Oil, Non-Tax Revenue, and Regime Stability: The Political Resource Curse Reexamined

Kevin Morrison

Department of Political Science Duke University

kmm15@duke.edu

Comments most welcome.

Prepared for presentation at the Harvard University Comparative Political Economy Workshop

October 2005

Abstract: Building on theories of regime change that focus on redistributional dynamics, this paper generates hypotheses regarding �non-tax� revenue and regime stability. Non-tax revenue, the importance of which has been largely ignored in theories of the public sector and regime change, is argued to include foreign aid as well as the majority of the oil revenue that accrues to governments. This non-tax revenue is hypothesized to affect redistribution in dictatorships but not in democracies, and to stabilize dictatorships but not democracies. These hypotheses are supported in cross-sectional time-series analyses of all developing countries over a period of 1970-2002.

Acknowledgments: I am grateful to Dylan Fagan for excellent research assistance, to John Doces, Marcela González Rivas, Robert Keohane, and Michael Ross for comments on an earlier version, and to Karen Remmer for comments and overall guidance. All errors are my own. An earlier version of this paper was presented at the Annual Meeting of the American Political Science Association in Washington, DC, in September 2005. I gratefully acknowledge financial support from a National Science Foundation Graduate Research Fellowship, a James B. Duke Fellowship, and a Vertical Integration Grant from the Duke University Graduate School. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the author and do not necessarily reflect the views of the National Science Foundation or any entity of Duke University.

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Oil, Revenue, and Regime Stability: The Political Resource Curse Reexamined

What is so peculiar about oil? The association of oil with authoritarian regimes has

been the focus of a large case-study literature (e.g. Beblawi and Luciani 1987b; Chaudhry

1997; Karl 1997), as well as recent statistical work on cross-national time-series datasets

(Ross 2001; Smith 2004). Overall, there seems to be something going on, but after so much

work, we still remain unclear as to the mechanisms by which oil affects political regimes.

The confusion is illustrated by the fact that the two most rigorous statistical analyses�by

Ross (2001) and Smith (2004)�come to different conclusions about oil. Ross (2001) argues

that oil leads to authoritarianism, and by implication is destabilizing for democratic regimes.

Smith (2004) argues that oil leads to regime stability, implying that oil wealth would stabilize

democracies. These empirical differences are evidence of a broader problem: a lack of

theoretical underpinning for the effects of oil wealth in different regimes.

The causal mechanisms between oil and democratic transition (or lack thereof) have

varied in the literature. The central argument, however, is that oil revenues provide central

governments with discretionary income that can be used to buttress their political position,

protecting them for pressures for democratic transition. As Jensen and Wantchekon state,

�The key mechanism linking authoritarian rule and resource dependence, both in democratic

transition and democratic consolidation, is the incumbent�s discretion over the distribution of

natural resources� (2004, 821). Similarly, Smith notes, �While scholars approach the political

economy of oil from diverse methodological origins, the theoretical arguments about the

structures and nature of the rentier state flow from the state’s access to externally obtained

revenues from the sale of oil� (2004, 233, emphasis added). For one group of scholars (e.g.

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Acemoglu, et al. 2004; Bazresch and Levy 1991; Chaudhry 1997; Crystal 1989; Entelis 1976;

Karl 1997; Vandewalle 1998), the key issue is that oil revenues allow governments to �buy

off political consensus� (Beblawi and Luciani 1987a, 7). By this argument, the soft budget

constraints that oil revenues provide enable governments to reduce the pressures for regime

change (Anderson 1995; Luciani 1987). A second group of scholars (e.g. Bellin 1994;

Chaudhry 1994; Clark 1997; Moore 1976; Ross 2001; Shambayati 1994; Skocpol 1982) have

pointed to the association of oil revenues with repression of various social groups and

citizens. The result of such repression is the same as buying off those groups: less pressure

for regime change.

This paper takes off from two points that can be made with regard to this literature.

First, the fact that two quite different causal mechanisms�cooptation and repression�have

been offered to explain oil�s relationship with authoritarianism indicates that there is possibly

nothing inherent in these resources that makes regimes act in certain ways. And if this is the

case, then it may make far more sense to think of these types of resources as simply revenue

entering a particular political economy, rather than as a resource with �antidemocratic

properties� (Ross 2001, 325). That they are used in authoritarian regimes for repression may

be nothing more than a reflection of those regimes� preferences over the use of state finances.

Presumably democratic regimes would use these resources in a different way, but we have no

theories to account for how.

