1

Rough Draft—not for attribution!

Is the Hidden Hand an Iron Fist? Capitalism & Political

Violence, 1970–2005

Indra de Soysa

Norwegian University of Science and Technology (NTNU) & Centre for the Study of Civil

War, PRIO

&

Hanne Fjelde

Department of Peace and Conflict Research, Uppsala University

& Centre for the Study of Civil War, PRIO

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1. Introduction

There is a long, contentious debate about capitalism as an economic system that delivers

welfare, social justice, and peace (Hayek, 1944; Lenin, 1916; Polanyi, 1944; Schumpeter,

1942; Smith, 1776). The current debate on the effects of globalization is in many ways a

continuation of this debate, which until recently has been contended between those who argue

that interdependence between rich and poor countries can spread modernization, including

liberal, capitalistic values, and economic and political development, and those who see global

capitalism as breeding dependence of the poor on the rich, leading to exploitation and socio-

political ruin (Apter, 2008; Boswell & Dixon, 1990; Stilwell, 2006; UNRISD, 1995; Weede,

2004). Recent empirical research in international relations finds considerable support for

peace between states that are characterized as ’liberal’, or even capitalistic, but there is very

little on the issue of whether the spread of capitalism across the world under the rubric of

what we term ‘globalization’ is a pacifying force within countries.1 The issue is not merely

‘academic’ but carries massive policy implications in this era of global governance where

what types of economic systems matter for achieving peace and prosperity need sound

empirical backing, rather than ideologically driven debate based largely on hearsay and

anecdote. Journalistic accounts of the ravages of capitalism, for example, have recently

received much notoriety, particularly on the heels of highly celebrated corporate scandals and

financial meltdowns (Klein, 2007)

Given the recent focus on ‘state capacity’ as a crucial source of civil peace, the issue of

globalization and peace gains added salience, since many believe, as did Karl Marx centuries

previously, that the state represents the interests of capitalists and therefore is unable to act

autonomously for bringing about social justice and peace. Current arguments about

globalization suggest that global capitalism driven by the profit motive allows capitalists the

upper hand over communitarian interests, which could lead to weakened state autonomy and

‘societal disarray’ (Rodrik, 1997; Stiglitz, 2002; UNRISD, 1995). Using the globalization

debate as a backdrop, this paper will empirically assess whether states which exhibit

capitalistic tendencies reflected by their economic policies are more likely to have serious

1 For arguments about the ‘liberal peace’, see (Oneal, 2003; Russett & Oneal, 2001). For the ‘capitalist peace’ proposition, see (Gartzke,

2007; Gartzke, 2009). On the question of globalization and peace, see (Bussmann, Schneider & Wiesehomeier, 2005; Mousseau, 2002;

Schneider, Barbieri & Gleditsch, 2003).

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domestic quarrels relative to those that do not.2 If states have onsets of civil war, then by

definition, it signifies that a state is unable to monopolize the use of force, a primary indicator

of strong state capacity. Alternatively, capitalism may lead to high social dissent, but because

of the usual collective action problems, large civil wars may not get generated due to high

repressive capabilities at the hands of capitalistic states—the so called ‘iron fist.’ Thus, we

also address the issue of whether more capitalistic economic policies drive high social dissent

and state repression. We use empirical data on economic freedom in multivariate models of

civil war and models of state repression, comparing the effects of capitalism with other

interesting, policy-relevant factors, such as ‘good governance’ and democracy.

Our results are easily summarized. Using data on economic freedom from 1970–2005, we

find that the higher the level of economic freedom, the lower the risk of civil war. These

results are robust to several different specifications of the models and sample size. Moreover,

economic freedom trumps per capita income, one of the most robust results on civil war

(Hegre & Sambanis, 2006). The substantive impact of economic freedom is in fact quite large,

relative to other significant factors. Including terms for good governance made no difference

to the basic results. Further, economic freedom has a consistent, robust, substantively large

effect on lower political repression, which signifies that economic freedom’s peace effect is

not due to higher repression of conflict under these conditions. Moreover, democracy’s

negative effects on repression are conditioned by higher economic freedom in ways that

benefit, not hurt, citizens, findings which support ‘liberal’ and capitalist peace arguments. We

find exactly the opposite results expected by arguments about the social effects of

globalization that sees political violence driven by the loss of state autonomy due to growing

power of capitalists over the economic policy process.

Marxist critiques of capitalism

Classical liberals, such as Adam Smith, David Ricardo, and Bernard Mandeville, argued that

individuals in pursuit of self interested goals served a higher social purpose ‘as if by a hidden

2 We use one of the most widely-cited measures of ‘economic freedom’ that captures how favourable a state is towards promoting capitalist

development along 22 economic and institutional dimensions (Gwartney & Lawson, 2005). Many others use this index in the spirit of

capturing the degree of ‘neoliberalism’ reflected in an economy as well as how friendly a state is towards entrepreneurship and private

enterprise (Boockmann & Dreher, 2003; de Haan & Sturm, 2009; Easterly, 2005).

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hand’ (Stilwell, 2006). They argued in favor of free markets for achieving prosperity and

other desired outcomes through spontaneous social cooperation. Such arguments were

expanded by political philosophers, such as Immanuel Kant, John Stuart Mill, and Norman

Angell, who viewed the expansion of trade, or the ‘commercial spirit,’ as the triumph of

civility over plunder. Commerce apparently made war unnecessary. Self-interested

individuals cooperated out of the profit motive. Classical liberals argued that cooperation

stems fundamentally from expected material gains rather than from religious ethics or

inherent feelings of sympathy for fellow beings. In its very essence, arguments about the

superiority of capitalism over the dominant economic system of the time, mercantilism, was

due to the ability of markets to create and distribute goods and services (wealth) more

efficiently. For markets to work efficiently, however, there had to be a system of good

property rights. Thus, capitalism is marked by the means of production being owned by and

secured for individuals and by its expansionary tendency, since the desire for profit drives

investment. Thus, a social-welfare maximizing ruler would be one who interfered least in the

workings of markets, merely respecting the property of individuals. At a minimum, the state

should provide public works that enhance the operation of markets (Stilwell, 2006).

