The Economic Consequences of US Interventions: An Empirical Inquiry

William Easterly (NYU) Nathan Nunn (Harvard)

Shanker Satyanath (NYU) Daniel Berger (NYU)

Preliminary version: January 30, 2009

Abstract What are the economic consequences of United States interventions to install and prop up political leaders in other countries? The absence of reliable information on covert interventions has hitherto served as an obstacle to seriously addressing this question. The recent declassification of Cold War CIA documents now makes it possible to systematically address this question in the Cold War context. We thus develop a new time series dataset of US interventions during the Cold War. We find that the economic consequences of US interventions are limited to political environments with limited checks and balance, namely autocratic regimes. Interventions increase the flow of US goods into autocracies, raising the share of total imports into the country from US firms. However, US interventions yield few economic benefits to intervened countries; they have no impact on income levels, and on exports from and foreign direct investment into the intervened country. We conclude that the main economic beneficiaries of US interventions are US exporters and identify the industries that were the largest beneficiaries.

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I. Introduction

What are the economic consequences of United States interventions to install and prop up political leaders

in other countries? The absence of reliable information on covert interventions has hitherto served as an

obstacle to seriously addressing this question. The recent declassification of Cold War CIA documents

now makes it possible to systematically address this question in the Cold War context.

We develop a new annual panel dataset of US interventions during between 1947 and 1989. Our primary

finding is that interventions raise the share of goods the intervened country imports from the US.

Looking more closely at trade flows, we find that the increase in the share of goods from the US comes

about because of an increase in goods from the US, a decrease in goods from all other countries, and no

change in total imports. Therefore, interventions cause a shift towards importing US goods.

There are two leading explanations for this finding. The first is that the intervention decreases the

bilateral trading costs between the US and the intervened country. Because of this it is now optimal for

the foreign country to import a greater proportion of goods from the US, rather than other countries. In

this case, the intervention (and the resulting decrease in bilateral trade costs) causes both the US and the

foreign country to be better off. The second explanation is that the intervention increases the US’s ability

to influence the foreign country, and one consequence of this greater influence is that the US is able to

force more of its goods on the foreign country.

While both effects could be simultaneously present, we undertake a number of strategies to identify which

of the two explanations is most strongly supported by the data. First, we examine heterogeneity of the

effects of interventions between autocratic and democratic regimes. Well known theories by Grossman

and Helpman (1994) and Bueno de Mesquita et al. (2003) yield the implication that if US political

influence is driving the increase in imports from the US, then the effectiveness of the influence (and

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hence the increased imports) will be greater in autocratic regimes (where the leader is supported and

accountable to only a small group) rather than in democratic regimes (where the leader has greater

accountability to a larger population). The data show very strongly that US interventions only increase

the share of US imports in autocratic regimes, and not in democratic regimes. This is consistent with US

political influence being at the heart of the effects of interventions.

Second, we look at the heterogeneous effects of interventions between imports from and exports to the

US. To this point, we have been focusing on the flow of goods from the US to the intervened country.

But, what about the flow of goods in the other direction? If the increase in US imports is driven by a

decrease in bilateral trade costs, then we would also expect an increase in the flow of goods from the

foreign country being imported by the US. Or, stated from the foreign country’s point of view, we would

expect an increase in the share of exports the foreign country ships to the US. Examining the data we find

no such effect. Although US interventions increase the flow of goods from the US to the intervened

country, they have no effect on the flow of goods from the intervened country to the US.

Our final strategy is to examine the heterogeneity of the effects of interventions across industries. We

find that US interventions increase the share of goods being imported from the US in nearly all industries,

while US interventions increase the share of goods being exported to the US from the intervened country

in some industries and decrease the share in other industries. This again confirms our previous findings

of an asymmetry between imports and exports.

This raises the question of whether the trade outcomes are in line with other important economic

outcomes of interventions. We thus also examine whether US interventions affect the future income of a

country, and find no effect. It thus appears that US exporters are the major beneficiaries of interventions.

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In the next section of the paper we offer a brief review of the previous literature on interventions. In

Section III we describe our data and their sources, including our new data set on interventions. This is

followed by two sections of results. In Section IV we present our core results on the consequences of US

interventions. In Section V we address the robustness of our core findings to selection concerns, by

taking account of the causes of interventions. Section VI concludes.

II. Literature review

There is a large literature that focuses on the institutional consequences of superpower interventions.

Bueno de Mesquita and Downs (2006) have recently provided an excellent survey of this literature and

we summarize some of the highlights below. One group of studies focuses on military interventions and

finds that interventions by democratic countries have a positive effect on democratic reform in the short

term, but generate political instability in the long term. (Kegley and Hermann, 1997 and Gleditsch et al.,

2004). Another group of political scientists focuses more narrowly on cases of interventions by the US.

Some of the case study literature finds that US interventions are not associated with democratization and

attributes this to US military and economic interests (Karl, 1990 and Rueschmeyer et al., 1992). Other

studies focus on the difficulty of imposing democracy from above (e.g., Herman and Broadhead, 1984,

O’Donnell et al., 1986, Whitehead, 1991); while others find that US interventions have a positive effect

on democracy under some limited circumstances (Meernik, 1996, Wantchekon and Nickerson, 1999,

Enterline and Greig, 2003). Easterly, Satyanath, and Berger (2008) study the effects of US and Soviet

interventions on democracy. Our paper differs from this body of work by focusing on the economic, as

opposed to the institutional consequences of interventions.