Second, if the key mechanism at work here is the state�s access to externally obtained

resources, we should not expect that oil revenues are particularly unique (though they might

make up a large share of such resources). In fact, there may be a variety of such resources,

whose key characteristic is that they are not derived from taxation, but rather available mainly

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as �windfalls� to the government. For example, some scholars have begun to feel that the

literature on oil revenues has relevance for another fungible, external resource: foreign aid

(Bräutigam 2000; Moore 1998; Therkildsen 2002).1

This paper explores the effect of this broader set of revenues�what I term �non-tax

revenues��on regime stability. Oil revenues by and large accrue to states through state-

owned enterprises, so the revenue does not come through taxation. As will be discussed

below, such non-tax revenues�which include foreign aid�can make up substantial amounts

of government revenue, and ignoring them in theories of regime stability has likely come at a

cost. I first review the rather sparse literature on revenue and regime stability and then

develop a theoretical framework based on recent work on the redistributional dynamics

inherent in regime change. This theoretical framework allows me to make predictions about

the effects of these resources. Next, I discuss data issues and give some descriptive statistics

about non-tax revenue. I then test the effects of non-tax resources on regime change in a

cross-national time-series dataset, comparing their effects to those of oil in both dictatorships

and democracies. It turns out that when non-tax revenue is taken into account, oil does not

affect regime stability in a significant way in either type of regime. It is not oil, per se, that

leads to regime stability, but government ownership of that oil�and in fact, other kinds of

non-tax revenue have similar properties. Furthermore, these revenues only lead to increased

stability in dictatorships, not in democracies.

1 It is interesting to note in this context that Mahdavy�s definition of a rentier state was a state that received substantial rents from �foreign individuals, concerns or governments� (1970, 428, cited in Ross 2001).

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Previous Literature and Theoretical Framework

The literature on revenue and regime stability is surprisingly sparse, despite the

emphasis on the centrality of revenue to the nature of regimes in landmark works by

Schumpeter (1918 (1954)), Musgrave (1959), Brennan and Buchanan (1980), and Levi

(1988).2 The work that does exist is usefully divided into that focused on tax revenue and that

focused on non-tax revenue (there is no work that systematically addresses them both).

The work on tax revenue and regime stability has generally focused on a proposed link

between taxation and representation in the transition from autocracies to democracies. The

principal argument is that important western democracies arose as a result of a bargain: rulers

in need of resources were forced to grant representation in exchange for taxes (Bates and Lien

1985; Levi 1988; North and Weingast 1989; Tilly 1990). As Ross (2004) points out, there are

two different versions of this argument. One, seemingly supported by scholars like Brennan

and Buchanan (1980) and Huntington (1991), is that citizens demand representation in

exchange for higher levels of taxes. The other argument, seemingly supported by the likes of

Bates and Lien (1985), is more conditional: citizens demand representation if the ratio of

government services to taxes falls below a certain threshold. Ross provides cross-national

statistical tests for these theses, finding support for the latter but not the former.

There is no work I know of that focuses specifically on non-tax revenue, as such, and

its relation to regime stability. However, certain kinds of non-tax revenue have been studied

on their own. Oil revenues are, in general, one example. The majority of oil revenue for

governments comes not through taxes on foreign companies but rather through state-owned

2 It should be noted that this paper is focused on regime stability in the sense of authoritarian regimes switching to democratic ones, and vice versa. The literature on this topic has existed parallel to a literature on regime stability in the sense of political regimes succumbing to civil war. For a recent work that examines revenue in the context of this latter kind of regime stability, see Snyder and Bhavani (2005). Ideally, these literatures would coincide�theoretically and empirically�more than they do now.

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companies. Seventy-five percent of the world�s oil production, and 90 percent of its reserves

are in the hands of such state-owned companies (Ivanhoe 2000). Ross (1999) has suggested

that this state ownership of oil companies may be an underlying factor in the association of oil

wealth with poor economic performance, but to my knowledge this has not been tested. More

importantly for the purposes at hand, state ownership of oil companies may also be important

for the association of oil wealth with regime stability.

Another kind of non-tax revenue that has been studied on its own is foreign aid.

Research has indicated that foreign aid is a highly fungible resource (Feyzioglu, et al. 1998)

and acts similarly to oil in the sense that it provides extra resources the government can use to

distribute to its key constituencies without taxation (e.g. Bratton and van de Walle 1997). For

example, van de Walle has argued that democratization in Africa was encouraged by a fiscal

crisis resulting from, among other things, an increased willingness on the part of donors to

restrict aid to countries that did not respect human rights: �With fewer resources at their

disposal and an increasingly decrepit state apparatus, leaders found it harder to sustain critical

clientelist networks, with the result that the old political aristocracy was more likely to

fractionalize� (2001, 240).

