Determinants of the Sacrifice Ratio: Evidence from OECD and non ...

Determinants of the Sacrifice Ratio: Evidence from
OECD and non-OECD countries
Sandeep Mazumder ∗
April 2012
Abstract
This paper measures sacrifice ratios for all countries in the world over an approximately forty
yeartime period, in additiontoexploringthedeterminantsofworldwidesacrificeratios. We testthe
most commonly-cited determinants: the speed of disinflation, openness, central bank independence,
inflation targeting, and political factors for both OECD and non-OECD countries. We find that
the speed of disinflation is the most important determinant of OECDsacrifice ratios, but puzzlingly
has no effect on non-OECDnations’ disinflation costs. Instead we find evidence that greater central
bank independence and more openness are associated with lower non-OECD sacrifice ratios. We
also find that the ratio of government debt to GDP–a variable that is not important when it comes
to OECD countries–is highly significant for non-OECD economies. Specifically, we find that higher
indebtedness is associated with lower sacrifice ratios in non-OECD nations, suggesting that greater
levels of debt do not lead to higher expectations of inflation.
JEL Classification: E31, E32, E58, E52, E42.
Keywords: Sacrifice ratios; disinflation.
∗ Address: Department of Economics - Carswell Hall - Wake Forest University - Box 7505 - Winston Salem, NC 27109.
Email Addresses: mazumds@wfu.edu.
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1 Introduction
The authority that conducts monetary policy in any given nation typically faces the task of con-
trolling the rate of inflation. For example, in the United States, the Federal Reserve implemented
contractionary monetary policy to deal with inflation in the early 1970s, the mid-1970s, and the early
1980s. However, such disinflationary policy does not come without cost. The cost of disinflation can
be quantified by the sacrifice ratio, which measures the amount of real GDP that must be given up
in order to reduce the inflation rate by one percentage point. This therefore raises two key issues
that macroeconomists face: first, we wish to measure the magnitude of output losses that are incurred
during disinflation episodes, and second, we wish to examine the determinants of the sacrifice ratio.
To that end, a great deal of research has been devoted to both measuring the sacrifice ratio and
examining its determinants. The seminal paper in this body of research is Ball (1994), who was
instrumental in establishing a method of selecting time periods that we can label as “disinflationary.”
Thereafter, Ball proceeds to specify a method in which the sacrifice ratio can be computed, namely
by computing the ratio of the sum of deviations of trend output from actual output, to the change
in trend inflation over the given disinflation episode. This method of computing sacrifice ratios is by
far and away the most widely-accepted and commonly-used technique of estimating disinflation costs,
and continues to be used by prominent papers in the literature. We therefore proceed in this paper
to use the Ball (1994) method of computing sacrifice ratios for our sample of countries.
Ball (1994) also examines the determinants of the sacrifice ratio, and finds that the speed of dis-
inflation (as determined by the amount of disinflation and length of the disinflation episode) and
flexible wage-setting are both responsible for lowering the costs of disinflation, while he argues that
the initial level of inflation at the start of a disinflation episode is not quantitatively important. Other
researchers have also examined a large variety of factors that may possibly be important for determin-
ing the sacrifice ratio. Key factors that are tested in the literature are: the degree of trade openness
(Temple, 2002), the amount of central bank independence (Jordan, 1997), the role of inflation target-
ing (Goncalves and Carvalho, 2009), and political factors such as ideology and democracy (Caporale,
2011).
Despite the various determinants of the sacrifice ratio that are tested, one overarching theme
appears in the literature. Almost all of these papers focus their analysis exclusively on advanced,
industrialized, or specifically, OECD economies. Meanwhile, the question of what determines the
sacrifice ratio has not been adequately addressed for the developing and emerging economies of the
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world. Examinationofnon-OECDsacrificeratiodataremainstobeanimportantbutunder-researched
area in the literature. Thus the goal of this paper is to fill this void by measuring the sacrifice ratio
on a far larger scale than has been done in the literature. In particular, this paper computes the
sacrifice ratio for every single country in the world over an approximately forty year time period. 1
This represents a far wider scope of countries than is typically considered in the literature, as well as
a lengthier period of time.
This then allows us to investigate the determinants of the sacrifice ratio for both OECD and
non-OECD economies. We examine all of the typical determinants that have been suggested by the
existing literature that focuses primarily on OECD countries. Namely, we test whether the change
in inflation, the length of the disinflation episode, the initial level of trend inflation, the degree of
openness, the independence of the central bank, and political factors are important in determining
the sacrifice ratio. We find that the speed of disinflation–i.e. the amount of disinflation and length of
the episode–is always economically and statistically significant in determining OECD sacrifice ratios,
while there is little robust evidence of any other important determinants.
However we find a puzzle emerges when we test for the determinants of non-OECD sacrifice ratios:
the speed of disinflation is not a significant determinant of non-OECD sacrifice ratios. Instead, we find
that higher central bankindependenceand greater tradeopennessbotharenegatively andsignificantly
associated withthecosts ofdisinflationinnon-OECDeconomies. Inother words, thereisevidencethat
a “credibility bonus” does exist in non-OECD economies, where greater separation between monetary
policymakers and the political regime allows for reductions in inflation at lower output costs. This
suggests that greater independence of monetary authorities is a policy that should be encouraged
in developing and emerging economies. We also find that greater openness in developing economies
enables disinflationtotake placeinaless costly manner. Thisagrees with theRomer (1993) hypothesis
that increases in output that come from an increase in inflation are negatively related to openness,
implying a negative relationship between openness and the sacrifice ratio. While Romer applied this
idea to developed economies, we find evidence that this prediction holds true for developing and
emerging economies as well.
We also examine the role of the ratio of central government debt to GDP, and find this to be
a highly robust determinant of the sacrifice ratio in non-OECD countries. This is true of various
measures of debt-to-GDP ratios. Somewhat curiously, however, higher levels of debt in non-OECD
1 The number of countries in the world varies according to the source. For example, at the time of writing, the United
Nations report 193 member countries, whereas the U.S. State Department lists 195 countries. This paper examines 189
countries.
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economies are associated with lower sacrifice ratios. This suggests two things to us. First, although
output typically falls during a disinflation episode, a higher level of government debt enables output
to be stabilized and perhaps actually increased, even during a disinflation. This appears to indicate
that the rise in government debt is accompanied by some other factor that enables output to expand
while inflation falls, such as an increase in productivity or some other favorable supply shock. Second,
in theory we would expect higher levels of indebtedness to lead to higher inflation expectations and
thus larger output costs of disinflation. Therefore the finding of a negative impact of debt on the
sacrifice ratio in non-OECD nations suggests that higher levels of debt have not led to higher inflation
expectations, which has enabled these economies to mitigate the output costs of disinflation. The
exact mechanism by which this occurs remains an interesting area for future work.
The rest of this paper as organized as follows: section 2 briefly reviews the relevant literature
concerning sacrifice ratios, and section 3 presents our estimates of worldwide sacrifice ratios. Sections
4 and 5 then examine the determinants of the output costs of disinflation in OECD and non-OECD
countries respectively. Finally we conclude in section 6.
2 Existing Literature
2.1 Measurement of the Sacrifice Ratio
The most prominent method by which sacrifice ratios are computed in the literature follows the work
of Ball (1994). The first step taken is to identify disinflation episodes. 2 Trend inflation is defined as
a centered, eight-quarter moving average of actual quarterly inflation. In other words trend inflation
for a given year is the average of the four quarters of inflation of that year and the two quarters on
either side. To identify disinflation episodes, we then identify peaks and troughs in trend inflation.
An inflation peak is one where trend inflation in year t is higher than trend inflation in years t − 1
and t+1, and an inflation trough is one where trend inflation in year t is lower than trend inflation
in years t − 1 and t + 1. Finally, Ball defines a disinflation episode as one that starts an inflation
peak and ends at an inflation trough, where trend inflation falls at least 2 percentage points (or 1.5
percentage points with annual data). This rule of looking at disinflations where inflation falls by at
least 1.5 percentage points is designed to separate significant aggregate demand policy changes from
smaller changes that result from shocks (Senda and Smith, 2008).
The sacrifice ratio is then computed as the ratio of the sum of deviations between trend output
2 In this paper we will use annual data, hence we focus on the annual data method of computing sacrifice ratios.
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and actual output, to the change in trend inflation over the disinflation episode. Trend output is
measured in the following way, following Ball (1994). First we assume that output is at its trend (or
natural level) at the beginning of a disinflation episode. Second, we assume that output returns to
trend one year after the end of the episode. The purpose of this second assumption is to capture
the persistent effects of disinflation. In other words, output appears to return to trend with a lag.
Finally, Ball assumes that trend output grows in a log-linear fashion between the inflation peak and
the year after the end of the disinflation episode. The numerator of the sacrifice ratio is then the sum
of the differences between this log-linear fitted line for trend output and the log of actual output. The
denominator of the sacrifice ratio is then simply the change in trend inflation over the course of the
disinflation episode.
Some researchers estimate the sacrifice ratio based on a Phillips curve (such as Hutchison and
Walsh, 1998 and Fischer, 1996), and use this model to derive a relationship between output and
inflation. However the major problem with this approach is that it constrains the inflation-output
tradeoff to be the same during periods of disinflation as it is during periods of accelerating inflation. If
the sacrifice ratio is influenced by factors that are unique to disinflations, this constraint becomes an
invalid one. For this reason, the vast majority of the literature now stays clear of estimating sacrifice
ratios based on the Phillips curve.
Others have also estimated the sacrifice ratio in different ways, but most of these alternative
methods are essentially variations of Ball (1994). Two prime examples of this are Zhang (2005) and
Hofstetter (2008). Zhang (2005) argues that the Ball (1994) method ignores long-lived effects that can
accompany a disinflation episode. Zhang instead measures trend output by calculating a Hodrick and
Prescott (1997) (HP) filter of log real GDP, and then computes the growth rate of the HP filter. Zhang
then assumes that potential output grows at this rate at the beginning of the disinflation episode, thus
giving an alternative method of computing trend output. Hofstetter (2008) is a further extension of
Zhang (2005) that agrees with the notion of long-lived effects, but instead assumes that output is at
trend one year prior to the start of a disinflation episode. Regardless of the minor variations that
are assumed, the Ball (1994) technique of measuring sacrifice ratios is widely-deemed to be the best
existing method.
2.2 Determinants of the Sacrifice Ratio
Ball (1994) finds that the main determinant of the sacrifice ratio is the speed of disinflation, measured
by the ratio of the change in trend inflation to the length of the episode. In particular, he finds that
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the sacrifice ratio is lower when disinflation is quick, suggesting that the “cold-turkey” approach to
disinflation may bebest if welfare is measured by output losses. Inaddition, Ball findsthat disinflation
costs tend to be lower in countries where wage-setting tends to be more flexible. However, he finds
that the initial level of inflation during a disinflation episode and the degree of trade openness are not
important determinants of the sacrifice ratio.
Subsequently a great deal of research has investigated the impact of other factors on the sacrifice
ratio. One such factor that has received a lot of attention is trade openness. Ball (1994) briefly
investigates this matter himself by measuring openness as the ratio of imports to GNP, and finds
statistically insignificant effects on the sacrifice ratio. Temple (2002) also examines the relationship
between openness and the sacrifice ratio, citing the Romer (1993) argument that more open economies
have lower inflation. Temple finds that there is a weakly negative correlation between inflation and
openness, and if anything there is only a weak relationship between openness and the output costs of
disinflation. Daniels et al. (2005) argue that the relationship between openness and the sacrifice ratio
must also account for the degree of central bank independence. Using the Franzese (2002) measure
of central bank independence, they find that the coefficient on openness becomes positive when the
interaction between central bank independence and openness is included in the model. Daniels et al.
(2005) reason that the Barro and Gordon (1983) framework that Romer (1993) relies upon is based
on purely competitive markets, whereas a framework that assumes imperfectly competitive markets
(such as in Razin and Yuen, 2002) actually implies that we should expect a positive relationship
between openness and the sacrifice ratio. However Bowdler (2009) lends further empirical evidence
to the negative impact of openness on the sacrifice ratio, where his analysis accounts for the type of
exchange rate regime. 3 In almost all cases, however, the evidence suggests that openness has at best
only a weak impact on the sacrifice ratio.
The sacrifice ratio also provides a useful way to test the impact of central bank independence.
Although he does not explicitly estimate sacrifice ratios, Walsh (1995) argues that greater central
bank independence is associated with higher sacrifice ratios. Walsh interprets this as a benefit of
an independent central bank, since they can have a bigger effect on the real economy. In other
words, an independent central bank can effectively insulate the economy during a recession if greater
independence is associated with higher output losses when trying to reduce the inflation rate. Indeed,
several authors have found a positive relationship between central bank independence and the sacrifice
ratio. For instance, Fischer (1996), Jordan (1997), and Down (2004) all find that greater independence
3 Temple (2002), Daniels et al. (2005), and Bowdler (2009) all measure openness as the share of imports to GDP.
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of central banks is associated with larger costs of disinflation for OECDand other advanced economies.
However, there is also contrasting evidence, such as in Brumm and Krashevski (2003) and Diana
and Sidiropoulos (2004), who find a negative association between central bank independence and
disinflation costs whenconsidering alternative estimation methodologies and different control variables
respectively. 4 Interestingly, Cukierman(2002) arguesthatregardlessofthesignofrelationshipbetween
central bank independence and the sacrifice ratio, greater independence of central banks increases the
probability that inflation targets are met, and welfare is consequently improved.
Therefore a recent strand of the literature has also examined the role of inflation targeting on
the sacrifice ratio. In response to previous authors, such as Bernanke et al. (1999) and Ball and
Sheridan (2003), who find no existence of a credibility bonus for countries who have adopted inflation
targeting, Goncalves and Carvalho (2008, 2009) examine the impact of inflation targeting on the
sacrifice ratio. They find that among the OECD nations, those who are inflation targeters have lower
sacrifice ratios and thus lower output losses during disinflation episodes. Furthermore, this result
accounts for the potential problem of self-selection by first examining whether countries with higher
average past inflation rates and lower debt levels are more likely to adopted inflation targeting in the
first place. However Brito (2010) finds that the Goncalves and Carvalho (2009) result is based on
a narrow set of OECD disinflations, and when the sample is expanded to a broader set of OECD
disinflations there is no longer any discernible impact of inflation targeting on the sacrifice ratio.
Indeed, Brito argues that even within the Goncalves and Carvalho (2009) sample, inflation targeting
does not matter if one controls for differences in common economic conditions both before and after
the mid-1990s.
The final class of sacrifice ratio determinants that is sometimes considered in the literature is
political factors. For example, Caporale and Caporale (2008) examine whether the governance of
countries’ political leaders matters. They find that right-wing governments have lower costs of disin-
flation than left-wing governments, perhaps dueto greater credibility since right-wing governments are
often thought to have stronger anti-inflation reputations. Caporale (2011) also tests whether political
institutions impact the costs of disinflations with a focus on Latin American and Caribbeaneconomies.
Caporale finds that more right-wing governments have less costly disinflations, while more democratic
governments also tend to have lower sacrifice ratios.
4 Additionally, Chortareas et al. (2002) find that more transparent central banks have lower sacrifice ratios.
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3 Data and Sacrifice Ratio Estimates
Inflation is measured as the percentage change in the annual consumer price index (CPI), which is
also the literature’s preferred measure of prices when it comes to measuring trend inflation. The
data for the CPI and real GDP are obtained for 189 countries for the period of 1969 to 2009 from the
International Macroeconomics Data Set of the U.S. Department of Agriculture (USDA). The USDA in
turn obtains their data from the World Bank’s World Development Indicators, the IMF’s International
Financial Statistics, and the USDA’s Economic Research Service. Aside from having a large sample
size, the advantage of looking at all the countries in the world is that we can examine the sacrifice ratio
and its determinants for both OECDand non-OECDeconomies. Almost all of the prevailing literature
has only used OECD data, even though significant differences may exist between the advanced and
developing economies of the world. 5
We proceed to estimate the sacrifice ratio in this paper based on the most commonly-used method
intheliterature, namelyBall(1994). 6 Weidentifyandmeasurethesacrificeratiointheexactsameway
as described in section 2.1 with one small modification: since our data is annual and not quarterly, we
define trend inflation as a centered, three-year moving average, as opposed to a centered, eight-quarter
movingaverage. 7 However, wefindthismakes little differencetothemeasurement ofthesacrificeratio.
For instance, comparing our sacrifice ratio to Ball (1994)’s–where we focus on disinflation episodes
under both methods that start within a year of each other and have the same length of episodes to
within a year of each other–we find a mean sacrifice ratio for OECD nations of 1.15, compared to
1.25 from Ball (1994). Indeed, the correlation between the two approaches of measuring the sacrifice
ratio is very high and positive with a magnitude of 0.80. For non-OECD economies, we find a lower
mean value of the sacrifice ratio (0.43), but with far greater variance than that exhibited by OECD
economies. 8 Tables A1 and A2 in the appendix list the data for our computed sacrifice ratios for
all nations. Overall we identify 78 disinflation episodes for OECD countries and 348 for non-OECD
economies.
5 Temple (2002) adds 21 developing economies to his dataset, while Bowdler (2009) and Chortareas et al. (2002) add
22 non-OECD countries to their sample. In addition, Hofstetter (2008) and Caporale (2011) focus entirely on Latin
America and the Caribbean. While these exercises are useful, they do an incomplete job of examining the non-OECD
economies in the world.
6 It is quite standard in the literature to focus on Ball (1994) as the sole measure of the sacrifice ratio. See, for
example, Jordan (1997), Temple (2002), Chortareas et al. (2002), Brumm and Krashevski (2003), Down (2004), Diana
and Sidiropoulos (2004), Daniels et al. (2005), Caporale and Caporale (2008), Goncalves and Carvalho (2009), Bowdler
(2009), and Brito (2010).
7 Just as in Ball (1994), we also limit disinflation episodes to those where trend inflation at the peak is less than twenty
percent.
8 The standard deviation of sacrifice ratios is 2.21 and 6.60 for OECD and non-OECD countries respectively.
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We also gather several variables that will be used as potential determinants of the sacrifice ratio.
∆π is the change in trend inflation over the disinflation episode, Length is the length in years of
each disinflation episode, and π0 is the initial level of trend inflation at the start of episode. Ideally
we would like to have data on nominal wage rigidity, but unfortunately this is not available for the
country coverage and time horizon considered in this paper. Instead we proxy for nominal rigidities
in a similar way to Hofstetter (2008), who defines “inflation history,” as the average of the inflation
rate of the ten years preceding the disinflation episode. Thus we measure inflation history based on
ten years preceding the episode, and we also compute a five year inflation history, denoted π H 10 and
π H 5 respectively.
For the degree of trade openness, Openness, we measure the ratio of imports to real GDP using
import data from the IMF’s IFS. We also use the Penn World Tables measure (Openness PWT ) as a
robustness check. Our data on central bank independence, CBI, are taken from Polillo and Guillen
(2005), who in turn use Cukierman (1992) to define central bank independence. The main advantage
of this data set is that it allows for some time variation in central bank independence, whereas the
majority of the literature that estimates CBI does so using fixed point estimates for the whole sample
period. 9 However the downside is that Polillo and Guillen (2005)’s data covers the period of 1989
to 2000, which limits our sample size when examining the role of central bank independence on the
sacrificeratio. Todealwiththisissue, wealsodefine CBI whichisCBI withtheadditionalassumption
that the level of central bank independence that existed in 2000 was also true of the years 2001 to
2008.
To measure inflation targeting, we define a dummy variable IT which is equal to 1 for inflation
targeting economies, and0otherwise. 10 Inaddition, wealso define IT whichis adummyvariableequal
to 1 if the country was an inflation targeter before the disinflation episode began, and 0 otherwise.
The advantage of this definition of inflation targeting is that it further pinpoints the exact impact
that adoption of inflation targeting has on the output costs of disinflation by refining the timing of
adoption. We also define a dummy variable PIT which is equal to 1 for countries that are considered
“potential” inflation targeters, and 0 otherwise. These potential inflation targeters are identified using
IMF (2006), Epstein (2007), and Stone (2003).
The political factors we consider in this paper are the political orientation of the country at the
9
For an example of recent research that does this and also provides a review of earlier work, see Crowe and Meade
(2008).
10
The list of inflation targeters is compiled from Roger (2010), IMF (2006), Epstein (2007), and Central Bank of
Iceland (2007). Also note that members of the European Monetary Union are automatically not counted as inflation
targeters as outlined in IMF (2006).
9