For Marxists, capitalism is too anarchical. It is an economic system in which capital exploits

labour. The owners of capital live off of their exploitation of labour, and the nature of the

production and reproduction of capitalism creates distinct classes where capital becomes

concentrated among a few. These classes will ultimately compete (even clash) over the

redistribution of the social surplus—rather than cooperation, the profit motive divides. Such

explanation of conflict, have a long pedigree that relies on explaining European revolutions as

the desire of the poor to emancipate themselves from the shackles of despotism and bourgeois

exploitation (Przeworski, 1990). The Cold War, for example, was seen as the extension of the

class-struggle logic on a World scale. Thus, conflicts in the developing world were seen as

class conflict, where the rural and urban poor agitated for reform against an entrenched elite

(often domestic and foreign capitalists), who resisted reform. Thus, a large amount of work

was devoted to identifying if and how inequality, both income and land inequality, assumed to

be the triggering mechanism of class conflict, related to civil violence (Boswell & Dixon,

1990; Muller & Seligson, 1987; Russett, 1964).

The literature on conflict and income inequality, the most widely-used proxy for capturing the

existence of a class gap, is highly mixed and theoretically somewhat ambiguous (Lichbach,

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1989; Weede, 1998). Since the poor face massive collective action problems, they may starve

in silence. If the capitalists control state power as Marxists claim they do, then state repression

may prevent large-scale civil violence. In fact, much recent, methodologically sophisticated

empirical studies find no relationship between various measures of income inequality and

civil war (Collier, Hoeffler & Rohner, 2009; Fearon & Laitin, 2003). Thus, whether or not the

poor can overcome collective action problems for challenging powerful elites may depend

heavily on the existence of effective state repression of dissent.

In fact, Przeworski and Wallerstein’s (1982) seminal article on the question of why the poor

don’t ‘soak’ the rich as often as we would expect, shows clearly that even if the poor would

be better off in the long-run, the ‘valley of transition’ when the rich withdraw their

‘investment’ would dissuade such action. In other words, there could be an equilibrium of

class compromise, not class war, leading to democracy and some redistribution without

outright expropriation (Przeworski & Wallerstein, 1982). This literature demolished Marxist

arguments about how democracy and redistribution would never be allowed by a state acting

in the interests of capital (Iversen, 2008). Notice, however, that much of this literature is

focused on industrial countries where developed class interests and distinctive class

consciousness exists, something that might be absent in much of the developing world. Thus,

rather than measures of inequality, we utilize a measure of ‘capitalist’ economic policies

directly in models of conflict and repression, which allows us to answer the question of

capitalistic economic policies and social peace head on relative to the heap of studies that

have addressed the issue indirectly by focusing on material conditions that ostensibly proxy

class consciousness, name the degree of inequality. Testing the effect of capitalism on civil

war alone is not enough, however, since a state captured by capitalistic interests could always

repress dissent. Therefore, we also test capitalism’s effects directly in models of state

repression, a form of one-sided state violence against dissent.

Capitalism & State capacity: the globalization debates

The issue of capitalism and state autonomy has resurfaced in debates on globalization. State

capacity is seen by many as central to understanding why some countries experience political

violence while others don’t (Benson & Kugler, 1998; Fearon & Laitin, 2003; Huntington,

1968; Mueller, 2004). Pessimists on globalization see the growing empowerment of markets

and global corporations as coterminous with the weakening of states—the so called ‘race to

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the bottom’ thesis. States will lower social standards to place ‘footloose’ capital. Such

arguments expect globalization to drive social disarray (Martin & Schumann, 1997; UNRISD,

1995). By definition, states must maintain monopoly over violence for maintaining legitimacy

and order. Simple regime type, such as democracy versus autocracy, are poor predictors of

civil wars and violent political dissent and repression (Bueno de Mesquita et al., 2005;

Davenport & Armstrong, 2004; Hegre et al., 2001; Huntington, 1968; Snyder, 2000). This

issue suggests that simply identifying a politically ‘good’ state vis-a-vis popular expectations,

such as democracy, does not automatically translate into peaceful state-society relations

because groups with some payoff for organizing violence against the state can always hedge

their bets against being eliminated when facing a relatively weak state. In other words, where

states are weak, violence just ‘happens.’ States are incapable of maintaining order regardless

of how ‘legitimate’ they may be among the population at large.

Despite a strong consensus around state capacity and peace, what state capacity actually is

and how to measure it are contested subjects. A recent analysis undertaken by the present

authors show that variables measuring the quality of institutions that govern economic

activity, namely a measure of ‘contract intensive money,’ predicts peace to a larger degree

than does a measure of the ‘extractive capacity’ of states (Fjelde & De Soysa, 2009). We also

find that governments that command a higher share of an economy (assumed to be a

government’s ‘purchasing power’ of peace) also face less risk of civil war. This result at first

glance might support the view that heavy government involvement in an economy may

moderate the harmful social effects of capitalistic society—the ‘compensation’ argument

(Rodrik, 1997). However, what exactly high government spending in capitalistic (more open)

economies actually achieves is heavily contested (Garrett, 1998). If Garrett’s ‘competition’

thesis is correct, then high government spending simply perpetuates more competitive

capitalism, not social insurance, thereby perpetuating peace, an answer that will sit very badly

with capitalism’s critics. We address this issue by offering a simple model based on what we

already know empirically about determinants of civil war, particularly on the feasibility thesis

of civil war. We also test the model in a more straight forward manner—could economic

systems that are more capitalistic manage social peace?

A Capitalist Civil Peace: How?

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The ‘capitalist peace’ arguments focused on interstate war are based on a simple logic--the

capitalist structure of production simply raises the cost of theft, making exchange far more

profitable. The growth of the spirit of commercialism force rulers to be wise if they are to do

well! Capital and knowledge required for successful production in modern economies is

easily withdrawn from conquerors, the essence of Przeworski and Wallerstein’s critique of

Marxist ideas about states and internal redistribution discussed above. In fact, the argument is

valid for both the domestic and international setting. As Gartzke (2009: 37) writes, ‘politics

has simply ceased to be a feasible mechanism for the production or acquisition of wealth.