Bueno de Mesquita and Downs’ (2006) paper is the latest contribution to the interventions literature.

Their paper focuses on military interventions in wars and militarized interstate disputes and finds that this

genre of interventions “lead to little if any improvement, and all too often erosion in the trajectory of

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democratic development.” (Bueno de Mesquita and Downs 2006, 627). Our paper differs from this

work in three ways. First, we focus here on the economic rather than on the political consequences of

interventions. Second, we do not focus exclusively on military interventions, but provide evidence of the

less easily quantified behind the scenes covert interventions in other countries. Third, in our analysis we

do not limit ourselves to studying countries which are experiencing violent conflict, but also consider

interventions with limited and no casualties.

There are a number of studies within economics that are also related to our analysis here. Our paper

relates to the empirical literature examining the economic effects of foreign interventions taking the form

of colonial rule (e.g., Acemoglu, Johnson, and Robinson, 2001, Engerman and Sokoloff, 1997, and Dell,

2008). Our paper complements these historic studies by more modern varieties of external interventions.

Because many of the interventions that we consider here are aimed at installing and/or propping up

leaders, our work complements the recent studies by Olken and Jones (2005, 2009) showing that who is

in power has important consequences for the macro-environment of an economy. (See also Duflo, 2004.)

In particular, the finding in Olken (2005) that leader deaths have larger effects in autocracies is in-line

with our similar finding that US interventions appear to be benign in democracies.

III. Data

The focus of this paper is on superpower interventions to install and prop up the leaders of other countries

during the Cold War. Recently declassified documents reveal that most such Cold War interventions took

the form of operations organized by the covert services of the superpowers, namely the CIA and KGB.

There is no pre-existing dataset that comprehensively captures such operations. Recent contributions to

the Cold War history literature (much of which is based on recently declassified documents) make it

possible to identify which countries were subject to such interventions. We have thus relied on this

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literature, supplemented by our own archival research, to construct a dataset of superpower interventions

to install and prop up leaders of other countries that includes covert interventions.

The variables in the dataset are as follows. Each variable has one variant which captures a US

intervention and one which captures a Soviet intervention. Although we are interested explicitly in the

effects of US interventions, in our analysis we always control for Soviet interventions as well.

1) Onset: This variable is coded as one in the period in which a leader is installed in office with the

support of the covert services of a superpower. This may be either via a coup or by providing slush funds

for elections.

2) Offset: Coded as one for the first point of time after an onset in which a superpower explicitly

relinquishes its ability to select the leader of a country. This may be by force (for example in the case of

Iran in 1979) or voluntary (as in the case of Gorbachev and Eastern European satellites in the late 1980s).

3) Counter: Coded as one for periods in which a superpower organizes counterinsurgency operations

for a leader who was not installed in office by the superpower. (One may think of this as an exclusively

counterinsurgency based intervention.)

5) Intermed: This variable captures superpower meddling in periods other than onset and offset

periods. It is coded as one for all periods between Onset and Offset as well as for periods coded as one

for Counter.

6) Invasion: Coded as one for all periods in which a superpower army invades a country and

successfully installs a leader in office. Note that covert onsets and invasions are not necessarily mutually

exclusive, since invasions and covert operations may be used simultaneously to install a leader.

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7) Any: This is our omnibus measure of successful superpower meddling in the domestic affairs of

other countries. All country periods coded as one on either Onset, Counter, Invasion, or Intermed, plus

periods not covered by these variables when the literature indicates a leader is depending heavily on

superpower support for survival in office (prop ups) are coded as ones. Note that offset years are coded

as one in our Any measure unless the offset occurs at the very beginning of a year, which generally is not

the case.

Throughout our baseline analysis, we only consider covert interventions that are successful. In other

words, our measures do not include failed interventions. We have collected data on failed covert

interventions. All of the results that we report are robust to the inclusion of this variable in our analysis as

well.

Our core analysis covers 131 countries, of which 48 were subject to at least one CIA intervention between

1947 and 1989. Of the 131 countries, 22 were subject to some form of KBG/MGB intervention. While

the sample is large, we are unable to handle a few partitioned/reunified countries due to difficulties in

gathering clean data on controls for different segments of a national unit.

We are aware of the fact that we may be missing some “secret” interventions but we see no reason why

these omissions should be systematically biased in a way that helps our results. If anything, the

incentives for the superpowers to reveal an intervention should be greatest if the outcome is positive so, if

anything, we are likely to be misclassifying some interventions that had adverse outcomes as non-

interventions.

When examining the consequences of interventions, our primary outcomes of interest are bilateral trade

flows and per capita income levels. The trade data are from two different sources depending on the level

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of industry aggregation. For analyses where we are only concerned with total annual bilateral trade

across all industries, we use trade data from the Correlates of War Project (COW) (Barbieri, Keshk and

Pollins, 2008). Aggregate bilateral trade data are available from 1870 to 2006. The trade data are

primarily from the International Monetary Fund’s Direction of Trade Statistics (DOTS), which is

available on CD-ROM.