There are, then, several different revenue sources that one might consider to be

important in a theory of regime stability and revenue. However, we lack a theory that could

help us understand how these different kinds of revenue interact with each other to affect

regime stability. Such a theory would not only have to address both kinds of revenue, but�

crucially�also address the demand side: the demand from society for expenditures.

A good place to start constructing such a theory�and the way in which hypotheses

will be generated for this paper�is to build off of works that focus on redistributional

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conflicts as central to regime change. The reason these works are helpful is that they begin to

address both the demand and supply sides of revenue, though they tend to ignore non-tax

sources of revenue. The redistributional approach to regime change has a distinguished

history, including the landmark works of Moore (1966) and Rueschemeyer, Stephens, and

Stephens (1992). These works have argued that democratization tends to be most resisted by

the rich. If one considers that political regimes are in essence a way of allocating resources in

society (Kitschelt 1992), it is intuitive to expect that richer citizens would prefer not to have

poorer citizens playing a role in such allocations, and vice versa. The most important recent

contributions in this body of work are by Boix (2003) and Acemoglu and Robinson (2005;

2001), who have used methods and theories largely developed in the social choice literature.

An important aspect of these recent works is that they build off work on the size of the

public sector that sees public revenue and expenditures as principally driven by

redistributional concerns. For example, Boix (2003) and Acemoglu and Robinson (2005;

2001) use formal models that employ the benchmark result of Meltzer and Richard (1981),

who argued that more unequal democracies will have larger governments than more

egalitarian democracies. As a result, these recent works on regime change suffer from a

problem shared by most theoretical and empirical works on government size: the possibility

of non-tax revenue is largely ignored. The Meltzer-Richard prediction, for example, is

generated solely by preferences over redistribution through taxation. Thus, while a large

literature has considered the determinants of the size of the public sector, (e.g. Boix 2001;

Persson and Tabellini 2003; Rodrik 1998), few scholars have studied the effects of non-tax

sources of revenue on government size (an exception being Remmer 2004).

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To understand how non-tax revenues might affect regime change in a redistributional

approach, it is necessary to understand how they might affect redistribution. And therefore it

is necessary to understand why�and how much�redistribution takes place in democracies

and dictatorships. If we define democracies as those regimes that have functioning elections,

it is generally safe to say that democracies give a more important say in politics to the poorer

masses than do dictatorships, where a far smaller group�almost always more well-off than

the rest�makes decisions over resource allocations. The result of this greater say in politics

is that democracies are usually thought to be better for the poorer members of society than

dictatorships.3 The recent work of Lindert (2004), for example, has carefully documented

how the expansion of the share of the population with political voice in western countries at

the end of the 19th and beginning of the 20th centuries (an expansion to the poorer elements of

society) led to an expansion in both social insurance and public education provision. This

assertion is also supported by the work of Bueno de Mesquita, et al. (2003), who demonstrate

that as the size of the winning coalition in a regime increases, so do important education and

health indicators.

The extent of redistribution in democracies is clearly dependent on certain constraints,

as a large literature has investigated. Some of these constraints that have been analyzed in the

literature include the political mobilization of the rich, electoral funding laws, and the

mobility of capital. And in fact, these constraints play a critical role in theories of regime

change based on redistribution. In the Acemoglu and Robinson framework, for example, the

reason democracies fall is because the threat of redistribution is too much for the rich, who

launch a coup. In the Boix framework, the mobility of capital makes democracy more likely,

3 See, for example, Sen (1999) and Zweifel and Navia (2000). For an argument that there is no difference between the regimes once adjustments are made for missing data, see Ross (2005).

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because the rich�able to move their money abroad�are not as afraid of the redistributive

power of democracies. For these reasons, democracies in these frameworks maximize

redistribution to a certain point, at which the rich are just indifferent between being in a

democracy and launching a coup.

Dictatorships redistribute for a different reason. If one assumes that those in power in

a dictatorship are generally the more well-off in a society, then it is a quick jump to

understand that they will want as little redistribution as possible. However, like democracies,

dictatorships also work under certain constraints. One of the most important of these is the

potential for revolution from the large portion of society not in power�the poorer portion.

While there is far less empirical work studying redistribution in dictatorships than in

democracies, many scholars (e.g. Acemoglu and Robinson 2005; Acemoglu, et al. 2004;

Grossman 1991; 1994; Huntington 1968) have theorized that an important reason that

dictatorships redistribute is to avoid such revolution. Rigolini (2003) provides some empirical

support of this hypothesis. Building on this thinking, the argument of Acemoglu and

Robinson (2005; 2000) is that the elite will redistribute just enough to keep the poor from

revolting. And when they cannot credibly promise enough redistribution to do this, they

democratize, because democracy is preferable to them over an outright revolution.

