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837
Journal of Economic Literature
Vol. XL (September 2002) pp. 837–880
Modern Hyper- and High Inflations
STANLEY FISCHER, RATNA SAHAY,
and
CARLOS A. VÉGH
1
1. Introduction
I
N HIS CLASSIC WORK
, Phillip Cagan (1956)
studied seven of the eight hyperinflations
that took place between 1920 and 1946.
2
Cagan defined a hyperinflation as beginning
in the month inflation first exceeds 50 per-
cent (per month) and as ending in the month
before the monthly inflation rate drops be-
low 50 percent for at least a year. Although
he did not specify a minimum span of time
for an inflationary episode to qualify as a hy-
perinflation, none of the Cagan seven lasted
less than ten months.
Hyperinflations are largely a modern phe-
nomenon. While the data must be highly im-
perfect, the evidence (table 1) indicates that
many of the famous pre-twentieth-century
inflations were modest by present standards:
the inflation associated with the Black Death
was less than 50 percent per annum, and the
Spanish inflation resulting from the discov-
ery of the New World averaged less than 2
percent and probably never exceeded 15
percent per annum. Inflation in the Roman
empire in the fourth century, following
Diocletian,
3
may in some years have reached
triple-digit levels measured in the prices of
denarius (a small—and getting smaller—
coin) but was very low measured in terms of
the gold solidus (a larger coin).
4
The more
recent inflations summarized in table 1, as-
sociated with wars and paper money, did on
occasion reach triple-digit per-annum levels.
The first recorded inflation that meets
Cagan’s definition of a hyperinflation appears
to be the assignat inflation of revolutionary
France, during which there were at least five
months in 1795–96 in which inflation ex-
ceeded 50 percent (see Forest Capie 1991;
and Thomas Sargent and Francois Velde
1995). The link with the French Revolution
supports the view that hyperinflations are a
modern phenomenon related to the need to
print paper money to finance large fiscal
deficits caused by wars, revolutions, the end of
empires, and the establishment of new states.
Between 1947 and 1984 there were no hy-
perinflations. Since 1984, there have been at
least seven (in six countries) in the market
economies—with the Nicaraguan hyperin-
flation the worst among the seven. By the
same Cagan definition, there were also in
1
Fischer: Citigroup. Sahay: IMF. Végh: econ. dept.,
UCLA. We thank Mary Hallward-Driemeier of the
World Bank for her contributions at an early stage in
the writing of the paper; Leonardo Bartolini, Peter
Doyle, Bob Flood, Javier Hamann, Esteban Jadresic,
Prakash Loungani, Peter Montiel, Maansi Sahay Seth,
Murat Ucer, two anonymous referees, and seminar par-
ticipants at the IMF, World Bank, and AEA meetings
for helpful comments and discussions; and Claire
Adams, Manzoor Gill, Nada Mora, Prachi Mishra, and
Kartikeya Singh for excellent research assistance. The
views expressed in this paper are those of the authors
and not necessarily those of the IMF.
2
The seven hyperinflations were: Austria, Oct.
1921–Aug. 1922; Russia, Dec. 1921–Jan. 1924;
Germany, Aug. 1922–Nov. 1923; Poland, Jan. 1923–Jan.
1924; Hungary I, March 1923–Feb. 1924; Greece, Nov.
1943–Nov. 1944; and Hungary II, Aug. 1945–July 1946.
In addition, there was, by Cagan’s definition, a hyperin-
flation in China from Oct. 1947 to March 1948 (Andrew
Huang 1948).
3
Inflation in the century leading up to Diocletian’s
price control edict in 301 AD appears to have averaged
under 4 percent per annum (Don Paarlberg 1993).
4
This appears to have been an early example of the
adage that inflation is a regressive tax, for the solidus
was reportedly too valuable to be held by the poor.
the past decade hyperinflations in transition
economies, particularly the countries of the
former Soviet Union. Table 2 shows hyper-
inflations during 1956–96, as defined by
Cagan, but excluding episodes that lasted
less than two months.
5
The Serbian case
stands out as the worst among recent hyper-
inflations, with a peak monthly inflation rate
that exceeds those in all the Cagan seven ex-
cept the post-World War 2 Hungarian hy-
perinflation.
6
Interwar controversies over hyperinfla-
tion centered on the question of whether the
process was driven by monetary expansion
(for example Constantino Bresciani-Turroni
1937, and Frank Graham 1930) or the balance
838
Journal of Economic Literature, Vol. XL (September 2002)
TABLE 1
HISTORICAL EPISODES OF HIGH INFLATION
Geometric Max.
Dates of Cumulative Annual Annual
Country/Episode Episodes Duration Inflation
1
Rate of Inflation Inflation Source(s)
Ancient Rome
Diocletian 151–301 151 years 19,900.0 3.6 n.a. Paarlberg (1993)
China/Sung
Dynasty 1191–1240 50 years 2,092.6 6.4 18.0 Lui (1983)
Europe/Black
Death
2
1349–1351 3 years 138.5 33.6 56.3 Paarlberg (1993)
Spain 1502–1600 99 years 315.2 1.4 14.6 Hamilton (1965),
Paarlberg (1993)
France/John Feb. 1717– 47 months 55.2 11.9 1,431.3 Hamilton (1936),
Law
6
Dec. 1720 Paarlberg (1993)
American Feb. 1777– 36 months 2,701.7 203.7 16,098.7 Fisher (1913),
Revolution
3,6
Jan. 1780 Paarlberg (1993)
French Feb. 1790– 73 months 26,566.7 150.5 92,067.6 Capie (1991)
Revolution
4,6
Feb. 1796
U.S. Civil War/ 1862–1864 3 years 116.9 29.4 45.1 Paarlberg (1993),
North Feb. 1861– 51 months 9,019.8 189.2 5,605.7 Lerner (1955)
Confederacy
6
Apr. 1865
Mexican Feb. 1913–
Revolution
5,6
Dec. 1916 47 months 10,715.4 230.6 7,716,100.0 Cardenas and
Manns (1989),
Kemmerer (1940)
China 1938–1947 10 years 2,617,681.0 176.6 612.5 Huang (1948)
1
Inflation expressed in percentage terms.
2
Price of wheat in England.
3
Depreciation of the continental currency (in units per Spanish Dollar), based on prices of beef, Indian corn,
wool, and sole leather.
4
Value of assignat.
5
Pesos per U.S. dollar.
6
Maximum annual inflation based on annualized maximum monthly inflation rate.
5
We exclude episodes lasting less than two months
because many transition economies, especially those in
the former Soviet Union, suffered at least one month of
more than 50-percent inflation when price controls
were lifted. Since these episodes were more in the
nature of a price-level adjustment than an ongoing
process of high inflation, we have changed the defini-
tion to exclude them.
6
The peak monthly rate in the post-World War 2
Hungarian hyperinflation was 41.9
´
10
15
.
of payments.