For part of our analysis, we examine trade data at the industry level. These data are from the United

Nations’ Comtrade Database. The advantage of the Comtrade data is that they are provided at a very

disaggregated level (4-digit SITC industries). However, unlike the COW trade data, the data only begin

in 1962, and therefore we miss coverage between 1947 and 1962 when we examine trade data at the

industry level.

Data on real per capita income are from Maddison (2003). The figures are given in 1990 International

Geary-Khamis dollars. Maddison’s income data provides the widest coverage of countries and time

periods. For overlapping countries and years, the Maddison income data are strongly correlated with the

widely used GDNGD (Growth Development Network Growth Data) income data. The correlation

between the two measures of real per capita GDP is 0.98. We also include total income as a control for

total country size in many of our estimating equations. This measure is also from Maddison (2003).

IV. Empirical Expectations

Our empirical hypotheses derive from a straightforward logic that is at the core of a number of models in

economics and political science, like Grossman and Helpman’s (1994) “Protection for Sale” model, as

well as of Bueno de Mequita et al.’s (2003) model of winning coalitions. In Grossman and Helpman,

governments choose the level of a socially suboptimal policy (trade tariffs) to set. In making their

decisions governments must trade off the effects of the policy on aggregate social welfare against the

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private benefits the government receives from groups that have political influence (in their model these

are lobbies). In their model the key parameter affecting the equilibrium policy is a parameter ‘a’, which

is the weight the government places on aggregate welfare relative to the private benefits the government

receives from setting a more distortionary policy. In reality the parameter ‘a’ is determined primarily by

the accountability of the leader or government to the welfare of its citizens, and therefore, all else equal, a

will be much higher in democracies than autocracies. An important result in their model is that the policy

(i.e., tariffs) are less distortionary the greater is a, the weight the government places on welfare relative to

private benefits.

This is an important insight that is directly applicable in our empirical setting. Part of the benefit of CIA

interventions is that the US is able to exert greater influence over the foreign leader or government to

choose policies that benefit the US or US firms at the expense of the welfare of the intervened country.

Part of the rents generated by the policy can be passed on to the leader supported by the US. This setting

is exactly analogous to Grossman and Helpman’s setting, except that the US government takes the place

of the private lobbies. As shown in their model, the private benefits from the socially distortionary policy

will be more successful at influencing the government in autocracies, where the government is less

accountable to its citizens, and is less influenced by their well being (i.e., when a is low). Therefore, if

we find any evidence of interventions benefiting US firms, at the expense of the intervened country’s

welfare, then we expect these effects to be much more pronounced in intervened autocracies, relative to

intervened democracies.

Bueno de Mesquita et al.’s (2003) model also indicates that a greater weight will be placed on broad

social welfare in countries where a political leader needs to gather the support of a large proportion of the

electorate in order to survive in office (i.e. democracies). The implication of both these models is that

democratic countries that are subject to external meddling are relatively likely to resist distorting trade in

favor of major export industries from the intervening power following an intervention. Thus, if we are to

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find any effect of US interventions, we expect a much stronger effect of US interventions on the outcomes

of interest in authoritarian regimes than in democratic environments. This constitutes our first empirical

hypothesis. We expect the effect of US interventions to be much more benign in democracies than in

autocracies.

When it comes to exports from the intervened country, the imbalance in size between the US and the

intervened country should mean that exporters from the intervened country have less influence on US

trade policy than domestic US producers who produce competing products. The latter should thus be in a

position to block an increase in exports from the intervened country. We thus do not expect a significant

relationship between a US intervention and the share of the US in a country’s exports irrespective of

whether the intervened country is autocratic or democratic. This is our second main empirical

expectation.

Theory does not give us clear guidance on what to expect when it comes to the effects of interventions on

other key economic variables, such as economic growth. Our conservative expectation is thus that there

will be no relationship between interventions and such variables. The overall implication is that the major

economic beneficiary of a US intervention will be US exporters, who will see their market share and sales

increase as a consequence of the intervention.

V. Core Results on the Consequences of Interventions

In this section we present our core results on the economic consequences of US interventions. In section

VI we address the robustness of these results to selection concerns, by taking account of the causes of

these interventions.

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In line with the empirical expectations described in the previous section, we start by looking at effects of

US interventions on the share of imports coming from the US. Since our empirical expectations differ for

autocratic and democratic environments, we examine these separately. We begin by examining the

environments where we expect a significant relationship between interventions and US share of imports,

namely authoritarian environments. Our estimating equation for the share of total imports into country c

that are from the United States takes the following form:

∑ ∑∑= =

−−= −

− +++++++=N

n

N

nctcntncntn

N

nW

cnt

UScnt

nctctctWct

USct Yy

mm

anySovietanyUSmm

0 0,,,

1 ,

,,2,1

,

, lnln εηλγββαα (1)

where USctm , denotes imports from the US into country c in year t. Similarly, W

ctm , denotes imports from

all countries into country c in year t. The dependent variable, Wct

USct mm ,, / , is then the share of total

imports into country c in year t that are from the US. Because the time period being considered is the

Cold War, t ranges from 1947 to 1989. Equation (1) also includes as controls year fixed effects and

country fixed effects, αt and αc. We also include N lags of the dependent variable; log per capita income

in period t (ln yt,c) and lags of this same variable; and log aggregate income in period t (ln Yt,c) and lags of

the variables. When choosing the number of lags to include, we continue to include lags to the point

where they are no longer significant. Our sample includes all country-year pairs for which we have the

necessary trade and intervention data. By construction, the United States and the Soviet Union are not in

the sample.