start of the disinflation episode, Left, and the level of democracy at the beginning of the episode,
Polity2. Leftis an index taken fromBeck et al. (2001) denotingthe rulingparty’s political orientation
in a country for a given year, where a greater value of Left indicates more left-wing governments.
Polity2is an indexof democracy, whereahighervalue indicates agreater level of democracy. Thedata
for democracy are obtained from the Center for Systemic Peace (Heston et al., 2011). In addition, we
will also consider debt-to-GDP ratios as a potential determinant of the sacrifice ratio. For robustness
we consider two alternative measures of debt-to-GDP ratios: the measures computed by Reinhart and
Rogoff (2011) and Jaimovich and Panizza (2010), denoted Debt RR and Debt JP respectively. Finally,
estimation isconductedusingordinaryleast squares(OLS)withheteroskedasticity andautocorrelation
consistent (HAC) standard errors.
4 Determinants of the Sacrifice Ratio in the OECD
4.1 Speed of Disinflation, Initial Inflation
Ball (1994) finds that the sacrifice ratio in OECD economies is decreasing in the speed of disinflation,
but the level of initial inflation at the outset of a disinflation episode does not have an important
impact on the sacrifice ratio. Many other authors, such as Fischer (1996), Jordan (1997), Brumm and
Krashevski (2003), and Hofstetter (2008) also confirm the importance of the speed of disinflation on
the sacrifice ratio, but there are a handful of papers that argue that the initial level of trend inflation,
π0, is negative and significant, such as Zhang (2005) and Goncalves and Carvalho (2009).
Table 1(a) contains our results that examine the impact of the speed of disinflation and amount of
initial inflation on the sacrifice ratio for OECD economies. In column (1) we regress the sacrifice ratio,
SR, on a constant and Speed = ∆π/Length. We agree with the prevailing arguments in the literature
that the speed of disinflation is indeed highly negative and significant in this sacrifice ratio regression.
Moreover, running the regression with the components of Speed, i.e. ∆π and Length, separately does
not alter this result. In fact the fit of the model, in terms of the R 2 , becomes much higher in regression
(2). We find that a one percentage fall in the rate of trend inflation is associated with an decrease in
SR of approximately 0.3, while an additional year of disinflation tends to raise the sacrifice ratio by
about 0.9. Therefore we conclude that the sacrifice ratio is lower in OECD nations when disinflation is
quick. In other words, there is some justification to a “cold-turkey” approach to disinflation, if welfare
is maximized by minimizing losses in total output over the course of a disinflation episode.
One of the key results obtained by Ball (1994) concerns the impact of nominal wage rigidity on
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the sacrifice ratio. Specifically, Ball finds that more flexible wage-setting economies tend to have
lower sacrifice ratios. Due to data limitations, we are not able to measure nominal wage rigidities for
the country coverage and time periods in this paper, so we follow Hofstetter (2008) who proxies for
nominal rigidities using inflation history. In particular, we define two measures of inflation history:
πH 5 and πH 10 which are five- and ten-year inflation histories respectively. Columns (3) and (4) in turn
add these measures of inflation histories to our previous model, where we again find that the speed
of disinflation is highly negative and significant. However, we find that nominal rigidities are neither
economically nor statistically significant in these regressions. 11
Finally in columns (5)-(8), we also add initial trend inflation, π0 to our model, where we find
that regressing the sacrifice ratio on a constant and π0 alone does indeed produce a negative and
significant coefficient. This suggests that a higher initial trend inflation rate may encourage more
frequent contract, and thus wage, renegotiations. This, in turn, could have the effect of reducing
nominal rigidities, meaning that a lower sacrifice ratio is obtained with a higher value of π0. However,
the finding of a negative and significant coefficient for π0 is not a robust result, since the statistical
significance disappears when we control for the speed of disinflation and nominal rigidities. Moreover,
the economic importance of π0 also falls by a substantial amount when we control for these other
factors. However the coefficients for ∆π and Length remain highly significant in all specifications
tested in Table 1(a), indicating that the speed of disinflation is an important determinant of OECD
sacrifice ratios.
4.2 Openness
Agreat deal oftheliteratureexamines theimpact oftradeopennessonthesacrificeratio. For example,
Temple (2002) extends the Romer (1993) hypothesis that more open economies are associated with
lower inflation by measuring the slope of the Phillips curve. If the slope of the Phillips curve is
genuinelysteeperinmoreopeneconomies, wecanexpectlowersacrificeratios. Templedoesindeedfind
a negative relationship between openness and the sacrifice ratio, but also finds that this relationship
is weak at best. Ball (1994) goes one step further by declaring that no discernible relationship exists
between openness and disinflation costs.
In Table 2(a) we investigate this matter for our sample of OECD disinflations. Columns (1)-(4)
report the result using Openness as our measure of trade openness, and columns (5)-(8) re-run these
11 This might imply that inflation history is not the best proxy for nominal wage rigidity, and is something that future
work can improve upon.
11

