analysis & interpretation of economic sanctions journal of economic studies, volume 24, number...
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The Analysis and Interpretation of Economic Sanctions §
Shane Bonetti Department of Economics University of St Andrews
Scotland
In the past decade there has emerged a lively literature on the analysis and
interpretation of economic sanctions. The focus of this literature is a search for
the correlates of success. The key issue is to explain the motives underlying the
imposition of economic sanctions.
The boldest and most innovative contribution to the recent sanctions literature
has been Hufbauer, Schott & Elliot's Economic Sanctions Reconsidered. Hufbauer,
Schott & Elliot (hereafter HSE) have produced a dataset unique in its coverage
and detail. While this data is excellent, many of the inferences drawn from it by
HSE are flawed. This paper explores these inferences in detail.
This paper also discusses three volumes which use the dataset produced by
Hufbauer and his colleagues. Van Bergeijk's Economic Diplomacy brings rigorous
statistical analysis to the HSE dataset. Kaempfer & Lowenbergs' International
Economic Sanctions pioneers the application of public choice theory to sanctions.
Kaempfer & Lowenberg claim to find some supporting evidence in the HSE
dataset for the importance of domestic political dynamics in determining the
outcome of sanctions. Finally, Martin's Coercive Cooperation is a useful reminder
that whether sanctions "work" is not the only question worthy of scholarly
interest. Martin uses the HSE dataset as the starting point for her attempt to
§ Peter A. G. van Bergeijk (1994), Economic Diplomacy, Trade and Commercial Policy: Positive and negative sanctions in a new world order, (Aldershot, Edward Elgar); Gary C. Hufbauer, Jeffrey J.
Schott & Kimberly A. Elliot (1985) (1990), Economic Sanctions Reconsidered: History and current
policy, (Washington D.C., Institute for International Economics); William H. Kaempfer & Anton D.
Lowenberg (1992), International Economic Sanctions: A public choice perspective, (Boulder, Westview Press); Lisa L. Martin (1992), Coercive Cooperation: Explaining multilateral economic sanctions, (Princeton, Princeton University Press).
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explain the prevalence and extent of international cooperation in the imposition
of economic sanctions.
1. The Empirical Analysis of Economic Sanctions
In Economic Sanctions Reconsidered (1985) (1990), Hufbauer, Schott & Elliot
attempt to tease from history some skeletal anatomy of the conditions conducive
to successful economic sanctions. Economic Sanctions Reconsidered is therefore an
exercise in scholarship by empirical generalisation. The first edition survey 103
sanctions episodes, beginning with the 1914-1918 blockade of Germany and
ending with US sanctions against Grenada in 1983-1984. The second edition adds
a further 13 episodes. Such a large number of cases is likely to create at first
glance a rhapsody of perceptions. To permit generalisation, HSE assign a
judgmental "success score" to each episode, and attempt to explain the variation
in success across episodes. HSE use their statistical analysis to adduce nine
"commandments" regarding the use of sanctions.
1.1 Data, Method, Results
For each sanctions episode HSE rank the "policy result" from 1 (failure) to 4
(success). The intermediate values are an "unclear but possibly positive outcome"
(2) and a "positive outcome" (3). The "contribution of sanctions" to this result is
ranked from 1 (none) to 4 (significant). The intermediate values are a "minor
contribution" (2) and a "modest contribution" (3). The "success score" of the
episode is the product of the "policy result" and "contribution" scores. Thus a
policy result of 3 and a contribution of 4 yields a score of 12. HSE define "success"
as a score of more than 8 out of a possible 16. By this definition, 34% of the 115
episodes analysed by HSE (1990) are classified as successes.1
1 There have been some odd summaries of HSE. E.g.: (i) "After analyzing 100 cases of economic sanctions ... [HSE] ... conclude that as a means of achieving political objectives the technique is all but useless": Leng (1993), 99. (ii) "[T]he basic study of (HSE) ... has re-evaluated more than 100 cases .... Not surprisingly, the study comes to the conclusion that in nearly all cases the expectations have not met the actual results": Jacobsen (1990), 114-115, note 1. These can be
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This is the most striking result of the HSE study. It is in direct contradiction to
the overwhelming consensus of scholars, carefully documented by Baldwin
(1985), that sanctions generally do not work. What the HSE study makes clear is
that this flawed consensus view was built on the shallow foundation of a
comparatively small number of high-profile sanctions episodes.
Not content with such a stunning contribution, HSE set themselves the task of
exploring the correlates of success. An important element in this is an
econometric success equation. HSE (1985) regress the success score against 18
variables. These variables and their estimated coefficients are listed in Table 1.
(Table 1 about here)
The putative implications of Table 1 can be briefly summarised. Economic
sanctions are likely to be more successful if the aims are modest, if prior sender-
target relations are good, if the sanctions impose heavy costs on the target, and if
the pre-sanction trade linkage between sender and target is large. Economic
sanctions are more likely to fail if covert action accompanies the sanctions, if
military force is used, if the sanctions are multilateral, if the target country
receives support from third countries, if the target is politically stable and
economically healthy, and if the sanctions continue for a long period.
1.2 Predictive Accuracy: An Illustrative Test
The sanctions against Iraq over the August 1990 invasion of Kuwait can be used
to illustrate and test the predictive power of the HSE success score equation.2 To
assess the likely outcome of the episode requires values for the 18 variables in the
equation. Assuming that the sanctions were accompanied by military action, that
third party support for Iraq was relatively insignificant, that import, export and
profitably contrasted with HSE's own summary: "Sanctions have been successful - by our definition - in 34 percent of the cases overall": Hufbauer, et al. (1990), 93. 2 Cf. van Berjeigk (1994a), Dehejia & Wood (1992), Hufbauer & Elliot (1991).
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financial controls were all used, that the cost imposed on the Iraqi economy was
20% of annual GDP, and that the cost to the sender was three on a scale of 1–4
(that is, a modest loss), the HSE equation predicts a success score of 7.7. By HSE's
definition, this counts as a failure, albeit marginal. Thus the HSE technique
predicts that the sanctions against Iraq would have failed even if full-scale war
had not overtaken events. However, the accuracy of this prediction is
questionable. The explanatory power of the equation is weak. As HSE remark: "The explanatory power of the ... equation is not high. Only 21 percent of the variance in success score is explained by the enumerated factors".3
That is, the technique cannot account for 79% of the variation of success scores.
This predictive weakness is made transparent by reference to significance tests
and the standard error. Of the 18 coefficients in the HSE function, only three
significantly differ from zero: the "World War" dummy; the dummy variable for
third party support; and the index of the political and economic health and
stability of the target.