Similarly, for the share of total exports to the US that are from country c:

∑ ∑∑= =

−−= −

− ++++++=N

n

N

nctcntncntn

N

nW

cnt

UScnt

nctctctWct

USct Yy

xx

anySovietanyUSxx

0 0,,,

1 ,

,,2,1

,

, lnln εηλγββαα (2)

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where USctx , indicates exports from country c to the US in year t. Similarly, W

ctx , denotes exports from

country c to all countries in the world in year.

Our sample of autocracies includes all observations for which country c is defined as being an autocracy

in year t and year t-1, where countries are defined as being autocratic if their Polity score ranges between

-10 and 0; they are defined as democratic if their Polity score ranges from 1 to 10. As shown, this results

in a sample of 2,503 observations or country-year pairs in the autocracy sample. Column (1) shows the

results for a fixed effects OLS specification with the share of the US in a country’s imports on the left

hand side. The column shows that the estimated coefficient for the composite measure of US

interventions is positive and statistically significant. The estimated magnitude of this effect is very large;

an intervention increases the share of US imports by 2.2 percentage points. This is extremely large given

the mean share of US imports in the sample which is 16% (see table A1).

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To better understand the mechanism behind the changing share of US imports we examine the effect of

interventions on total world imports into the intervened country and the effect on imports from the US

only. These estimates are reported in columns (4) and (7). The results show clearly that the increase in

the share of US imports is being driven by an increase in the volume of imports from the US and not from

a decrease in the volume of imports from the World as a whole. While the effect of interventions on total

world imports is not statistically different from zero, there is a very large effect on the volume of imports

from the US. Because we measure trade flows in natural logs, the coefficients for the intervention

variable provides the estimated percentage change in the trade flow for an intervention (i.e., a one unit

change in the intervention variable). According to the estimate in column (7), a US intervention increases

the volume of US imports by 26%. To compare this to figure to the estimated effect of column (1), which

is given in percentage points rather than percent, we need to convert the column (1) estimate to a percent

14

change in the share (which we evaluate at the mean). The 2.2 percentage point increase in the share of

US imports represents an increase in the share of US imports of (evaluated at the mean of 0.16) 0.022 /

0.16 = 0.14 or 14%. This effect is smaller, but comparable to the estimated effect on total US imports

from column (7). The difference can be explained by the small (and statistically insignificant) effect of

the intervention on total imports reported in column (4).

Overall, the pattern that we observe in the data is that, within autocracies, US interventions result in an

increase in imports from the US, while aggregate imports are unchanged. This results in a significant

increase in the share of imports that are from the US.

To better understand the dynamic effects of interventions, we turn to our finer, more disaggregated

measures of interventions, where we distinguish between onset years, intermediate years, offset years,

military invasion years, and counter insurgency years. This helps us unpack the coefficient on our

aggregate intervention variable. The estimation results are reported in columns (2), (5), and (8). Because

we do not find any interesting correlations with invasions and counterinsurgencies, to conserve space we

do not report their coefficients in the table. Instead we focus our discussion on the onset, intermediate,

and offset intervention variables.

Again, the results paint a very clear picture. The onset year of an intervention and the intermediate years

have equal, but large effects on US imports and the share of imports from the US, and there is no

statistically significant effect on total imports. The offset period is uncorrelated with any change in US

imports or the US import share.

The effect of interventions is being driven by the onset and intermediate periods of the intervention.

Imports from the US immediately increase following an intervention. If we compare the coefficients of

the onset and intermediate period variables, we see that they are similar. This tells us that the effects of

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prolonged interventions are felt as strongly during the first (i.e., onset) year of the intervention as in

subsequent (i.e., intermediate) years of the intervention. All of the above results are robust to additionally

controlling for gravity variables as well as for the extent of foreign aid (not shown).

The final estimates that we report in Table 1 are estimates based on matching techniques. We use a

Genetic Matching program pioneered by Jasjeet Sekhon (2009).1 The matching variables and their

Kolomogorov-Smirnov p-values are listed in Table A2 of the appendix.

Matching estimates of the effect of our aggregate intervention variable on US import share, total world

imports, and US imports are reported in columns (3), (6), and (9). The matching estimates confirm the

findings from our regular OLS estimates: a positive and significant effect of interventions on the US

import share and the volume of US imports, but no effect on the volume of world imports. In addition,

the magnitudes of the coefficients are similar.

We now turn to the effects of interventions on exports to the US for authoritarian regimes. Estimates of

equation (2) are reported in table 2. The structure of the table is exactly the same as table 1 except that

now the dependent variables are based on exports to the US, rather than on imports from the US. The

estimates show that we do not find any evidence of an effect of US interventions on exports to the US.