egressions using the Penn World Tables measure of openness, Openness PWT . We start by regressing
SR on a constant and openness, and then we also run separate regressions that control for the speed of
disinflation, nominal rigidities, and the initial level of trend inflation. For the first measure of openness
we find a positive relationship with the sacrifice ratio, but one that is not statistically significant. For
the Penn World Tables measure of openness, we find no statistical significance, and further still the
coefficient on trade openness is essentially zero in all specifications. What is most striking about this
set of results is that openness is never statistically significant regardless of which specification we
examine. Therefore, we concur with Ball’s assessment that there is no association between the degree
of trade openness and the sacrifice ratio. In other words, OECD member nations that have more open
economies will not necessarily see smaller output costs of disinflations as a result of their openness. We
do continue to find, however, that the amount of disinflation and length of disinflation–which together
measure the speed of disinflation–continue to be highly significant determinants of the sacrifice ratio.
4.3 Central Bank Independence
One of the most researched areas in the literature concerning sacrifice ratios has to do with central
bank independence. Some authors, such as Jordan (1997), find that economies with more independent
central banks tend to have higher sacrifice ratios. At first glance, this might appear to be an argument
against central bank independence, but as Walsh (1995) argues, it may actually be an argument
in favor of more central bank independence. In particular, if greater central bank independence is
related to higher sacrifice ratios, this means that the monetary policy authority of the nation stands
to have greater influence on the real economy, which is a particularly useful property to have during
a recession or even when faced with the threat of a recession. Nonetheless, most researchers would
expect that central bank independence reduces the sacrifice ratio if credibility has been achieved. To
that end, some researchers do find a negative relationship between central bank independence and
sacrifice ratios, such as Diana and Sidiropoulos (2004). This suggests that more independence of
the central bank can produce a “credibility bonus.” In other words, one of the primary advantages
of having an independent central bank is that it allows greater credibility due to the separation of
monetary policymakers from political entities, thereby enabling central banks to fight inflation in a
more efficient manner.
We thusproceed to examine the role of central bankindependenceon oursample of OECDsacrifice
ratios. Column (1) in Table 3(a) shows the regression of SR on a constant and CBI (measured using
12

Polillo and Guillen, 2005) for OECD economies. 12 From this model we see that CBI does have a
significant impact on the sacrifice ratio, and in a negative way. In other words, there is some evidence
of a credibility bonus from this regression result. However, this result is not robust to the addition of
∆π and Length to the model (column (2)) and also when including our proxy for nominal rigidities
(columns (3) and (4)). Instead it is the length of the disinflation episode that matters most, suggesting
that the number of years of the disinflation episode matters more than whether the central bank is
independent or not.
Finally, we also check the Daniels et al. (2005) hypothesis that the coefficient on openness is
positive in the sacrifice ratio regression when its interaction with CBI is included in the model. In
other words, trade openness alone might not have an impact on the sacrifice ratio, but it may be
the joint impact of trade openness together with central bank independence that can have significant
effects on the costs of disinflation. We check for this in columns (5)-(8) of Table 3, where (5) and (6)
regress SR on a constant, CBI, openness, and the interaction between CBI and openness (for our two
measures of trade openness), and columns (7) and (8) also then control for the speed of disinflation
as well. We find that including the interaction between central bank independence and openness does
tend to produce a positive coefficient for openness in OECD nations. Moreover in (6), we see that
Openness PWT and the interaction between CBI and Openness PWT are both statistically significant.
However, this significance is not robust to the inclusion of ∆π and Length to the model (columns (7)
and (8)), therefore we conclude that there is at best limited evidence that central bank independence
and openness together are important for OECD sacrifice ratios, at least from a statistical perspective.
This conclusion is also robust to the use of CBI which slightly extends our sample size (columns
(9) and (10)), where central bank independence and openness remain statistically insignificant once
controlling for ∆π and Length. From an economic perspective, the magnitude of the coefficients for
CBI and CBI are always large, but the sign varies according to the specification tested. We therefore
consider this an indeterminate result, meaning that CBI is not a significant determinant of sacrifice
ratios in advanced economies. Nonetheless, we continue to find that the speed of disinflation is a
significant determinant of OECD sacrifice ratios, even when we control for the level of central bank
independence.
12 One thing to note is that the sample size is much smaller with our CBI regressions than with other potential
determinants that we test, due to limited availability of data for CBI. The use of CBI helps to somewhat alleviate this
problem.
13

4.4 Inflation Targeting
The debate about whether inflation targeting is useful or not is one that remains unresolved among
macroeconomists, and to that end, we turn next to investigate the impact of inflation targeting on the
output costs of disinflation. One way in which inflation targeting will be noticeably useful is if it leads
to a reduction in the sacrifice ratio. Goncalves and Carvalho (2009) address this very issue, where
they find that inflation targeting has a negative and significant impact on the sacrifice ratio, once
controlling for the speed of disinflation and the initial level of inflation at the start of an episode. 13
Indeed, Goncalves and Carvalho (2008) argue that inflation targeting countries in the OECD have
sacrifice ratios approximately one-third of the average of non-inflation targeting countries. Our data
agrees that inflation targeting economies have lower sacrifice ratios on average than that of non-
inflation targeting nations, but not in the order of magnitude as suggested in Goncalves and Carvalho
(2008). 14
Our results in Table 4(a) suggest that inflation targeting does not have an important effect on
OECD sacrifice ratios. In (1) we regress SR on a constant and IT, in (2) we also add ∆π and Length,
and finally we add our proxies for nominal rigidities in (3) and (4). In all cases, the coefficient on
IT is never statistically significant, and in fact is frequently of unexpected sign (namely, positive).
It remains to be the case that the speed of disinflation is the most economically and statistically
significant determinant of OECD sacrifice ratios.
Bernankeetal. (1999) makethevalidpoint, however, thatthetimingofinflationtargeting adoption
may be important. In other words, instead of defining our inflation targeting dummy variable as being
equal to one for all countries that are inflation targeters, we should instead focus on countries who had
adopted inflation targeting before the disinflation episode begins. Thus we also examine the impact of
IT (defined in section 3) on the sacrifice ratio, the results of which can be seen in columns (5) and (6)
of Table 4(a). We find this new definition of our inflation targeting dummy variable does improve the
results in the sense that we now obtain the expected negative coefficient. In addition, the economic
importance of the IT coefficient is reasonable, where the results indicate that countries that adopt
an inflation target before the disinflation episode have lower sacrifice ratios in the amount of 0.56.
However we do not find this to be a statistically significant result.
Lastly, we also examine the impact of PIT in conjunction with IT, where PIT includes countries
13 Goncalves and Carvalho (2009) also control for government debt and monetary policy transparency.
14 The mean value of the sacrifice ratio for OECD inflation targeters is 1.76 in our data, compared to 1.99 for non-
inflation targeters.
14

that are potential inflation targeters. In other words, perhaps it is not just the adoption of an inflation
target that matters, but the announcement of future adoption that may matter more, since firms,
households, output markets, and financial markets may all augment their expectations to include the
central bank’s future commitment to an inflation target. Columns (7) and (8) report these results, and
we find that PIT does play an important role in an economic sense, since a country that is a potential
inflation targeter has a lower sacrifice ratio in the region of 0.9-1.0. Indeed, the coefficient on PIT
is almost significant at the 5% level, but is not quite significant in either (7) or (8). Meanwhile, we
continue to obtain counter-intuitive positive signs for IT, though this is statistically indistinguishable
from zero.
Overall, we conclude that inflation targeting has not played an important role for OECD sacrifice
ratios, similar to what Brito (2010) finds, although there is some evidence that potential inflation
target adoption might be important. This suggests that the benefits of inflation target adoption–in
terms of lower output costs of disinflation–disappear after the adoption of the inflation target has
actually taken place.
4.5 Political Factors
The final class of determinants of OECD sacrifice ratios that is considered in the literature deals with
political factors. For instance, Caporale and Caporale (2008) find that more right-wing governments
in the OECD are associated with lower costs of disinflation. We therefore also check whether political
factors are important for our sample of OECD sacrifice ratios. Specifically we test whether political
orientation and level of democracy can help explain sacrifice ratios.
Table 5(a) displays our results for governance and democracy. In column (1) we regress SR on a
constant and Left, whereagreater valueof Leftdenotes governments that are moreleft-wing in terms
of their political orientation. We then also re-run this regression, while also controlling for the speed
of disinflation and nominal rigidities (columns (2)-(4)). In all cases, we find a negative coefficient for
Left, indicating that more left-wing governments tend to have lower sacrifice ratios. Caporale (2011)
argues that the very opposite happens, that more right-wing governments have greater anti-inflation
sentiments. Our results suggest that perhaps the Caporale result is not as strong as one might think
when applied to our sample of OECD sacrifice ratios, and in fact, it may be that more left-oriented
governments have lower output costs of disinflation. However this finding is not significant, since the
coefficient for Left is not significant in any of these regressions, while both ∆π and Length remain
highly statistically significant.
15