If these redistributional dynamics are correct, then non-tax revenues should have very

different effects on redistribution�through taxation and spending�in dictatorships and

democracies. In dictatorships, the elite in power only want enough resources funneled to the

poor to keep them from revolting. In the absence of non-tax revenue, these resources will

have to come from the pockets of the rich. However, non-tax revenues give the rich some

flexibility. In the absence of an increased threat, they can simply redistribute less of their own

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resources to satiate the masses, while spending on the poor would stay basically the same. It

may be noted that at the extreme, this kind of dynamic would lead a purely �distributional�

state (Delacroix 1980). In the presence of an increased threat from the poor, the additional

resources enable the rich to top-up spending on the poor. On the other hand, in democracies,

non-tax revenues accruing to the state should have no effect on taxation of the rich, since the

median voter, being less well-off, will still want to maximize redistribution from the rich.

Instead, non-tax revenues will simply add to the amount of funds that can be spent on the

poor. Table 1 summarizes these predictions.

Table 1: Predictions for the effects of rises in non-tax revenues

Taxation of rich Spending on poor

Dictatorships Decreases, or stays the same in the face of increased threat

Stays the same, or increases in the face of increased threat

Democracies Stays the same Increases

Accordingly, these redistribution dynamics imply that non-tax revenues will have

different effects on the stability of dictatorships and democracies. In redistributional

approaches to regime stability, put rather simply, dictatorships fall because they spend too

little on the poor, and democracies fall because they take too much from the rich. Because

non-tax revenue should not have an effect on taxation of the rich in democracies, there is no

reason to suspect that such revenue will have any effect on regime stability either. In

dictatorships, however, the influx of extra resources can enable stressed dictatorships to

funnel more resources to the poor, thereby obviating the need to democratize. In other words,

non-tax revenue should have a stabilizing effect on dictatorships, but no effect on

democracies. The following sections explore these hypotheses empirically.

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Some Details on Non-tax Revenue

As the conception of non-tax revenue advanced above is relatively new, it is useful to

begin with a discussion of descriptive statistics. The best available data on non-tax revenues

is from the International Monetary Fund�s Government Finance Statistics. Unfortunately for

researchers interested in this revenue over a long time period, the IMF (2001) recently

changed the way they categorize revenue. Revenue has been coded in the new way only from

1990 to present, but the data for the previous kind of coding by the IMF (1986) is available

over a time period of 1970-2002. Therefore, to attain a longer time-series, I have used the

1986 coding.

The IMF�s variable for non-tax revenue can be found in the World Bank�s (2004)

World Development Indicators (WDI). The World Bank notes that the indicator consists of

�not compulsory, nonrepayable payments for public purposes, such as fines, administrative

fees, or entrepreneurial income from government ownership of property. Proceeds of grants

and borrowing, funds arising from the repayment of previous lending by governments,

incurrence of liabilities, and proceeds from the sale of capital assets are not included.� As the

description implies, this indicator does not include receipts from foreign aid, which are a

crucial part of my definition of non-tax revenue. I have therefore created my own variable

that sums the value of non-tax revenue (as defined by the IMF) and net aid receipts (also from

WDI), both as a share of GDP. The resulting variable is quite close to the theoretical concept

outlined above�revenue the government receives that does not derive from taxation.4 My

sample consists of all non-OECD countries for which data is available. There are 2225

4 Where relevant, I made similar adjustments to the IMF�s indicator for total revenue, adding foreign aid to them because the IMF does not.

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observations of non-tax revenue (henceforth, non-tax revenue will refer to my variable that

includes foreign aid), comprising 129 countries.

The first point to make is that, for many countries in the world, this type of revenue is

quite significant. In the 2225 observations, non-tax revenue makes up an average of 35

percent of government revenue. Table 2 lists some of the countries for which non-tax revenue

is crucial. In countries such as the Democratic Republic of Congo, Kuwait, and the United

Arab Emirates, non-tax revenue makes up virtually all of government revenue in certain

years. The table also shows that Middle Eastern countries tend to get their revenue from non-

tax revenue, indicating that theories explaining authoritarianism in oil-rich countries on the

basis of tax-based arguments (e.g. Boix 2003) are incomplete. And finally, the table indicates

that the importance of these revenue sources crosses regional boundaries. All of this points to

the importance of studying this kind of revenue, which has been largely ignored in the

political science literature.