Specifically, interventions do not affect the volume of goods exported from the intervened country to the

US. US interventions increase the flow of goods from the US to the intervened country, but do not

1 Genetic matching permits a search of the space of distance metrics for the optimal distance metric to achieve balance. The space which is searched is a set of generalized weighted decomposed Mahalanobis metrics of which the standard Mahalanobis distance is the simplest. Unfortunately, this creates a very difficult matching problem in that the function being maximized is nonlinear and often discontinuous. Therefore, standard derivative based methods (e.g. Newton-Raphson) will frequently fail to find the actual maxima. Sekhon's Genoud maximizer uses evolutionary operators (with some local hill-climbing) to maximize these functions. The value of using the genetically matched estimates is greatest in small samples and when the covariates are not normally distributed, and in an infinite sample converges to the same results as using a simple Mahalanobis distance would.

16

increase the flow of goods from the intervened country to the US. The increase in trade from the

intervention appears to be very one sided.

We do find however that Soviet interventions in general, and the intermediate period of these

interventions in particular, decrease the share of exports that are going to the US. In an intermediate

period of an intervention, the share of exports going to the US is three percentage points lower, and the

total volume of exports to the US is decreased by 46%. Although it is unclear what is driving these huge

effects, one possibility is that it is US policy. After a Soviet intervention, US firms may discontinue

importing from the intervened country, or there may be an official embargo against trade with the

country.

17

We re-estimate equations (1) and (2) among a sample of countries that were democracies (and remained

democracies) when the intervention occurred. The results are reported in table 3. We find no robust

evidence of any systematic effects of US interventions on the share of US imports or exports. This is also

true if one examines the volume of US and world imports or exports separately as we did in tables 1 and

2. (To conserve space we do not report these estimates.)

To this point, we have been examining the effects of US interventions on the aggregate imports of all

goods. One way to gain a better sense of exactly the reason behind these increased imports is to examine

18

which industries are driving this result. That is, are there a few key industries for which imports from the

US increases drastically, or do imports in all industries increase by approximately the same amount.

We examine these questions by examining trade data that is disaggregated by industry. To do this, we

move from the aggregate COW trade data to the disaggregated Comtrade trade data provided by the UN.

The drawback of using the UN data is that we only have data for the post-1962 period of the Cold War.

We begin our analysis by estimating a version of equation (1) separately for 63 2-digit SITC industries.

The results of this are reported in table 4. Each row of the table reports the estimated coefficient for US

any from equation (1). We report standardized beta coefficients so that the coefficients from each

regression are directly comparable. The dependent variable in each regression is the share of imports

from the US relative to world imports in a 2-digit SITC industry. The corresponding 2-digit SITC code

and the industry description are reported in the final two columns of the table. The industries are ordered

by the estimated coefficient for US any, from lowest to highest.

It is clear that there is some heterogeneity across industries in the effects of US interventions on the share

of imports from the US. However, what is remarkable is that for almost all of the industries interventions

increase the share of imports from the US. This is true for 55 of the 63 industries. We only find a

negative effect of US interventions on the share of US imports in 8 industries, and in all 8, the coefficients

are not statistically different from zero.

19

20

21

Table 5 reports the same results as table 4, except that the share of exports to the US is examined, rather

than the share of imports from the US. There are a few notable differences between the results in tables 4

and 5. First, when looking at the estimates for share of US exports in table 5, we observe more

heterogeneity than when US imports were examined. Unlike the case with imports from the US,

interventions decrease the share of trade with the United States in a number of industries. For 24 of the

63 industries, the estimated effect of the US intervention on the share of exports going to the US is

negative, and for 4 industries the negative effect is statistically significant. This contrasts with the case

for imports, where we only see a decrease in trade with the US for 8 industries, and in none of these

industries is the result statistically significant.

The asymmetry of the results from tables 4 and 5 confirm our earlier finding that US interventions have

non-symmetric effects on trade flows. Looking at the aggregate data we found that US interventions

increased the share of imports from the US, but did not increase the share of exports going to the US.

Now looking at disaggregated industry level data, we find that US interventions increase the share of a

country’s imports that are from the US in nearly every industry, and they increase the share of the

country’s exports to the US in some industries, but decrease them in other industries.

Using the disaggregated industry level trade data, we now take a closer look at which industries are

affected, and in which manner, by US interventions. Specifically, we examine the industry-level change

in US imports and exports following a US intervention to see whether the changes in trade flows follow a

pattern consistent with comparative advantage.

We begin by first introducing a measure of revealed comparative advantage (RCA) that we use in the

analysis. The measure, which was first proposed by Balassa (1965), is calculated as follows:

22

∑ ∑∑

∑=

i cict

iict

cict

ictict x

x

xx

RCA,,

,,

,,

,,,, (4)

where xt,c,i denotes exports from country c in industry i and year t. The measure is a ratio of two ratios.

The first ratio (i.e., the numerator of equation (4)) is country c’s share of world exports in industry i. The

second ratio (the denominator) is country c’s share of world exports in all industries. Therefore, the RCA

measure compares the country’s share of global exports in an industry to the same share in all industries.