We also test Polity2 in our sacrifice ratio regression, which measures the level of democracy of the
nation in question, where a greater value of Polity2 denotes more democratic governments. Caporale
(2011) argues that more democratic governments tend to have lower sacrifice ratios since the greater
opennessof such governments makes it less likely that policy changes comeas asurprise. Thereforeone
can expect expectations and prices to adjust more quickly since policy choices in a more democratic
government reflect, at least indirectly, the preferences of the country’s voters. However, our empirical
results in columns (5)-(8) indicate that Polity2 is not a significant determinant of OECD sacrifice
ratios, in neither an economic nor statistical sense. Finally, we check whether political orientation and
democracy together are important determinants of the sacrifice ratio in the OECD (columns (9) and
(10)), and find that these variables remain insignificant when tested together.
5 Determinants of the Sacrifice Ratio in non-OECD countries
5.1 A Puzzle
Our results for OECD economies suggest that the speed of disinflation, in terms of the amount of
disinflation and length of disinflation episode, is the most important determinant of the sacrifice
ratio. This result is robust to examining a variety of other factors, namely openness, central bank
independence, inflation targeting, and political factors. We next proceed to examine whether these
same factors can explain the behavior of sacrifice ratios in non-OECD economies.
In column (1) of Table 1(b) we regress SR on a constant, and Speed = ∆π/Length, and obtain
a positive coefficient. This presents a puzzle to us, since we expect the speed of disinflation to be
negatively related to the sacrifice ratio, which is precisely what we find for OECD sacrifice ratios. We
then also re-run the regression with ∆π and Length entered into the regression separately (column
(2)), and still obtain nostatistical significance. Furthermorethe coefficient for ∆π is positive, although
the small magnitude (0.11) indicates that this variable is not economically important for non-OECD
countries. In addition, we find that nominal rigidities are statistically indistinguishable from zero, and
in fact have coefficients magnitudes that are very close to zero (columns (3)-(4)). Controlling for the
initial level of inflation, π0, also makes no differences to these inferences (columns (5)-(8)). Therefore
the factors that are dominant in the literature, namely, the speed of disinflation, nominal rigidities,
and the initial level of trend inflation, play no important role in non-OECD economies. In other words,
the output costs of disinflation in the developing and emerging economies of the world behave rather
differently from those of advanced economies. More specifically, there is no evidence that a cold-turkey
16

disinflation would be less costly in non-OECD economies in terms of output losses, which is contrary
to what we find for OECD nations. At the very least, this brings to attention the need to pay closer
attention to disinflations in developing economies. As of yet, this represents an under-researched and
not well-understood area of the literature. Next, we proceed to investigate what other factors might
therefore be of more significance in determining non-OECD sacrifice ratios.
When examining the role of inflation targeting in the developing countries of the world, we find
no sign of this being an important determinant of the sacrifice ratio. Specifically, Table 4(b) tests IT,
IT, and PIT (alongside IT) in our sacrifice ratio regressions. We do not find any robust evidence
that inflation targeting is important for non-OECD economies. On the two occasions where we do see
some statistical significance (regressions (4) and (5)), we obtain incorrect coefficient signs. Therefore
we conclude that inflation targeting is not important for non-OECD economies, just as was the case
with OECD member nations. We also check whether political factors have played an important role
in determining the behavior of non-OECD sacrifice ratios, and the results in Table 5(b) suggest that
Left and Polity2 are not significant when entered as the only political variable in the sacrifice ratio
regression (columns (1)-(8)). However there is some evidence that when we control for both political
orientation and democracy, that Left has a positive and significant coefficient (column (9)). This
indicates that more left-wing governments have higher sacrifice ratios in developing economies, which
in turn implies that the more right-wing governments of the developing world have tougher stances
towards inflation, which agrees with the arguments of Caporale (2011) who specifically examines
Latin American and Caribbean economies. However this result is not robust to the ten-year measure
of inflation history, π H 10
(column (10)). We also test whether trade openness is an important factor
behind non-OECD sacrifice ratios in Table 2(b). We do find one instance of a negative and significant
coefficient forOpenness PWT inregression(8), butthisresultisnotrobusttoswitchingtotheπ H 5 proxy
of nominal wage rigidity (column (6)). Therefore it appears, at least at first glance, that openness is
not a significant determinant of disinflation costs in non-OECD nations.
5.2 Central Bank Independence and Openness
However, this interpretation changes radically once we consider the role of central bank independence
on non-OECD sacrifice ratios, the results of which can be seen in Table 3(b). 15 In regression (1), we
regress SR on a constant and CBI and find no statistical significance. Indeed, when we control for
15 Also note that the R 2 s for these results are the highest we obtain for non-OECD economies out of all results in this
paper.
17

∆π, Length, and nominal rigidities (proxied by πH 5 and πH 10 ), we still find no statistical significance
(columns (2)-(5)). However, we find the results change dramatically if we follow the Daniels et al.
(2005) reasoning. Specifically, Daniels et al. (2005) arguethat opennessandcentral bankindependence
should be jointly tested in the sacrifice ratio regression, and further still the interaction between the
two variables may also be important. The reason for testing openness and central bank independence
together lies in firms’ price-setting behavior. In particular, a higher degree of trade openness will tend
to lower firms’ ability to change prices in response to changes in money supply, thereby reducing the
incentive for a central bank with discretionary power to undertake inflationary policy. In other words,
the interaction between openness and central bank independence may be a key determinant of the
sacrifice ratio.
In column (5) of Table 3(b), we regress SR on a constant, CBI, Openness, and the interaction
between the two for non-OECD economies. We find a negative and significant coefficient for both
openness and central bank independence. Moreover, both coefficients are very large in magnitude,
suggesting that these variables are not only statistically important, but are extremely economically
relevant as well. These results suggest that greater central bank independence and greater openness
both have the effect of lowering sacrifice ratios in non-OECD economies. When we also control for
the speed of disinflation (column (7)), we find that openness remains negative and significant, while
CBI barely misses statistical significance at the 5% level. Nonetheless, the results clearly indicate
that both CBI and Openness are economically important determinants of non-OECD sacrifice ratios.
In regression (6), we again regress SR on a constant, central bank independence, openness, and
the interaction term, but using the Penn World Tables measure of openness. We again find that both
CBI and Openness PWT are negative and significant, although the magnitude of the coefficient for
openness is smaller under the Penn World Tables measure. Indeed, the interaction between central
bank independence and openness is positive and significant. 16 Daniels et al. (2005) find a negative
and significant coefficient on this interaction term when considering OECD economies, which they
suggest shows that greater openness reduces the effect of central bank independence on the output
costs of disinflation. Hence, we find that the opposite is true of the developing economies in the world:
greater openness enhances the effect of central bank independence. In other words, countries that
have a higher degree of trade openness are more likely to find that their central bank becomes more
effective in terms of reducing output losses during a disinflation episode, if they are more independent.
16 Note that the interaction between CBI and our other measure of openness, Openness, is positive in regressions (5)
and (7) as well, and is extremely close to significance at the 5% level in both specifications.
18

Indeed, this finding is robust to controlling for the speed of disinflation (column (8)), where CBI and
Openness PWT continue to produce highly negative and significant coefficients.
In addition, we also repeat the regressions from (7) and (8) but with CBI as our measure of central
bank independence (columns (9) and (10)), which helps to extend our sample size, and we again
find that central bank independence and openness are highly negative and significant for non-OECD
economies, while their interaction is positive and significant. Thus the results from Table 3 suggest
that although openness and central bank independence are not statistically important for OECD
member nations, the opposite is true for non-OECD economies. For these developing and emerging
economies, greater openness and more independent central banks both tend to lower the output costs
of disinflation. Furthermore, greater openness in these developing and emerging economies enhances
the effect of central bank independence.
5.3 Debt-to-GDP Ratios
The final potential determinant that we will consider in this paper is one that has not received much
attention in the literature, namely the size of a nation’s central government debt, relative to GDP.
Goncalves and Carvalho (2008) is one paper that checks for the role of debt on the sacrifice ratio,
which is applied to OECD nations and a handful of developing economies. They find no impact of
debt on the output costs of disinflation. Although, Goncalves and Carvalho (2009) do not explicitly
include debt as a regressor in their final sacrifice ratio regression, they do implicitly include it by first
using debt-to-GDP ratios as a determinant of whether countries adopt inflation targeting in the first
place. Durham (2001) does explicitly test whether the debt-to-GDP ratio is an important factor that
affects the sacrifice ratio, where Durham anticipates a positive relationship between debt and output
cost of disinflation. The reasoning for this is that governments with substantial levels of debt may
face the temptation to monetize their debt, thereby also creating inflation. Therefore we may expect
to find a positive relationship between the stock of government debt and the sacrifice ratio, meaning
that countries with lower levels of debt will tend to have lower sacrifice ratios. Indeed, this is what
the empirical evidence of Durham (2001) supports when considering high-income countries, although
the author does find some evidence of a negative relationship between debt and sacrifice ratios for
low-income countries.
We thus proceed to examine the role of central government debt-to-GDP ratios on the sacrifice
ratio. Table 6(a) displays theresults for OECDeconomies, wherewe findthat debtis not an important
determinant of thesacrificeratio, since weobtain nostatistical significance inany specification. Indeed
19

the coefficient magnitudes themselves tend to be very close to zero. However, the same is not true of
non-OECD economies, the results of which can be seen in Table 6(b). In regressions (1)-(4) we test
the impact of the Debt RR measure of debt-to-GDP ratios on the sacrifice ratio. We find a negative
and significant coefficient in all four regressions, even when we control for the speed of disinflation
and nominal rigidities. In models (5)-(8), we then repeat these regressions except using the Debt JP
measure of debt-to-GDP instead. We obtain the exact same inferences as before: debt obtains a
highly negative and significant coefficient in all of these models tested. Lastly, we also control for
political orientation and democracy in (9) and (10), and find that political factors are not significant
determinants of non-OECD sacrifice ratios once we control for debt.
Thus we find that debt is a statistically significant factor that impacts the behavior of non-OECD
sacrifice ratios, although in a negative way. Moreover this finding of a negative and significant coeffi-
cient is a highly robust result. This outcome suggests two things to us. First, we usually expect output
to fall duringadisinflationepisode, andwhilethisstill may betruein many scenarios, it appearsthat a
higher level of government debt enables output to be stabilized–and further still, output may actually
rise–during disinflation episodes in non-OECD nations. This probably suggests that the increase in
government debt occurssimultaneously with someother factor that allows productiontoincrease while
inflation falls. Candidates of these other factors may be an increase in productivity or another type of
favorable supply shock. This is an interesting issue that warrants future research. Second, we would
expect a priori that a higher level of debt is associated with higher inflation expectations, and thus
higher output costs of disinflation. Hence the finding of a negative coefficient for debt in non-OECD
economies indicates that higher levels of debt have not led to higher inflation expectations. As a
result, these developing economies have been able to reduce output losses during disinflation episodes,
despite a higher level of government debt. The exact mechanism by which inflation expectations are
influenced by debt in developing and emerging economies remains an area for future research.
6 Conclusion
The sacrifice ratio is something that has been estimated by many authors over several different time
periods. However, the existing body of research has focused almost exclusively on advanced, indus-
trialized, or OECD economies. This paper seeks to fill a gap in the literature by measuring sacrifice
ratios using the commonly-used Ball (1994) methodology, which we apply to the entire world over a
roughly forty year period.
20