Furthermore, the HSE equation has a standard error of 4.6: "This suggests that the equation ... cannot distinguish between circumstances that lead to marginal failures ... and circumstances that produce marginal successes".4
The standard error measures the average variability of the actual from the
predicted success score. The standard error of 4.6 success score points means that
the success score of the Iraqi sanctions is highly likely to be in the range 7.7 ± 4.6.
The standard error is so large that (at a probability of 95%) we can only predict
that the score would have been somewhere between 3.1 and 12.3 out of a possible
16. The predictive power of the equation is so weak that it tells us only that the
predicted outcome of the episode is somewhere between feeble failure and
comfortable success.
3 Hufbauer, et al.(1985), 79. 4 Hufbauer, et al.(1985), 79.
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1.3 Predictive Accuracy: A Systematic Test
A more thorough test of the predictive accuracy of the success equation can be
conducted by examining "out-of-sample" forecasts. Table 2 compares the
predicted and actual outcomes of 12 episodes included in HSE (1990) which
occurred after the sample period used to construct the success score function in
HSE (1985).
(Table 2 about here)
This predictive record may be summarised in several ways. First, the predicted
success rate is 42%, while the actual success rate was 17%. Second, the root mean-
squared error of prediction is 3.8 points on the 16 point scale. Finally, the episode
outcome (success or failure) is correctly predicted in 58% of cases. This may
appear reasonably high. However, with a binary variable like success or failure,
any randomising device could be expected to predict the outcome accurately in
50% of cases.
The Fischer Exact test (ρ=0.682, N=12, S1=2, S2=5, X=1, α=0.05) reveals that the
predictive performance of the HSE success score equation is not significantly
different from that which would be expected by random prediction. The
Spearman rank-order correlation coefficient between the predicted and actual
success scores (rs = 0.112) is not significantly different from zero at any
conventional level of significance. That is, the hypothesis that the predicted and
actual success scores are unrelated cannot be rejected. The phi coefficient (rφ =
0.28) is insignificantly different from zero. There is therefore no apparent
relationship between the actual and predicted division into success and failure.
The result of the Wilcoxon rank-sum test (p= 0.384) is greater than any
conventional level of significance. Hence the hypothesis of identical distributions
can be rejected. In short, this evidence is consistent with extremely weak
predictive accuracy as measured by out-of-sample performance.
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1.4 Analysis by Comparison of Averages
The HSE (1985) multiple regression equation tracks history poorly, and is a weak
predictive device. HSE (1990) relies in its stead on a crude analysis of averages.
Principally, this means classifying sanctions by several criteria and examining the
arithmetic average success score for each class. Some salient features of successes
and failures for categorical and ordinal variables are summarised in Table 3.
(Table 3 about here)
However, comparison of averages alone cannot disentangle systematic and
random variations. Statisticians have laboured long to answer Edgeworth's
question, "under what circumstances does a difference in figures correspond to a
difference in fact?".5 The answer to this question is the significance test in its
various guises, which shows whether a difference is sufficiently large that it
cannot be attributed to random factors. HSE conduct no significance tests.
Without them we cannot be sure that any of the differences on which they base
their "commandments" are systematic.
In an attempt to rectify this omission, chi-square tests are used here to assess the
null hypothesis that success and the relevant condition are independent, and
Cramer's C is used to measure the strength of any detected association of success
and the specified condition. The results are summarised in Table 4.
(Table 4 about here)
Not all of the HSE data is categorical or ordinal. Table 5 summarises these ratio
and interval measures in the HSE dataset, and tests of their significance.
(Table 5 about here)
For an adherent to the HSE methodology, Tables 4 and 5 make generally
depressing reading. They are summarised briefly below, by sanction
characteristic.
5 Edgeworth (1884), 38, cited in Stigler (1986), 308.
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(1) Policy Goal: At the heart of the HSE analysis is the claim that success varies
according to the type of policy goal. Initially, HSE classify policy goals as: modest
policy changes; destabilisation of target governments; disruption of military
adventures; impairment of military potential, or other major policy changes.
When the goals are multiple the most ambitious takes precedence. Observations
were pooled into two groups: modest policy changes and other cases. This
pooling was on the basis that the former group displayed generally higher
success scores. This classification of policy goals is a central organizing feature of
their analysis. However, the chi-square test of independence shows that success
and policy goal are independent. That is, the data are not consistent with HSE's
claim that "the success rate depends importantly on the type of policy or
governmental change sought".6
(2) International Assistance: HSE claim that "external assistance (to the target) ...
erodes the chances of success".7 The data are not consistent with this claim.
(3) Type of sanction: HSE claim that their data reveal "a better track record for
financial sanctions alone", echoing earlier assertions by Deese (1984) among
others. The null hypothesis that success and type of sanction are independent
cannot be rejected by a chi-square test. The data are not consistent with HSE's
claim.
(4) Cost to the Sender: HSE advise that "a country should shy away from
deploying sanctions when the economic costs to itself are high".8 The support for
this assertion is that the average "cost to sender" index is lower in success cases
than in failure cases. However, the difference is rather small. The chi-square test
6 Hufbauer, et al. (1990), 93. 7 Hufbauer, et al. (1990), 97. 8 Hufbauer , et al. (1990), 103.
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is consistent with the null hypothesis that the cost index and success are
independent. The data are not consistent with HSE's claim.
(5) Time Period: It is possible to split the HSE dataset into two approximately
equal parts (pre- and post-1973), to test whether there has been any "time-trend"
in sanction success, perhaps as a consequence of declining US hegemony. The
data are consistent with significantly lower success rates in the second half of the
sample.
(6) Target health and stability: HSE claim "a direct correlation between the
political and economic health of the target country and its susceptibility to
economic pressure .... Countries in distress ... are far more likely to succumb to
coercion".9 In support of this assertion they cite an average health and success
index of 1.9 in success cases and 2.3 in failure cases. The null hypothesis that the
stability index and success are independent can be rejected. The data are
consistent with HSE's claim.
(7) Size: There is a long history of using national income as a measure of power.10
However, the results of both chi-square tests and t-tests are consistent with HSE's
conclusion that "relative size is not ... helpful in predicting success".11
(8) Companion Covert and Military Policies: The modern view is that, while
economic sanctions were once usually used as a complement to military
endeavour, they are now primarily a substitute for such action. HSE do not claim
that any particular relationship exists between success and companion policies.
The data reveal no relationship.
9 Hufbauer, et al. (1990), 97. 10 E.g. Davis (1954), 208; Knorr (1956); Merritt & Zinnes (1989), 13; Organski (1958), 436. 11 Hufbauer, et al. (1990), 99.