If the ratio is above one, then this means that the country captures a greater share of global exports in the

industry than it does on average. This is then taken as an indicator that the country has a comparative

advantage in producing in this good. If the ratio is less than one, then the country captures less of the

world export share than average, and therefore the country has a comparative disadvantage in producing

this good.

The logic of comparative advantage provides clear predictions about how the effects of interventions

should differ depending on the RCA of the intervened country and the RCA of the US if the increased

trade flows from the intervention are being driven solely by lower bilateral trade costs. First consider the

change in imports from the US to the intervened country. If the intervention decreases bilateral trade

costs between the US and the intervened country, then the volume of goods being shipped from the US

should increase most in the industries in which the US has a comparative advantage. In addition, the

RCA of the foreign country should also affect how the intervention affects the flow of imports from the

US. In industries in which the intervened country has a low RCA, one should see a greater increase in

trade flows from US interventions.

We examine these predictions with the following estimating equation:

23

∑∑=

−=

− +++++

×+×++

×+×++++=

N

nctcntn

N

n

jcntnictiUSt

ictctiUStctct

ictctiUStctctictj

ict

ymRCAimporterRCAUS

RCAimporteranySovietRCAUSanySovietanySoviet

RCAimporteranyUSRCAUSanyUSanyUSm

0,,

1,,,8,,7

,,,6,,,5,4

,,,3,,,2,1,,

ln

ln

ελγββ

βββ

βββααα (3)

In equation (3) the unit of observation is a year t, a country c, and an industry i. The dependent variable is

the natural log of imports into country c and in industry i that are from country j. We consider the cases

where j is the United States and where j is the entire world. The regression includes year fixed effects,

country fixed effects, and industry fixed effects. As before US anyt,c denotes our composite indicator that

equals one if any intervention occurs in year t in country c, any Soviet anyt,c is the analogous measure for

Soviet interventions. In equation (3) we allow the effect that an intervention has on the flow of goods

coming from the US to differ depending on the comparative advantage of the importing country and the

comparative advantage of the United States. The variables that measure either country’s comparative

advantage in the production of good i in year t are denoted US RCAt,US,i and Foreign RCAt,c,i.

When j = US, we expect, β2 > 0 and β3 < 0. That is, the increase in imports from the US should be greater

in industries in which: (i) the US has a comparative advantage, and (ii) in industries in which the foreign

country does not have a comparative advantage.

Estimates of equation (3) are reported in the first two columns of table 6. In the first column we allow the

effects of interventions to differ by the RCA of the United States and of the importing country. The

estimated coefficient for US any shows that US interventions increase the flow of imports from the US.

Further, none of the RCA interactions is statistically significant. Therefore, the increase in imports does not

seem to be shaped by comparative advantage. The variable US RCA enters directly with a statistically

significant and positive coefficient. This tells us that, independent of interventions, foreign countries

always import more from the US in industries in which the US has a comparative advantage.

24

The results of column (2) provide estimates that are consistent with expectations. Namely, the negative and

statistically significant coefficient for Foreign RCA tells us that the foreign country imports less in

industries in which it has a comparative advantage. This provides some verification that our RCA measure

does capture comparative advantage, and that the insignificance of the coefficients for foreign RCA and

USany x Foreign RCA found in column (1) are a not a figment of noisy data.

In columns (3) and (4), we re-estimate equation (3), but examine the flow of exports to the US and to the

world, rather than imports. The estimates show that the impact of interventions on the flow of exports to

25

the US is higher when: (i) the US does not have a RCA in the production of the good, and (ii) the foreign

(exporting) country does have a RCA in the production of the good. In other words, the change in exports

does seem to follow the logic of comparative advantage.

Again we find a stark asymmetry. Looking at the export side, the data seem consistent with the view that

the intervention decreased trading costs between the US and the intervened country and this causes

increased specialization of production and trade between the countries. However, looking at the import

side, we find that imports from the US increase in all industries and the increase does not seem to follow a

logic that is consistent with comparative advantage. That is, on the import side the data are not consistent

with the increase in US imports arising from a reduction in bilateral trade costs between the two countries.

This is consistent with a role for political influence in affecting trade flows.

We now turn to an examination of the effects of US interventions on other outcomes interest; specifically,

short and longer-term economic growth. We examine the evidence for the effect of interventions on

short- and long-term income growth by estimating equation (5). The dependent variable in equation (5) is

the average annual growth rate of real per capita income in the N years following period t. We report

results for the cases for N = 1, 5, 10 years. We control for an N year lag of the dependent variable, as well

as the log per capita income in period t, t-1, and t-2.2 As before, all estimates control for year fixed

effects and country fixed effects.3

∑=

−−+ ++

−++++=

− 2

0,,

,,,2,1

,, lnlnlnlnln

nctcntn

cNtctctctct

ctcNt yN

yyRUSanyUSany

Nyy

ελγββαα (5)

2 In the one year growth regression (N = 1), the one year lagged dependent variable is dropped from the regressions because it is a linear combination of ln yt-1 and ln yt-2, which are already included in the estimating equation. 3 Once we examine growth rates long than 1 year, there is mechanical non-independence of the growth rates from year to year. For this reason, for our 5 and 10 year growth estimates (N = 5, 10), we cluster all standard errors at the country level.

