Property Rights, Growth, and Conflict*

Terra Lawson-Remer

The New School Graduate Program in International Affairs

lawsonrt@newschool.edu

*The author is grateful for helpful comments from Dalton Conley, Kevin Davis, William Easterly, Augustin Fosu, Daniel Klerman, Nathan Nunn, Nicola Persico, Sam Popkin, and David Trubek; for research support from the United Nations World Institute for Development Economics Research (UNU-WIDER); and for capable research assistance from Lauren Schmitz and Cameron Brinitzer.

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Abstract: Property insecurity of non-elites can be compatible with or even enhance economic growth, but also encourages conflict—which can undermine long-run growth and economic development. Using a new set of indicators that measure the property insecurity of marginalized ethno-cultural minority groups, this article demonstrates that the severity of property insecurity for the worst-off group in a country is strongly associated with the onset of armed conflict, and once civil war is controlled for, property insecurity for marginalized minorities corresponds with higher growth rates. Economic growth can occur when the property rights of elites are secure but marginalized minorities face high a risk of expropriation, as land may be reallocated into the hands of investors with skills and access to capital. However, the potentially growth enhancing effect of forced displacement and resettlement is reduced because the property insecurity of minorities also increases the likelihood of armed conflict.

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1 Introduction

Perhaps you have heard of us. We are Mexican, mostly indigenous, and we took up arms on January 1, 1994 demanding a voice, a face and a name for the forgotten of the earth. Since then, the Mexican government has made war on us, pursues and harasses us seeking our death, our disappearance and our absolute silence. The reason? These lands are rich with oil, uranium and precious lumber. The government wants them for the great transnational companies. We want them for all Mexicans. The government sees our lands as a business. We see our history written in these lands. In order to defend our right (and that of all Mexicans) to live with liberty, democracy, justice and dignity we became an army and took on a name, a voice and face.

– Subcomandante Marcos, Juana Ponce de León, April 1999, Letter to Mumia Abu Jamal

The conventional wisdom has long held secure private property rights to be a critical

ingredient of economic growth (North 1990; Smith 1776; Williamson 1985; Acemoglu et al.

2001; Belsey and Ghatak 2009; Posner 1998). Yet, historically, economic development has

often involved the expropriation of land and resources from marginalized minorities, and

the reallocation of these resources into the hands of more politically powerful

constituencies and investors with access to capital (Thompson 1975, Allen 1982). At the

same time, insecure property rights can foster anti-government grievances, motivating

dispossessed groups to rebel and increasing the likelihood of armed conflict.

Chiapas provides the rest of Mexico with essential resources, including oil, timber, cattle,

corn, sugar, coffee, and beans (Collier and Quaratiello 1999). The Zapatista uprising in

Chiapas throughout the 1990’s may be traced in part to the accelerating loss of communal

land tenure rights and displacement of indigenous groups by more politically connected

local caudillos, who were seeking to exploit these valuable resources commercially (Collier

and Quaratiello 1999; Harvey 2005, 1998).

The complex relationship between property insecurity, growth and conflict is also readily

apparent in the violent separatist conflict that engulfed Bougainville, Papua New Guinea

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(PNG) from 1988-1997. Traditionally, land in Bougainville was collectively owned through

matrilineal clan lineages, with use rights shared by all members, and ownership inalienable

and nontransferable (Regan 2003). Copper was discovered in Bougainville in the mid-

1960s, and the PNG government claimed the minerals—selling the Panguna copper mining

concession to Bougainville Copper Ltd., a subsidiary of Rio Tinto Ltd.. The government

forcibly relocated entire villages, and excluded Bougainville from the revenue-sharing

agreements it negotiated with Rio Tinto. The prioritization of the state’s and the

corporation’s property rights at the expense of the Bougainvilleans’ initially generated high

economic returns: from 1972 to 1989 the Panguna mine contributed 16% of Papua New

Guinea’s GDP and 44% of its exports (Regan 2003).

However, in 1988, the convergence of grievances regarding the effects of mining, the

inequitable allocation of revenues, and long-standing political exclusion provoked a group

of marginalized Bougainvilleans to attack a number of Rio Tinto’s buildings, destroying the

mine’s power supply. Seeing the economic lifeline of the country as under an existential

threat, and believing a strong preemptive response would deter further opposition, the

PNG government responded with a military crackdown. The indiscriminate violence

polarized the Bougainvillean population, fueling a widely supported ethno-nationalist

rebellion with separatist aims. The mine was closed in 1989 due to the uprising and the

conflict intensified through the 1990s. By 1996 between 15,000 and 20,000 civilians and

combatants had been killed in the conflict, and another 60,000 people displaced (Regan,

2003). The war also resulted in the cessation of all economic activity: roughly 10,000

mining jobs and 10,000 more in the cocoa and copra sectors were lost, and significant

mining and transportation infrastructure destroyed. The economic impact of the mine’s

closure, the direct costs of the conflict, and the indirect costs of lost growth opportunities

incited a severe fiscal crisis in PNG by the mid-1990s (Regan 2003). In Bougainville the

growth enhancing prioritization of elites’ property rights were ultimately undermined by

violent conflict.