7
The latter view accorded a
major role in the inflationary process to the
assumed exogenous behavior of the ex-
change rate. According to Bresciani-Turroni,
this view was held throughout the German
hyperinflation by the Reichsbank, bankers,
industrialists, much of the press, and most
German economists. Cagan advanced the
analysis within a monetary framework by in-
cluding the role of expectations, asking
whether the process of expectations forma-
tion itself might have caused hyperinflation,
and concluding—assuming adaptive expec-
tations—that underlying monetary growth
was instead responsible.
Since 1956, the formal analysis of hyperin-
flations has advanced in a number of direc-
tions, each of which brought in its train a
large literature.
8
First, with the development
of the theory of rational expectations, the no-
tion that expectations alone could have
caused hyperinflation became more difficult
to sustain, except if there were multiple equi-
libria, some of them hyperinflationary and
others not. Such an outcome is possible, for
instance, if the inflation tax is subject to the
Laffer curve, as is implied by the demand for
money function assumed by Cagan (Michael
Bruno and Stanley Fischer 1990).
9
The in-
troduction of rational expectations also led to
a more sophisticated econometric treatment
of the demand for money, and therefore to
attempts to estimate money demand func-
tions in hyperinflations under the constraint
of rational expectations (for example,
Thomas Sargent and Neil Wallace 1973).
Second, consideration of inflation as a tax,
formalized for instance in Martin Bailey
(1956), implied a change in emphasis from
monetary to fiscal factors as the root cause of
hyperinflations—with the complication that
in the presence of the Keynes-Tanzi effect
(whereby, due to lags in tax collection,
higher inflation reduces the real value of
government tax revenues), an initially
money-driven inflation could generate a
growing fiscal deficit in an unstable feed-
back process.
10
Third, in a famous article, Sargent (1982)
studied the process of ending hyperinfla-
tions, emphasizing that a credible change in
policies, preferably embedded in legal and
institutional changes, could bring a hyperin-
flation to an end at essentially zero cost.
Along similar lines, the notion that higher
inflation reduces the normal policy lags
meant that there could be scope for hetero-
dox policies, involving for instance tempo-
rary wage and price controls, that would
make it possible to move from a high infla-
tion to a low-inflation equilibrium very rap-
idly and at low output cost.
Fourth, and closely related to Sargent’s
approach, the development of the game-
theoretic approach to policy made it possible
to analyze the concept of credibility (Torsten
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
839
7
It should be noted that, at the time, some analysts
also emphasized the role of expectations; see David
Laidler and George Stadler (1998).
8
Of course, the verbal accounts of some of the inter-
world war authors contain many of the mechanisms
and subtleties developed more formally in the later lit-
erature.
9
In the presence of multiple equilibria, the key
question becomes whether “learning” (or any other
convergence process) will lead the economy to the
“good” (i.e., non-explosive) Laffer curve equilibrium.
While, theoretically, learning does not rule out the pos-
sibility of convergence to sunspot equilibria (Michael
Woodford 1990), experimental evidence suggests that
the economy will tend to converge to a low inflationary
steady-state (Ramon Marimon and Shyam Sunder
1993). Also, as pointed out by Woodford (1990), there
are many different ways—all equally plausible and sat-
isfying some weak criteria for rational decision-making—
of specifying a learning process. For the case of linear
rational expectations models, Albert Marcet and
Thomas Sargent (1995) analyze the speed of conver-
gence in a setting in which agents learn by fitting
ARMA models to a subset of state variables. For details
on learning and its relation to the rational expectations
hypothesis, see the excellent review by George Evans
and Seppo Honkapohja (2001).
10
However, high inflation could actually reduce the
fiscal deficit if the real value of government expendi-
ture falls by more than real tax revenues. Eliana
Cardoso (1998) points to the so-called Patinkin effect,
the converse of the Tanzi effect, which could arise if,
for instance, nominal government spending is fixed and
its real value reduced by inflation—an equilibrating
mechanism that was operative during Brazilian high
inflations.
Persson and Guido Tabellini 1990), thus
providing analytic content for a concept fre-
quently invoked by central bankers and
other policy makers.
In addition to the deepening understand-
ing of hyperinflation, the period since 1956
has also seen the introduction of the impor-
tant concept of chronic inflation by Felipe
Pazos (1972). Pazos emphasized that the in-
flationary problem in many countries, espe-
cially in Latin America, was not so much one
of occasional outbursts of hyperinflation fol-
lowed by stability, but rather that of an ongo-
ing process of double-digit (per annum) in-
flation, rising occasionally to triple digits.
11
Institutional mechanisms created to protect
against the effects of inflation make the
problem more deep-seated and difficult to
deal with. In particular, Pazos emphasized
the difficulties for disinflationary policies
caused by overlapping, often indexed, wage
contracts. Devastating as hyperinflations are
when they occur, the problem of moderate
or chronic inflation better describes the
form in which inflation confronts most coun-
tries that have suffered the effects of infla-
tion in the last half-century.
Increasing evidence on the real effects of
inflation-stabilization programs in chronic-
inflation countries brought to the forefront
the possibility that—contrary to conventional
wisdom—disinflation may lead to an initial
expansion in economic activity—particularly
in GDP and consumption—as argued by
840
Journal of Economic Literature, Vol. XL (September 2002)
11
Marcet and Juan Pablo Nicolini (1998) study a
model with learning that can explain sudden outbursts
of high inflation in chronic inflation countries. In a sim-
ilar vein, see Carlos Zarazaga (1993).
TABLE 2
HYPERINFLATIONS, 1956–96 (CAGAN DEFINITION)
1,2
During Hyperinflation
Duration Cumulative
Countries Dates of Episode (in months) Inflation
Angola
3
Dec. 94–Jun. 96 19 62,445.9
Argentina May 89–Mar. 90 11 15,167.0
Bolivia Apr. 84–Sep. 85 18 97,282.4
Brazil Dec. 89–Mar. 90 4 692.7
Nicaragua Jun. 86–Mar. 91 58 11,895,866,143
Congo, Dem. Rep. Oct. 91–Sep. 92 12 7,689.2
Congo, Dem. Rep. Nov. 93–Sep. 94 11 69,502.4
Armenia Oct. 93–Dec. 94 15 34,158.2
Azerbaijan Dec. 92–Dec. 94 25 41,742.1
Georgia Sep. 93–Sep. 94 13 76,218.7
Tajikistan Apr. 93–Dec. 93 9 3,635.7
Tajikistan Aug. 95–Dec. 95 5 839.2
Turkmenistan Nov. 95–Jan. 96 3 291.4
Ukraine Apr. 91–Nov. 94 44 1,864,714.5
Serbia Feb. 93–Jan. 94 12 156,312,790.0
Sources: IMF, International Financial Statistics; national authorities, and IMF staff estimates.
1
Cagan defines hyperinflation “as beginning in the month the rise in prices exceeds 50 percent and as ending in
the month before the monthly rise in prices drops below that amount and stays below for at least a year. The defi-
nition does not rule out a rise in prices at a rate below 50 percent per month for the intervening months, and
many of these months have rates below that figure.”