These non-tax revenues are also large relative to the size of the economy. Table 3 lists

the components of revenue�tax and non-tax�as share of GDP by region. It also lists the

regional averages of oil exports as a share of GDP, a common indicator of oil dependence. Of

note is the fact that among the six regions, sub-Saharan Africa and South Asia rank fourth and

sixth in terms of their oil exports as a share of GDP. Yet they rank second (tied) and fourth

respectively in terms of their non-tax revenues, as a result of large aid inflows. The Middle

East, as one might expect, is ranked first in both variables.

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Table 2: The Importance of Non-tax Revenue in Countries� Revenue Streams Percentage of total revenue that is non-tax revenue (1 = 100 percent) Observations Mean Std. Dev. Min Max Bahrain 22 0.76 0.07 0.62 0.89 Bangladesh 18 0.62 0.08 0.42 0.74 Bhutan 20 0.79 0.07 0.68 0.88 Bolivia 17 0.53 0.10 0.39 0.66 Botswana 26 0.53 0.06 0.41 0.68 Burkina Faso 21 0.61 0.06 0.53 0.78 Congo, Dem. Rep. 31 0.45 0.24 0.18 0.99 Congo, Rep. 21 0.50 0.20 0.27 0.81 Iran 25 0.61 0.15 0.32 0.87 Jordan 28 0.54 0.13 0.37 0.75 Kuwait 26 0.88 0.24 0.10 0.99 Madagascar 20 0.50 0.14 0.30 0.73 Maldives 23 0.63 0.09 0.55 0.92 Mali 14 0.61 0.07 0.50 0.73 Nepal 31 0.56 0.08 0.41 0.69 Nicaragua 31 0.38 0.18 0.15 0.74 Oman 30 0.70 0.12 0.24 0.78 Sierra Leone 26 0.53 0.19 0.18 0.82 Syria 24 0.50 0.19 0.21 0.78 Uganda 19 0.40 0.22 0.15 0.91 United Arab Emirates 24 0.77 0.22 0.45 1 Table 3: The Importance of Non-tax Revenue, in economic terms All variables are as a percent of GDP (100 = 100 percent). Data are for the 1511 observations in which all variables are available. Oil

exports Tax revenues

Non-tax revenues excluding aid

Aid Total non-tax revenues*

Middle East and North Africa

16 18 14 4 18

East Asia and Pacific

8 17 4 6 10

Sub-Saharan Africa

4 20 3 7 10

South Asia 1 12 3 5 8 Europe and Central Asia

2 25 4 2 5

Latin America and Caribbean

9 17 3 2 5

*Total non-tax revenue is the sum of the previous two columns (differences are due to rounding). Regional breakdowns are as defined by the World Bank.

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Analysis of the Redistribution Hypotheses I now present the results for the first set of hypotheses, regarding the effects of non-tax

revenue on redistribution in democracies and dictatorships. For my indicator for political

regime, I have chosen to use the definition of Przeworski et al. (2000), who define

democracies as regimes with functioning elections. Specifically, a regime is coded as

democratic if the chief executive is elected, the legislature is elected, there is more than one

party, and incumbents lose elections. If all of these characteristics are not present, the regime

is a dictatorship. There are therefore no �in-between� regimes�either a regime is a

democracy or a dictatorship. This binary coding of Przeworski et al., and their focus on

elections, matches well with the theoretical approach outlined above. Recent redistributional

approaches to regime change have also considered regimes as dichotomous, and the defining

characteristic of regimes is the ability (or lack thereof) for large numbers of citizens to vote.

Boix, for example, defines democracy as a regime in which �all individuals vote (or may

vote). In a dictatorship, only the preferences of part of society are taken into account to

decide the final allocation of assets� (2003, 10). The distinction Acemoglu and Robinson

make is quite similar: �In a democracy the majority of the population is allowed to vote�.

[N]ondemocratic regimes share one common element: instead of representing the wishes of

the population at large, they represent the preferences of a subgroup of the population, the

�elite�� (2005, 16).

I use two dependent variables in the analysis in this section. As discussed above,

redistribution is made up of the �taking away� from the rich and the �giving to� the poor. For

the former I use income tax revenue as a percent of GDP, since income tax is considered a

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progressive tax, and for the latter I use the sum of health, education, and welfare spending as a

share of GDP, since these types of spending are generally considered to be progressive.