This suggests that economic growth can occur when the property rights of the majority are

secure but marginalized minorities face a high risk of expropriation—because land is

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reallocated into the hands of (a) more politically powerful constituencies who use their

influence to support aggregate growth-enhancing policies, and (b) investors with access to

capital and other complementary productive inputs (Lawson-Remer 2012). However, the

potentially growth enhancing effect of forced displacement and resettlement is mitigated

because the property insecurity of minorities is also correlated with conflict, which reduces

growth. Succinctly stated, property insecurity of non-elites can be compatible with or even

enhance economic growth, but also encourages conflict—which can undermine long-run

growth and economic development.

This article applies a new set of cross-national indicators that measure the property

insecurity of marginalized minority groups to examine the complex relationship between

property rights, growth, and conflict. The empirical findings presented here demonstrate

that severe property insecurity for the worst-off group in a country is strongly related to

the likelihood of armed conflict. However, controlling for civil war, the property insecurity

of marginalized minority groups is actually associated with higher growth rates. In net,

property insecurity among vulnerable groups allows for growth-enhancing investment and

accumulation, and is compatible with the political accountability of elites to other elites or

the majority, but can also jeopardize growth by enhancing prospects of conflict.

Multiple factors influence when and whether property insecurity for marginalized groups

will generate armed resistance, and when and whether simmering low intensity conflict

rises to the level of civil war. The empirical results here indicate a strong relationship

between the severity of property insecurity and the likelihood of civil war—suggesting, in

short, that the screws on the property rights of marginalized minorities can be turned only

up to a certain point, after which the pressure incites violence and becomes

counterproductive. However, the relationship between property insecurity and armed

resistance indicates a statistical likelihood and is by no means automatic; there are many

cases in which severe property insecurity, such as that seen by the Native Americans

during U.S. westward expansion, has been highly growth enhancing and has not led to civil

war. And given that there is no direct relationship between property insecurity and long-

run growth until civil war is taken into account, the empirical findings suggest that the

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growth-enhancing and conflict-inciting pathways cancel each other out, leading to a zero

net effect of property insecurity on growth in aggregate. Although the property insecurity of

marginalized groups can impact growth through these two pathways, the net effect of property

insecurity in any given case is inevitably context specific and determined by a host of variables.

2 Background 2.1 Literature Review

There is an extraordinarily large and diverse body of research regarding the relationship

between property rights and economic development, with the vast majority of this work

arguing that secure property rights are a necessary prerequisite for economic

development.

At a micro level, secure property rights are thought to generate economic growth by

incentivizing efficient levels of investment and ensuring that a resource is neither over nor

under-utilized (Demsetz 1967; Hardin 1968; Besley and Ghatak 2009; Field and Torero

2006; Udry and Goldstein 2005; Posner 1998); generating efficiency gains by reducing

transaction costs in exchanges between parties and allowing reallocation of resources to

more efficient users; (Coase 1960; Belsey and Ghatak 2009) and facilitating access to credit

and the conversion of dead assets into investment capital (De Soto 2003; Field 2005). At a

macro level, secure private property rights—as an essential pillar of individual liberty—are

thought to engender political accountability, which in turn leads to economic policies that

are broadly growth-enhancing rather than narrowly beneficial to only powerful, rent-

seeking elites (Hayek 1976; Engerman and Sokoloff 1997, 2002, 2005; Acemoglu et al.

2004; Acemoglu 2003).

However, unstated in these theories is that it fundamentally matters whose property rights

are secure. From a neoclassical and new institutional “micro” perspective, only secure

property rights for those with complementary productive inputs—skills, knowledge,

capital, etc.—leads to economic growth (Lawson-Remer 2012). And from a political

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economy and new institutional “macro” viewpoint, only secure property rights for those

who will use their political voice to agitate for growth enhancing economic policies are

important for development. In other words, aggregate economic growth can involve the

expropriation of land and resources from marginalized minorities and the reallocation of

these resources into the hands of more politically powerful constituencies and more

efficient investors.