2
Excludes the following one- and two-month episodes. In the market economies, Chile (Oct. 1973) and Peru
(Sep. 1988, July–Aug. 1990). In the transition economies, Estonia (Jan.–Feb. 1992), Latvia (Jan. 1992), Lithuania
Miguel Kiguel and Nissan Liviatan (1992)
and Carlos Végh (1992). The recession typi-
cally associated with disinflation appears to
occur later in the programs. Interestingly,
the initial expansion appears to be related to
the use of the exchange rate as the main
nominal anchor. Several types of models
have been developed to explain these puz-
zling stylized facts, which emphasize the role
of inflation inertia, lack of credibility, pur-
chases of durable goods, and supply-side ef-
fects (see Guillermo Calvo and Végh 1999
for a critical review).
Cagan (1956, p. 25) justified treating hy-
perinflations separately on the grounds that
they permit “relations between monetary
factors . . . to . . . be studied . . . in what
almost amounts to isolation from the real
sector of the economy.” In this paper, we fol-
low Cagan’s approach of studying inflation-
ary episodes, but rather than confine our-
selves to hyperinflations strictly defined—
which are quite rare—we examine the still
relatively rare episodes of very high infla-
tion, defined as inflations in excess of 100
percent per annum (an exact definition is
provided below).
We do this for four main reasons. First, in-
flations in this range are sufficiently disruptive
that in practice virtually no country has been
willing to live with them for more than a few
years. Second, both popular usage—which of-
ten refers to triple digit inflation as hyperinfla-
tion—and the literature have tended to treat
100 percent as a distinguishing line between
high and extraordinary inflations. Third, in
studying episodes of extreme inflation, it is
useful to have the extra statistical degrees of
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
841
TABLE 2 (Cont.)
During Hyperinflation Twelve Months After Hyperinflation
Monthly Inflation Rate
Monthly Inflation Rate
Geometric Geometric
Average Median Highest Average Median Highest
40.3 36.0 84.1 9.5 5.3 38.1
58.0 61.6 196.6 12.0 11.2 27.0
46.6 51.8 182.8 5.7 2.7 33.0
67.8 70.2 80.8 14.8 14.4 21.5
37.8 31.4 261.2 1.8 0.8 20.3
43.8 35.2 114.2 15.9 12.6 40.9
81.3 65.0 250.0 12.9 12.8 26.2
47.6 44.5 437.8 2.4 2.0 7.8
27.3 23.1 64.4 5.2 3.3 27.8
66.6 66.3 211.2 0.4 0.9 13.0
49.5 36.4 176.9 0.1 3.3 6.6
56.5 63.0 78.1 2.9 2.1 19.6
57.6 55.7 62.5 11.2 9.7 25.0
25.0 14.9 285.3 10.9 7.7 28.4
228.2 54.2 175,092.8 1.0 0.2 12.4
(Jan. 1992), Krygyz Republic (Jan. 1992), and Moldova (Jan.–Feb. 1992). In addition, we also excluded Belarus
(April 1991, Jan.–Feb. 1992), Kazakstan (April 1991, Jan. 1992), Russia (April 1991, Jan. 1992), and Uzbekistan
(April 1991, Jan.–Feb. 1992) even though by Cagan’s definition these episodes lasted more than two months, as
they appear related to two price jumps (April 1991, and Jan.–Feb. 1992).
3
Period after hyperinflation is from July–Dec. 1996.
freedom offered by the larger sample of coun-
tries that have experienced very high inflation,
rather than hyperinflations. Fourth, as it turns
out, certain simple economic relationships
stand out more clearly in high inflations than
they do in normal conditions.
We start by characterizing in section 2 the
dynamic behavior of inflation in different
ranges, first by listing the frequency of infla-
tionary episodes in different ranges, and
then by using transition matrices to assess, in
particular, whether inflationary dynamics
are different at high inflation rates. For the
remainder of the paper we concentrate on
episodes of very high inflation. In our defi-
nition (formally stated in section 2), a “very
high-inflation episode” takes place when the
twelve-month inflation rates rises above 100
percent. Based on this formal definition, we
identify 45 such episodes in 25 countries. In
section 3, we proceed to examine several
mechanisms that are basic to the analysis of
inflation such as the relationship between
money growth and inflation on the one hand
and among fiscal deficits, seigniorage, and
inflation on the other. We also examine the
causal relation among money, inflation, and
exchange rates, as well as the concept of in-
flation inertia. In section 4, we shift gears
and focus on (i) the behavior of macroeco-
nomic variables during high-inflation peri-
ods compared with low-inflation periods and
(ii) the real effects of disinflation. Section 5
concludes by summarizing the results and,
in the process, identifying ten key stylized
facts associated with very high inflation.
2. Characteristics of High Inflation
2.1 Inflationary Episodes and Dynamics
Table 3a presents data for 133 market
economies on the frequency of inflationary
episodes for specified ranges of the inflation
rate in the period 1960–96 (or, if data were
not available, the longest available subsam-
ple). An inflationary episode is defined as
taking place when the twelve-month infla-
tion rate rises above the lower bound of the
specified range. In that case, we take the
start of the episode to be the first month of
that twelve-month period, and the last
month to be the first month before the
twelve-month inflation rate falls below the
lower bound and stays there for at least
twelve months.
12
For example, take the 100-
percent threshold, and imagine a country
whose twelve-month inflation rate is above
100 percent only in, say, June 1970. Then,
under our definition, this country experi-
enced a 100-percent inflationary episode
from July 1969 to June 1970. Notice that,
under this definition, the minimum duration
of an episode is twelve months.
Although a variety of adjectives have been
used to categorize inflationary episodes, for
instance moderate, high, extreme, and hyper-
(Rudiger Dornbusch and Fischer 1993),
there is as yet no agreed convention.
13
Seen
in international perspective, the ranges in the
table can be regarded as “moderate to high”
(for the 25–50 percent range), and “high” (for
the 50–100 percent range), with the remain-
ing categories constituting at the least “very
high” inflation rates—although 25 percent
per annum would not be regarded as moder-
ate in many countries.
Table 3a tells us that most countries, most
of the time, experience inflation of less than
25 percent per annum.
14
However, over two-
thirds (92) of the countries in the sample ex-
perienced an episode of more than 25-percent
per-annum inflation. Over half (49) of those
countries in turn suffered from an episode in
excess of 50 percent per annum, while 25
842
Journal of Economic Literature, Vol. XL (September 2002)
12
Although our definition is modeled on that of
Cagan (1956) in his classic article, it differs in one im-
portant respect from his: namely, Cagan based his defi-
nition on monthly rates of inflation whereas ours is
based on twelve-month inflation rates.
13
The ranges used in this paper draw largely from
previous work. One way to proceed would be to look
for breaks in the transition probabilities. If any were
found, this would suggest that inflation behaves differ-
ently in different ranges. We follow this approach only
in examining some results of Michael Bruno and
William Easterly (1995) discussed later in this section.