We then seek to find the determinants of these sacrifice ratios, for both OECD and non-OECD
economies. For OECD economies, we find that the speed of disinflation is overwhelmingly the most
important determinant of the sacrifice ratio, and this finding is robust to examining a variety of
different specifications. In particular, there is strong evidence that output losses during a disinflation
episode are minimized if the disinflation occurs in a relatively quick fashion. In other words, the cold-
turkey approach to disinflation may be warranted if welfare is measured by minimizing total output
losses. Other determinants that are widely considered in the literature, namely the initial level of
trend inflation, openness, central bank independence, inflation targeting, and political factors do not
appear to be important determinants of the sacrifice ratio, although there is some limited evidence
that the potential adoption of an inflation target tends to reduce output losses during a disinflation
episode.
When examiningthedeterminants of non-OECDsacrifice ratios, wefindsomething of apuzzle: the
speed of disinflation–which is a highly robust determinant of OECD sacrifice ratios–has no significant
impact on disinflations in the developing and emerging economies of the world. In other words, the
cold-turkey approach to disinflation appears not to be warranted in non-OECD nations. Instead,
we find that both central bank independence and openness are important determinants of non-OECD
sacrificeratios, wheremoreopeneconomiesthatalsohavemoreindependentcentral bankstendtohave
lower output costs of disinflation. In other words, a greater degree of trade and a greater separation
of monetary policymakers from political regimes in non-OECD countries can be beneficial in terms
of reducing sacrifice ratios. In addition, we unexpectedly find that non-OECD economies with higher
ratios of debt to GDP tend to have lower sacrifice ratios. This suggests that the mechanism by which
higher levels of debt is translated into inflation expectations is quite different in non-OECD economies
as we expect might happen in OECD nations. This remains an interesting area of research that future
research should seek to examine.
21

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25

Table 1: The Sacrifice Ratio, the Speed of Disinflation, and Initial Inflation
Dependent Variable: SR (1) (2)
(a) OECD
(3) (4) (5) (6) (7) (8)
Constant
3.68
(0.63)
-1.27 -1.47 -0.87 3.57 -0.79 -1.10 -1.08
∗∗
(0.55) ∗
(0.68) ∗
(0.78) (0.55) ∗∗
(0.82) (0.93) (0.97)
Speed=∆π/Length
-1.92
(0.53) ∗∗
∆π
-0.34
(0.07)
-0.33 -0.34 -0.26 -0.27 -0.41
∗∗
(0.07) ∗∗
(0.08) ∗∗
(0.10) ∗
(0.11) ∗
(0.16) ∗
Length
0.87
(0.11)
0.90 0.83 0.81 0.85 0.86
∗∗
(0.13) ∗∗
(0.13) ∗∗
(0.14) ∗∗
(0.15) ∗∗
(0.15) ∗∗
π H 5
-0.00
(0.01)
0.01
(0.01)
π H 10
-0.01
(0.01)
-0.01
(0.01)
π0
-0.19
(0.04)
-0.06 -0.06 0.06
∗∗
(0.05) (0.07) (0.11)
0.153 0.409 0.411 0.368 0.151 0.407 0.406 0.358
N 78 78 71 60 78 78 71 60
(b) Non-OECD
Dependent Variable: SR (1) (2) (3) (4) (5) (6) (7) (8)
Constant
0.17
(0.44)
-1.24
(1.21)
-1.26
(1.22)
-0.088
(0.44)
-0.64
(0.92)
-1.73
(1.65)
-1.84
(1.74)
-0.26
(0.52)
Speed=∆π/Length
0.17
(0.30)
∆π
0.11
(0.14)
0.14
(0.16)
-0.00
(0.06)
0.07
(0.10)
0.09
(0.12)
-0.02
(0.06)
Length
0.22
(0.21)
0.19
(0.20)
0.05
(0.17)
0.25
(0.23)
0.22
(0.22)
0.06
(0.16)
π H 5
0.00
(0.01)
-0.00
(0.00)
π H 10
0.00
(0.00)
0.00
(0.00)
π0
0.10
(0.11)
0.06
(0.07)
0.08
(0.08)
0.02
(0.04)
R 2
-0.002 0.006 0.004 -0.010 0.003 0.004 0.002 -0.013
N 348 348 316 280 348 348 316 280
R 2
Note: SR is the sacrifice ratio, ∆π is the amount of disinflation (trend inflation at peak minus trend inflation at trough)
over the disinflation episode, Length is the number of years of the disinflation episode, π H 5 and π H 10 are the average of
inflation in the previous 5 and 10 years respectively, and π0 is trend inflation at peak. OLS estimation is implemented
with HAC standard errors. ** and * denote significance at the 1 and 5 percent levels respectively.
26

Table 2: The Sacrifice Ratio and Openness
Dependent Variable: SR (1) (2)
(a) OECD
(3) (4) (5) (6) (7) (8)
Constant
1.59
(0.45)
1.93 -1.40 -1.13 -1.56 -0.95 -1.46 -1.02
∗∗
(0.45) ∗∗
(0.60) ∗
(0.61) (1.15) (1.07) (1.25) (1.16)
Openness
1.73
(2.37)
1.25
(1.43)
1.95
(1.50)
1.67
(1.71)
Openness PWT -0.00
(0.01)
-0.00
(0.00)
-0.00
(0.00)
-0.00
(0.00)
∆π
-0.32
(0.08)
-0.35 -0.26 -0.26 -0.39 -0.41
∗∗
(0.07) ∗∗
(0.12) ∗
(0.11) ∗
(0.18) ∗
(0.16) ∗
Length
0.84
(0.13)
0.87 0.84 0.84 0.85 0.85
∗∗
(0.11) ∗∗
(0.17) ∗∗
(0.15) ∗∗
(0.18) ∗∗
(0.15) ∗∗
π H 5
π H 10
π0
R 2
-0.00 0.01
(0.01) (0.01)
-0.01 -0.01
(0.01) (0.01)
-0.03 -0.06 0.06 0.06
(0.07) (0.07) (0.12) (0.11)
-0.006 -0.013 0.358 0.402 0.355 0.398 0.301 0.346
N 75 78 75 78 68 71 58 60
(b) Non-OECD
Dependent Variable: SR (1) (2) (3) (4) (5) (6) (7) (8)
Constant
0.40
(0.48)
0.83
(0.38)
-1.45 -0.87 -1.84 -1.29 -0.15 0.666
∗
(1.26) (1.67) (1.80) (2.30) (0.56) (0.639)
Openness
0.22
(0.54)
0.34
(0.46)
0.18
(0.49)
0.41
(0.47)
Openness PWT -0.00
(0.01)
-0.00
(0.01)
-0.01
(0.01)
-0.01
(0.00) ∗
∆π
0.12
(0.14)
0.10
(0.14)
0.12
(0.12)
0.09
(0.13)
0.01
(0.05)
-0.04
(0.05)
Length
0.23
(0.22)
0.25
(0.19)
0.22
(0.23)
0.25
(0.19)
0.04
(0.15)
0.14
(0.15)
π H 5
0.01
(0.01)
0.00
(0.00)
π H 10
0.00
(0.00)
-0.00
(0.00)
π0
0.05
(0.08)
0.06
(0.09)
-0.01
(0.04)
0.01
(0.04)
-0.003 -0.002 0.004 0.004 -0.001 -0.002 -0.016 0.012
N 321 329 321 329 290 299 256 268
R 2
Note: Openness is trade openness measured by the ratio of imports to real GDP, and Openness PWT is the Penn World
Tables’ (Heston et al., 2011) measure of trade openness, defined as the ratio of exports plus imports to real GDP per
capita. OLS estimation is implemented with HAC standard errors. ** and * denote significance at the 1 and 5 percent
levels respectively.
27

Table 3: The Sacrifice Ratio and Central Bank Independence
Dep. Var.: SR (1) (2) (3) (4)
(a) OECD
(5) (6) (7) (8) (9) (10)
Constant
4.94
(1.36)
-0.83 -1.26 -1.22 1.53 0.93 -1.61 -0.76 -0.13 -0.20
∗∗ (1.40) (1.96) (1.94) (2.81) (2.37) (2.80) (2.22) (2.63) (1.80)
CBI
-5.28
(2.51)
-3.17 -3.34 -3.31 3.19 5.26 -1.70 -2.93
∗ (1.90) (2.00) (2.00) (6.46) (6.00) (6.07) (6.25)
CBI
-3.67
(4.65)
-1.71
(4.15)
Openness
15.35
(13.36)
4.79
(13.12)
-0.07
(11.73)
OpennessPWT 0.07
(0.03)
-0.00 0.00
∗ (0.03) (0.02)
CBI× -38.12 -8.62
Openness (27.80) (25.96)
CBI× -0.17 -0.00
OpennessPWT (0.07) ∗ (0.08)
CBI× 5.22
Openness (19.44)
CBI× -0.00
OpennessPWT (0.04)
∆π
-0.29
(0.09)
-0.45 -0.44 -0.28 -0.30 -0.38 -0.37
∗∗ (0.30) (0.27) (0.10) ∗∗ (0.10) ∗∗ (0.11) ∗∗ (0.12) ∗∗
Length
1.01
(0.17)
1.05 1.05 1.01 1.02 0.97 0.92
∗∗ (0.22) ∗∗ (0.21) ∗∗ (0.20) ∗∗ (0.21) ∗∗ (0.19) ∗∗ (0.18) ∗∗
πH 5
-0.05
(0.03)
πH 10
-0.02
(0.01) ∗
π0
0.20
(0.24)
0.18
(0.20)
R 2
0.072 0.514 0.489 0.492 -0.001 0.103 0.421 0.474 0.341 0.381
N 29 29 29 29 28 29 28 29 36 37
(b) Non-OECD
Dep. Var.: SR (1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Constant
1.42
(1.56)
1.52
(1.78)
1.03
(2.22)
0.86
(2.31)
8.35
(3.06)
10.09 8.87 10.20 5.86 7.38
∗ (2.85) ∗∗ (3.71) ∗ (3.18) ∗∗ (2.05) ∗∗ (2.41) ∗∗
CBI
-1.39
(3.25)
-1.25
(3.25)
-1.79
(2.96)
-0.05
(4.24)
-21.32
(10.02)
-25.93 -20.98 -24.86
∗ (8.93) ∗∗ (10.58) (8.59) ∗∗
CBI
-12.01
(4.33)
-16.74
∗∗ (5.65) ∗∗
Openness
-31.11
(12.85)
-32.76 -24.80
∗ (13.14) ∗ (7.45) ∗∗
OpennessPWT -0.15
(0.05)
-0.17 -0.13
∗∗ (0.04) ∗∗ (0.03) ∗∗
CBI× 84.20 83.28
Openness (42.80) (44.44)
CBI× 0.42 0.41
OpennessPWT (0.15) ∗ (0.13) ∗∗
CBI× 57.59
Openness (18.36) ∗∗
CBI× 0.31
OpennessPWT (0.09) ∗∗
∆π
-0.18
(0.25)
-0.26
(0.22)
-0.27
(0.24)
-0.22
(0.12)
-0.41
(0.26)
-0.23
(0.10)
-0.38
∗ (0.20)
Length
0.16
(0.49)
0.19
(0.49)
0.14
(0.49)
0.23
(0.28)
0.57
(0.33)
0.26
(0.22)
0.55
(0.30)
πH 5
0.01
(0.05)
πH 10
-0.00
(0.00)
π0
0.09
(0.17)
0.10
(0.19)
R 2
-0.031 -0.079 -0.154 -0.145 0.139 0.096 0.119 0.154 0.158 0.181
N 32 32 32 32 31 32 31 32 43 44
28
Note: CBI is an index of central bank independence taken from Polillo and Guillen (2005), and CBI is CBI extended to 2008.
OLS estimation is implemented with HAC standard errors. ** and * denote significance at the 1 and 5 percent levels respectively.