Because of this, and because modern productive processes are more dependent than ever on

the provision of public goods, politics is much less cut-throat (literally) than it used to be,

both within and between international borders [our italics]. Such arguments, however, are far

too imprecise to be applicable in the domestic setting. For one, as many observe, the threat to

property because of politics is ever present in poor countries where the median voter’s income

is below mean income, but even more seriously, the location of civil violence today is mostly,

if not wholly, in countries with less than ‘modern’ economies, with little modern production.

In other words, when it comes to civil violence, the benefit of sophisticated production

structures for inducing peace is far less obvious. We explore below how the basic insight of

why more capitalistic economies might raise the premium on peace is still valid in the

developing-country context—i.e. why economies favorable to entrepreneurship can do better

than others, net of the level of wealth (economic sophistication) of a country.

The seminal theoretical and empirical analyses of civil war conducted by Collier and Hoeffler

(1998; 2004) as well as Fearon and Laitin (2003) find that opportunity factors explained the

onset of civil war to greater degrees than factors that typically generate large grievances.

These authors conclude that civil violence may be a function of opportunistic (fortune-

seeking) behavior as opposed to selfless (justice-seeking) behavior, largely because of the

immense collective action problems surrounding the provision of public goods, such as social

and economic justice (Collier, 2000; Collier & Hoeffler, 2004). Conflicts will occur where it

is ‘viable’ for groups to organize (Collier, Hoeffler & Rohner, 2009). If this is true, then

opportunistic behavior of organizing violence against states must be shaped by many factors,

including the socio-political and economic environments that shape the size and nature of the

payoffs for investing in violence over other potentially ‘profitable’ enterprises.

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In fact, the ‘loot-seeking’ model of rebellion that makes conflict attractive and viable at the

same time is the expected payoff to investment in rebellion. Such arguments however rarely

consider the opportunity costs associated with alternative investments—any potential rebel

could easily be a natural resource exporting ‘corporation’ paying taxes to the state as much as

a warlord who has to invest much of the loot (not to mention the discomfort of living in the

bush) for fighting the state. However, if the state is characterized as one that rather

monopolizes all economic activity and expropriates all surpluses that are created—i.e. Mancur

Olson’s ‘roving’ rather than ‘stationary’ bandit—then there will be few incentives to invest in

taxable enterprise. In other words, there will be large ‘deadweight losses’ in the economy

since the tax rate is not optimal, nor property rights secure. In other words, such an

environment poses risks for productive enterprise. Warlord politics, in other words, is

‘competition’ among ‘roving’ bandits. Where property rights are insecure and capricious

political processes govern economic life, there is motivation for organizing in the shadows

around capturing rents and defending them (Skaperdas, 2003). In other words, when

economies are characterized as having distorted markets and high tax rates, they suffer

‘deadweight losses,’ production falls but demand for goods remain constant, which allows

super profits in the form of smuggled goods—entrepreneurship is forced into the shadows.

These groups over time will possess a particular form of conflict-specific capital, such as

access to armaments, tunnels, finance, and shadow networks that give them advantages over

state forces. Such shadowy groups apparently now make up a large part of the violent

environments globally (Mueller, 2004).3 We agree with Skaperdas (2003) that the economy

cannot be divorced from its governance, since the restraints on particular forms of behavior of

homo economicus is shaped by the incentives that govern the system.

The issue of capitalistic, or production-friendly environments, may relate to questions of

conflict and peace through the link between natural resources, weak states, and civil war. If

resources provide lootable income and governments are weak under resource-wealthy

conditions, then why have rulers not used the resource wealth to build up more viable states?

The most convincing arguments are that rulers fear replacement and thereby don’t build

institutions that would lead to alternative bases of power. If capitalism builds alternative

sources of economic power in a society, then resource wealthy rulers have little incentive to

open economies that would lead to a modern economy (Fors & Olsson, 2007). There is by

3 For a comparative view of warlordism, see (Marten, 2006).

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now a large body of literature on the ‘rentier state’ that are based on similar arguments

(Beblawi, 1990; Bellin, 2004; Ross, 2001). Again, we test this directly by assessing the degree

to which more capitalistic economic frameworks produce social peace.

One may have already noticed now that what makes capitalism provide the goods are good

institutions that are capable of upholding the rule of law (protect property). This may by

definition require a strong state, but not necessarily one that intervenes in the economy. The

issue then is whether capitalism and peace go together because of good institutions that pacify

people and allows a state to coerce it easily, and not necessarily due to any inherent pacific

benefits from free enterprise and the commercial spirit as some classical liberals argue. In

order to estimate the net effects of both, we parse out the effects of good institutions by

entering various proxies of good governance, legal security and property rights protection,

bureaucratic strength, and the control of corruption as controls in our models.

Measuring capitalism

Assessing the relationship between globalization and social outcomes is now a growth

industry (Dreher, Gaston & Martens, 2008). Few, however, have empirically addressed the

issue of capitalism and civil peace. Most studies that have addressed globalization and

conflict have proxied economic openness with measures of trade dependence, or openness to

foreign investment. The results thus far have been somewhat mixed. Hegre et al. (2003) find

no direct effect of trade/GDP on the risk of civil war, nor do they detect a significant effect of

FDI/GDP. They do, however, find suggestive evidence of an indirect negative effect of trade

on internal conflict, working through the channels of economic growth. Eldabawi and Hegre

(2008) corroborate this indirect effect of openness, working via economic growth.4 Due to

several factors, trade, or FDI, are imperfect proxies for an economy’s overall governance

structure in terms of capital friendliness—a country with high resource exports could be a

high trader!

Bussman and Schneider (2007) argue that states that pursue a policy of economic openness

exploit their comparative advantage and produce and consume more, thus enhancing

4 Elbadawi and Hegre (2008) also examines the long and short-term impacts of terms-of-trade shocks on the risk of conflict, but find no

significant results.

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economic welfare and societal peace. By heightening the opportunity costs of rebellion,

openness facilitates peace. Corroborating this argument, Bussman and Schneider find that the

level of trade openness, measured as the sum of export and import, divided by GDP, is a

significant predictor of civil peace. Also the level of FDI flow influences peace positively.