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(9) International cooperation: There are often serious limits to the achievement of
cooperation in economic sanctions episodes. One limit is that a "decision to
impose an economic sanction must be made quickly and secretly to prevent
cushioning actions by the embargoed country".12 Notwithstanding this, there are
good grounds for believing that if cooperation can be achieved rapidly it will
increase the probability of success. However, the null hypothesis that
cooperation and success are independent cannot be rejected. As HSE correctly
observe "the idea that international cooperation is a necessary ingredient in all
sanctions is misplaced".13
(10) Prior Relations: HSE assert that "sanctions seem most effective when aimed
against erstwhile friends".14 The null hypothesis that the prior relations index
and success are independent can be rejected. The data are consistent with HSE's
claim.
(11) Presanction trade relations: It is a fundamental doctrine of economics that
there are mutual gains from trade. If such gains did not exist trade would not
occur. Economic sanctions involve the sacrifice or the threat of sacrifice of these
gains. Sanctions are therefore costly to both sender and target and, all other
things being equal, the more open is an economy the greater will be its
vulnerability to the costs caused by economic sanctions.15 However, it may be
that the ratio of presanction trade linkage between the target and the sender, as a
percentage of the target's total trade, is a rather coarse measure of vulnerability
to sanctions.16 The t-test reveals a significant difference, in the hypothesised
direction, between trade linkage in success and failure cases.
12 Roney (1983), 136-137. 13 Hufbauer, et al. (1990), 95. 14 Hufbauer, et al. (1990), 99. 15 Hirschman (1980), 18; van Ham (1992), 102; Wolf (1983), 405. 16 Galtung (1967); Bornstein (1968), 419; Kapunga (1973), 46.
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(12) Duration: In principle, duration has an ambiguous effect on success. The
longer the duration the greater the opportunities for the target to adjust to the
sanctions, and to find substitutes for sanctioned items. A negative duration effect
may also be the consequence of excessive use of gentle and gradualist escalation
from threats, to voluntary sanctions, to selective mandatory sanctions, to
comprehensive mandatory sanctions.17 On the other hand, the longer the
duration the greater the probability of the exhaustion of the resources and
resistance of the target. HSE's treatment of their data make any test of duration
effects rather coarse. In particular, they unnecessarily round to whole years.
Although more accurate measurement of the duration of the sanctions episodes
only reduces the average duration marginally, from 5.5 to 5.4 years, in nearly
10% of cases the rounding results in overstatement of the duration of the episode
by a factor of four or more. For example, in the "Nightfrost" incident the USSR
imposed sanctions against Finland in November of 1958.18 These sanctions were
removed in January 1959. Yet HSE give the duration of this episode as one year.
Similarly, on August 24 1963 the US threatened sanctions against South Vietnam
over certain human rights issues.19 Restoration of aid programs was promised on
3 November 1963. Again, HSE count this episode as lasting one year. HSE argue
that one of the implications of their case studies is that effective sanctions tend to
be short and sharp. The hypothesis that the population variance of success and
failure cases is equal is unsupported by the F-test results in Table 5. Therefore, a
one-tailed Cochran approximate t-test is used. The null hypothesis is that the
mean duration is the same in successes (µ= 2.87, s=2.79, n=41) and failures (µ=
7.75, s=10.01, n=77). The alternative hypothesis is that the mean duration is
greater in failure cases. Cochran's t'= 3.97 > 1.67 which is the critical value at the
5% level of significance. Thus the null hypothesis can be rejected.20 Of course, the
17 Kapunga (1973), 48-52. 18 Hufbauer, et al. (1985), 298-301. 19 Hufbauer, et al. (1985), 382-388. 20 The failures includes 24 episodes in which the sanctions are continuing. Removing the
continuing episodes substantially reduces the mean duration of unsuccessful episodes (µ= 4.25,
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relationship between duration and success may be non-linear. It may be that
sanctions need to be imposed for more than some minimum period before they
bite effectively, but that the maintenance of sanctions beyond some critical
maximum duration is indicative only of misplaced belligerence in a losing battle.
The tests conducted above do not examine that possibility.
1.5 Conclusion
Economic Sanctions Reconsidered has become the standard reference in the
empirical study of economic sanctions. Its statistical analysis and its "nine
commandments" seem to be regarded by many as providing convincing evidence
of the factors conducive to success. An incomplete list includes Berridge (1987),
Christiansen & Powers (1995), Cohen (1985), Doxey (1987), Dumas (1995),
Hanson (1988), Holsti (1992), Kaempfer & Lowenberg (1986), Lenway (1988) and
Tsebelis (1990).
However, Leitzel (1987) was correct in concluding that "the statistical evidence in
support of any of the commandments is scanty at best". In short, only prior
relations, target health, time period and duration, trade linkage and cost to the
target appear to be significantly related to success. All of the other measures of
sanctions characteristics are not significantly related to success. Thus if any policy
implication is to be drawn from the HSE data using the HSE method it is this: to
maximise success briefly attack weak but friendly countries to whom you are an
important trading partner (and do it before 1973!).
2. Problems & Pitfalls in Judging Sanctions Success
s=4.44, n=53). Using the one-tailed Cochran approximate t-test, t'=1.80 > 1.68 which is the critical value at the 5% level. Thus the rejection of the null hypothesis of equal duration in success and failure cases is robust to the inclusion or exclusion of censored episodes.
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This section considers three possible explanations for the paucity of reliable
correlates of success revealed by the HSE method of comparing averages: success
measurement; case selection and uncertainty.
2.1 The Measurement of Success
There are several general problems in measuring success. First, it seems that the
success of economic sanctions is not always judged by the standards applied to
other forms of statecraft.21 Second, all measurement is approximate, particularly
when the "measurement" lacks the objectivity and replicability which is the
hallmark of scientific procedure.22 Finally, sanctions scholars may not have all of
the information required to form accurate judgements.23 Beyond these intangible
difficulties, there are three specific problems with the measure of success adopted
by HSE.
2.1.1 Objectives
Sanctions usually have multiple objectives.24 The objectives often evolve over
time.25 When goals are multiple the most ambitious takes precedence, so that
HSE adjudge success against the most ambitious announced objective. This
procedure is problematic for several reasons.
The first problem is clarity. Expressed objectives are frequently vague. An
example illustrates: "In late January 1965, the Johnson Administration ... suspended food shipments to the UAR. ... The suspension was a form of coercion against President Nasser to cease UAR aid to the Congolese rebels. In addition to the Congo, the United States and the UAR had several other differences .... Except for the Congo issue the Johnson administration made no explicit demands ....