Table 4: The Sacrifice Ratio and Inflation Targeting
Dependent Variable: SR (1) (2)
(a) OECD
(3) (4) (5) (6) (7) (8)
Constant
1.99
(0.31)
-1.68 -1.62 -1.76 -0.87 -0.81 -1.46 -1.57
∗∗
(0.51) ∗∗
(0.82) (0.88) (0.99) (1.11) (0.83) (0.91)
IT
-0.23
(0.43)
0.57
(0.33)
0.62
(0.37)
0.81
(0.47)
0.56
(0.37)
0.74
(0.47)
IT
-0.56
(1.41)
-0.56
(1.50)
PIT
-1.02
(0.54)
-0.92
(0.57)
∆π
-0.35
(0.07)
-0.29 -0.44 -0.25 -0.38 -0.29 -0.42
∗∗
(0.10) ∗∗
(0.15) ∗∗
(0.10) ∗
(0.16) ∗
(0.10) ∗∗
(0.15) ∗∗
Length
0.92
(0.11)
0.91 0.94 0.83 0.83 0.91 0.93
∗∗
(0.14) ∗∗
(0.15) ∗∗
(0.16) ∗∗
(0.17) ∗∗
(0.14) ∗∗
(0.14) ∗∗
π H 5
-0.00
(0.01)
0.01
(0.013)
0.00
(0.01)
π H 10
-0.01
(0.01)
-0.01
(0.01)
-0.01
(0.01)
π0
-0.04
(0.06)
0.06
(0.10)
-0.08
(0.06)
0.03
(0.11)
-0.06
(0.06)
0.04
(0.11)
-0.011 0.416 0.415 0.374 0.400 0.349 0.414 0.370
N 78 78 71 60 71 60 71 60
(b) Non-OECD
Dependent Variable: SR (1) (2) (3) (4) (5) (6) (7) (8)
Constant
0.40
(0.38)
-1.26
(1.20)
-1.82
(1.77)
-0.22
(0.51)
-1.84
(1.74)
-0.27
(0.52)
-1.88
(1.84)
-0.230
(0.523)
IT
0.64
(0.50)
0.58
(0.52)
0.44
(0.78)
0.97
(0.41)
0.30 0.94
∗
(0.97) (0.48)
IT
0.71
(0.30)
0.73
∗
(0.41)
PIT
-0.52
(0.85)
-0.09
(0.51)
∆π
0.11
(0.14)
0.09
(0.12)
-0.01
(0.06)
0.09
(0.12)
-0.02
(0.06)
0.08
(0.10)
-0.014
(0.064)
Length
0.22
(0.21)
0.22
(0.23)
0.05
(0.16)
0.22
(0.22)
0.06
(0.16)
0.25
(0.26)
0.058
(0.174)
π H 5
-0.00
(0.00)
-0.00
(0.00)
-0.00
(0.00)
π H 10
0.00
(0.00)
0.00
(0.00)
0.00
(0.00)
π0
0.07
(0.08)
0.01
(0.04)
0.08
(0.08)
0.02
(0.04)
0.08
(0.10)
0.02
(0.04)
R 2
-0.002 0.004 -0.001 -0.012 -0.001 -0.016 -0.003 -0.016
N 348 348 316 280 316 280 316 280
R 2
Note: IT a dummy variable equal to 1 for inflation targeters (0 otherwise), IT is a dummy variable equal to 1 if the
country was an inflation targeter before the disinflation episode began (0 otherwise), and PIT is a dummy variable equal
to 1 for potential inflation targeters (0 otherwise). OLS estimation is implemented with HAC standard errors. ** and *
denote significance at the 1 and 5 percent levels respectively.
29

Table 5: The Sacrifice Ratio and Political Factors
Dep. Var.: SR (1) (2) (3) (4)
(a) OECD
(5) (6) (7) (8) (9) (10)
Constant
2.58
(0.51)
-0.98 -0.65 -0.57 1.00 -1.49 -1.20 1.76 -0.69 2.05
∗∗ (0.73) (1.04) (1.08) (0.49) ∗ (0.69) ∗ (1.20) (2.80) (1.21) (2.69)
Left
-0.35
(0.25)
-0.29
(0.19)
-0.29
(0.20)
-0.31
(0.24)
-0.26
(0.19)
-0.25
(0.23)
Polity2
0.09
(0.05)
-0.00
(0.05)
-0.03
(0.07)
-0.35
(0.29)
-0.04
(0.07)
-0.33
(0.28)
∆π
-0.33
(0.07)
-0.27 -0.40 -0.32 -0.26 -0.34 -0.26 -0.33
∗∗ (0.11) ∗ (0.16) ∗ (0.07) ∗∗ (0.12) ∗ (0.18) (0.12) ∗ (0.17)
Length
0.90
(0.12)
0.85 0.86 0.89 0.89 0.93 0.88 0.92
∗∗ (0.15) ∗∗ (0.15) ∗∗ (0.12) ∗∗ (0.17) ∗∗ (0.17) ∗∗ (0.17) ∗∗ (0.17) ∗∗
πH 5
-0.00
(0.01)
0.01
(0.01)
-0.00
(0.01)
πH 10
-0.01
(0.01)
-0.01
(0.01)
-0.01
(0.01)
π0
-0.04
(0.07)
0.06
(0.11)
-0.05
(0.07)
0.01
(0.12)
-0.04
(0.07)
0.01
(0.12)
R 2
0.010 0.428 0.413 0.366 -0.005 0.407 0.408 0.378 0.413 0.380
N 71 71 71 60 74 74 67 57 67 57
(b) Non-OECD
Dep. Var.: SR (1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Constant
0.55
(0.70)
-1.47
(1.13)
-2.02
(1.74)
-0.39
(0.55)
0.05
(0.16)
0.03
(0.53)
0.09
(0.63)
-0.13
(0.57)
-0.14
(0.61)
-0.26
(0.58)
Left
0.08
(0.29)
0.07
(0.30)
0.06
(0.31)
0.26
(0.14)
0.36
(0.15)
0.26
∗ (0.16)
Polity2
0.03
(0.02)
0.03
(0.02)
0.02
(0.03)
0.01
(0.03)
0.00
(0.03)
-0.00
(0.04)
∆π
0.10
(0.17)
0.05
(0.12)
-0.06
(0.05)
-0.01
(0.04)
-0.01
(0.05)
-0.02
(0.05)
-0.02
(0.05)
-0.02
(0.05)
Length
0.31
(0.22)
0.34
(0.25)
0.17
(0.18)
0.03
(0.15)
0.00
(0.16)
0.00
(0.17)
0.00
(0.17)
-0.00
(0.17)
πH 5
-0.00
(0.00)
0.00
(0.00)
0.00
(0.00)
πH 10
-0.00
(0.00)
0.00
(0.00)
0.00
(0.00)
π0
0.07
(0.09)
0.00
(0.04)
0.00
(0.04)
0.03
(0.04)
-0.01
(0.04)
0.02
(0.04)
R 2
-0.004 0.003 -0.003 0.001 0.000 -0.007 -0.019 -0.022 0.001 -0.015
N 269 269 269 237 254 254 229 202 226 199
Note: Left is an index denoting the party orientation of a country, where a greater value for Left indicates more leftwing
governments (data from Beck et al., 2001). Polity2 is an index of democracy (data from the Center for Systemic
Peace), where a higher value of Polity2 indicates a greater level of democracy. OLS estimation is implemented with
HAC standard errors. ** and * denote significance at the 1 and 5 percent levels respectively.
30

Table 6: The Sacrifice Ratio and Debt-to-GDP Ratios
Dep. Var.: SR (1) (2) (3) (4)
(a) OECD
(5) (6) (7) (8) (9) (10)
Constant
1.97
(0.49)
-1.18 -1.33 -1.41 2.05 -0.92 -1.00 -1.15 3.17 2.25
∗∗ (0.72) (1.26) (1.37) (0.45) ∗∗ (0.66) (1.01) (1.00) (2.30) (2.63)
DebtRR 0.00
(0.01)
-0.01
(0.01)
-0.00
(0.01)
-0.01
(0.01)
-0.00
(0.01)
DebtJP -0.00
(0.01)
-0.00
(0.01)
0.00
(0.01)
0.00
(0.01)
0.00
(0.01)
Left
-0.07
(0.23)
-0.24
(0.20)
Polity2
-0.55
(0.26)
-0.36
∗ (0.31)
∆π
-0.32
(0.08)
-0.28 -0.52 -0.31 -0.29 -0.42 -0.28 -0.27
∗∗ (0.13) ∗ (0.20) ∗ (0.08) ∗∗ (0.16) (0.18) ∗ (0.07) ∗∗ (0.08) ∗∗
Length
0.88
(0.14)
0.89 0.91 0.79 0.79 0.80 0.99 0.86
∗∗ (0.20) ∗∗ (0.19) ∗∗ (0.13) ∗∗ (0.17) ∗∗ (0.17) ∗∗ (0.14) ∗∗ (0.16) ∗∗
πH 5
0.02
(0.04)
-0.00
(0.02)
πH 10
0.06
(0.04)
-0.02
(0.02)
π0
-0.04
(0.07)
0.08
(0.14)
-0.01
(0.10)
0.11
(0.12)
R 2
-0.016 0.370 0.355 0.297 -0.016 0.340 0.325 0.305 0.454 0.37
N 65 65 58 49 61 61 58 54 57 54
(b) Non-OECD
Dep. Var.: SR (1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Constant
1.05
(0.37)
2.31 1.86 2.09 0.76 0.66 0.45 0.70 2.32 0.69
∗∗ (1.01) ∗ (1.41) (1.48) (0.44) (0.66) (0.89) (1.01) (1.07) ∗ (0.77)
DebtRR -0.01
(0.00)
-0.01 -0.02 -0.02 -0.02
∗∗ (0.00) ∗∗ (0.00) ∗∗ (0.01) ∗∗ (0.00) ∗∗
DebtJP -0.01
(0.00)
-0.01 -0.01 -0.01 -0.01
∗∗ (0.00) ∗∗ (0.00) ∗∗ (0.00) ∗∗ (0.00) ∗
Left
0.18
(0.22)
-0.06
(0.22)
Polity2
0.03
(0.04)
0.08
(0.04)
∆π
-0.07
(0.11)
-0.14
(0.13)
-0.17
(0.14)
0.00
(0.06)
0.01
(0.07)
-0.01
(0.07)
-0.08
(0.16)
0.05
(0.07)
Length
-0.19
(0.32)
-0.13
(0.34)
-0.14
(0.36)
0.02
(0.18)
0.03
(0.18)
-0.01
(0.20)
-0.16
(0.37)
-0.12
(0.20)
πH 5
0.00
(0.00)
0.00
(0.00)
πH 10
0.00
(0.00)
-0.00
(0.00)
π0
0.07
(0.10)
0.09
(0.10)
0.00
(0.07)
0.02
(0.07)
R 2
0.037 0.045 0.034 0.049 0.027 0.015 -0.003 -0.007 0.039 0.025
N 76 76 64 59 160 160 152 138 64 126
Note: Debt RR is the ratio of total gross central government debt to GDP (data from Reinhart and Rogoff, 2011), and
Debt JP is the ratio of central government debt to GDP (data from Jaimovich and Panizza, 2010). OLS estimation is
implemented with HAC standard errors. ** and * denote significance at the 1 and 5 percent levels respectively.
31