Bussman and Schneider (2007) find moreover that changes in economic openness, measured

as the yearly growth rate of the trade to GDP, are associated with an increased risk of civil

war, suggesting that the short-term redistributive effects of economic liberalization might

precipitate civil unrest.5 In general, however, outcome measures such as the trade to GDP

ratio or FDI flows are problematic because they are outcome variables, not policy variables

(Steinberg and Saideman, 2008). They might thus reflect a number of economic and

geographic attributes of a country and not necessarily the policy process. To account for this,

Bussmann and Schneider (2007) also add a measure of the regulatory aspect of economic

integration, with data measuring capital control relaxation.

Steinberg and Saideman (2008) examine how the role of government intervention in the

economy affects ethnic peace. They argue that high levels of government intervention

precipitate civil war, by increasing the net benefits of rebellion. They use a measure of

government intervention in the economy from the Heritage Foundation and find that

‘economic freedom’ is associated with a lower risk of ethnic violence. In an additional test,

they also use a more inclusive definition of conflict, relying on data from the UCDP/PRIO

dataset (but a unconventional operationalization – in three steps – and only a cross-section of

data (2001-2004) for the main analysis). Others have addressed the question of political

repression (or respect for human rights) using the notion of contract-rich environments, which

is a feature of capitalism, and find that such environments lead to better human rights

conditions (Mousseau & Mousseau, 2008). Thus, we test further what is still rather tentative

evidence for a ‘capitalist civil peace’ by using a comprehensive measure of ‘economic

freedom,’ which shows relatively wide coverage and is perhaps the most widely-used in

empirical studies on the effects of capitalism (Gwartney & Lawson, 2005). Previous studies

that have used this measure to test the effects of neoliberal policies on growth (de Haan &

Sturm, 2009), the effects of IMF conditionality on policy change (Boockmann & Dreher,

2003; Dreher & Rupprecht, 2007), and the effects of economic freedom on corruption (Graeff

5 Bussman et al. (2005) test a similar argument on a sample of Sub-Saharan Africa. Blanton and Apodaca (2007) make a similar test of the

globalization argument, focusing only on developing countries.

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& Mehlkopf, 2003), on democracy (Feng, 2003), and subjective wellbeing and happiness

(Veenhoven, 2000).

The Fraser Institute defines economic freedom in the following manner:

Individuals have economic freedom when property they acquire without the use of force, fraud, or theft is protected from physical invasions by others and they are free to use, exchange, or give their property as long as their actions do not violate the identical rights of others. An index of economic freedom should measure the extent to which rightly acquired property is protected and individuals are engaged in voluntary transactions.

They measure the concept by aggregating economic factors capturing the friendliness of the

economy to entrepreneurs along 22 dimensions (Gwartney & Lawson, 2005). This measure is

partly based on objective factors, such as the degree of actual trade, and subjective readings of

particular policy stances. Thus, Mongolia may in fact be more economically free relative to

Germany, even if Germany is far more dependent on others for actual trade. Others too have

used the Economic Freedom Index as measures of ‘neo-liberal’ policy in similar studies

(Boockmann & Dreher, 2003; Looney & McNab, 2008). The correlations between the Index

of Economic Freedom and the log value of total trade to GDP from the World Development

Indicators is generally low (r = 0.32). The index is reported in quintiles from 1970 onwards

until 2000 after which annual values are reported. We interpolate the data for the years in

between the quintiles from 1970 until 2000.

As mentioned above, separating the effects of capitalism as an economic system from the

’governance components’ that make up strong institutions is not straightforward.

Conceptually, one could have a more free economic system that favors only some people over

others; i.e. have corrupt bureaucracies or weakly institutionalized rule of law, such as

protection of property and legal rights, as well as its opposite; i.e. relatively closed economic

environments for capitalistic activity with ‘good’ governance and little corruption. Thus, we

enter several measures, namely the Fraser’s Institutes own measure of legal security and

property rights protection that is one of the components of the index of economic freedom, an

indicator of ‘contract intensive money’, subjective assessments of the quality of the

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bureaucracy, and the effectiveness of the control of corruption.6 The correlations among the

institutional variables and economic freedom are presented in table 1. As seen there, there is

generally high congruence between the institutional variables and economic freedom, but the

associations are far from perfect.

TABLE 1 ABOUT HERE

Methods and Data

We are interested in estimating the effects of economic freedom on serious political violence.

Our primary focus thus is on organized violence against a state. Secondarily, we test the

notion of one-sided violence by assessing whether economic freedom predicts higher state

repression of dissent. As our main dependent variable measuring large-scale violent challenge

of states, or civil war, we use data from the UCDP/PRIO Armed Conflict Dataset v.4-2008

(Gleditsch et al. 2002, Harbom, Melander and Wallensteen, 2008).7 An intrastate armed

conflict is defined as a contested incompatibility between a government and one or more

opposition groups that results in at least 25 battle deaths in a year. To address the problems

associated with temporal dependence in time series cross-section analysis, we add a variable

that records the time since the last onset of armed conflict, or in the case of no conflict, the

time since the first observation of the country in our dataset. Since the legacy associated with

a previous armed conflict is likely to be non-stationary, we specify this variable as a decay

function. The function of time that has passed without conflict is given by 2 to the power of –

(time since last onset of conflict/α) where α is the half-life parameter (Raknerud and Hegre,

1997). After comparing the log-likelihood of different models, we choose a functional form

where the influence of last conflict decays over time with a half life of 2 years.8 Notice that

accounting for the proximity of conflict also has implications for the analysis if coders of

6 For a full treatment of CIM, its measurement, and association with trust in institutions and its relationship to state capacity and political

violence, see (Clague et al., 1999; Fjelde & De Soysa, 2009). The measures of bureaucratic quality and corruption are taken from the

International Country Risk Guide Data, which are subjective evaluations of the quality of governance assessed by a commercial company

that services the international business community, see http://www.prsgroup.com/.

7 See also the Uppsala Conflict Data Program webpage found at www.ucdp.uu.se.

8 The dataset structured for quantitative analysis was downloaded from http://new.prio.no/CSCW-Datasets/Data-on-Armed-

Conflict/UppsalaPRIO-Armed-Conflicts-Dataset/. For more detailed information about the coding of the two onset variables see the

accompanying document on the same webpage.