21 Caporoso & Haggard (1989), 106-107. 22 Trusted (1979), 43-44. 23 Davis (1991), 75; Hill (1994), 9; Holsti (1975), 133; Holsti & North (1965), 156; Krasner (1978), 247; Snyder, et al. (1962), 56. 24 Baldwin (1985); Bayard, et al (1983) 74; Deese (1984), 151; Weintraub (1982), 38. 25 Mandel (1987), 41; Weintraub (1982), 8.
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Instead the administration told Nasser than an improvement in overall US-UAR relations was needed. This gave President Nasser latitude to select the areas for improvement".26
The enunciation of such vague objectives has several causes. The cautious and
circumlocutive language which characterises international relations may be the
root cause. However, there are circumstance in which the enunciation of vague
objectives is rational, in which ambiguity has utility. Paradoxically, vague
objectives minimise the range of possible loopholes which the target might
exploit.27 In addition, clear objectives invite clear measurement of success. If the
penalties for perceived failure are high or if the sender is strongly averse to the
risk of appearing to fail, a sensible prophylactic measure is to announce vague
objectives.
The second difficulty in judging sanction success according to stated objectives
derives from exaggeration. Decision makers confronted with difficult choices are
subject to "a well-established phenomenon that cognitive psychologists call
'spreading'. Someone who has made a difficult decision is likely to feel
uncomfortable about it, ... so he will tend to exaggerate the considerations that
favoured it and to minimize the considerations that went against it".28 Its effect
may be a proclivity to overstate the objectives of sanctions episodes, so that it
may be unrealistic and inappropriate to judge success solely against the most
ambitious announced objective.
Finally, judgement against announced objectives is complicated by the
prevalence of signals and symbols in sanctions episodes. The aim of economic
sanctions may not be to coerce the target to adopt or eschew a specific course of
action. The aim may be to project a particular image or threat, either domestically
or internationally.29 Sanctions may satisfy a desire for vengeance, in which case it 26 Weintraub (1982), 31. 27 Baldwin's gorgeous campus unrest example illustrates: Baldwin (1985), 54-5. 28 Pears (1984), 56. 29 Jervis (1970), 14, 28; Knorr (1984), 203; Northedge & Donelan (1971), 39.
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is of little consequence whether the supposed coercive purpose succeeds.30 The
objective can even be "simply to avoid what might be interpreted as a reward
soon after a specific action or event".31
If the primary aim of sanctions is a demonstration effect to third parties, or some
reaffirmation or alteration of reputation, sanctions may proceed even though
both sides believe the sanctions will not alter target behaviour. An example
illustrates. US sanctions against Cuba are one of the more frequently cited cases
of the failure of sanctions.32 Baldwin (1985) argues cogently that these symbolic
sanctions were implemented even though both sender and target believed that
the target's behaviour would probably not be altered.
2.1.2 The Success/Failure Divide
For each sanctions episode HSE rank the "policy result" from 1 (failure) to 4
(success) and the "contribution of sanctions" to this result from 1 (none) to 4
(significant). The "success score"(S) is the product of these two rankings. HSE
define "success" as a score of more than 8 out of a possible 16. This success
benchmark might be incorrect. To see this, randomly choose a policy result and a
contribution score, in each case in the range (1,2,3,4). The expected value of each
score is 2.5. Thus the expected success score for a random event where all
"results" and "contributions" are equiprobable is E(S) = 2.5 x 2.5 = 6.25. This may
be the appropriate bench-mark delineating success and failure. If a sanctions
episode has an outcome better than one would expect randomly, it should count
as a success.
Some refinements to this expected score calculation are possible. Consider the
assignment of contribution scores to sanctions episodes, when it has been
30 Clawson (1993); Knorr (1984), 203; Nossal (1989). Cf. Weintraub (1982), x-xi. 31 Deese (1984), 149. 32 E.g. Adler-Karlsson (1968); Bienen & Gilpin (1980); Doxey (1975)(1980) [cf. Doxey (1987)]; Knorr (1975); Losman (1979); Roca (1985); Schreiber (1973).
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determined that the policy result is a failure (i.e. 1). It requires a peculiar mental
flexibility to see that a sanction may have had an important influence on a weak
outcome. It would seem difficult to assign a score for the contribution of
sanctions other than 1 once a policy result score of 1 has been assigned. Certainly
HSE find it impossible to do so. In every case in which the policy result is unity,
the contribution of sanctions is also scored at unity. This suggests treating the
ordered pairs (Result, Contribution) = (1,2), (1,3) and (1,4) as having zero
probability. Then the expected outcome and the benchmark for success and
failure changes to either E(S)=5.9 or E(S) = 7.33 Some support for the argument
that 5.88≤ E(S) ≤ 7 can be garnered from the mean score of S= 6.35 for the cases
considered in HSE (1990).34
2.1.3 Causation
The assessment of the "contribution of sanctions" necessarily involves a
judgement about causation. The problem of judging the nature and direction of
causation in social sciences is notorious. In the physical sciences a necessary
condition for a causative relationship is that cause precedes consequence
chronologically. In the social sciences however, it is common that one event is
prompted by the anticipation of another, so that consequence predates cause. In
33 There are two possible alternative expected scores. First, if (1,1) has a probability of 0.25, but each of the other feasible combinations of scores has a probability 1/16, E(S)=5.88. Thus outcomes S ≥ 6 would be treated as successes. Alternately, if each of the thirteen possible combinations of scores, including (1,1), are treated as equiprobable then E(S) = 7. 34 Denote the probability of a success score (S) given by a "result" i and a "contribution" j as P[S(i,j)]. Then compare the actual and prior distribution of S:
Distribution X2 A. P[S(i,j)] = P[S(i,k)] ‚ i, j, k 39.2 B. P[S(1,1)] = 0.25; P[S(1,j)] = 0 ‚ j≠1; P[S(i,j)] =1/16 ‚ i≥2 35.2 C. P[S(1,j)] = 0 ‚ j≥2; P[S(1,1)] = P[S(i,j)] = 1/13 ‚ i≥2 54.5 A is a distribution with equal probability assigned to all possible outcomes. B is a distribution with probability 0.25 assigned to (1,1). C is a distribution where all combinations except (1,2), (1,3)
and (1,4) are equiprobable. X2 ~ χ2(df=8, α=0.05) =15.5. In each case the test statistic exceeds the critical value. Thus while convincing arguments can be constructed that the HSE definition of success (S≥9) is inappropriate, none of the alternatives presented are consistent with the observed distribution in the HSE sample.