14
The total number of country-months in the sample
included in table 3a is 44,910. For 80.1 percent of those
months, the monthly inflation rate is less than 1.9 per-
cent (corresponding to an annual rate of 25 percent).
experienced an inflationary episode of more
than 100 percent and eleven countries suf-
fered from at least one episode of more than
400-percent per-annum inflation. The average
duration of the inflationary episodes is re-
markably similar—and, at three–four years,
surprisingly long—while the maximum dura-
tion declines as the inflation rate rises. Only
one country (Argentina) that experienced an
inflationary episode in excess of 400 percent
per annum repeated the experience.
Data on inflationary episodes in 28 transi-
tion economies are presented in table 3b. All
of these economies experienced an episode
of inflation of more than 25 percent; indeed
most of them (19 out of 28) suffered from an
inflationary episode in excess of 400 percent
per annum. Most of the extreme inflations in
these countries were at the start of the transi-
tion process when, in light of large monetary
overhangs, the price level jumped in re-
sponse to price liberalization. For this group
of countries, over the period since prices
were freed,
15
monthly inflation was generally
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
843
TABLE 3A
MARKET ECONOMIES: FREQUENCY OF EPISODES BY LEVEL OF INFLATION, 1960–96
1
(monthly data)
Range of Duration (in months)
Annualized Number of Number of
Inflation
2
Episodes
3
Countries Average Minimum Maximum
25 and above 212 92 41.0 12 313
50 and above 87 49 43.4 12 216
100 and above 45 25 40.0 12 208
200 and above 17 13 47.2 15 106
400 and above 13 11 43.9 17 98
TABLE 3B
FREQUENCY OF EPISODES BY LEVEL OF INFLATION, 1987–96
1
(monthly data)
Range of Duration (in months)
Annualized Number of Number of
Inflation
2
Episodes
3
Countries Average Minimum Maximum
25 and above 30 28 56.5 16 104
50 and above 25 25 53.0 14 103
100 and above 25 23 45.9 12 100
200 and above 24 22 40.6 13 59
400 and above 20 19 39.7 13 59
Sources: IMF, International Financial Statistics, national authorities, and IMF desk economists.
1
The starting period for market economies (133 in total) was determined by data availability, while for transition
economies (28 in total) by the period in which prices were freed on a large scale.
2
25% per annum
=
1.9% per month; 50% per annum
=
3.4% per month; 100% per annum
=
5.9% per month;
200% per annum
=
9.6% per month; 400% per annum
=
14.4% per month.
3
See text for definition of an inflationary episode.
15
The starting dates selected depend on when
prices were freed and on data availability. Thus,
they tend to vary across the transition economies,
being 1991 for most of Eastern Europe and
Mongolia, 1992 for the former Soviet Union, 1988
for Poland, 1990 for the former Yugoslavian states
and Vietnam, 1986 for China, and 1976 for
Hungary.
above 25 percent per annum,
16
although in-
flation in most of them is now into the low
double- or even single-digit annual rates.
In table 4, we present related (to table 3a)
information on the statistical properties of
inflation in the market economies, in the
form of a transition matrix. Categorized by
the inflation rate in year T (rows), these ma-
trices show the frequencies with which the
inflation rate in the subsequent year (T
+
1)
is in different ranges.
17
For instance, if the
inflation rate in year T is in the range of
25–50 percent, the probability that it will be
less than 25 percent in the following year is
46.5 percent (corresponding to the entry in
the second row, first column).
Three features of table 4 are noteworthy.
First, when the inflation rate is less than 25
percent, it is very likely (95.4 percent prob-
ability) to be in that range in the following
year. In contrast, for all higher inflation
ranges (excluding the last range which has
no upper bound), the probability that infla-
tion will stay in its current range is less than
50 percent.
18
Second, consider the columns
labeled “Probability will rise” and “Prob-
ability will fall.” The probability that infla-
tion will rise to a higher range increases
from 4.6 percent in the lowest range to 47.1
percent in the next-to-last range.
19
This
captures the idea that higher inflation is
more explosive. Third, until inflation
reaches the 200-percent level, it is still
more likely to fall than rise.
Finally, combining table 2 with informa-
tion in table 3a, we see that of the eleven
market economies that experienced
episodes of inflation of more than 400 per-
cent,
20
more than half (six) also had a hy-
perinflation as defined by Cagan. This cer-
tainly suggests that extreme inflations
carry with them a high danger of hyperin-
flation.
844
Journal of Economic Literature, Vol. XL (September 2002)
TABLE 4
MARKET ECONOMIES: TRANSITION MATRIX
1
Range of
Year T + 1 Probability
Number of
Inflation
<
25 25–50 50–100 100–200 200–400
>
400 Will Rise Will Fall Observations
Year T
< 25 95.4 4.1 0.4 0.1 0.0 0.0 4.6 0.0 3343
25–50 46.5 38.4 13.3 1.4 0.4 0.0 15.1 46.5 279
50–100 10.6 23.0 47.5 14.8 1.6 2.5 18.9 33.6 122
100–200 10.1 11.9 18.6 42.4 15.3 1.7 17.0 40.6 59
200–400 11.7 5.9 5.9 11.8 17.6 47.1 47.1 35.3 17
> 400 2.7 0.0 8.1 13.5 8.1 67.6 0.0 32.4 37
Total 3857
Source: IMF, International Financial Statistics.
1
Calculated as number of observations in year T
+
1 in the corresponding column range as a percentage of num-
bers of observations in the corresponding row range in year T. (Rows add up to 100.) Based on pooled, cross-
section annual data 1960–96, from 133 countries.
16
Of a total sample of 2,023 monthly inflation rates,
only 37 percent were below 1.9 percent.
17
We have also calculated a transition matrix for the
corresponding monthly rates of inflation. For all but
the 200–400 percent per-annum range, the probability
of inflation remaining in a given range is smaller with
monthly than with annual data. Further, the probability
that the inflation rate will fall is uniformly higher for
the monthly than the annual data. These results are
due mainly to the greater variability in monthly infla-
tion rates compared to annual rates.
18
In discussing tables 4 and 5, we refer to frequen-
cies and probabilities interchangeably.
19
However, there are relatively few observations in
the higher inflation ranges.
20
The eleven countries are Angola, Argentina,
Bolivia, Brazil, Chile, Democratic Republic of Congo,
Israel, Lebanon, Nicaragua, Peru, and Suriname.
2.2 Very High Inflations
In the remainder of this paper, most of
our attention will focus on episodes of very
high inflation as defined in section 2. This
definition does not require the monthly in-
flation rate to be within the range every
month, nor does it imply that the average
inflation rate within an episode necessarily
exceeds 100 percent per annum.