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economic freedom systematically code down the level of economic freedom when observing

violence.

Our second dependent variable, state repression, is from two sources (Cingranelli & Richards,

1999; Gibney & Dalton, 1996). The CIRI data scale on ‘physical integrity rights’ and the PTS

scale use very similar sources, namely the US state department and Amnesty International

country reports for devising their indexes, but they collate their data somewhat differently

yielding a high correlation between the two (r=0.85), but one that is less than perfect. These

data are employed by most studies of state repression since the seminal work of Steve Poe and

associates (Carey & Poe, 2004; Hafner-Burton, 2005; Landman, 2005; Poe & Tate, 1994;

Poe, Tate & Keith, 1999).

Naturally, we need to employ different models and estimating techniques for testing these two

different outcomes. In the civil war tests, we use standard logistic regression. We use a set of

core variables gleaned from the findings of the Collier-Hoeffler studies and the Fearon-Laitin

studies. We control for per capita income, which has proved to be one of the strongest

predictors of civil war. Thus, we estimate the effects of capitalistic economic environments

net of how modern and productive (per capita) and economy is. These data are obtained from

the World Bank’s World Development Indicators CD rom and log transformed to reduce the

effect of extreme values (World Bank, 2007). Large countries also seem to have a greater risk

of civil war. To control for country size we include total population log transformed (World

Bank, 2007). This is an important control variable since the degree of a countries desire to be

economically open and free might be a function of the size of its domestic market. Country

size and the nature of social fractionalization in a society are generally linked. The effect of

social fractionalization on the risk of civil war is mixed and theoretically contested (Collier,

Hoeffler & Rohner, 2009; Esteban & Ray, 2008; Fearon & Laitin, 2003). We enter a measure

of ethnic fractionalization obtained from Fearon and Laitin (2003) in linear and quadratic

form in order to model the effect of fractionalization and polarization simultaneously. We also

enter a dummy variable capturing whether or not a country is an exporter of oil measured as 1

if oil exports are greater than 1/3 of total export revenues and 0 if not (Fearon & Laitin, 2003),

and an indicator measuring the extent of mountainous terrain in a country, which is a very

salient factor explaining the opportunity for rebellion.

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Additionally, we control for regime type. We use the Polity IV score of democracy (Polity2),

which ranges from -10 to 10 and create a system of discrete variables measuring democracy

(democracy = 1 if Polity > 6, 0 if not), semi-democracy (semi-democracy=1 if Polity >-6<7, 0

if not), and autocracy (autocracy = 1 if Polity <-6, 0 if not) (Gurr & Jaggers, 1995). We leave

out semi-democracies as the reference category.

The two indicators of repression come in the form of a 9-point scale (CIRI) and a 5-point

scale (PTS). The CIRI data measure rights, thus we invert the index so that it now measures

the degree of repression. It is generally acceptable to use OLS on the CIRI scale because it is

relatively normally distributed, but mostly because the scale is hard to interpret due to the

nature of the way in which information is aggregated. In other words, what the cut-off points

indicate substantively are not easily distinguishable. The PTS has the following cut-offs:

1 if countries are under secure rule of law, political imprisonment and torture are rare, and the political murders are extremely rare; 2 if imprisonment for non-violent political activities is limited, torture and beating are exceptional, and political murder rare; 3 if political imprisonment is extensive, execution and political murder may be common, and detention for political views are acceptable; 4 if the practices of level 3 are expanded to a larger segment of population, murders and disappearances are common, but terror affects primarily those who interest themselves in political practices and ideas 5 if level of terror are population wide, and decision makers do not limit themselves by which they pursue private and ideological goals

We estimate the PTS using ordered probit regression because of the relative ease of

interpreting the cut-off points. The control variables that go into the repression models are

quite similar to the civil war models. Per capita income and political democracy are strong

predictors of lower repression (Davenport & Armstrong, 2004; de Soysa & Nordås, 2007;

Landman, 2005; Poe, Tate & Keith, 1999), while country size (Landman, 2005), oil wealth

(de Soysa & Binningsbø, 2009; Kisangani & Nafziger, 2007), and the incidence of civil war

increase political repression (Poe, Tate & Keith, 1999). Surprisingly, unlike the civil war

literature, most empirical studies find that ethnic fractionalization reduces political repression

(de Soysa, 2009; Lee et al., 2004). Given arguments about the detrimental effects of social

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fractionalization on good economic policymaking, we enter this term in the model (Easterly &

Levine, 1997). Additionally, others find that ‘socialist’ governments and British legal systems

reduce repression (Poe, Tate & Keith, 1999). The addition of these variables is important

since any effect of capitalism might in fact be an effect of a British legal heritage, or the fact

that a ‘socialist’ heritage is absent in the model. It is also important to estimate the effects of

the structure of the economy from the growth rate of income. We enter annual per capita

economic growth in the model (World Bank, 2007). Additionally, we enter a term for the

history of peace, or a count variable of the years of peace since 1946, and in order to account

for any trending in our measures over time, we enter a year dummies. In other words, if

human rights and capitalism both trend upwards over time, this is accounted separately.

There are several thorny estimating issues to address with pooled time-series, cross-section

data (TSCS) because of complicated correlation structures between and within units (Beck &

Katz, 1995). Concerning OLS estimations, we use the Beck-Katz panel corrected standard

errors with an AR1 correction for autocorrelation. When using the ordered probit estimations,

we use the cluster option in STATA, which computes Huber-White corrected robust standard

errors with the assumption that observations are independent across units but non-independent

within. These robust standard errors are robust to heteroscedasticity and serial correlation

(Wiggins, 1999). We also test our models of repression with and without lagged dependent

variables.