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short, causation cannot be observed and cannot be demonstrated.35 That being so,
the success score equation seems a little odd. It is the product of a contribution
judgement and a result judgement, and gives equal weight to these two
judgements. Yet the degree of certainty and reliability which can be attached to
policy result judgements is much greater than that which can be attached to the
causation judgements implicit in the contribution score. At a practical level, the
recognition that causation is difficult to judge has several implications. It may be
sensible to ignore causation entirely, and to rate episode success by the policy
result, a procedure suggested by Lam (1990). Alternatively, it is possible to
reduce the weight attributed to causation in the overall judgement of success.
Thus, the contribution and result indexes could be rescaled so that the latter has a
heavier influence on the success score.
2.2 Case Selection
Although thorough compared with earlier efforts, HSE's selection of cases are
incomplete and unrepresentative in several ways. First, there is an undue
emphasis placed on those episodes in which a threat to impose sanctions was
actually carried out. Unactioned threats are under-represented in their sample.
Yet threats are often at least as powerful as actions so that economic sanctions
may have greater potency as a threat than they do in actual practice. Certainly,
threats are more common than action in the field of economic sanctions. Yet of
HSE's 115 cases only five involve the "mere" threat of economic sanctions.
Second, the HSE dataset concentrates too heavily on high-profile and spectacular
examples of economic sanctions to the exclusion of more subtle and possibly
more effective secret or quasi-secret sanctions.36 Making the threat to impose
sanctions subtle or secret may increase the probability of success. Succumbing to
35 Bell & Staines (1979), 97, 99; Blechman & Kaplan (1978), 67, 70; Brams (1985), 109; Dahl (1986), 46-47, 51; Doxey (1980), 8; Levy (1989), 110. Cf. Mosley (1987), 34. 36 Tarrow (1995), 472; Weintraub (1982), ix.
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such a threat involves less loss of face than succumbing to a public threat.
However, there are several complications. Public announcement of a threat is a
mechanism of pre-commitment or bridge burning, making it more costly for the
sender to renege on the threat. In consequence, public threats are more credible.
Furthermore, in some circumstances the target can escalate a sanctions episode
by publicising a secret threat. In this way the target can commit itself not to
capitulate, raising the stakes by committing its reputation to the issue.37 Clearly,
the outcome of sanctions may critically depend on "publicity" variables.
Third, the HSE dataset concentrates on the use of economic sanctions in pursuit
of "political objectives". Gilpin (1984) argues that economic threats are most
successful if they are in the same policy area as the desired compliance. The HSE
dataset might understate the aggregate success rate by excluding the use of
economic sanctions to achieve economic policy objectives.
Finally, positive sanctions receive scant attention relative to that lavished on
negative sanctions.38 Sometimes the same outcome can be alternatively
expressed as a threat or a promise. Thus senders can express intended sanctions
as the imposition of costs if the target fails to conform, or as the forbearance from
the imposition of these same costs if the target conforms. From that point of view,
the distinction between threats and promises seems merely semantic. However,
one major difference between threats and promises arises from a consideration of
a common cognitive distinction drawn by the target. The response of the target to
threats and promises usually differs. Threats evoke fear, anxiety and resistance.
Promises evoke hope, reassurance and attraction. This makes a difference to the
likely outcome. Threats generate resistance to compliance. Threats convey
37 Deese (1984), 159-160; Gilpin (1984), 115; Knorr (1975), 108-109, 152-162, (1977), (1984), 187, 199; Leng (1993), 101-103; Olson (1979), 472-473, 485 ; Schelling (1960), 15-30. 38 Baldwin(1989), 48 , 58 ff.; Galbraith (1986), 213; Knorr (1984), 201; Leng (1993), 115; Morgenthau & Thompson (1985), 558; Morrisey, et al. (1992), 1; Tedeschi, et al. (1973), 203; Weintraub (1982), xvi. Cf. Frankel (1973), 156.
18
hostility. Promises enhance the target's willingness to cooperate on other issues.
Threats impede such cooperation. HSE consider only negative sanctions and to
that extent, their dataset is again unrepresentative.
2.3 Uncertainty
There may be factors inherent in sanctions episodes rendering the statistical
approach fruitless. If the outcome of conflict is clear ab initio, conflict is
unnecessary and unlikely. This is a principle of broad applicability.39 It suggests
an interpretation of the predictive weakness of the statistical analysis in Economic
Sanctions Reconsidered.
An example illustrates. There are circumstances in which the mere threat of
industrial action is sufficient to achieve the desired outcome. Equally there are
circumstances in which industrial action can be anticipated to have no effect on
the employer's behaviour. In both circumstances, a strike is unnecessary and
unlikely. In general, when the outcome of contemplated conflict is quite clear,
peace is observed if conflict would impose significant costs on the combatants.
This means that uncertainty is generally a necessary condition for the occurrence
of explicit conflict. This is the case for economic sanctions. Apart from an appeal
to the logic of conflict, there are two pieces of evidence indicating the role of
uncertainty in sanctions episodes. The first is the five cases of "mere" threats
recorded in Economic Sanctions Reconsidered. Three are classified as "perfectly
successful". The other two are classified as "total failures".40 This is as uncertainty
considerations would predict. The actual imposition of sanctions is only
necessary ex ante in intermediate cases between total failure and success. The
39 Ashenfelter (1987); Bartos (1970), 46; Hermann & East (1978), 15; Isaacs (1965), vii; Kennan (1986); Maurer (1984), 59-60. 40 The successes were League of Nations threats against Yugoslavia (1921) and Greece (1925), and US/Canadian threats against South Korea (1975-1976). The failures wereUSSR v Romania (1962-1963), and threats against East Germany regarding the Berlin Wall: Hufbauer, et al. (1985), 124-31, 505-507, 336-39, 360-364.
19
second is the econometric and statistical evidence presented above. Uncertainty
considerations suggest that weak predictive and explanatory power may be
inherent, rather than a consequence of methodological defects. This logic of
conflict implies that a large proportion of sanctions episodes involve innate
uncertainty. In consequence, the relationship between objective circumstance and
success might necessarily be weak.