26

Table 7 reports estimates of equation (5) among for autocracies in our sample. Columns (1)-(2), (5)-(6),

and (9)-(10) report estimates for 1, 5 and 10 year growth respectively. In the odd numbered columns we

use our aggregate measures of US and Soviet interventions, and in the odd numbered columns we use our

disaggregated measures. Overall, we do not find robust evidence for any effect of interventions on future

growth. For 1 year growth we find some weak evidence of a positive effect of interventions, which is

driven by the intermediate years of the intervention, but as show in columns (3)-(4) this result is not

robust to our use of matching as an alternative estimation strategy. We also find not evidence of any

growth effects when we examine 5 and 10 year average annual growth rates.

We were unable to run analogous regressions for Soviet imports and exports because Soviet era

trade data is widely considered to be unreliable. This arises primarily from the difficulty of

pricing trade that occurs between two communist countries. Therefore, although some Soviet

trade data do exist from trade that occurred with market economies, it is far from incomplete.

Using the incomplete and imperfect Soviet trade data available, do not find any robust systematic

relationships in the data.

In table 8 we report the same estimates for our sample of democracies. Again we find no systematic

robust evidence that interventions have an effect on either short-term or long-term economic growth.

27

28

V. Accounting for selection and the determinants of US interventions

A concern with all of the results reported to this point is that they may be spurious, driven by other factors

other than US interventions. We have included a comprehensive set of control variables in an attempt to

best control for these other factors. Our country fixed effects capture all time invariant differences

between countries. Similarly, our year fixed effects capture differences in the global environment in each

29

year. In our trade regressions we also control for country-year specific characteristics, such as lags of the

dependent variables, present and lagged real per capital GDP, and present and lagged aggregate GDP.

Despite our best attempts our results still may be biased by factors that we have not controlled for which

are also correlated with interventions. Our strategy here is to first examine which factors are correlated

with US interventions. After these factors are determined, we then re-estimate our equations controlling

for these factors. As we will show, US interventions appear to be orthogonal to the most likely potential

determinants. We do find a robust politically driven determinant of interventions, and show that even

controlling for this, all of our previous results hold.

In our specifications we consider a range of economic and political variables. While the results shown are

for a linear probability model (LPM) with fixed effects, all results are robust to estimating a probit model.

We begin by discussing potential economic motives for interventions and then turn to political motives.

The most likely economic motive for interventions is that they are aimed at increasing the foreign market

for US goods. We test for this motive using the following estimating equation.

∑

∑∑

=−

=−

=−−−

++

++Δ+++=

N

nctcntn

N

ncntn

N

ncntnctctctct

y

anySovietUSanyXXUSany

0,,

0,

1,,12,11,

ln εη

λγββαα (6)

The logic of our estimating equation is the same as that used in the previous section. We consider data in

a panel environment, where an observation is a country c in a year t. As before, all estimates include

country fixed effects and year fixed effects. The core difference with equation (6) is that our outcome

variable is now US interventions, which we continue to denote by USany. We continue to control for lags

of the dependent variable and real per capita GDP as well as its lags.

30

The variable ctX ,1− denotes a one year lagged measures of either imports from or exports to the US. The

results are qualitatively identical if we use the contemporaneous measure rather than the one year lag. We

consider a wide variety of measures on the hypotheses that have been put forth about the motives of US

interventions. We also consider a measure of the 5 year change in ctX ,1− , which we denote by ctX ,1−Δ (

ctct XX ,6,1 −− −≡ ).

The estimates are reported in table 9. Columns (1)-(4) report estimates with lagged levels of trade flows

as the independent variables. We include the log of the value of imports from the US; the share of

imports from the US relative to total imports from all countries; the log value of exports to the US; and

the share of exports to the US relative to total exports from the country; all measure in year t-1. In

columns (5)-(8), we include the 5 year change of these measures. We find none of the trade variables to

be statistically significant. This is also true if one constructs other similar variables, such as shorter or

longer changes in the variables, or if one uses longer lags. We find not evidence at all that past trade

flows affect the probability of an intervention taking place.

31

We turn next to potential motives. The most plausible alternative motives are security related. These

motives could be related to any security issue, and we do not take a stand on the specific issue here.

Consider the preferences of the US and a foreign country on some security issue. When the optimal

outcome (ideal point) for the US on some security issue differs significantly from that of the foreign

country, a US intervention provides a mechanism through which the US can move the foreign country’s

preferred outcome closer to that of the United States. Because interventions come at a cost, it will only be

optimal for the US to intervene if the distance between the two country’s most preferred outcomes is

sufficiently large. This suggests that, all else equal, interventions will be more likely when countries are

less closely aligned with the United States on key security policies. This is one prediction that we bring

to the data. We use whether there exists an alliance between the country and the US as an indicator that

32

the preferences of the foreign country are more in line with those of the US.4 Therefore, the prediction is

that all else equal, an intervention is less likely when a country shares an alliance with the US.