Results

The estimations of economic freedom’s effect on civil war are reported in table 2.9

Table 2 About Here

In column 1, we run our baseline model of conflict for the entire post-war period. The results

are a perfect replication of those reported by Collier, Hoeffler, and Rohner (2009), Fearon and

Laitin (2003) and many others using similar data. Per capita income strongly predicts peace,

while oil wealth, mountainous terrain, and large populations, mostly interpreted as factors

associated with the opportunity for rebellion, predict civil war positively. Moreover, we find

9 The data and do files that generated all the reported results will be made available upon publication.

16

support for arguments about ethnic polarization and conflict because of a clear curvilinear

effect for ethnic fractionalization. Ethnic fractionalization in linear form only is positive and

significant on conflict as several others have recently reported (Collier, Hoeffler & Rohner,

2009; Schneider & Wiesehomeier, 2008). Also, there is some evidence for higher risk of

conflict among semi-democracies as autocracies are negatively and significantly associated

with the onset of civil war while full democracy also lowers the risk. These results are

generally the same when we test this baseline model for the period for which we have the

economic freedom variable, which is 1970 onwards, albeit in weaker form for some of the

variables. Nevertheless, when we test the same sample of countries and time period reflecting

the availability of economic freedom, the results uphold.

In column 2, we enter economic freedom to the baseline model. As seen there, the greater the

capitalistic tendencies in an economy, the lower the chance of an onset of civil war. This

result is statistically highly significant. Interestingly, when we enter economic freedom, per

capita income is no longer statistically significant. While the bi-variate correlation between

income and economic freedom is high, income explains roughly 45% of the variance of

economic freedom. A test for variance inflation (VIF) did not show values that are

problematic for these variables or the model as a whole. As several others have reported,

income’s effect of peace is fragile when quality of institutions are accounted (Fjelde & De

Soysa, 2009; Mousseau & Mousseau, 2008). Given the heavy focus on poverty and state

capacity, future research should probe the issue further. The result is not due to a sample

effect since income is significant if we drop economic freedom for the same set of

observations. Columns 3, 4, 5, and 6 all show that economic freedom predicts peace

consistently and robustly despite changes in sample size and time periods tested. In column 3,

CIM’s effect on the risk of civil war is also negative, net of the degree of economic freedom,

which is interesting. Thus, both measures capture different aspects of civil war risk. None of

the other institutional variables are able to trump the effects of economic freedom. These

estimations suggest clearly that rather than income, or the level of development, regardless of

regime type; i.e. democracy, and regardless of good governance in terms of ‘fairness,’ a good

climate for economic productivity and entrepreneurialism matters. Notice that when

bureaucratic quality is controlled (column 5), democracy’s effect on the risk of a civil war

onset turns positive and statistically significant at the 10% level.

17

But, how much might economic freedom matter for the risk of civil war. We compute

substantive effects by examining marginal effects. First, we compute a baseline risk of

conflict, holding all variables at their mean values. After that we re-compute the change in

this baseline risk after changing economic freedom by the mean value plus a standard

deviation, holding all of the controls at their mean values. The baseline risk for the model

with all variables at their mean values is 0.0155, and the re-computation’s prediction dropped

to 0.0104, a decrease of 33%. Interestingly, doing the same exercise with the log of per capita

income yields roughly the same substantive change in the baseline prediction.

We conduct a number of robustness checks on the basic model with economic freedom in the

estimation (column 2) to check its sensitivity to testing method and change in the parameters

of the model. First, we drop the variable measuring the brevity of peace and simply follow the

Fearon and Laitin (2003) method of testing onset with a lagged civil war variable. The

existence of civil war will surely bias the coding of economic freedom. Using this alternative

specification does not alter the basic results in the slightest. Next, we test onsets with a 5- and

8-year year hiatus in fighting rather than the 2-year hiatus. The results are almost identical.

We added the growth of per capita income, which is thought to affect civil war onset, but the

effect of our main variable of interest was unchanged. The growth rate of income was

statistically not significant. We also drop various insignificant variables, but none of these

specification changes affected economic freedom’s result on the risk of a civil war onset.

Lagging the index of economic freedom by 1, 2, 3, 4, and five years yielded very similar

results.

In table 3, we turn to the issue of state repression of rights of people regardless of whether or

not civil war is ongoing. States could suppress dissent and prevent large-scale violent

challenges.

Table 3 About Here

As seen in column 1, economic freedom shows a statistically significant negative effect on

state violations of physical integrity rights of citizens. This effect holds across the models

presented in the table, including when we introduce a lagged-dependent variable in column 5.

Most of the results of the controls confirm previous findings. Income per capita has a strong

negative effect on repression, as does democracy, ethnic fractionalization, and the time since

18

the last civil war. Population size, oil wealth, and ongoing civil war, on the other hand show

positive effects on repression. These findings are highly consistent with those reported

previously. While the British and Socialist legal systems show negative effects on repression,

results consistent with those reported previously, they are fragile. Interestingly, in column 2,

when we enter CIM together with economic freedom, CIM’s effect is positive and significant.

This result may suggest that despite the fact that people (capitalists) may make contracts

between themselves in some settings, which may make up a large portion of the total capital

stock, states may still face dissent and need to repress if they are forced to play a protective

role. In any case, the rest of our institutional variables are strongly negatively related to

repression. Despite this, the net effect of economic freedom robustly relates to reduced

political repression.

In table 4 we report the tests of the Political Terror Scale.

Table 4 About Here

The basic results are the same as above except that oil exporting countries are now

statistically not significant. Interestingly, when we run the same model as in column 1 without

economic freedom, oil exporter becomes positive on political terror and statistically

significant below the 1% level (not shown). This result may suggest that some of the

‘resource curse’ effects on political dissent may work through the heavy state involvement in

the economy and distorted economic policies.10 Unlike the robust effects using the CIRI scale,

in column 3, economic freedom misses statistical significance when we use the control of

corruption in the model. Nevertheless, the effect of economic freedom is mostly negative and

highly significant and substantive impacts rather large, even when including a lagged

dependent variable (not shown).

In order to assess substantive impacts, we examine marginal effects by computing the

predicted probability of the model with all variables held at their mean values for the outcome

level 4 on the PTS scale (see definition above). We then re-compute this probability with

economic freedom held at the mean plus a standard deviation while the controls remain at

their means. The baseline prediction changes by 53% for economic freedom, but only 32%

10 See de Soysa and Binningsbø (2009) for a fuller treatment of this issue.

19

when we do the same exercise with per capita income. In fact, the impact of going from the

mean value of democracy in the sample to full democracy (1), the change is 58%, only

slightly greater than that of economic freedom. The largest substantive impact on political

repression as one can well imagine is the incidence of civil war. Going from a world of mean

civil war to all civil wars (1) increases the baseline prediction by 343%, roughly 6.5 times the

effect of a standard deviation increase of economic freedom.