3. Further Econometric Analysis
The predictive and explanatory weakness of the HSE success equation might
simply be a consequence of using the wrong estimation technique. The
dependent variable is a "limited" dependent variable for which the range of the
variable is intrinsically a finite discrete set. The success score is finite in that the
score must fall between one and sixteen inclusive. It is discrete in that it can only
assume certain integer values. OLS regression produces biased estimates when
the dependent variable is limited.41
One of the tasks which van Bergeijk pursues in his Economic Diplomacy, Trade
and Commercial Policy (1994) is to bring rigorous multivariate statistical
analysis to the search for the correlates of success. Indeed, van Bergeijk
(19487, 1989, 1994a, 1994b, 1995) stands out in this field for the elegance and
parsimony of his work. Using logit estimators, van Bergeijk constructs
statistical models of the outcome of sanctions using a subset of the HSE
dataset. The dependent variable is a dummy set to one if the HSE definition of
success is fulfilled, that is if the success score exceeds eight. The ability to
predict the outcome of sanctions episodes with a reasonably high degree of
accuracy is the minimal requirement for an acceptable model, and van
Bergeijk typically achieves predictive accuracy of the order of 70-80%. All of
van Bergeijk's preferred models have acceptable diagnostic statistics and
41 Dhrymes (1986).
20
goodness of fit, and significant coefficients. Van Bergeijk's preferred equation,
which predicts the outcome correctly in 83% of cases, is strikingly sparse. It
shows that the probability of success is larger the greater is the sender-target
trade linkage, the less stable is the target, the briefer is the duration of
sanctions, and the stronger is the reputation of the sender.
While van Bergeijk's statistical work is a vast improvement on HSE's flawed
analysis, it is not without problems. Five are noteworthy.
(1) The "reputation" variable is problematic. Van Bergeijk argues that the
sender's reputation is an important influence on the outcome of sanctions.
However, since reputation is not directly observable or measurable, he
proxies it with the number of occasions on which the sender has imposed
sanctions in the previous ten years. The attempt to test for reputation effects is
laudable, but the definition of the proxy seems rather arbitrary. Indeed, van
Bergeijk admits that the ten year definition was "found after experimentation"
(van Bergeijk, 1987, 19). Van Bergeijk could be right in arguing that
reputational considerations play a role in determining the outcome of
sanctions. However, in the spirit of parsimony, it would seem preferable to
attempt to explain or predict without reference to variables like these,
especially when there is no clear-cut or obvious method of measuring the
variable. It is inevitable that the statistical analysis of economic sanctions will
involve variables which are, to some degree, judgmental or subjective. This
plethora of judgmental variables is regarded by some as a basis for scepticism
towards econometric analyses of sanctions. One way in which this scepticism
can be stemmed or limited is to avoid adding to the "problem", by
incorporating variables in predictive equations which require arbitrary
definitions.
21
(2) Like virtually all existing sanctions prediction work (Looney & Knouse, 1991;
Dehejia & Wood, 1992) van Bergeijk uses the duration of the sanctions episode as
an explanatory variable. However, it seems likely that duration is an endogenous
variable, and therefore should not be specified as an independent variable in an
equation for the prediction of the outcome of sanctions (Lam, 1990).
(3) Using the HSE definition of success inevitably entails the problem of
causation outlined in Section 2.1.3.
(4) Recent work has cast some doubt on the robustness and out-of-sample
predictive accuracy of the van Bergeijk equations (Dehejia & Wood, 1992; van
Bergeijk, 1994a). Primarily due to interest in the question of whether "Operation
Desert Storm" was premature, much recent work has focused on predicting the
outcome of the multilateral sanctions against Iraq over the invasion of Kuwait
(Hufbauer & Elliot, 1991; Dehejia & Wood, 1992; van Bergeijk, 1994a), and indeed
a similar test is presented in Section 1.2 above. However, the characteristics of
that episode were a considerable distance from the mean characteristics observed
in the HSE dataset, and is no surprise that predictive models do not extrapolate
well to that episode.
(5) Finally, like most attempts at predicting or explaining the outcome of
sanctions (Lam, 1990; Looney & Knouse, 1991; Dehejia & Wood, 1992), van
Bergeijk focuses solely on the success-failure divide proposed by Hufbauer, et al.
(1985, 1990). However, for policy purposes, this division is too coarse. In
contemplating economic sanctions, the policy-maker's interests are likely to
extend beyond the mere probability of success and failure in the broad. In
particular, policy makers seem to be keenly averse to disaster and, perhaps to a
lesser extent, desirous of spectacular success. Thus it seems sensible to attempt to
model the circumstances conducive to or productive of these outcomes.
22
4. Interpretations
The main prism through which economic sanctions have been viewed in the
success literature is as an instrument of coercion. Formal models are scarce,
though van Bergeijk (1994b) constructs an instructive expected utility model. One
way in which models of this kind might be extended is to treat sanctions as a war
of attrition. Nations enter the war of attrition hoping that conflict will become
intolerable for their opponent before it becomes intolerable for themselves. The
sender sacrifices the gains from trade for both parties (i.e. both sender and target)
in the hope that the target will concede defeat first. Persistence is costly but the
persistent prevail.
However, the pre-occupation with the correlates of success which characterises
this coercive perspective is not the only way in which economic sanctions may be
studied. The recent literature suggests two quite different perspectives.
4.1 Public Choice Theory
Kaempfer & Lowenbergs' International Economic Sanctions (1992) pioneers the
application of public choice theory to the analysis and interpretation of economic
sanctions, though some similar insights are to be found in the earlier work of
Olson and of Krasner. The essence of the public choice approach is that the
motive for imposing sanctions is not primarily to maximise economic damage in
the target nation. That coercive motive is secondary to the aim of profitably
supplying the demands of domestic interest groups. Thus sanctions are
interpreted as a means of redistribution of wealth or political power within the
sender's polity. Similarly the extent to which sanctions are effective in producing
the desired change in the target country depends on the operation of the
"political market" in the target country, and in particular on the lobbying power
of those individuals most sharply affected by the sanctions.
23
One general problem with this approach is that it is not clear that economic
sanctions fit the analytic pattern of public choice theory. That pattern typically
begins with the observation that some government action fails to achieve, or is an
inefficient means of achieving, its avowed purpose. There follows an attempt to
explain the government action by reference to individual self-interest. However,
as noted above, when applied to economic sanctions the premise of this
argument is counterfactual. More than one third of the 115 episodes analysed by
HSE (1990) are classified as successes. It is not at all clear that, by comparison to
other forms of statecraft, this is a relatively low success rate. Certainly, Kaempfer
& Lowenbergs' practice of describing the success rate as "only" one third does not
establish the argument.
Kaempfer & Lowenberg adopt a dogmatic attitude towards the venerable if
hoary "level of analysis" problem (e.g. Singer, 1961): should models of political
behaviour focus on individuals, on political parties, on the nation state or on
international alliances as the unit of analysis? Kaempfer & Lowenbergs' answer
to this is a dismissal of approaches other than methodological individualism: "Foreign policy is shaped by individuals within nations, not by decisions made by anthropomorphized countries".42
Of course, Kaempfer & Lowenberg are not alone among economists in this
attitude to analyses which are not individualistic, and they are perhaps not the
worst offenders. However, the study of economic sanctions stands at the
intersection of economics and politics. It would seem sensible to permit a
plurality of methodologies. Work in this field should be judged by the usual
standards of clarity, logical consistency, parsimony and consistency with the
evidence. It should not be judged by the extent to which it conforms to some
imagined or supposed "correct" methodology.