Over the past fifteen years, cross-country econometric evidence has been used by a wide

range of researchers to support the theoretical claim that ‘good institutions’, particularly

strong private property rights and protection from expropriation, lead to economic growth

(Acemoglu et al. 2001, 2002; Kaufmann et al. 1999, 2002; Knack and Keefer 1995; Rodrik et

al. 2004; Glaeser et al. 2004). Yet this recent cross-country property rights research

generally relies on indicators that efface the heterogeneity in property rights enjoyment

within countries (Lawson-Remer 2012). A one-dimensional conception of property rights

ignores the significant variation in risk of expropriation faced by different ethnic, cultural,

and religious groups in the same country. Because political power determines the scope,

allocation, and enforcement of property rights, (Libecap 1989; Alston et al. 2009; Wyman

2005). property rights insecurity for less politically or economically powerful minority

groups often exists alongside secure property rights for those with the ability to influence

the allocation and enforcement of property rights entitlements, including, in different

contexts, majority groups, foreign investors, and domestic elites.

The property insecurity of less politically or economically powerful marginalized groups,

which may be growth-enhancing in some contexts, might also precipitate armed conflict

and decrease growth indirectly. A robust body of research has demonstrated that civil war

reduces economic growth by destroying human and physical capital, disrupting economic

activity, diverting public expenditures to unproductive military outlays, and causing capital

flight. The five-year average growth rate is 5% lower, and the thirty-five year average rate

is 30% lower, in countries that experience a civil war than those that do not (Murdoch and

Sandler 2002). The annual growth rate during civil war is reduced by 2.2% on average,

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while even once a war ends, 17% of GDP continues to be lost to increased military spending

over a ten year period (Collier and Hoeffler, 1998).

In recent years a significant body of work has emerged that utilizes cross-country

quantitative data to examine the factors that drive the onset and incidence of civil wars

(Collier and Hoeffler 1998, 2002, 2004; Collier and Rohner 2008; Elbadawi and Sambanis,

2002; Fearon and Laitin, 2003; Fearon 2005; Humphreys, 2005; Ross 2004; Reynal-Querol

2002, 2005; Miguel, Satyanath, and Sergenti, 2004; Djankov and Reynal-Querol, 2007;

Humphreys 2005).

A few stylized facts emerge from this body of research. There is fairly robust evidence that

low per capita income and low growth increase the likelihood of civil war (Collier and

Hoeffler 1998, 2002, 2004; Fearon and Laitin 2003; Miguel, Satyanath, and Sergenti, 2004).

The evidence is mixed regarding the role played by ethnic cleavages: some studies indicate

that high degrees of social fractionalization make civil war more likely (Reynal-Querol

2002; Montalvo and Reynal-Querol 2005), but other studies indicate that social

fractionalization, which includes both religious and ethnic cleavages, is statistically

uncorrelated with civil war (Fearon and Laitin 2003). Other research presents strong

evidence that it is ethnic dominance (where one group composes between 45% and 90% of

the population), not fractionalization per se, which makes civil war more likely (Collier and

Hoeffler 2002, 2004). The scholarship regarding the relationship between natural

resources and civil war has divergent findings, but four regularities: (1) oil dependence

appears to be linked to the initiation, but not the duration, of conflict; (2) “lootable

resources” such as gemstones, opium, coca, and cannabis do not seem to be linked to the

initiation of conflict, but they do seem to lengthen preexisting wars; (3) heavy reliance on

agricultural commodities seems to be uncorrelated with civil wars; and (4) the claim that

primary commodities broadly – including oil, non-fuel minerals, and agricultural goods –

are associated with the onset of civil war does not appear to be robust (Ross 2004).

Additionally, large population size, mountainous terrain, and a high proportion of young

males between 15 and 29 are associated with a higher likelihood of civil war (Fearon and

Laitin 2003; Collier and Hoeffler 1998, 2002, 2004; Collier and Rohner 2008). Examined

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through the lens of institutions, strongly secure property rights can be viewed as a proxy

for the strength of the state government, because strong states, which are more capable of

providing effective protection against expropriation by private actors, may also be more

capable of detecting dissent and deterring rebellion (Djankov and Reynal-Querol 2007).

Most relevant to the present inquiry, horizontal inequality—which reflects the difference in

income and wealth between ethnic, religious, and cultural groups—appears to generate

conflict (Stewart 2003), although vertical inequality does not.