Appendix: Sacrifice Ratio Tables
This appendix displays each of the disinflation episodes for OECD nations (Table A1) and non-OECD
nations (Table A2) in our sample from 1972 to 2008, using annual data. The tables display the onset
of each disinflation episode, the length of the episode, the rate of trend inflation at the peak, the
amount of disinflation, and the associated sacrifice ratio.
32

Table A1: OECD Sacrifice Ratios
Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Australia 1975 5 14.52 5.45 0.34
1981 5 10.32 3.68 2.43
1987 7 8.25 6.67 0.67
1995 4 3.05 2.19 0.17
Austria 1974 5 8.50 4.24 1.53
1981 7 6.19 4.51 0.77
1992 7 3.66 2.73 3.51
Belgium 1975 5 11.54 6.34 -0.09
1982 6 8.01 6.67 1.58
1990 9 3.26 2.02 7.08
Canada 1974 4 9.76 1.62 1.40
1981 5 11.15 6.99 1.80
1990 4 5.13 3.95 2.77
Czech Republic 1997 7 9.32 7.74 2.34
Denmark 1981 6 11.40 7.31 0.12
1988 7 4.44 2.66 2.74
Estonia 2001 3 4.45 1.79 0.29
Finland 1975 5 16.27 7.32 2.24
1981 7 11.06 7.03 0.93
1989 7 5.85 4.96 8.07
2001 4 2.50 1.86 1.18
France 1975 3 11.65 2.20 -0.39
1981 7 12.95 10.11 0.84
1990 9 3.37 2.58 7.78
Germany 1974 5 6.62 3.13 2.74
1981 7 5.67 5.26 2.14
1993 7 4.07 3.09 0.91
Greece 1974 4 18.59 5.90 -0.11
1991 10 18.57 15.51 2.85
Hungary 1979 4 7.65 1.67 0.94
Iceland 2001 4 4.89 1.82 6.48
Ireland 1975 4 18.89 6.37 0.31
1980 8 14.44 10.28 1.09
1990 5 7.71 5.22 3.32
2001 4 5.03 2.33 -0.65
Israel 1990 5 18.81 7.70 -0.01
1995 6 11.22 8.74 -0.83
2001 4 2.64 2.11 5.07
Italy 1975 4 17.60 2.52 -0.31
1981 7 19.06 13.84 0.93
1990 4 6.33 1.77 0.22
1994 5 4.57 2.68 -0.61
Japan 1974 6 15.52 10.28 0.19
1980 8 5.48 5.02 3.33
1990 6 2.87 2.64 0.16
1997 5 0.86 1.63 3.09
33

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Luxembourg 1975 5 11.54 6.33 -0.41
1982 6 8.00 6.65 2.12
1990 9 3.25 2.02 5.75
Netherlands 1975 4 9.63 4.71 -0.89
1981 7 6.39 6.35 1.60
2001 5 3.26 1.91 3.77
New Zealand 1981 3 16.31 7.51 0.08
1986 8 14.76 13.41 2.44
1995 4 2.60 1.80 1.06
Norway 1975 4 10.10 2.78 -0.89
1981 5 11.97 5.59 1.48
1987 7 7.54 5.53 3.83
Portugal 1990 9 12.31 9.91 2.31
Slovakia 1994 4 10.64 4.44 -0.69
2000 3 9.98 3.58 0.18
2003 4 6.46 3.50 2.27
Slovenia 2001 5 8.26 5.41 1.09
South Korea 1991 4 8.04 2.85 2.00
1997 4 5.63 3.26 4.86
Spain 1990 9 6.48 4.44 6.46
Sweden 1981 7 11.47 6.71 0.82
1990 4 8.75 5.71 1.34
1994 5 3.13 2.85 -1.01
Switzerland 1974 4 8.41 7.05 1.97
1981 7 5.39 4.03 3.13
1991 7 5.10 4.65 2.88
United Kingdom 1975 4 18.89 6.37 0.07
1980 8 14.44 10.28 2.90
1990 5 7.71 5.22 2.39
United States 1974 4 8.80 2.17 3.73
1980 7 11.71 8.66 1.42
1990 9 4.82 2.79 9.07
34

Table A2: Non-OECD Sacrifice Ratios
Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Afghanistan 2004 3 16.53 6.40 -0.19
Algeria 1978 6 13.60 6.72 0.58
1985 4 10.32 2.77 2.06
Antigua and Barbuda 1977 2 13.60 2.52 0.59
1981 5 15.60 13.19 2.03
Argentina 2003 3 14.58 6.26 -0.09
Armenia 2003 4 4.27 1.63 5.19
Bahamas 1974 4 9.64 5.12 8.94
1980 5 10.77 6.58 5.41
1991 8 5.84 4.48 8.05
Bahrain 1981 6 8.03 10.26 3.12
1996 5 1.56 2.63 1.29
Bangladesh 1994 4 8.15 2.64 0.30
1998 4 6.72 4.14 -0.23
Barbados 1980 7 14.06 11.20 3.70
1990 5 5.17 4.15 3.83
1996 4 3.99 3.08 -2.14
Belize 1974 4 17.75 14.17 0.66
1982 5 7.69 5.36 5.23
1995 5 3.96 4.45 5.46
Benin 1991 2 6.94 2.06 -0.11
1995 4 19.30 16.12 -0.12
2001 3 3.55 1.93 -1.64
Bermuda 1991 9 4.84 2.67 4.64
Bhutan 1982 5 12.62 6.55 3.12
1992 5 13.16 4.89 0.23
1997 6 8.63 5.97 -0.22
Bolivia 1991 4 15.72 7.42 0.92
1995 8 10.25 8.30 -1.84
Bosnia Herzegovina 1998 6 8.53 8.06 -1.12
Botswana 1975 3 13.89 2.58 1.27
1980 6 13.93 5.04 -1.73
1992 9 14.09 6.45 -0.07
2001 3 7.73 7.20 -0.01
Brazil 2002 6 10.00 5.51 1.72
Brunei 1982 3 5.55 3.36 -0.79
1994 6 4.23 3.99 -1.00
Bulgaria 2001 4 7.83 3.32 0.41
Burkina Faso 1978 3 13.65 3.64 0.16
1981 7 10.44 11.47 -0.14
1988 5 3.21 5.37 2.16
1995 2 8.74 4.34 -0.29
1997 4 4.51 3.30 1.78
Burundi 1975 2 12.76 2.96 0.54
1983 4 9.44 5.25 0.73
1990 2 9.22 3.28 -0.64
2004 2 10.68 2.63 0.16
Cambodia 1997 5 9.35 8.74 -0.22
Cameroon 1974 7 13.72 4.77 3.28
1983 3 13.75 4.54 -0.14
1986 5 9.81 9.97 -0.16
1995 5 15.99 13.90 -0.16
2001 4 2.83 1.87 -1.29
35

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Cape Verde Islands 1983 6 12.14 7.98 -1.69
1990 4 8.25 4.13 2.36
1996 6 7.62 6.70 -1.19
2002 3 2.14 2.24 0.55
Central African Republic 1976 5 18.90 12.35 -1.33
1983 6 10.15 13.50 -1.87
1990 3 -0.58 1.58 0.56
1995 4 15.83 16.39 0.68
2002 2 3.43 1.97 2.34
Chad 1981 2 8.67 2.91 1.61
1983 4 9.83 14.45 -1.29
1989 2 3.68 4.09 1.52
1991 2 -0.22 2.56 -4.83
2001 3 7.15 7.79 2.14
China 1979 5 5.28 3.25 5.71
1989 3 14.01 8.76 1.09
1995 6 17.72 18.18 -0.29
Costa Rica 1995 8 18.08 8.14 -0.11
Cote D’Ivoire 1978 7 19.00 15.07 1.09
1987 4 7.85 7.21 -0.50
1995 6 14.29 11.78 -2.90
Croatia 1999 5 5.04 3.73 0.44
Cuba 1993 5 16.83 21.67 -0.04
Cyprus 1976 2 8.44 2.24 -1.71
1980 8 11.24 8.76 2.08
1992 7 5.47 2.98 2.06
Djibouti 1982 4 7.03 6.91 -0.58
1989 2 8.75 3.45 -1.29
1995 8 5.27 3.80 7.33
Dominica 1990 5 4.99 4.02 -2.07
Dominican Republic 1974 4 14.24 6.21 -0.84
1980 3 11.16 4.23 0.12
1996 2 8.74 2.57 -0.16
Ecuador 1974 6 17.23 5.61 -1.26
Egypt 1981 2 15.32 1.58 -0.73
1990 4 19.28 8.01 0.43
1994 8 11.99 9.43 -0.93
El Salvador 1975 3 14.34 3.67 0.07
1980 4 15.63 3.45 6.54
Equatorial Guinea 1989 3 3.18 5.46 1.27
1994 5 19.06 15.28 2.42
2002 5 7.91 3.38 -6.87
Eritrea 1991 4 17.67 8.19 0.88
1996 4 11.80 4.60 -7.26
Ethiopia 1981 3 4.18 2.85 -1.15
1984 4 14.40 17.32 1.91
1992 2 13.54 4.50 -1.01
1994 4 13.29 13.33 -1.07
1998 4 4.28 6.25 -0.56
Fiji 1973 2 15.85 2.97 -0.34
1975 4 13.00 6.03 1.88
1980 6 11.16 7.32 1.73
1989 7 8.71 6.70 0.58
1997 5 4.04 2.00 -0.49
36