42 Kaempfer & Lowenberg (1992), 6.
24
Whatever the merits of methodological individualism, it critically shapes
Kaempfer & Lowenbergs' attitudes to evidence and explanation, and to the
treatment of testable propositions. It seems sometimes that an explanation is
acceptable, in the public choice view, if and only if it is individualistic, and
whether or not it fits the empirical evidence better than any non-individualistic
alternative.
A related problem is that there are few directly verified or verifiable empirical
propositions which emerge from Kaempfer & Lowenbergs analysis, by
comparison for example with the rich array of propositions elicited by Downs
(1957) in his pioneering exposition of electoral behaviour.
Two representative examples illustrate these problems. First, Kaempfer &
Lowenberg assert that: "[T]he structure of interest group politics within a given country ... helps determine whether the country will have a high propensity to resort to sanctions instead of other foreign policy tools".43
It is difficult to imagine the precise characteristics of interest group politics which
might explain: (1) the dramatic differences in European and American
propensities to resort to sanctions; (2) variations in the extent to which the
European nations have resorted to sanctions; (3) the apparent greater propensity
of the United States to impose sanctions in the past two decades.
Certainly, Kaempfer & Lowenberg seem unable to detail interest group
characteristics which would satisfactorily explain these differences. Surely these
differences are more readily explicable by reference to considerations of history,
power, objectives and experience, without the need for abstruse and intricate
interest group constructs.
43 Kaempfer & Lowenberg (1992), 53.
25
Second, one of the clear testable implications of public choice theory is that,
because producers are more cohesive and politically effective than consumers,
sanctions are more likely to restrict imports than to restrict exports. The HSE
database shows that, for the US at least in the past several decades, this
prediction is flatly contradicted by the evidence. Among several "explanations"
which they offer for this apparent rejection of public choice theory, Kaempfer &
Lowenberg argue that "a stronger preference for export controls" may explain the
prevalence of export sanctions. If "explanations" of this variety are admissible,
then public choice theories cease to have testable or even meaningful empirical
content. If every occasion on which the predictions of a theory are rejected is
"explained away" by hypothesising a "taste" which produces the anomalous
result, then public choice theory is rendered tautological.
4.2 Cooperation
Sanctions are interesting because they often challenge the serious limits to
international cooperation. In Coercive Cooperation (1992) Martin focuses on the
prevalence and extent of international cooperation in the imposition of economic
sanctions. This is an important variable, yet in the pre-existing literature one
rarely finds much more than bland assertions that cooperation is necessary for
success but difficult to achieve. Martin develops a surprisingly rich suite of game
theoretic models of the decision to cooperate. She derives seven testable
propositions from these models. These propositions are confronted with the HSE
dataset. Martin uses the results of this "aggregate" statistical analysis as a guide
for the conduct of four meticulously documented case studies. Her primary
conclusion is that cooperation is much more likely to be achieved if the leading
sender undertakes significant costs and if sanctions are sponsored by an
international institution. Martin suggests that this statistical regularity reflects an
attempt by the leading sender to achieve credibility.
26
This terse summary scarcely does justice to the rich detail of Coercive Cooperation.
Martin's tailored mixture of formal theory, testable implications, rigorous
statistical analysis, and detailed case studies, provides an excellent template of
the mode of research most likely to advance our understanding of sanctions.
5. Conclusions
It would be useful if the consequences of contemplated sanctions could be
predicted with precision. Applying a battery of statistical tests to the historical
record is one way of investigating the correlates of success. However, the tests
must meet at least minimal standards of statistical inference, or the conclusions
drawn will be unreliable. This is the unfortunate fate of Economic Sanctions
Reconsidered. It is suggested here that the data support fewer conclusions
regarding the determinants of success, and certainly far more modest and
cautious policy implications, than HSE claim.
Van Bergeijk's Economic Diplomacy has advanced our understanding of the
mechanisms which generate success, and is a valiant attempt to repair some of
the defects in statistical method in the HSE study. However, it too has several
drawbacks: explanatory variables with ad hoc definitions; the use of duration as
an explanatory variable; a definition of success requiring unreliable judgements
regarding causation; serious doubts regarding out-of-sample predictive accuracy;
and an inability to distinguish degrees of success and failure. Many of these
difficulties are remediable. For example, Bonetti (1996) addresses the first three of
these problems. That paper reports that success is correlated positively with prior
sender-target relations, with the use of import sanctions, and with the cost of the
sanctions to the target, and negatively with cooperation in the imposition of the
sanction and the cost of the sanctions to the sender. The cost arising from the
exclusion of reputation and duration is a 10% lower level of within-sample
predictive accuracy than is achieved by van Bergeijk. However, there remain
27
serious flaws in most existing statistical analyses of the correlates of success in
economic sanctions episodes. This analytic weakness may derive from the
method of defining and measuring success, from the heroic judgements about
causation generally implied in these measures, from sampling bias in the
selection of case studies, or from the uncertainty which is a pre-condition for
much explicit conflict.
There are three lessons to be drawn from all of this. First, the statistical analysis
of the correlates of success in sanctions episodes is at an insufficiently advanced
stage of development to serve as a substitute for the traditional qualitative
techniques of international policy analysis. Second, whether it can ever be
otherwise remains an open question. Uncertainty considerations suggest that it
cannot. It may be that more reliable and robust answers to the key question of the
circumstances in which sanctions succeed will require an integration of the
coercive theories presented by van Bergeijk, the insights from Martin's Coercive
Cooperation on the determinants of cooperation in the imposition of sanctions,
and the analysis of Kaempfer & Lowenbergs' International Economic Sanctions of
the role of domestic political dynamics in influencing the outcome of sanctions.
The results and argument presented here are a counsel of reticence and caution
in predicting the outcome of specific sanctions episodes.44
Finally, whether sanctions "work" is not the only one issue worthy of scholarly
interest. There remain substantial gaps in the analysis of sanctions, including: (1)
the determinants of the duration of sanctions; (2) theories of the choice of the
form of economic sanctions; (3) exploration of how economic sanctions end, and
more generally of the causes of de-escalation in international crises.45 It may be
that such problems are more amenable to solution than the "success" problem has
proved.