The relative importance of grievances versus greed or feasibility in increasing the

likelihood of civil war and armed conflict remains a robust debate (Collier and Hoeffler

1998, 2002, 2004; Collier and Rohner 2008; Elbadawi and Sambanis, 2002; Fearon and

Laitin, 2003; Fearon 2005; Humphreys, 2005; Ross 2004; Reynal-Querol 2002, 2005;

Miguel, Satyanath, and Sergenti, 2004; Djankov and Reynal-Querol, 2007). On the one hand

a body of research contends that grievances are ubiquitous, and armed conflict is

constrained only by the feasibility of mounting an insurrection (Collier and Hoeffler 1998,

2002, 2004). On the other hand a diverse body of work identifies economic, political,

ethnic, or religious grievances as the underlying determinants of war and conflict

(Elbadawi and Sambanis 2002, Ballentine and Sherman 2003, Switzer 2001).

Yet this research remains largely unconvincing because the objective indicators that have

been used as proxies to measure feasibility or greed could actually represent greed,

feasibility, or grievances. For example, low levels of per capita GDP and low or negative

growth rates—both which have been used as proxies for greed and feasibility (Collier and

Hoeffler 1998, 2002, 2004) may make armed resistance easier by reducing the cost of

recruiting rebel soldiers, but economic deprivation may also be a source of grievances,

particularly when individuals perceive economic woes as partially the fault of the

government. Likewise, natural resource wealth may make civil war more likely by

motivating rebel leaders to fight for power in order to gain control of the resource wealth,

eroding state governance capacity, or providing a source of rebel group financing (Collier

and Hoeffler 1998, 2002, 2004). At the same time however, extensive natural resource

extraction might generate grievances (Switzer 2001, Klare 2001), even if these grievances

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cannot be objectively measured in cross-country comparable data. For example, the

extraction process can pollute the lands of local residents, exacerbate horizontal inequality,

increase perceptions of social exclusion, and require the forced resettlement of local

communities (Extractive Industries Review 2003).

Research has largely neglected the significant role that property rights insecurity—

generated by displacement from land, forced resettlement, and resettlement by policy—

can play in provoking conflict and civil war. Property rights insecurity may be a source of

anti-government grievances, so the property insecurity index developed and applied here

can shed light on the relative importance of greed, feasibility, and different types of

grievances in precipitating armed conflict.

Numerous case studies suggest a connection between property insecurity and armed

conflict. Grievances by dispossessed indigenous communities towards the landed elite and

the state have plagued El Salvador, Guatemala, and Bolivia since the colonial era, and were

a primary cause of conflicts from the 1950’s to the 1980’s (Gleijeses 1992). Likewise, the

deadly civil war that engulfed Bougainville over the past three decades, and the low

intensity Chiapas conflict throughout the 1990’s, can be attributed in part to dispossession

of politically powerless property-holders by more-well connected elites.

The failure of the government to protect the property rights of some citizens, or

participation by the government in selective resource expropriation, can generate

grievances against the government by the group whose land or property is expropriated

(Ballentine and Sherman 2003)—motivating dispossessed groups to take up arms.

2.2 Measuring Security of Property Rights

2.2.1 Standard Measures of Property Security

Over the past three decades a virtual cottage industry in governance indicators has

emerged, including indices that that aim to measure countries’ level of property rights

security. This section examines two property rights indicators that have been widely

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influential: the International Country Risk Guide (ICRG), and the Heritage Foundation’s

property rights index—both of which are included as components in the World Bank’s

Worldwide Governance Indicators. These three indices have been widely used in cross-

country research as a proxy for “institutional quality” broadly, and for the security of

property rights specifically (Knack and Keefer 1995; Boschini et al. 2007; Djankov and

Reynol-Querol 2010; Mehlum et al. 2006; Kaufmann et al. 2009).

The ICRG was first created in 1980 by the editors of a weekly newsletter on international

finance and economics, with the goal of “meet[ing] the needs of clients for an in-depth and

exhaustively researched analysis of the potential risks to international business

operations” (Political Risk Services, n.d.). The primary users and consumers of the ICRG

ratings data are institutional investors, banks, multinational corporations, importers,

exporters, and foreign exchange traders (Political Risk Services, n.d.). Given that the

intended customers of the ICRG are capital investors and multinational corporations, the

information on expropriation risk is meant to reflect the risk posed to the enterprises of

the large and often multinational businesses that are purchasing the ICRG data, not the

property rights of marginalized ethno-cultural minority groups, who are clearly not

purchasing the ICRG data.

The Heritage Foundation scores “the degree to which a country’s laws protect private

property rights and the degree to which its government enforces those laws” (Heritage

Foundation 2009). The index is a subjective score, based on information gleaned from the

Economist Intelligence Unit, Country Commerce; U.S. Department of Commerce, Country

Commercial Guide; U.S. Department of State, Country Reports on Human Rights Practices;

and the U.S. Department of State, Investment Climate Statements. Once again, all these

sources, except for the U.S. State Department Reports, have as their primary audience large

commercial investors interested in assessing the investment risks posed to their business

ventures.