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
French Polynesia 1974 3 12.90 3.73 1.90
1979 7 12.28 12.79 0.99
1988 2 5.26 6.39 -0.06
1992 2 7.72 2.82 0.12
1994 4 5.02 4.77 1.90
2002 3 5.16 4.08 0.33
Gabon 1983 4 10.61 17.64 -2.17
1989 4 8.57 11.87 -0.73
1995 4 19.71 22.68 -0.83
2001 2 8.60 9.82 0.13
Gambia 1976 5 15.78 11.79 -0.02
2002 5 19.51 15.82 -0.43
Georgia 2000 2 9.38 4.53 0.07
Ghana 2004 2 18.14 5.88 0.05
Grenada 1977 7 18.49 15.04 108.31
1988 2 6.67 1.95 -0.21
1990 2 4.77 1.56 -0.82
1992 2 4.48 1.67 1.61
1994 5 2.94 1.86 10.38
Guatemala 1974 4 14.48 4.04 1.14
1980 4 11.20 8.45 0.03
Guinea 1992 7 18.53 15.20 -0.09
Guinea Bissau 1974 4 8.85 5.22 0.20
1979 2 7.38 1.51 11.31
2001 3 5.10 4.87 2.40
Guyana 1974 3 19.47 15.95 -0.68
1979 4 11.04 5.19 -4.04
Haiti 1974 4 18.15 14.54 0.46
1980 4 13.91 5.91 1.14
1984 4 9.10 10.45 0.05
Honduras 1974 4 8.81 2.45 4.52
1980 7 13.20 9.80 1.96
Hong Kong 1978 2 2.89 3.03 -0.22
1982 4 10.62 6.48 0.31
1989 11 10.44 13.44 -0.83
India 1973 5 17.33 16.26 0.43
1982 4 10.96 3.42 -0.72
1991 4 11.54 2.61 1.75
1997 6 9.79 5.83 0.41
Indonesia 1980 7 15.51 8.90 -0.37
2002 3 9.99 2.23 0.31
Iran 1976 4 17.14 2.85 -7.88
2003 3 15.19 1.81 0.40
Jamaica 2004 3 13.08 2.02 0.01
Jordan 1975 3 11.29 1.60 -1.68
1980 7 12.45 11.56 -0.39
1990 5 18.11 15.05 -0.12
1997 4 4.21 3.19 1.18
Kazakhstan 2000 4 10.00 3.60 -1.60
Kenya 1975 6 16.13 4.98 -0.23
1981 7 15.38 7.56 3.66
1997 6 8.98 3.14 -1.93
Kiribati & Tuvalu 1992 6 5.47 4.00 8.04
2002 4 3.67 4.53 0.13
37

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Kuwait 1977 4 7.94 10.79 -5.60
1981 7 7.36 6.33 1.04
1990 4 7.71 7.18 5.65
1995 4 2.92 1.65 1.60
Laos 2003 4 12.20 6.03 0.37
Lebanon 2003 2 2.95 1.99 -1.29
Lesotho 1976 3 14.17 5.35 -3.15
1981 3 15.02 6.09 1.21
1987 4 14.95 3.15 -3.20
1992 4 14.21 3.72 2.55
1996 5 10.84 9.43 -0.35
2003 3 15.20 10.31 0.43
Libya 1977 2 13.71 4.58 1.00
1979 2 11.17 6.06 -1.77
1983 6 11.11 7.13 17.40
1992 10 10.78 17.98 -4.97
Macau 1989 5 9.59 2.70 -3.28
1994 7 7.17 9.44 0.28
Macedonia 2001 4 4.71 4.34 1.05
Madagascar 1974 4 12.14 7.26 -0.44
1987 4 18.78 9.00 -1.69
2001 2 11.63 4.42 2.59
Malawi 1975 5 12.18 9.80 -0.96
Malaysia 1974 3 10.79 6.82 0.98
1981 6 7.40 6.74 -1.93
1997 6 3.81 2.40 10.69
Maldives Islands 1992 4 17.24 12.20 0.57
1996 4 6.44 6.32 -1.68
Mali 1986 7 3.21 4.78 -0.29
1995 5 14.47 13.76 0.00
2001 3 3.18 2.99 -0.64
Malta 1974 2 7.91 2.38 -0.45
1980 5 11.47 11.99 -0.23
1994 4 4.23 1.72 -2.00
Marshall Islands 1980 3 12.26 4.47 2.94
1983 5 9.67 6.23 4.46
1990 6 4.93 2.18 -19.52
Mauritania 1974 4 14.73 9.77 0.21
1985 3 9.26 3.62 -1.06
1992 4 8.38 3.26 -0.67
1997 5 5.78 1.83 -2.48
Mauritius 1974 4 19.10 8.88 -0.36
1989 4 11.77 4.39 -0.35
1998 5 6.85 3.41 -1.38
Micronesia 1994 4 3.58 3.48 -2.83
Mongolia 1980 3 16.31 5.19 0.31
Morocco 1975 2 11.33 1.65 -1.33
1981 4 10.81 2.02 -1.08
1985 4 9.64 6.86 -0.32
1994 5 5.48 3.99 2.34
Mozambique 2003 4 14.29 4.77 0.02
Namibia 1984 4 16.77 3.61 -0.02
1988 4 15.05 8.57 1.21
1994 4 12.31 4.65 -0.05
2004 4 12.16 4.78 -0.27
38

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Namibia 1984 4 16.77 3.61 -0.02
1988 4 15.05 8.57 1.21
1994 4 12.31 4.65 -0.05
2004 4 12.16 4.78 -0.27
Nepal 1973 5 13.21 8.50 -0.25
1981 4 12.51 4.75 2.00
1987 3 12.91 4.22 -0.68
1991 4 13.65 5.82 0.20
1997 5 8.16 5.43 -1.11
New Caledonia 1974 4 12.92 9.53 0.46
1980 3 12.26 4.47 1.17
1983 4 9.67 4.35 0.68
1987 4 6.43 2.86 -14.26
1992 7 5.70 3.66 -3.91
Nicaragua 1997 6 11.22 6.21 -2.04
Niger 1977 3 18.96 9.74 -1.53
1981 7 14.95 18.72 2.65
1989 4 -1.67 2.82 -0.18
1995 6 17.30 15.76 -0.17
2001 3 3.18 2.75 -0.75
Nigeria 2004 4 15.63 7.23 -0.04
Oman 1990 4 3.54 3.19 -2.48
1995 7 1.26 2.21 0.83
Pakistan 1980 7 10.70 6.09 -0.87
1995 8 11.70 8.58 0.59
Palau 1987 4 5.75 2.89 0.97
1991 3 4.67 3.09 4.42
1999 2 10.55 2.57 0.25
2001 3 10.49 5.20 0.17
Panama 1972 5 6.59 2.90 -3.11
1980 8 9.70 9.29 -9.20
Papua New Guinea 1974 5 14.00 8.63 1.97
1980 7 8.63 4.46 4.09
1990 4 6.13 2.09 -1.51
1999 8 14.70 13.07 4.50
Paraguay 1973 4 15.74 8.89 0.45
2002 4 10.67 3.76 0.52
Philippines 1973 4 19.65 11.03 0.40
1980 3 16.27 5.16 -0.29
1990 5 13.92 6.16 2.32
1997 5 8.22 5.01 1.61
Republic of South Africa 1981 3 14.52 1.69 3.16
1986 4 17.04 3.09 -1.45
1990 11 14.80 9.39 4.37
2002 4 6.82 5.35 0.63
Rwanda 1978 2 7.75 3.48 -0.38
1983 5 8.06 9.44 1.39
2005 2 11.71 1.70 0.72
Samoa 1974 4 15.18 7.99 -0.81
1989 2 10.07 3.44 0.32
1991 2 7.48 4.51 0.47
1993 2 7.61 3.98 1.12
1995 2 4.85 1.74 -1.79
1997 3 4.82 3.67 -0.17
2003 2 8.17 2.07 0.14
2005 2 7.32 3.59 0.45
39

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Saudi Arabia 1979 7 4.25 6.86 -1.34
1990 4 2.66 2.14 -7.43
1995 6 2.22 3.41 -1.65
Senegal 1974 4 19.85 14.57 -1.55
1983 6 13.59 15.43 0.53
1995 5 14.30 13.40 0.10
Seychelles 1984 3 3.66 2.44 -2.22
1991 6 3.04 3.28 2.81
2000 4 6.20 3.75 -0.82
Singapore 1974 3 14.85 13.56 0.26
1980 7 6.93 7.06 -2.54
1990 10 3.08 2.71 -9.81
Solomon Islands 1975 3 11.06 4.68 -0.95
1981 4 14.16 5.21 -1.72
1988 4 14.22 2.71 0.96
1995 2 11.55 1.72 -1.41
1997 4 10.75 3.43 -6.61
2002 4 9.00 1.88 0.17
Sri Lanka 1974 3 9.52 6.46 -0.15
1981 6 18.31 12.59 -0.52
1989 6 15.68 6.39 0.14
1997 3 11.62 4.88 0.25
2002 2 10.01 2.19 -0.14
St. Kitts and Nevis 1981 4 11.79 7.94 2.16
1991 2 6.19 2.13 0.75
1993 3 5.20 4.97 0.27
1998 4 5.42 3.32 -1.10
St. Lucia 1990 4 4.42 1.89 -2.10
1995 3 3.94 2.57 1.23
1999 4 3.47 2.59 2.71
St. Vincent and the Grenadines 1977 3 15.51 3.65 -2.53
1980 5 12.83 8.79 0.12
1990 5 6.03 4.75 3.24
1997 5 2.33 1.72 -6.07
Suriname 1976 2 15.78 5.74 -0.03
1978 7 12.94 11.79 1.57
1988 2 13.73 5.46 -0.96
Swaziland 1974 2 14.29 1.67 -4.54
1980 4 18.40 6.62 0.78
1986 5 15.86 6.00 -1.78
1994 5 12.69 5.59 1.27
2001 5 10.06 5.44 -0.40
Syria 1974 5 17.28 12.70 -2.41
1981 3 17.33 7.44 -0.84
1994 6 15.98 17.04 -1.07
Taiwan 1980 6 15.03 14.86 1.04
1995 4 3.62 2.70 -0.65
Thailand 1974 3 15.05 9.36 0.48
1980 6 14.09 12.37 -0.15
1997 4 6.48 5.31 3.77
Togo 1976 4 17.37 10.61 0.23
1981 5 14.38 14.79 1.45
1987 2 1.34 1.65 -0.74
2001 3 2.96 2.12 -0.52
40

Country
Start of Length Initial Trend Change in Trend Sacrifice
Episode (years) Inflation (%) Inflation (%) Ratio
Tonga 1981 3 16.04 9.12 -0.32
1986 3 14.37 8.15 -0.31
1991 4 9.41 8.27 0.57
2003 4 11.00 4.11 -2.94
Trinidad and Tobago 1974 4 17.94 7.04 0.96
1980 7 15.51 6.82 -7.70
1989 4 10.07 3.04 -2.17
1993 4 8.69 4.61 -0.68
Tunisia 1985 5 10.26 2.86 4.71
1990 4 7.49 2.65 -1.34
1994 7 4.98 2.44 1.41
Uganda 1995 5 8.52 5.38 -0.56
2000 2 3.81 2.31 0.15
United Arab Emirates 1993 6 5.57 4.40 -4.56
Uruguay 2003 4 14.17 7.77 -0.74
Vanuatu 1981 4 14.92 12.17 -1.07
1988 8 10.85 9.04 -5.51
Venezuela 1980 4 16.65 7.46 0.24
Vietnam 1997 5 5.38 4.82 0.93
West Bank 1995 6 11.93 7.82 -6.72
Yemen 2005 2 15.05 1.53 -0.07
Zaire 1979 10 13.54 11.73 -1.01
1996 7 9.18 3.05 15.29
Zimbabwe 1975 4 12.50 3.02 2.11
1981 2 11.47 2.44 -0.21
1983 5 9.98 7.52 1.71
41