21
Detailed data on the 45 episodes of very
high inflation in 25 countries are presented in
table A1 (in the appendix). Twelve of the
countries (eighteen episodes) are in South
America or the Caribbean (Argentina, Bolivia,
Brazil, Chile, Costa Rica, Jamaica, Mexico,
Nicaragua, Peru, Suriname, Uruguay, and
Venezuela), nine countries (nineteen
episodes) are in Africa (Angola, Democratic
Republic of the Congo, Ghana, Guinea-
Bissau, Sierra Leone, Somalia, Sudan,
Uganda, and Zambia) with Afghanistan (two
episodes), Israel (one episode), Lebanon
(three episodes) and Turkey (two episodes)
completing the list. The longest episodes were
in Argentina (over seventeen years) and Brazil
(over fifteen years); the Democratic Republic
of the Congo (formerly Zaire) suffered from
six episodes totaling fifteen years. The sur-
prise in these data is the number of very high-
inflation episodes in African countries, whose
inflationary experience has been studied
much less than that of many other countries in
the group, particularly a number of Latin
American countries and Israel.
22
Bruno and Easterly (1995) present data
suggesting that 40 percent per annum is a
critical inflation threshold, above which
the probability of inflation rising to 100
percent per annum becomes much larger.
Table 5, which uses more finely defined in-
flation ranges than table 4, shows that the
probability of annual inflation rising in-
creases as the inflation rate rises toward
100 percent. These data confirm the impres-
sion that inflation tends to become more
unstable as it rises. Even so, there is no
inflation range in table 5 for which inflation
is more likely to rise than fall. Nor does
there seem to be a significant discontinuity
at 40-percent inflation.
Tables 2 through 5 present useful charac-
terizations of different aspects of the infla-
tionary process, with an emphasis on high
inflations. In summary, most of the time, in
most countries, inflation is low, and low in-
flation is stable. However, since 1960, most
countries have suffered from at least one
episode of inflation of more than 25 percent
per annum, and as many as 25 (out of 133)
market economies have experienced an
episode of very high inflation (i.e., twelve-
month inflation above 100 percent).
Further, the data suggest that inflation is
more likely to increase the higher it is or,
equivalently, that higher inflation is rela-
tively more unstable than lower inflation.
3. Inflationary Mechanisms
Having documented the dynamic behavior
of inflation, the natural next step is to try to
determine what are the key macroeco-
nomic variables that underlie inflationary
processes.
23
To that effect, this section first re-
visits and confirms a basic tenet of monetary
economics: in the long run, money growth
and inflation are highly correlated. In this (ad-
mittedly narrow) sense, therefore, “inflation is
always and everywhere a monetary phenome-
non,” as famously argued by Milton Friedman
(1963). While a useful starting point, the high
correlation between money growth and infla-
tion actually raises more questions than it an-
swers. The first question is causation: does
money cause inflation? Or is there reverse
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
845
21
This is because of the end-point requirement in
the definition; namely, that the twelve-month rate stay
below 100 percent for at least twelve months for an
episode to end. It can be seen from table A1 that in
thirteen of the 45 episodes, the (geometric) average in-
flation rate within an episode is less than 100 percent
per annum. Note also that the end of two episodes (in
Congo and Venezuela) is dictated by the end of the
sample period (December 1996).
22
See Carmen Reinhart and Kenneth Rogoff (2002)
for a recent analysis of high inflation in Africa.
23
From this point onwards—and since we will be
mostly looking at long-run relationships—we will re-
strict our attention to market economies.
causation from inflation to money/exchange
rate? Our basic finding is that, more often
than not, causation (in the Granger sense)
runs from exchange-rate changes and inflation
to money growth. We interpret this result,
however, as saying that once inflation has been
triggered, monetary policy has typically been
accommodative, thus allowing inflation to be
driven by temporary shocks and by its own dy-
namics (i.e., inflation persistence). This leads
to the next question: what triggers inflation to
begin with? The standard explanation is fiscal
imbalances. By and large, we find that fiscal
deficits indeed explain high inflation using
standard regression techniques. Finally, we
tackle the issue of inflation persistence by pro-
viding two definitions based on autoregressive
processes, which allow us to quantify persis-
tence and examine how it varies with the level
of inflation.
3.1 Data and Methodology
Since several of the econometric exercises
in this section rely on a common data set and
regression techniques, we first describe the
sample and the common methodology be-
hind them. We used as large a sample as pos-
sible with regard to both the number of coun-
tries and the time period covered. However,
both the quality and availability of data on
several macroeconomic variables varied
widely across countries. To maintain consis-
tency across all the panel regressions that
were run and to maximize the number of
countries included in the sample, we imposed
the condition that a country be included in
the sample only if there were at least ten an-
nual observations during the 1960–95 period
for each of the five variables—inflation, re-
serve money, broad money (including foreign
currency deposits), fiscal balance, and nomi-
nal GDP—that were needed for running the
regressions. Consequently, 94 countries were
selected (all market economies), each with at
least ten annual observations.
For each type of regression reported be-
low, we allowed for different coefficients for
high- and low-inflation countries, where the
high-inflation countries were the 24 in this
sample that experienced at least one episode
of very high inflation (as described in the
previous section).
24
In the panel regressions,
we also allowed for lags of the independent
variables to affect the dependent variable of
846
Journal of Economic Literature, Vol. XL (September 2002)
TABLE 5
MARKET ECONOMIES: PROBABILITY OF INFLATION BEING ABOVE 100 PERCENT NEXT YEAR
DEPENDING ON INFLATION IN THE CURRENT YEAR
1
Probability that Inflation Next Year
Range of Will Be Above Will Will Number of
Inflation 100 Percent Rise Fall Observations
Current Year
<
20 0.1 6.0 0.0 3171
20–40 1.0 12.6 41.8 388
40–60 7.5 25.2 41.1 107
60–80 15.7 29.4 41.2 51
80–100 37.0 37.0 48.1 27
>
100 71.7 0.0 28.3 113
Total 3857
Source: IMF, International Financial Statistics.
1
Calculated as number of observations in a given range followed by observations in the 100% and above range,
next range, and range below, respectively, as percentage of observations in the initial range (pooled, cross-section
annual data 1960–96, from 133 countries).
24
The only high-inflation country not included (due
to lack of data) is Afghanistan.
interest. In addition, subsamples that in-
cluded only the high-inflation countries
were tested to see whether the coefficients
during their high-inflation episodes dif-
fered from their low-inflation episodes.
In all panel regressions we allowed for coun-
try and period-specific effects.
To set the stage, figure 1 shows the averages
of inflation, money growth (M2), seigniorage
(as percent of GDP), and fiscal balance (as
percent of GDP) for high-inflation countries
(24 countries) and low-inflation countries (70
countries). As is evident from figure 1, high-
inflation countries also exhibit high levels of
money growth, seigniorage, and fiscal deficit.
The remainder of this section will formally
examine these relationships.
3.2 Money and Inflation
Figure 2 and table 6 show the cross-
sectional (long-run) relationship between in-
flation and money growth, with each observa-
tion representing the simple average over the
sample period of the inflation and the money
growth rates, each defined as ln(1
+
x/100)
where x is the corresponding annual rate. As
shown, the relationship between money
growth and inflation is extremely strong and
close to one-to-one.