2.2.2 A New Index of Property Insecurity

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The Property Insecurity (PI) index is a composite measure of the property insecurity

experienced by minority groups in a country. The index is based on scores in three

dimensions: dispossession from land, forced internal resettlement, and internal

resettlement by policy. Data is drawn from the Minorities at Risk (MAR) database, which

assesses the political and economic exclusion of ethno-cultural minorities1 in every country

with a population of at least 500,000. Experts assign a numerical score indicating the

severity of exclusion to each group along an array of political, economic, social, and cultural

dimensions. Like the ICRG and Heritage Foundation indices, the Property Insecurity (PI)

Index measures the de facto, rather than de jure, protection from expropriation experienced

by ethno-cultural minority groups. The PI index detects state failure to protect the

property rights of minority groups from incursions by other (possibly more powerful and

influential) private actors, as well as direct state acts of expropriation. In contrast to other

frequently used measures of property rights security, the PI index directly measures the

security of property rights for marginalized groups. Countries that score well in terms of

strongly secure property rights in aggregate and a low risk of expropriation faced by

foreign investors and domestic elites often contain minority groups who suffer from

significant levels of land dispossession and forced resettlement (See Appendix).

There are three versions of the Property Insecurity Index. The first, Property Insecurity

(Weighted), is a sum of group property insecurities weighted by the group’s proportion of

the population. The second, Property Insecurity (Max), reflects the property insecurity of

the worst-off group in a country. The third, Property Insecurity (Mean) reflects the average

property insecurity score of minority groups within a country.

1 The Minorities at Risk (MAR) Project “monitors and analyzes the status and conflicts of politically-active

communal groups”. A “minority at risk” refers to “an ethnopolitical group (non-state communal group) that:

collectively suffers, or benefits from, systematic discriminatory treatment vis-à-vis other groups in a society; and/or

collectively mobilizes in defense or promotion of its self-defined interests.” The following four dichotomous

variables identify the factors present in the group which make it a minority at risk: (1) the group is subject to

discrimination at present; (2) the group is disadvantaged due to past discrimination; (3) the group is an advantaged

minority; and (4) the group supports political organizations advocating greater group rights. Groups are included in

the MAR database if the country in which they reside had a population greater than 500,000 and the group itself had

a population larger than 100,000 or 1 percent of the country population.

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Property Insecurity (Weighted) = Σ(GPROg)Pg (1)

Property Insecurity (Max) = Pworst (2)

Property Insecurity (mean) = Average(Pg) (3)

Where GPROg is the group’s proportion of the country’s total population and Pg =

(DMEVICTg + DMRESETg + DMRES g)/3 = Property Insecurity for Group g.

3 Empirical Results: Growth, Conflict, and Property Insecurity

3.1 Conflict: Data, Econometric Model, Results and Analysis

Although other recent studies have emphasized the role played by economic, ethnic, and

geographic factors in influencing the likelihood of armed conflict, the empirical findings

presented here demonstrate that the displacement and resettlement of minority groups—

an objective measure of anti-government grievances—is strongly correlated with the

likelihood of civil war. Controlling for income, growth rates, natural resource dependence,

social fractionalization, and ethnic dominance, the results here reveal that countries in

which minority groups have suffered severe levels of property insecurity are significantly

more likely to experience internal armed conflicts.

The baseline dataset is drawn from Collier and Hoeffler (2004), which creates country

periods based on five-year increments. There are 733 possible units of observation,

beginning 1980-1984 and ending 1995-1999. Due to missing data, the estimation sample

varies depending on the variables included in the model. To test robustness I also included

the same left and right-hand side variables in a specification with one-year country periods,

using interpolated values to mitigate the problems introduced by listwise deletion. I deal

with the potential of reverse causality by measuring the property insecurity of minority

groups at the start of the five-year period, rather than using the period average. The

dependent variable is a dummy variable indicating whether a war started during the time

period observed. This is based on the Correlates of War (COW) dataset. According to the

COW definition, a war exists when (a) there is organized military action that results in at

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least 1,000 battle deaths in a given year; (b) at least five percent of the deaths were

inflicted by the weaker party (to distinguish wars from genocides); and (c) the national

government at the time was involved. Countries in which a war was already ongoing at the

start of the period – so neither ‘war onset’ nor ‘at peace’ apply – are coded as missing.

The model utilizes the measure of property insecurity that is most sensitive to severe

property insecurity of ethno-cultural minority groups—Property Insecurity (Max)—as the

independent variable of interest. A country receives a high Property Insecurity (Max) score

when any minority group, regardless of size, experiences severe levels of displacement,

resettlement, or forced resettlement.