Recall the Marxist arguments above about why democracy is impossible under conditions of

capitalism. Since states are bound to be structurally dependent on capital and thereby might be

‘captured’ by capitalists, reform is impossible. Violent dissent is one way in which to

overthrow capitalist states to bring about social harmony. We are now able to test how the

interaction between democracy and economic freedom matters for repression. We already

know that democracy and economic freedom have independent negative effects on repression.

Thus, the interactive effects will tell us how democracy’s effect on repression might be

conditional on the level of economic freedom and vice versa. We use the basic model in table

4, column 1 and enter an interactive term between the dummy variable for democracy and the

measure of economic freedom. Table 5 displays the results:

Table 5 About Here

We report just the variables of interest. As seen there, the interaction between democracy and

economic freedom remains negative and significant on the level of political terror (p<0.008),

as does the independent term for economic freedom (p<0.01), which suggests that economic

freedom predicts lower repression at zero democracy. Notice, however, that the independent

term for democracy is now positive and almost statistically significant at the 10% level

(p<0.12). The three terms are highly significant, jointly (p <0.00001). The conditional effects

plot (see figure I) shows the relationship clearly. Democracy’s effects on lowering repression

are accelerated, not mitigated, as the level of economic freedom increases.

Figure I About Here

Conclusion

20

Skeptics of globalization and neo-Marxist theories of democracy and social justice fear the

spread of capitalistic values. Apparently, the conditions favourable to capital will drive a ‘race

to the bottom’ where weakened states capitulate to the interests of capital. The empowerment

of commercial interests, it is argued, will erode the autonomy of states to act in the best

interests of the collective. Liberals, from the time of Adam Smith and other classical writers

see the sprit of commercialism as a source of good. Most previous studies have tried to

address the question of internal peace and harmony from the point of view of Marxist ideas of

class conflict, often using income inequality in empirical work to capture such dynamics. We

use a measure of capitalistic economic policies, the index of economic freedom, directly in

models of civil war onset and political repression of human rights to address these questions.

Our results taken together show robust evidence supporting liberal positions. States that have

an economic system favoring private commercial interests and thereby lower involvement of

the state in regulation and other economic activity show a lower risk of civil war and lower

propensity for repression of human rights. We also demonstrate that democracy’s effect on

lower repression is not adversely conditioned by higher economic freedom, but the contrary

seems to be true. Democracies with low economic rights for private individuals demonstrate a

positive effect on political repression. Our results are robust to several different testing

procedures, data, and alternative specifications.

21

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Table 1. Bi-variate correlations between economic freedom and institutional quality Econ

Free Leg.Sec&PRP CIM Bur.Qualit

y No Corruption

Econ. Freedom 1 Leg. security & PRP

0.70 1

CIM 0.64 0.56 1 Bur.Quality 0.59 0.72 0.57 1 No Corruption 0.45 0.67 0.40 0.64 1

28

Table 2.

Logit regressions of economic freedom on the onset of civil war

(1) (2) (3) (4) (5) (6) VARIABLES onset2 onset2 onset2 onset2 onset2 onset2 onset2_decay 0.186 0.0883 0.0870 0.333 0.508 0.398 (0.208) (0.291) (0.270) (0.373) (0.409) (0.376) Ln income/pc -0.429*** -0.386* -0.0589 -0.436* -0.398 -0.393 (0.0804) (0.206) (0.212) (0.229) (0.301) (0.283) Ln population 0.264*** 0.494*** 0.509*** 0.466*** 0.548*** 0.534*** (0.0619) (0.100) (0.0993) (0.108) (0.125) (0.115) Oil exporter 0.650*** 0.217 0.123 0.166 0.381 0.327 (0.202) (0.309) (0.330) (0.401) (0.428) (0.410) Ln Mountains 0.115** 0.00838 0.0234 -0.0132 -0.156 -0.132 (0.0549) (0.0978) (0.104) (0.105) (0.127) (0.127) Ethnic fraction 3.918*** 8.345*** 6.115*** 8.093*** 9.913*** 9.949*** (1.317) (2.154) (1.937) (2.504) (2.926) (2.967) Eth. Fraction2 -3.252** -7.633*** -5.212** -7.232*** -9.194*** -9.240*** (1.536) (2.375) (2.050) (2.671) (3.170) (3.183) democracy -0.409* 0.0746 -0.0701 0.266 0.399 0.361 (0.236) (0.279) (0.291) (0.309) (0.332) (0.344) autocracy -0.616*** -0.392 -0.496 -0.387 -0.334 -0.346 (0.187) (0.330) (0.310) (0.384) (0.494) (0.473) Econ. freedom -0.337*** -0.262** -0.343** -0.264** -0.316** (0.106) (0.106) (0.153) (0.125) (0.125) CIM -2.759*** (1.037) LSPR 0.0525 (0.131) BQ -0.162 (0.162) No Corruption -0.181 (0.141) Constant -3.448*** -5.034*** -5.728*** -4.646** -5.811** -5.205** (0.809) (1.861) (1.844) (1.955) (2.345) (2.172) Observations 6777 3150 2650 2387 1943 2003 R-squared .09 .13 .12 .13. .16 .16 # onsets 222 95 88 76 62 64 % onsets of total 3.3 3.0 3.3 3.2 3.2 3.2

*** p<0.01, ** p<0.05, * p<0.10 Robust standard errors in parentheses

CIM = Contract Intensive Money LSPR = Legal Security and Property Rights (Fraser Institute) BQ = Bureaucratic Quality (ICRG) No corruption = control of corruption (ICRG)

29

Table 3. PCSE Regressions of Economic Freedom & State Repression with & without lagged dependent variable