25
The regression coeffi-
cient is in fact 1.115 and highly significant
(table 6, column 1). Furthermore, the rela-
tionship holds even when the sample is bro-
ken up into high- and low-inflation countries
(table 6, column 2). In the long run, there-
fore, the data show a very strong relationship
between money growth and inflation.
Does the money-inflation link remain
valid in the short run? To answer this ques-
tion, we ran a panel regression with annual
data in which, in addition to allowing for dif-
ferent coefficients on money growth in the
low- and high-inflation countries, we also al-
low for two lags of money growth. We then
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
847
200
Inflation M2
Figure
1. Inflation, Money Growth, Seigniorage, and Fiscal Balance
1
1
High-inflation countries as defined in text. Each bar is calculated by taking the average for all countries in that group for each
year, and then averaged over all the years. 94 countries in total, each with ten or more observations.
150
100
50
0
200
High inflation
countries
Low
inflation
countries
150
100
50
0
Seigniorage Fiscal Balance
6
High inflation
countries
Low inflation
countries
4
2
0
–6
–2
–4
6
4
2
0
–6
–2
–4
25
The outlier in figure 1 is Nicaragua (the further-
most from the regression line).
take a subsample that includes only high-
inflation countries and test for different co-
efficients on high- and low-inflation episodes.
We find that while the relationship be-
tween money and inflation remains highly
significant (table 6, columns 4 and 5) for both
groups of countries, the coefficient for low-
inflation countries is much lower, a result
that is perhaps not surprising given that we
are looking at a short-run relationship and
the fact that GDP growth is not taken into
account in the regressions. When two lags on
money growth are included in the panel re-
gression (table 6, column 5), the coefficients
on both contemporaneous and lagged money
growth are significant and different across
high- and low-inflation countries. The con-
trast between high- and low-inflation coun-
tries in the speed with which the effects of
money growth are transmitted is quite dra-
matic: the bulk of the inflationary effects of
money growth occurs remarkably early in the
high-inflation countries; in contrast, in low-
inflation countries the effects are distributed
evenly across the current and previous peri-
ods. In the panel subsample with only high-
inflation countries (table 6, columns 6 and 7),
the previous results of a strong effect of
money growth on inflation carry through. We
also find a differential effect during high-
and low-inflation episodes within high-infla-
tion countries, which is likely to be due to (i)
GDP growth being more important relative
to the inflation rate during low-inflation
years, and (ii) the negative impact of high in-
flation on the demand for money.
26
In line
with our previous findings, adding lags shows
that the bulk of the effects takes place con-
temporaneously (table 6, column 6).
In sum, the data show that the inflation-
money growth link is exceptionally strong,
both in the long and short run. While the re-
lationship may not necessarily be instanta-
neous nor precisely one-for-one, there can
848
Journal of Economic Literature, Vol. XL (September 2002)
1.2
0 0.2
Figure
2. Inflation and Money (M2) Growth
1
1960–95 averages
1
Slope of regression line is 1.115 with a t-statistic of 12.13; 94 countries in total, each with 10 or more observations.
0.6
0.8
1
0.4
0.2
0
1.2
0.6
0.8
1
0.4
0.2
0
0.4 0.6
LN(1 + M2 Growth)
LN(1 + inflation/100)
0.8 1 1.2
26
We could not reject the OLS model in favor of a
fixed-effects one, indicating the overwhelming effect of
money growth on inflation that is common across the
high-inflation countries.
TABLE 6
INFLATION AND MONEY GROWTH
DEPENDENT VARIABLE: INFLATION RATE
1,2
(T-STATISTICS IN PARENTHESES)
Annual Panel High
Independent Cross-Section Annual Panel Inflation Countries
Variables
OLS OLS OLS Fixed
4
Fixed
4
OLS
6
Fixed
4,7
(1) (2) (3) (4) (5) (6) (7)
Intercept 0.069
***
0.047
***
( 4.96) ( 8.19)
Intercept/hi
3
0.041 0.100
**
( 0.87) (2.10)
Intercept/low
3
0.028
***
0.059
***
( 3.13) (4.26)
M2
1
1.115
***
0.972
***
(12.13) (30.64)
M2/hi
1,3
1.091
***
1.011
***
0.886
***
0.978
***
0.881
***
(8.160) (109.70) (74.75) (21.86) (17.30)
M2/low
1,3
0.804
***
0.219
***
0.165
***
0.513
***
0.421
***
(11.92) (7.50) (5.57) (9.97) (6.37)
M2/hi( 1)
1,3,5
0.242
***
0.228
**
(16.33) (3.89)
M2/low( 1)
1,3,5
0.190
***
0.152
***
(6.40) (2.57)
M2/hi( 2)
1,3,5
0.078
***
0.085
( 6.54) ( 1.17)
M2/low( 2)
1,3,5
0.111
***
0.022)
(3.78) ( 0.98)
R-squared 0.917 0.925 0.855 0.902 0.922 0.919 0.937
Adj. R-squared 0.916 0.923 0.855 0.897 0.917 0.918 0.933
Observations 94 94 2318 2318 2130 410 380
Sources: IMF, International Financial Statistics; authors’ estimations.
Note: Significance at the 10-, 5-, and 1-percent level is indicated by one, two, and three stars, respectively.
1
Inflation rate if defined as ln(1
+
inflation/100), money growth as ln(1
+
M2 growth). Minimum of 10 observa-
tions per country.
2
All results corrected for heteroskedasticity if it existed.
3
Hi and low refer to coefficients for high- and low-inflation countries or high- and low-inflation episodes.
4
Fixed refers to a fixed-effects model with both country and time dummies, both of which are significant unless
otherwise indicated.
5
The number in parentheses next to the independent variables refers to the number of lags.
6
Fixed effects model of this regression was not significant.
7
Time dummies not significant.
be no doubt that inflation can be ended if
the monetary taps are turned off.
27,28
In this
sense, therefore, our evidence overwhelm-
ingly confirms what every schoolchild
knows: inflation is always and everywhere a
monetary phenomenon. This, however, is
only the beginning of wisdom.
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
849
turn off the monetary taps permanently, the under-
lying fiscal problems must be addressed.
Otherwise, low inflation will only be purchased at
the cost of future high inflation (i.e., Sargent and
Wallace’s 1981 celebrated unpleasant monetarist
arithmetic).
27
We are aware that in talking about causation we
have taken a step that goes beyond the inflation-money
growth correlations. But it is a short step, since money
growth is always potentially controllable—if necessary
with a change in monetary operating practices.
28
Naturally, for the government to be able to
3.3 Money, Exchange Rates, and Inflation
With the money-inflation link established,
there remains the question: What drives
money growth? The question is relevant be-
cause high inflations are not popular, and it
is reasonable to believe that it is rare for gov-
ernments to take a deliberate policy decision
to have a high inflation—even if a set or se-
quence of policy decisions produces a high
inflation.
29
The usual answer to the question
of what drives money growth is fiscal
deficits: in this view, inflation is a fiscal phe-
nomenon. We shall turn to this view shortly.