The statistical estimations here are based on an error-correction model of the type

utilized in other recent research on government spending and revenue (Iverson and Cusack

2000; Remmer 2004; Rodden 2003). The model is of the form:

∆Yi,t = α + ∆Xi,tβ + Φ(Yi,t-1 � Xi,t-1γ) + εi,t

in which Yi,t is the revenue or spending variable in country i in time t, and X is a matrix of

independent variables. Therefore the dependent variable is the change in revenue or spending

as a share of GDP from one year to the next. The independent variables include both the

annual rate of change and the lagged values of the independent variables, as well as the lagged

value of dependent variable. As Remmer writes about this type of model,

The underlying theoretical assumption is that the relationship between the variables in the model

resembles a moving equilibrium in which the dependent variable may not only fluctuate in response to

short-run changes in the independent variables but also assume over the long run levels consistent with

those of the independent variables. The central advantage of the model is thus that it makes it possible

to distinguish between the short- and long-term relationship of X and Y. (2004, 82)

The equation actually estimated is as follows:

∆Yi,t = β0 + Yi,t-1β1 + ∆Xi,t β2 + Xi,t-1β3 + εi,t,

in which β1 estimates Φ in the error correction model, β2 estimates β (thus representing the

short-term relationship between X and Y), and β3 estimates Φγ (and thus the long-term

relationship between X and Y). As is standard in the literature, the equation was estimated

using ordinary least squares with panel-corrected standard errors, to accommodate the

problems that plague cross-sectional time series research designs, notably heteroskedasticity

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and contemporaneous correlation of errors across countries (Beck and Katz 1995). The

estimation also accounts for panel-specific patterns of first-order autocorrelation.

While the principal variable of interest in the regression is non-tax revenue, it is

important to control for other variables that might be driving changes in income tax revenue

or social spending. For both sets of regressions, building off recent work on government size,

I include five additional variables in the model. First, I control for population (in log form),

since prior research (e.g. Shadbegian 1996) has indicated that larger countries are more

efficient at public good provision because of economies of scale. Second, I control for the

percentage of the population that is 65 years and older, since this tends to drive pensions (e.g.

Perotti 1996), an important part of public spending. Third, I control for trade dependence,

measured as exports plus imports as a percent of GDP, building off work that asserts a

relationship between trade openness and the public sector (e.g. Rodrik 1998). Fourth, I

control for per capita GDP, to account for the effect of economic development on the public

sector (e.g. Boix 2001). In the income tax regressions, the fifth variable is central government

expenditure as a share of GDP, to account for the potential impact of changes in spending

requirements in a country (e.g. Remmer 2004). Likewise, in the spending regressions, I

include tax revenue as a share of GDP, in account for the potential impact of changes in tax

revenue. Finally, in all of the regressions I include dummy variables for the 1970s and 1980s

decades, as well as dummy variables for geographic region. All of these variables, as well as

the dependent variable, are attained from the World Bank (2004).

Table 4 presents the regression results for income tax, where dictatorships and

democracies are as defined above and for which the codings are taken from Cheibub and

Gandhi (2004), who use the previously discussed regime definitions of Przeworski et al.

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Table 4: Determinants of Changes in Income Tax Revenue as a Share of GDP (log)

Dictatorships Democracies Coefficient Standard Error Coefficient Standard Error Non-tax revenues as a share of GDP (log) t-1 -0.046** 0.020 0.030 0.022 GDP per capita(log) t-1 -0.032* 0.017 0.059*** 0.020 Population(log)t-1 0.023* 0.012 0.016* 0.009 Share of population over 65 t-1 0.020** 0.009 0.002 0.005 Trade/GDP t-1 0.001*** 0.000 0.001 0.000 Government Expenditures as a share of GDP(log) t-1 0.039 0.036 0.017 0.034 ∆ Non-tax revenues as a share of GDP (log) -0.013 0.040 0.042 0.035 ∆ GDP per capita (log) 0.487*** 0.183 -0.128 0.234 ∆ Population (log) 3.120* 1.604 -0.258 1.123 ∆ Share of population over 65 -0.088 0.174 0.057 0.123 ∆ Trade/GDP 0.003*** 0.001 0.003*** 0.001 ∆ Gov�t Expenditures as a share of GDP (log) 0.131* 0.067 0.203** 0.083 Income tax revenue as a share of GDP(log) t-1 -0.075*** 0.021 -0.093*** 0.025 Constant -0.524** 0.254 -0.680** 0.274 1970s -0.001 0.028 0.045* 0.024 1980s -0.029 0.023 0.023 0.019 Africa 0.040 0.031 0.107 0.075 Middle East 0.023 0.028 0.072 0.098 Latin America 0.001 0.027 0.096 0.071 Europe and Central Asia -0.164* 0.097 0.036 0.091 South Asia 0.006 0.033 0.126** 0.063 Observations 669 506 Countries 52 47 R2 0.115 0.154 Wald χ2 68.69 1544.64 *≤0.10 **≤0.05 ***≤0.01

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(2000). As predicted, there is a significant negative relationship between non-tax revenues

and changes in tax revenue in dictatorships, but not in democracies. There also seems to be

an interesting pattern with regard to GDP per capita. As dictatorships get richer, they tend to

tax the rich less, while richer democracies tend to tax the rich more.