(1) (2) (3) (4) (5) (6) VARIABLES CIRI CIRI CIRI CIRI CIRI CIRI repression repression repression repression repression repression Ln income/pc -0.307*** -0.319*** -0.0856 -0.255*** -0.308*** -0.124*** (0.0660) (0.0720) (0.0654) (0.0704) (0.0621) (0.0333) Econ. growth -0.00836 -0.00764 -0.0101 -0.0178** -0.0166** -0.00851 (0.00612) (0.00615) (0.00666) (0.00763) (0.00784) (0.00585) democracy -0.744*** -0.722*** -0.653*** -0.669*** -0.598*** -0.314*** (0.117) (0.115) (0.125) (0.130) (0.124) (0.0630) Ln population 0.445*** 0.470*** 0.471*** 0.487*** 0.459*** 0.148*** (0.0261) (0.0284) (0.0246) (0.0297) (0.0289) (0.0205) Oil exporter 0.451*** 0.379*** 0.338*** 0.484*** 0.429*** 0.188*** (0.117) (0.122) (0.121) (0.126) (0.123) (0.0613) Britsh legal syst. -0.0874 -0.348*** -0.0301 0.00348 -0.0321 0.0226 (0.106) (0.128) (0.106) (0.109) (0.107) (0.0452) Socialist legal syst. -0.404** -0.553*** -0.296** -0.558*** -0.284 -0.127 (0.163) (0.193) (0.138) (0.149) (0.180) (0.0844) Civil war 1.426*** 1.410*** 1.376*** 1.452*** 1.457*** 0.847*** (0.121) (0.126) (0.122) (0.147) (0.142) (0.100) Civil peace yrs -0.0273*** -0.0286*** -0.0183*** -0.0236*** -0.0236*** -0.00446** (0.00307) (0.00328) (0.00320) (0.00342) (0.00330) (0.00173) Ethnic fraction. -0.841*** -0.677*** -0.518** -0.766*** -0.801*** -0.283*** (0.220) (0.219) (0.218) (0.251) (0.248) (0.110) Year 0.0597*** 0.0585*** 0.0515*** 0.0474*** 0.0371*** 0.0191*** (0.0116) (0.0118) (0.0128) (0.0147) (0.0142) (0.00719) Econ. Freedom -0.365*** -0.390*** -0.145** -0.304*** -0.280*** -0.106*** (0.0628) (0.0617) (0.0702) (0.0625) (0.0624) (0.0344) CIM 1.380** (0.537) LSPR -0.376*** (0.0557) BQ -0.193*** (0.0664) No corruption -0.177*** (0.0478) Lagged repression -0.651*** (0.0374) Constant -114.3*** -112.9*** -99.75*** -90.64*** -69.46** -31.31** (23.07) (23.51) (25.46) (29.22) (28.44) (14.39) Observations 2395 2078 2219 1871 1951 2296 # countries 112 100 109 100 103 112 R-squared 0.401 0.394 0.432 0.426 0.426 0.796

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.10

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Table 4. Ordered probit regressions of economic freedom and political terror (1) (2) (3) (4) (5) PTS PTS PTS PTS PTS Ln income/pc -0.289 -0.270 -0.104 -0.210 -0.236 (3.11)*** (2.63)*** (1.13) (1.83)* (2.29)** Econ. growth -0.014 -0.012 -0.010 -0.019 -0.022 (1.98)** (1.66)* (1.49) (2.10)** (2.44)** democracy -0.732 -0.656 -0.688 -0.623 -0.542 (5.47)*** (4.84)*** (5.01)*** (4.54)*** (4.07)*** Ln population 0.248 0.262 0.294 0.292 0.269 (5.21)*** (4.93)*** (5.90)*** (5.19)*** (4.95)*** Oil exporter 0.248 0.176 0.142 0.271 0.190 (1.45) (1.03) (0.90) (1.47) (1.06) Britsh legal -0.027 -0.112 0.075 0.115 0.081 (0.16) (0.61) (0.44) (0.61) (0.44) Socialist legal -0.300 -0.437 -0.096 -0.386 -0.221 (1.56) (2.26)** (0.44) (1.68)* (1.01) Civil war 1.168 1.152 1.065 1.235 1.248 (7.39)*** (7.21)*** (7.02)*** (6.78)*** (7.21)*** Civil peace yrs -0.018 -0.016 -0.011 -0.014 -0.013 (3.75)*** (3.16)*** (2.52)** (2.73)*** (2.74)*** Ethnic fraction. -0.678 -0.619 -0.501 -0.609 -0.590 (2.05)** (1.87)* (1.51) (1.54) (1.55) Econ. Freedom -0.287 -0.287 -0.102 -0.304 -0.297 (3.31)*** (3.19)*** (1.15) (3.24)*** (3.13)*** CIM 0.424 (0.82) LSPR -0.366 (6.34)*** BQ -0.170 (2.20)** No corruption -0.179 (2.48)** Observations 2390 2062 2229 1828 1895 # Countries 110 98 107 99 102 P< Chi2 .00001 .00001 .00001 .00001 .00001 Robust z-statistics in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

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Table 5.

civpeaceyrs -.0155056 .0045185 -3.43 0.001 -.0243618 -.0066494 civilwar 1.176742 .1535995 7.66 0.000 .8756929 1.477792 ethfrac -.6464245 .3220902 -2.01 0.045 -1.27771 -.0151394legal_soci~t -.3902966 .188207 -2.07 0.038 -.7591756 -.0214177 legal_brit -.0336759 .1664375 -0.20 0.840 -.3598874 .2925357 lnpop .2582987 .0439174 5.88 0.000 .1722222 .3443753 oil .1954696 .1596247 1.22 0.221 -.1173891 .5083283 democxef -.3216473 .1228761 -2.62 0.009 -.5624801 -.0808146 ief -.1726024 .0839377 -2.06 0.040 -.3371173 -.0080875 democ_dummy 1.139697 .7284022 1.56 0.118 -.2879449 2.567339 gdppcgrw -.0131588 .0069913 -1.88 0.060 -.0268615 .0005438 lnincome -.2864192 .0950291 -3.01 0.003 -.4726727 -.1001656 statedep Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust (Std. Err. adjusted for 110 clusters in cow)

Log pseudolikelihood = -2446.9083 Pseudo R2 = 0.3201 Prob > chi2 = 0.0000 Wald chi2(36) = 419.11Ordered probit regression Number of obs = 2443

Figure I.

-4-3

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0ris

k of

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2 4 6 8 10economic freedom

democracy x Econ.Freedom Econ.Freedom at democ=0