The above mechanism addresses the effects of variation in the benefits of interventions on the propensity

to intervene. However, variations in the costs of interventions can also affect this probability. First, the

costs of shifting policy towards the US’s ideal point should be lower if the intervention is in an

authoritarian regime than in a democratic one, since there are less internal checks and balances to

overcome in the former case. As well, international opposition to an intervention, and opposition from

US citizens, is also likely to be higher if the leader being toppled was installed through a democratic

process. Presumably, the fact that we are focusing separately on authoritarian regimes (effectively

controlling for regime), and are also including fixed effects and GDP as controls, addresses this issue to

some degree. Even within authoritarian regimes, there may be significant variation in how authoritarian

the regime is and therefore in the effective cost of and intervention. Specifically, in authoritarian

environments that have experienced democratic rule in the recent past the toppling of a leader is more

likely to be met with domestic and external pressures to reinstall democracy and to choose security

policies via the democratic process. In such environments the costs of shifting security policy towards the

US ideal point is likely to be higher, since both domestic and international opposition has to be overcome

in order to shift the country’s ideal point to the US’s ideal point.

The above considerations lead us to expect that interventions are most likely to occur in authoritarian

countries which are not allies of the United States, and which do not have a recent history of democratic

rule. It is plausible that our two factors – history of autocracy and alliance with the US – interact with

each other to determine the probability of an intervention in an authoritarian environment. For example,

4 There is of course a long standing tradition of using alliances as a proxy for common security preferences beginning with Bueno de Mesquita (1981).

33

even if a country has no recent democratic history (and the costs of an intervention are thus relatively

low), the proximity of preferences of a US ally may be so close as to not justify an intervention.

In line with this reasoning we apply the following estimating equation to authoritarian regimes.

∑ ∑∑∑= =

−−=

−=

−

−−−−

+++++

×++++=N

n

N

nctcntncntn

N

ncntn

N

ncntn

ctctctctctct

YyanySovietUSany

histautocalliancehistautocallianceUSany

0 0,,,

0,

1,

,1,13,12,11,

lnln εμηλγ

βββαα (7)

In equation (7), alliancet-1,c is an indicator variable that equals one if country c is in an alliance with the

US in year t-1; autoc histt-1,c is the number of continuous years prior to time t that the country had an

authoritarian regime. All other variables are defined in the same manner as in equation (6).

When the country has an alliance with the US (alliance = 1), the effect of autoc hist is given by β2+ β3,

and when the country does not have an alliance with the US (alliance = 0), then the effect of autoc hist is

given by β2 only. The coefficient β1 tells us the effect of the alliance on the probability of intervention for

a country with a very recent democratic episode (i.e., autoc hist = 0). Since very few interventions occur

in a democratic environment, this coefficient is not empirically relevant for almost all observations in our

sample.

Estimates of equation (7) are reported in column (1) of table 10. We estimate positive coefficients for

autoc hist (β1) and alliance (β2), and a negative coefficient for their interaction (β3). According to the

coefficients, when a regime is not allied with the US (alliance = 0), then the effect of a history of

autocracy is positive (β2 = .003). However, this effect disappears in the presence of an alliance (β2+ β3 =

.003 – .003 = 0). That is, the US is more likely to intervene the older the autocratic regime only if the

regime is not aligned with the US.

34

Given these relationships in the data, we next check that our core results of the effects of interventions are

robust to controlling for alliance, autoc hist, and the interaction of the two. We thus re-estimate equations

(1)-(4), with these variables added on as controls. The core results are reported in columns (2)-(6) of

table 10. As shown, the results are qualitatively identical to previous estimates even when we control

explicitly for the determinants of US interventions. We continue to find that US interventions increase

the flow imports from the US (columns (2)-(3)). As well, we still find a fundamental asymmetry in our

results. There is no relationship between US interventions and the flow of exports to the US (columns

(4)-(5)). As before, we also continue to find no effects among democracies in the sample (column (6)).

We can thus be more confident that our results from section IV are not driven by omitted characteristics

correlated with the determinants of interventions.

35

VI. Conclusions

In this paper we have undertaken a systematic empirical evaluation of the economic consequences of US

interventions to install and prop up foreign leaders during the Cold War. We have done so by

constructing a dataset that takes account of covert in addition to overt interventions. We find that the

main economic effect of these interventions is to increase the market share of US products in authoritarian

regimes. US interventions do not increase exports, or future income, and thus do not appear to increase

economic welfare in the intervened countries. Although US interventions have economic consequences,

we do not find that they are driven by an economic calculus (at least to the extent that we are able to

36

capture them in our economic variables). Rather, they indeed appear to be driven by security concerns

and associated costs and benefits, as policy makers claim.

To the extent that our Cold War findings can be generalized to the current environment our findings have

some deep implications that are relevant to current day concerns. Conditional on interventions occurring,

policy makers concerned about the welfare of citizens of intervened countries need to pay special

attention to the imbalance between imports from and exports to the US that emerges in the wake of

interventions. Unless the increase in imports from the US is directed towards increasing export capacity

and/or accompanied by an opening of US markets to imports from the intervened country, the

intervention is unlikely to have positive welfare effects.

This paper leaves open significant avenues for future research. For example, we have only begun to

explore the precise mechanisms by which imports from the US increase following an intervention. Our

current research focuses on developing the databases that are adequate to addressing these questions in a

convincing way.

37

VII. Appendix

38

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