I now turn to the spending regressions, which are represented in Table 5. The results

for democracy support the hypotheses above, with non-tax revenues positively and

significantly associated with increases in social spending in democracies. Interestingly, non-

tax revenue is also positively and significantly associated with social spending in

dictatorships. This seems to indicate that, as hypothesized above, increases in non-tax

revenue have occurred in stressed dictatorships, which then funnel the revenue into spending

on the poor.

The results in this section indicate that, as theorized above, non-tax revenues will be

stabilizing in dictatorships but not in democracies. To reiterate the theory, dictatorships fall

because the poor receive too little, and it has been shown here that non-tax revenues enable

the rich in dictatorships to fund social spending while diminishing redistribution of their own

income. As such, the hypothesis that non-tax revenues will stabilize dictatorial regimes still

seems sound. On the democratic side, it was theorized that democracies fall because they tax

the rich too much. Since non-tax revenues have been shown here to have little effect on such

taxation�instead, non-tax revenues in democracies tend to increase social spending�these

revenues should not have any significant effect on democratic regime stability. With some

empirical support for this causal mechanism, I now move on to testing the regime change

variable directly.

18

Table 5: Determinants of Changes in total Social Spending (Health, Education, and Welfare) as a Share of GDP (log)

Dictatorships Democracies Coefficient Standard Error Coefficient Standard Error Non-tax revenues as a share of GDP (log) t-1 0.033*** 0.010 0.017** 0.008 GDP per capita(log) t-1 0.028 0.018 0.021** 0.010 Population(log)t-1 -0.007 0.008 -0.006 0.005 Share of population over 65 t-1 -0.001 0.008 -0.003 0.003 Trade/GDP t-1 0.000 0.000 0.000 0.000 Tax Revenue as a share of GDP(log) t-1 0.026 0.020 0.025 0.022 ∆ Non-tax revenues as a share of GDP (log) 0.063** 0.029 0.022 0.018 ∆ GDP per capita (log) -0.406*** 0.108 -0.110 0.103 ∆ Population (log) -2.434** 1.216 -1.401** 0.607 ∆ Share of population over 65 0.118 0.097 0.004 0.054 ∆ Trade/GDP -0.001 0.001 -0.001** 0.001 ∆ Tax Revenue as a share of GDP (log) 0.084** 0.042 0.193*** 0.050 Social Spending as a share of GDP(log) t-1 -0.108*** 0.022 -0.066*** 0.021 Constant 0.194 0.173 0.160 0.104 1970s 0.027 0.018 -0.046*** 0.016 1980s 0.023 0.017 -0.041*** 0.013 Africa -0.010 0.039 -0.050** 0.020 Middle East 0.009 0.026 dropped Latin America 0.015 0.026 -0.006 0.012 Europe and Central Asia -0.070 0.070 0.014 0.023 South Asia -0.016 0.045 -0.023 0.028 Observations 511 409 Countries 48 43 R2 0.163 0.144 Wald χ2 131.13 77.42 *≤0.10 **≤0.05 ***≤0.01

19

Analysis of the Regime Change Hypothesis In order to study regime change, the dependent variable in these regressions is a binary

variable that takes a value of �1� if there is a change from one year to the next in the regime

coding by Cheibub and Gandhi (2004). It takes a value of �0� if there is no change.

I use a statistical model identical to the one underlying the revenue and spending

regressions above, both so the results are comparable and also for underlying theoretical

reasons. As discussed above, an error correction model enables the study of both long-term

and short-term relationships between variables. Many theories of regime change imply that

certain independent variables could have both long-term and short-term effects. For example,

there are hypothesized effects on regime change of both the level of income in a country

(Lipset 1959) and economic growth and decline (Remmer 1991). For this reason, many

scholars (e.g. Przeworski, et al. 2000) include both level and growth of GDP per capita in

their regressions. However, few scholars do this with other variables they include in the

regressions.

A close reading of the resource curse literature, however, implies that a similar

approach should be taken to oil variables. It is often unclear whether scholars are talking

about the effects of levels or changes in oil revenue, but one can certainly generate hypotheses

about both based on the literature. For example, I read the following hypothesis as one about

the level of oil: �resource wealth retards democratization by enabling governments to boost

their funding for internal security� (Ross 2001, 328). And I read this next one as being a

hypothesis about the change in oil revenues: �during [oil] booms politicians are likely to flood

the domestic economy with revenues, spending unwisely and spurring destabilizing inflation�

20

(Smith 2004, 233). It is possible that both levels and changes have effects, and the error-

correction model enables the study of both.