The outcome variable – civil war onset – is dichotomous, so a logit specification is used.

The probability of civil war onset in country i at time t is related to our independent

variables by a maximum log likelihood function, where Pit is a country’s property insecurity

score at the start of the period, Xit is a vector of controls, and conflict is a dummy variable

with a value of 1 if a civil war began in a country during the time period.

prob(conflictit = 1) = πit = 1/(1 + e−zi) (7)

zit = α + β1Pit + β2Xit (8)

πi = 1/(1 + e−(α + β1Pit + β2xit)) (9)

Controls are the main factors that have been shown in other studies to be associated with

the onset of civil war: logged per capita income, growth, natural resource abundance, time

passed since previous war, and population size. As growth is likely negatively impacted by

conflict (Miguel, Satyanath and Sergenti 2004) the growth measure on the righthand side is

time-lagged to reflect growth in the previous five-year period.

Natural resource abundance is measured in a few different ways. Following Collier and

Hoeffler (2002, 2004), Collier and Rohner (2008), and Sachs (1995), a measure for the

proportion of primary commodities exports in GDP (SXP) and the square of this term

(SXP2) is used. (Collier et al. 2009; Collier and Hoeffler 1998, 2002, 2004; Sachs and Warner

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1995). The square is included because there is some evidence that the likelihood of civil

war onset increases until an extreme level of dependence on resource extraction is

reached, at which point the probability of war begins to decrease (Collier and Hoeffler

2004, Collier and Rohner 2008). Fuel exports as a proportion of total exports and fuel

exports as proportion of GDP is also measured in order to more narrowly identify the effect

of oil, as primary commodity exports is a very broad measure of extractive industry

dependence. However, all the measures of natural resource abundance that contain GDP in

the denominator include information regarding the size and structure of the economy

(Ross 2008) so interpretation of the natural resource coefficients should be treated

cautiously.

Because the existence of property insecurity for ethno-political minorities may be related

to the number of minority groups within a country, social fractionalization is controlled for

to avoid omitted variable bias and to ensure that the index of property insecurity is not

simply proxying for ethnic or religious diversity. The statistical impact of ethnic and

religious cleavages on the risk of conflict has been controversial in the literature (Collier

and Hoeffler 1998, 2004; Collier and Rohner, 2008; Fearon and Laitin, 2003; Reynal-Querol

2002; Montalvo and Reynal-Querol 2005). The fractionalization index used here is

multiplicative, so religious and ethnic cleavages are both included as independent lines of

social fracture (Source: Collier and Hoeffler 2004). Likewise, property insecurity might be

correlated with ethnic dominance, and tensions driven by ethnic dominance may be driving

conflicts, making the association between property insecurity and conflict spurious. To

avoid this kind of omitted variable bias here, a dummy variable for whether the majority

ethnic group composes between 45% and 90% of the population is included as a control

(Source: Collier and Hoeffler 2004).

Findings, shown in Table 4, reveal that Property Insecurity (Max) is significantly and

positively related to civil war onset. These results are robust, and hold across all models.

In the core model, which uses five year country periods and interpolated values for the

property insecurity scores at the beginning of each period, the marginal effect of logged

Property Insecurity (Max) on the onset of civil war is .0487 at the means for all variables,

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corresponding to a 4.8% increase in the likelihood of civil war. Because the property

insecurity indicator is logged, a more revealing indicator of the relationship between

property insecurity and civil war onset is the average partial effect of (logged) property

insecurity on civil war onset, obtained by averaging all individual partial effects across the

sample. The average partial effect of Property Insecurity (Max) on the probability of civil

war is .107, indicating that a one unit change in the log of the Property Insecurity (Max)

indicator score increases the likelihood of civil war by 10.7%.

These results are significant at the 1% level in two specifications and the 5% level in three

specifications. Interestingly, neither social fractionalization nor ethnic dominance are

remotely significant in our model. Only the impacts of per capita income and months prior

peace are consistently substantial and significant in the 5 year framework, while the effect

of growth is consistently significant in the 1 year framework for specifications including

property insecurity but not those including Risk of Expropriation. Results were robust to

including various different measures of natural resource abundance. Interestingly,

including Risk of Expropriation on the right-hand side caused significance to disappear on

most other variables in both 1 and 5 year frameworks, including growth and per capita

income, indicating colinearity.

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18

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The property insecurity indicator distinguishes between institutional failures writ large,

perhaps better measured by the ICRG index, and government failures that

disproportionately impact specific minority groups.