44 Kegley & Skinner (1976), 304; Steiner (1994), 45. Cf. Hufbauer & Elliot (1991). 45 Gulliver (1979), 164; Nicholson (1970), 117
28
29
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Table 1 Explanatory Variables and Estimated Coefficients
T1= Time Trend, the last two digits of the year -0.05
T2= Length of episode, in years -0.02
D1= 1 if a modest policy change is sought; 0 otherwise +1.04
D2= 1 for World Wars I and II; 0 otherwise +10.3
D3= 1 if covert action is employed; 0 otherwise -0.46
D4= 1 if military force is employed ; 0 otherwise -0.39
D5= 1 if the target receives significant support from a third -2.96
party; 0 otherwise
D6= 1 if the sender's GNP is up to 10 times greater than the +1.76
target's GNP; 0 otherwise
D7= 1 if sender's GNP is between 10 and 100 times larger than +0.51
the target's GNP; 0 otherwise
D8= 1 if export controls are used; 0 otherwise -1.52
D9= 1 if import controls are used; 0 otherwise -0.73
D10= 1 if financial controls are used; 0 otherwise -0.26
X1= International cooperation in the imposition of the -0.17
sanctions, ranked from 1 (none) to 4 (significant)
X2= Index of prior relations between sender and target, +1.27
ranked from 1 (antagonistic) to 3 (cordial)
X3= Political and economic stability of the target, ranked -1.43
from 1 (distress) to 3 (strong & stable)
X4= Cost of sanctions to the target, as a percentage of GNP +0.18
X5= Presanction trade linkage between the target and the +0.03
sender, as a percentage of the target's total trade
X6= Cost of the sanctions to the sender, ranked from -0.94
1 (net gain) to 4 (major loss).
Constant 12.23
Source: Hufbauer, et al.(1985). Coefficients rounded to 2 significant figures.
36
Table 2 Predicted and Actual Outcomes of 12 Sanctions Episodes
(S= Success; F= Failure)
Predicted Actual
Episode Score S/F Score S/F
US v Iran (84.1) 2.8 F 6 F
US v South Africa (85.1) 3.5 F 6 F
US v Syria (86.1) 3.4 F 6 F
US v Angola (86.2) 4.7 F 2 F
US v Panama (87.1) 3.5 F 4 F
US v Haiti (87.2) 11.1 S 6 F
US v El Salvador (87.3) 11.1 S 16 S
Japan & Others v Burma (88.1) 9.2 S 6 F
US, UK v Somalia (88.2) 10.3 S 4 F
India v Nepal (89.1) 6.6 F 9 S
US v China (89.2) 5.0 F 1 F
US v Sudan (89.3) 9.8 S 1 F Note: The bracketed numbers are HSE's episode numbers.
37
Table 3 Success Rates (%) by Various Factors
% No. §
1. Goal
Modest Policy Change 33 51
Destabilization 52 21
Disruption of military adventures 33 18
Military Impairment 20 10
Other major policy changes 25 20
2. Assistance to Target
Assistance 22 32
No Assistance 39 88
3. Type of Sanction
Financial Sanctions 33 34
Financial + Trade Sanctions 52 56
Trade Sanctions 33 25
4. Cost to Sender
1: net gain to sender 39 41
2: little effect on sender 37 54
3: modest loss to sender 15 20
4: major loss to sender 40 5
5. Target Health & Stability
1: Distress 52 25
2: Significant problems 34 59
3: Strong and stable 18 40
6. Time Period
Pre 1973 44 61
Post 1973 24 59
7. Size
Sender GNP/Target GNP
0-10 33 27
11-100 33 43
101+ 36 50
8. Use of companion military policies
Present 37 43
Absent 32 77
9. International Cooperation
1: No cooperation 43 54
2: Minor cooperation 25 28
3: Modest cooperation 30 20
4: Significant Cooperation 36 14
10. Prior Relations
1: Antagonistic 13 23
2: Neutral 32 56
3: Cordial 53 38 § "No." is the total number of episodes, both successes and failures, in that category.
38
Table 4 Chi Square Tests of Independence
X2 χ2(df,α=0.05) C
1. Goal 4.7 9.49 0.20
2. Assistance to Target 2.88 3.84 0.15
3. Type of Sanction 2.01 5.99 0.13
4. Cost to Sender 3.93 7.81 0.18
5. Target Health & Stability 8.44 5.99 0.26
6. Time Period 5.66 3.84 0.22
7. Size 1.20 5.99 0.10
8. Use of companion policies 0.27 3.84 0.05
9. International Cooperation 2.81 7.81 0.16
10. Prior Relations 10.4 5.99 0.30 Notes
(1) χ2 is the critical value of the chi-squared statistic. The null hypothesis is that success and the
specified variable are independent. If X2<χ2 the null hypothesis of independence cannot be rejected.
(2) Cramer's C which is a nonparametric measure of association defined as C = [X2 /(N(L-1))]¡ where N is the sample size and L is the lesser of the number of rows and columns in the contingency table: Siegel & Castellan (1988), 225-232.
Table 5 Mean Values of Ratio/Interval Variables by Success and Failure
Results of F and t Tests
Success &
Failure F Test t Test S F F FU FL t Crit t Significant?
Cost 2.4 0.95 4.82 1.80 0.55 2.245 1.70 Yes
Trade 28.1 18.4 1.07 1.53 0.65 2.07 1.66 Yes
Size 188.9 199.9 1.04 1.8 0.55 0.16 1.66 No
Duration 2.87 7.75 0.08 1.61 0.62 3.97 1.67 Yes Notes (1) "Cost" is the cost of sanctions to the target, as a percentage of GNP. "Trade" is the presanction trade linkage between the target and the sender, as a percentage of the target's total trade. "Size" is the ratio
of sender's GNP to target's GNP. "Duration" is the length of episode, in years.
(2) The F test examines the hypothesis of equality of population variance. FU and FL are respectively
upper and lower bounds for this test at a 5% level of significance. If FL<F<FU the evidence is
consistent with the hypothesis of equal variance.
(3) For the t tests the null hypothesis is that the mean value is the same in success and failure cases. The alternative hypotheses are that the mean cost, mean trade linkage and mean size is greater in success
cases, and that mean duration is shorter in success cases. Crit t is the critical value of the t distribution at the 5% level of significance. (4) When the hypothesis of equal variance is satisfied by the F test, a pooled variance one -tailed t-test
is used to examine the null hypothesis. For cost and duration the hypothesis that the population variance of success and failure cases is equal is unsupported by the F test results. A one-tailed Cochran approximate t-test is therefore used: Snedecor & Cochran (1980).