An alternative answer to what drives
money growth is that rapid money growth,
and hence high inflation, is the unintended
consequence of inappropriate monetary
policies, for instance policies directed at
producing real outcomes that are inconsis-
tent with the real equilibrium of the econ-
omy, be it for unemployment, the real ex-
change rate, real wages, or the real interest
rate.
30
For instance, as noted in the intro-
duction, there was an active controversy
during and after the German hyperinflation
over whether inflation was caused by money
growth or the balance of payments. The lat-
ter view can be made consistent with the ev-
idence that inflation is a monetary phenom-
enon by thinking of monetary policy as
seeking to maintain a constant real exchange
rate in circumstances where the nominal ex-
change rate is being moved by exogenous
forces (e.g., speculation, access to external
loans, terms of trade shocks, reparation pay-
ments, and so forth).
An examination of the short-run dynamics
of money, inflation, and the exchange rate
should shed light on the issue of whether
monetary policy reacts to or leads inflation
and the exchange rate. To try to disentangle
the dynamic relationships—in particular to
see whether money growth leads or lags infla-
tion—we conducted Granger-causality tests
by running vector autoregressions (VARs) in a
three-variable system containing the inflation
rate, nominal exchange rate (percentage
change), and money growth. The results are
based on data from only eight of the 24 mar-
ket economies. The data consisted of quar-
terly series for the longest sample period for
which data were available for each country
(see table 7 for details).
31
An analysis of the
remaining seventeen very high-inflation
countries was not conducted because of large
gaps in the availability of time-series data.
For each country, we first ran an unre-
stricted VAR. We then ran a series of re-
stricted VARs by excluding each variable,
one at a time, from the equations for the
other two variables (still in the three-
variable system) and conducted chi-squared
tests to see whether the exclusion of these
variables is rejected. Table 7 presents the re-
sults of the three-way Granger causality
tests. Seasonal dummies were used only if
they were jointly significant at the 5-percent
level in the unrestricted VAR regression.
The most appropriate lag length was chosen
on the basis of statistical significance.
32
The last three columns in table 7 report
whether a chi-squared test rejects the exclu-
sion of the variable of interest from the VAR
regressions at the 5-percent level (two stars),
the 10-percent level (one star), or does not
reject the exclusion (a dash). For example, in
the case of Argentina, the results indicate
that exchange-rate movements Granger-
cause money growth and inflation, while in-
flation and money growth do not Granger-
cause each other or changes in the exchange
rate. The overall picture that emerges is that
850
Journal of Economic Literature, Vol. XL (September 2002)
29
It is sometimes argued that the Soviet inflation of
the early-1920s was a deliberate act of policy; it has
also been argued that the German hyperinflation was
an attempt to demonstrate that reparations could not
be paid.
30
This is the so-called “shocks and accommodation”
view of monetary policy in chronic inflation countries;
see, among others, Charles Adams and Daniel Gros
(1986), Bruno and Fischer (1986), Bruno and R.
Melnick (1994), and Calvo, Reinhart, and Végh (1995).
31
The sample period is not confined to very high-
inflation episodes.
32
We also ran the VARs imposing a uniform three-
quarter lag length. The results on the statistical signifi-
cance of the exclusion restrictions were unchanged, ex-
cept in the case of Somalia.
Granger causality appears to run more often
from exchange-rate changes or inflation to
money growth than vice versa.
33
These regression results should not be in-
terpreted as implying that, in some circum-
stances, inflation is not caused by money
growth, or that inflation could not be stopped
if monetary policy changed and money growth
was reduced to a very low level.
34
One expla-
nation for the creation and persistence of very
high inflation which we find plausible is that
inflation initially emerges as an undesired re-
sult of other policy decisions (the obvious can-
didate being fiscal imbalances), and continues
because policymakers often tend to accom-
modate shocks (the shocks-and-accommoda-
tion view mentioned above)—thus allowing
inflation to be driven by exogenous shocks and
its own dynamics—and/or are reluctant to in-
cur the costs needed to get rid of chronic in-
flation. There may be several reasons for such
reluctance. First, once the public expects high
inflation to continue, it may become too costly
for the government not to validate the public’s
expectations (see, for instance, Calvo 1988a).
Second, even if the mechanisms were found
to credibly commit to low inflation, political
battles over the distribution of the required
fiscal adjustment may lead to a period of inac-
tion that will erode the political support to
proceed further (Alberto Alesina and Allan
Drazen 1991). As a result, things often need to
get worse (in the form of outbursts of ex-
tremely high inflation as in Argentina and
Brazil in the late 1980s) before they get better
(Drazen and Vittorio Grilli 1993).
3.4 Fiscal Deficits, Inflation,
and Seigniorage
As mentioned above, the most commonly
held view about the ultimate origins of
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
851
TABLE 7
VAR-BASED GRANGER CAUSALITY TESTS IN SELECTED HIGH-INFLATION COUNTRIES
Years Annualized Appropriate Exchange
and Average Seasonal Lag Length Money Rate
Country Quarters Inflation Dummies
1
(in quarters)
2
Growth
3
Inflation
3
Change
3
Argentina 1967:1–1991:1 191.8 No 1 — —
**
Ghana 1966:1–1996:4 32.6 Yes 3
* ** *
Jamaica 1970:3–1996:4 20.7 Yes 1 — —
**
Peru 1967:1–1996:4 99.1 Yes 5
** ** **
Somalia 1967:1–1989:3 26.2 Yes 2 —
**
—
Sudan 1966:1–1994:2 32.6 Yes 3
** ** **
Turkey 1970:1–1996:4 46.0 Yes 1
**
— —
Uruguay 1967:1–1996:4 59.3 Yes 2 —
** **
Sources: International Finance Statistics, International Monetary Fund; and authors’ calculations.
1
Seasonal dummies were used in the VAR regressions when they were jointly significant at the 5-percent level.
2
Lag length determined by the one that was most significant.
3 **
=
significant at 5-percent level.
*
=
significant at 10-percent level.
—
=
not significant at 5-percent or 10-percent levels.
33
Our results are thus broadly consistent with the con-
clusions of Montiel (1989) and Dornbusch, Federico
Sturzenegger, and Holger Wolf (1990). They are also con-
sistent with earlier analysis of the classical hyperinflations
by Frenkel (1977, 1979) and Sargent and Wallace (1973).
In particular, Sargent and Wallace (1973) conclude, based
on Cagan’s seven hyperinflations, that the causality from
inflation to money is typically stronger than from money
to inflation. (See also Beatrix Paal 2000.)
34
In fact, as shown by Sargent and Wallace (1973),
causality from inflation to money is entirely consistent
with a model in which inflation is driven by the need to
finance a fixed real amount of government spending. In
such a model, the “causality” from inflation to money
growth emerges because the public’s expected rate of
inflation influences future money growth through the
government budget constraint.
inflation is that it results from fiscal imbal-
ances. But does the data bear this out? To
answer this question, we turn to an empiri-
cal analysis of the relationship between fiscal
deficits, seigniorage, and inflation. These
links derive from the flow fiscal identity:
fiscal deficit
=
seigniorage
+
borrowing (1)
with the inflation-deficit link emerging
from the link between seigniorage and in-
flation. In addition, there is an associated
intertemporal fiscal constraint which re-
quires that the present discounted value of
primary deficits (i.e., deficits net of interest
payments) plus the government’s initial
debt be equal to the present discounted
value of seigniorage.