This distinction matters critically from a policy perspective. For example, if the key factor

underlying civil war is weak central governments, rather than repressive or exclusionary

state institutions that expropriate land and resources from marginalized groups, or at least

fail to adequately protect these groups from expropriation by others, then strengthening

brutally autocratic regimes could be viewed as a viable strategy for preventing civil wars –

regardless of whether this increases repressive state practices. However, the findings here

suggest that anti-government grievances, specifically severe property insecurity for some

but not all groups, may make armed conflict more likely. From a policy standpoint, these

results suggest that attention should be paid to eliminating repressive and discriminatory

state practices, since the failure of government institutions to protect the property security

of members of politically marginalized ethno-political groups appears to increase the

likelihood of civil war. In other words, there is a strong tendency for an inconsistent

application of property rights to provoke conflict.

These findings are by no means conclusive, however, as possible problems of reverse

causality and omitted variables still exist. The key shortcoming of the model is that pre-

existing ethnic tensions and low intensity conflicts may be causing both the onset of civil

wars and the property insecurity of ethno-cultural minorities: ethnic tensions could drive

both high levels of property insecurity and increase the likelihood of civil war, rather than

property insecurity precipitating civil war directly. I deal with this possibility by

controlling for both ethnic dominance and religious and ethnic fractionalization, and

results remain highly positive and significant even with these controls included. However,

if ethnic tensions are uncorrelated with either ethnic dominance or fractionalization, then

the possibility of omitted variable bias remains. Attempting to identify another more

adequate proxy measure for ethnic tensions may be a fruitful line for further research.

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3.2 Growth and Conflict: Data, Econometric Model, Results and Analysis

Findings in 3.1 demonstrate that property insecurity is correlated with a higher likelihood

of armed conflict. Extensive previous research has found that civil war reduces economic

growth in both the short and long-term by destroying human and physical capital,

disrupting economic activity, diverting public expenditures to the military, and causing

capital flight. However, previous research has also demonstrated that property insecurity,

taken alone, has no impact on economic growth rates, either positive or negative (Lawson-

Remer 2012). These apparently contradictory empirical relationships suggest that the property

insecurity of ethno-cultural minorities may impact growth through two pathways: increasing

growth directly by reallocating resources and property into the hands of more efficient investors,

but decreasing growth indirectly by precipitating conflict. In sum, this implies that property

insecurity for some could lead to higher growth rates if not for the conflict and instability it often

incites.

Here we examine this hypothesis, i.e., the possibility that property insecurity is correlated with

higher growth rates, once the impact of conflict is taken into account.

The relationship between property insecurity, civil war, and growth is examined with unbalanced

panel data from 1980-2004. This is the same dataset used in the prior model, except now growth

rates in the additional period of 2000-2004 are included. Country periods are again divided into

five - year increments. The dependent variable is annual growth, averaged over five years. The

independent variable of interest is the measure of property insecurity. The primary control

variable is whether a civil war began during the prior five-year period. The log of per capita

GDP is also included, to control for conditional convergence. The model is tested both using

values at the beginning of the five year periods and averages over the preceding five year period.

I first examine property insecurity on its own, and then test robustness by including both

Property Insecurity and Risk of Expropriation in the same model. Depending on which property

insecurity measure is used and whether independent variables are lagged or not, the sample size

ranges from 212 to 387 observations.

21

The relationship is first tested using pooled panel data in a standard OLS specification:

Git = β0 + β1Pit + β2conflictit + β3logYit + β4Xit + єit (10)

Where Git is growth for country i over time period t, Pit is the property security score for country

i at the beginning of the period t or averaged for the previous period, conflictit is a dummy

variable for whether a civil war began in country i during time period t, Yit is per capita GDP at

the beginning of the period or averaged for the previous period, Xit is a vector of covariates, and

єit is the error term.

While standard for a first approach to the question, the cross-sectional OLS results using pooled

panel data are potentially suspect for three reasons. First, country-specific historical factors

could be influencing both growth and property insecurity. The most effective and parsimonious

way to deal with potential omitted variable bias would be to include country specific fixed

effects. In a fixed effects model coefficients reflect the impact on the dependent variable of

changes in the independent variable over time. However, a fixed effects model only detects

within-country variation, and is inappropriate when variables are time-invariant or a significant

component of variation is between rather than within countries. Here much of the variation in

property insecurity is between countries, rather than within countries over time. Therefore a

random effects model is employed instead, which uses the expected mean sum of squares to

estimate the within and between variance components, allowing inclusion of between country

variation in our model. A Hausman test is used to test consistency and statistical validity by

comparing results against a fixed effects specification.

