-612.
Stable URL:
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15
A Theory of the Term Structure of Interest Rates
John C. Cox; Jonathan E. Ingersoll, Jr.; Stephen A. Ross
Econometrica, Vol. 53, No. 2. (Mar., 1985), pp. 385-407.
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18
Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric
Analysis
Lars Peter Hansen; Robert J. Hodrick
The Journal of Political Economy, Vol. 88, No. 5. (Oct., 1980), pp. 829-853.
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18
A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent
Covariance Matrix
Whitney K. Newey; Kenneth D. West
Econometrica, Vol. 55, No. 3. (May, 1987), pp. 703-708.
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References
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Inflation and Uncertainty at Short and Long Horizons
Laurence Ball; Stephen G. Cecchetti; Robert J. Gordon
Brookings Papers on Economic Activity, Vol. 1990, No. 1. (1990), pp. 215-254.
Stable URL:
http://links.jstor.org/sici?sici=0007-2303%281990%291990%3A1%3C215%3AIAUASA%3E2.0.CO%3B2-2
Money and the Price Level Under the Gold Standard
Robert J. Barro
The Economic Journal, Vol. 89, No. 353. (Mar., 1979), pp. 13-33.
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Financial Fragility and Economic Performance
Ben Bernanke; Mark Gertler
The Quarterly Journal of Economics, Vol. 105, No. 1. (Feb., 1990), pp. 87-114.
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Agency Costs, Net Worth, and Business Fluctuations
Ben Bernanke; Mark Gertler
The American Economic Review, Vol. 79, No. 1. (Mar., 1989), pp. 14-31.
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Are Output Fluctuations Transitory?
John Y. Campbell; N. Gregory Mankiw
The Quarterly Journal of Economics, Vol. 102, No. 4. (Nov., 1987), pp. 857-880.
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The Case of the Negative Nominal Interest Rates: New Estimates of the Term Structure of
Interest Rates during the Great Depression
Stephen G. Cecchetti
The Journal of Political Economy, Vol. 96, No. 6. (Dec., 1988), pp. 1111-1141.
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A Theory of the Term Structure of Interest Rates
John C. Cox; Jonathan E. Ingersoll, Jr.; Stephen A. Ross
Econometrica, Vol. 53, No. 2. (Mar., 1985), pp. 385-407.
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Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
David A. Dickey; Wayne A. Fuller
Econometrica, Vol. 49, No. 4. (Jul., 1981), pp. 1057-1072.
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Forecasting the Depression: Harvard versus Yale
Kathryn M. Dominguez; Ray C. Fair; Matthew D. Shapiro
The American Economic Review, Vol. 78, No. 4. (Sep., 1988), pp. 595-612.
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The Debt-Deflation Theory of Great Depressions
Irving Fisher
Econometrica, Vol. 1, No. 4. (Oct., 1933), pp. 337-357.
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Was the Deflation During the Great Depression Anticipated? Evidence from the Commodity
Futures Market
James D. Hamilton
The American Economic Review, Vol. 82, No. 1. (Mar., 1992), pp. 157-178.
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Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric
Analysis
Lars Peter Hansen; Robert J. Hodrick
The Journal of Political Economy, Vol. 88, No. 5. (Oct., 1980), pp. 829-853.
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Real Wages, Employment, and Inflation
Robert E. Lucas, Jr.; Leonard A. Rapping
The Journal of Political Economy, Vol. 77, No. 5. (Sep. - Oct., 1969), pp. 721-754.
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A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent
Covariance Matrix
Whitney K. Newey; Kenneth D. West
Econometrica, Vol. 55, No. 3. (May, 1987), pp. 703-708.
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