35
As a result of the re-
strictions imposed by this intertemporal
constraint, there may be complicated dy-
namic relationships among the terms
within the fiscal budget identity (1). For in-
stance, for a given present discounted value
of primary deficits, less use of seigniorage
today will necessarily require the use of
more seigniorage tomorrow, as shown by
Sargent and Wallace’s (1981) monetarist
arithmetic.
36
Fiscal Deficits and Seigniorage. We start
by exploring the relationship between
seigniorage and fiscal deficits. Even though
in the short run, higher fiscal deficits may be
financed by borrowing, the intertemporal
budget constraint and optimal tax arguments
suggest a positive association between
seigniorage (as a financing source) and the
deficit. Hence, we expect a negative rela-
tionship between seigniorage and the fiscal
balance (which is the variable used in the
econometric analysis).
37
Figure 3 shows the cross-sectional rela-
tionship between seigniorage and the fiscal
balance, each expressed as a share of GDP,
for 94 market economies. Seigniorage was
computed as the increase in the nominal
stock of high-powered money in a given
year, divided by nominal GDP in that year. A
negative relationship is visible (figure 3 and
table 8, column 1): a ten-percentage-point
reduction in the fiscal balance leads on aver-
age to a 1.5-percent increase in seigniorage
revenues (both as a share of GDP), with the
highest levels of seigniorage (more than six
percent of GDP) recorded for Israel, Chile,
Argentina, Malta, and Nicaragua.
When panel regressions with annual data
are run, the coefficient on the fiscal balance
becomes even more significant but remains
unchanged quantitatively as compared to
the results obtained in the cross-section re-
gressions (compare columns 1 and 2, table
8). When different coefficients are allowed
for the high- and low-inflation countries
(table 8, column 3), the coefficient for high-
inflation countries rises sharply while that
for the low-inflation countries falls and be-
comes insignificant. The difference between
the coefficients of the high- and low-inflation
countries is statistically significant. A ten-
percentage-point reduction in the fiscal bal-
ance in the high-inflation countries leads, on
average, to a 4.2-percentage-point increase
in seigniorage (both as a share of GDP).
Allowing for separate coefficients (and con-
stant terms) raises the adjusted R-squared
from 0.048 to 0.334 (table 8, column 3).
When panel regressions for the subsample
of high-inflation economies are run, the sim-
ple OLS yields, as expected, a much higher
coefficient than that obtained for all market
economies (compare column 4 to column 2,
table 8). The largest effects of the fiscal bal-
ance on seigniorage revenues are obtained
during the high-inflation periods: a ten-
percentage-point reduction in the fiscal bal-
ance leads to a 6.27-percentage-point increase
in seigniorage revenues, both as a share of
GDP (table 8, column 5). On the other hand,
852
Journal of Economic Literature, Vol. XL (September 2002)
35
Naturally, this formulation presupposes that the
fiscal authority is solvent in an intertemporal sense.
36
In a similar vein, Drazen and Elhanan Helpman
(1990) show how the anticipation of future policies may
trigger inflation today.
37
The public finance perspective that treats
seigniorage as another form of taxation may suggest
that seigniorage revenue should be more closely associ-
ated with the level of government spending rather than
with the deficit (see, for example, Végh 1989).
the effect of the fiscal balance on seigniorage
revenues during the low-inflation years is
small and statistically insignificant.
The data thus show that the relationship
between the fiscal deficit and seigniorage is
strong only in the high-inflation countries.
Moreover, even in these countries, the fiscal
deficit-seigniorage relationship is strength-
ened during periods of high inflation com-
pared to low-inflation years.
Inflation and Seigniorage. Even though in
the high-inflation countries seigniorage rises
as a share of GDP as the deficit increases,
the relationship between inflation and
seigniorage is likely to be more complicated
because seigniorage revenues may eventu-
ally decline as inflation rises; that is, there
may be a Laffer curve effect as inflation con-
tinues to rise. The reason for the fall in
seigniorage revenue at high rates of inflation
is that the tax base—real money balances—
may fall more, in proportional terms, than
the growth rate of the money base, thus
leading to a fall in seigniorage.
38
Working with the same samples as those
used for seigniorage and fiscal deficits, we
estimate a nonlinear relationship between
seigniorage and inflation of the following
form:
Seigniorage
= a + b
inflation
+ g
(inflation)
2
,
where we expect
b
to be positive and
g
to be
negative, that is, seigniorage revenues rise as
inflation rises, reaching a maximum and
then declining with further increases in the
inflation rate. The cross-sectional plot is pre-
sented in figure 4 (table 9, column 2), which
Fischer, Sahay, and Végh: Modern Hyper- and High Inflations
853
10
–15 –10
Figure
3. Seigniorage and Fiscal Balance
1
1960–95 averages
1
Slope of regression line is –0.152 with a t-statistic of –2.30; 94 countries in total, each with 10 or more observations.
8
–2
6
4
2
0
10
8
6
4
2
0
–5 0
Fiscal Balance/GDP
Seigniorage
(Change in high powered money in percent of GDP)
5 10 15 20
38
The Laffer curve shape emerges from the steady
state relationship between the inflation rate and
seigniorage. If, for instance, expectations lag behind ac-
tual inflation, it may be possible for a time to increase
seigniorage by accelerating inflation even beyond the
steady state revenue maximizing rate.
shows the estimated nonlinear relation-
ship.
39
Seigniorage revenues are maximized
when inflation reaches 174 percent.
The main message to emerge from table 9
is that a Laffer curve is visible and significant
in high-inflation countries (table 9, column
4) and in high-inflation episodes for the sub-
sample with the high-inflation countries
only (table 9, column 6). These findings are
consistent with the notion that a Laffer
curve is more likely to emerge the higher is
the level of inflation.
In terms of the linear regressions, table 9
indicates that, as expected, the coefficient
on the inflation rate is significant for both
high- and low-inflation countries (table 9,
column 3) and for both high- and low-
inflation episodes for the subsample of high-
inflation countries (table 9, column 5).
Fiscal Deficits and Inflation. Figure 5
shows the deficit-inflation link for the whole
sample. As shown in table 10, column 1, the
relationship is significant in the cross-section
regression. This relationship, however, be-
comes insignificant when different constant
terms and coefficients are allowed for in the
high- and low-inflation market economies
(table 10, column 2).
When annual panels are considered, the
relationship between the fiscal balance and
inflation becomes significant for the high-
inflation countries but does not for the low-
inflation countries (table 10, column 3).
A reduction in the fiscal balance by 1 per-
cent of GDP in the high-inflation countries
leads to an increase in the inflation rate
by 4.2 percent. The introduction of lags