Two other potential problems are possible reverse causality, and serial correlation in the

dependent variable. This possibility is already addressed to some degree in the OLS

specification because lags of the independent variables are used. To deal additionally with

these possibilities, robustness of results is tested using a systems General Method of

Moments (GMM) model, which uses lagged differences to instrument for levels and lagged

levels to instrument for differences (Blundell and Bond 1998). GMM also mitigates serial

correlation problems by instrumentation.

22

For all three econometric models and for a range of specifications including and excluding

various controls, the impact of Property Insecurity (Max) on growth is robustly positive

and significant when civil war is controlled for. Results are shown in Tables 5, 6, and 7.

The relationship holds true in the OLS framework, in the Random Effects and GMM

specifications, using property insecurity values at the beginning of the period or lagged one

period, and when Risk of Expropriation and log of per capita GDP are included in the

model. The impact of Property Insecurity (Mean) is also positive and significant in seven of

the eight specifications. In contrast, when civil war is not included as a control, Property

Insecurity is no longer significant in any specification.

23

24

25

These findings strongly support the hypothesis that property insecurity of marginalized

ethno-cultural minorities can contribute to economic growth directly, while indirectly

undermining growth by increasing the likelihood of conflict. A crucial relationship

between property security and insecurity, economic development, and conflict can be seen:

while property insecurity for marginalized groups may facilitate economic growth by

allowing resources and property to be reallocated into the hands of more efficient

investors, it is also highly correlated with an increased risk of armed conflict—which

undermines growth. This calls into question the wisdom of pursuing short-term growth

strategies that depend upon the property insecurity of some since this may provoke violent

conflict that can undermine growth in the long term.

5 Conclusion

Property rights are complex in both legal content and political and economic meaning, not

a traffic light along a one-dimensional continuum of “strong to weak”. Understanding the

role played by property rights in economic development and armed conflict requires

nuanced attention to complex heterogeneity in property rights enjoyment.

When heterogeneity of property rights enjoyment is considered, the data shows that

property insecurity of non-elites can be compatible with or even enhance economic

growth, but also encourages conflict—which can undermine long-run growth and

economic development. Empirically, the severity of property insecurity for the worst-off

group in a country is strongly correlated with the onset of armed conflict, suggesting that

severe property insecurity for marginalized minorities precipitates armed conflict.

However, controlling for civil war, property insecurity is actually associated with higher

growth rates. Taken together these finding suggest that reallocating resources and property

into the hands of more efficient investors through forced displacement and resettlement is

potentially growth-enhancing, but this growth effect is mitigated because property

insecurity also generates conflict, which reduces growth.

26

While these findings challenge widely held assumptions regarding the relationship

between property rights security, conflict, and economic development, this article should

be viewed as a first foray into a widely neglected and promising field of inquiry rather than

a conclusive treatment of the subject. This study examines civil conflicts with more than

1000 battle-related deaths in a given year; incorporating low and medium intensity

conflicts into the analysis could be a fruitful area of future research. And although the

econometric specifications attempted to guard against potential reverse causality using

time lags and GMM, and to control for omitted variables in a variety of different ways,

endogenaity and omitted variable bias remain possible; at this point strong correlations are

clear, but the directions of causality requires further investigation. Rather than taking

these findings as conclusive, these results suggest the need for a new line of research that

takes into account the complexity and heterogeneity of property rights, and considers the

role played by property insecurity in both sowing the seeds of conflict and clearing the

ground for growth.

The practical implications of these findings cut two ways. On the one hand, if aggregate

growth is the objective, then policymakers may wish to ignore (or encourage) the

expropriation of land and resources from marginalized groups, and the reallocation of

these resources into the hands of more productive investors. However, aggregate

economic growth does not necessarily mean inclusive economic growth: those with the

least power and voice may be left out and left behind by growth-enhancing policies that

strengthen the property rights of some but weaken the property rights of marginalized

groups. On the other hand, if avoiding armed conflict and civil war is the primary concern,

then special care should be taken to safeguard the property rights of marginalized

groups—even if this means lower economic growth rates.

The bifurcated nature of this policy conundrum opens up a range of questions regarding

the factors that turn the property insecurity of marginalized groups from growth-

enhancing to conflict-provoking. Does the severity of concomitant state repression or the

size of the dispossessed group matter? Is the value and nature of the land or resource

determinative? What is the importance of the level of per capita GDP of a country, or

27

outside economic opportunities seen by members of dispossessed groups? What is the role

of pre-existing informal and customary norms regarding property rights ownership? This

paper does not attempt to address all these issues, but rather to begin on a line of

important and largely neglected research.

28

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