Again, the principal variable of interest is the non-tax revenue variable. However, in

this regression I am also particularly interested in how non-tax revenue compares to the

variable that scholars have used to measure oil dependence: oil exports as a share of GDP.

This variable can be constructed using the World Bank�s World Development Indicators, and

as Smith writes, it �highlights both the role of oil as a source of export revenues and its

importance in the domestic economy� (2004, 236). I also control for other variables that

might affect regime stability. First, I control for levels and changes in GDP per capita, for the

reasons mentioned above. Second, I control for ethnolinguistic fractionalization (ELF), since

many scholars (e.g. Horowitz 1985) have argued that social fragmentation increases

instability in certain regimes. The measure I use is the probability that two randomly chosen

individuals in a country do not speak the same language. Roeder (2001) provides

observations of this variable for both 1961 and 1985. For all observations prior to and in

1980, I used the 1961 measure, and for all subsequent years I used the 1985 measure. Finally,

like Przeworski et al. (2000) and Smith (2004), I control for past instability in a country,

measured simply as the number of all past regime changes in that country in the sample. The

results are estimated by logistic regression with unaltered standard errors, as in Smith (2004).

Table 5 reports the results. As predicted, non-tax revenues have a significant

stabilizing impact on dictatorships but not in democracies. The oil exports variable generally

fails to reach standard levels of significance in either of the regressions, though the change

variable is significant at the 0.10 level in the dictatorships regression. Interestingly, ELF is

21

Table 5: Determinants of Regime Instability Dependent variable is dichotomous, coded as �1� if the regime changes in the current year and �0� if there is no change (therefore a negative coefficient is a �stabilizing� effect). Observations were included in the dictatorships (democracies) regression if they were coded as dictatorships (democracies) in year t-1. Dictatorships Democracies Coefficient Standard Error Coefficient Standard Error Non-tax revenues as a share of GDP(log) t-1 -1.090*** 0.338 -0.371 0.671 Oil exports as a share of GDP(log) t-1 -0.093 0.084 0.121 0.181 GDP per capita(log) t-1 0.040 0.355 -1.330* 0.805 ∆ Non-tax revenues as a share of GDP(log) -1.777** 0.869 -0.782 1.298 ∆ Oil exports as a share of GDP(log) -0.308* 0.166 0.460 0.350 ∆ GDP per capita(log) -4.339 4.501 -16.026** 7.199 Ethnolinguistic Fractionalization 4.656*** 1.709 -0.834 2.538 Sum of past regime failures t-1 0.046 0.170 0.539* 0.316 Regime transition t-1 0.556 1.267 1.191 1.146 Constant -10.107*** 3.126 4.196 6.018 1970s -2.208*** 0.715 3.534** 1.394 1980s -0.763 0.564 0.800 1.187 Africa 0.356 0.855 -0.850 1.860 Middle East dropped -0.724 1.744 Latin America 1.628 0.817 -1.255 1.187 Europe and Central Asia 1.430 1.042 dropped South Asia 2.278 1.415 -1.558 1.725 Observations 659 578 Countries 65 52 Log Likelihood -77.97 -34.76 *≤0.10 **≤0.05 ***≤0.01

22

only destabilizing to dictatorships, and GDP per capita�both its level and change�are only

significant in the democracy regression.

Because past works have indicated that oil does have impacts on transitions to and

from democracies, we want to be confident that the results here are not driven simply by the

sample of observations for which non-tax revenue is available. The principal difference

between the oil and non-tax variables is that there are no observations of the non-tax variable

prior to 1970, whereas observations for the oil variable stretch back into the 1960s. Once one

drops these years prior to 1970, the sample of countries for which only the oil variable is

available is very similar in important respects to the sample in which it and the non-tax

variable are both available. Table 6 reports a comparison of the two samples. As can be seen,

they share very similar characteristics in terms of their overall oil exports-to-GDP ratio, their

regime failures observed, and their existing political regimes. They are also quite similar in

terms of their temporal, spatial, and economic characteristics. While we of course cannot rule

out that the results here are driven by the sample, this comparison of samples gives increased

confidence.

The result of these regression analyses is therefore an inability to reject the hypotheses

advanced above in the theoretical discussion. It seems indeed to be the case that non-tax

revenues have stabilizing effects of dictatorships, but not in democracies, for the

redistributional reasons outlined above.

23

Table 6: Sample properties for oil and non-tax variables

Sample in which oil as a

percent of GDP is observed

Sample in which both the oil and non-tax variables

are observed Observations 2330 1496 Mean of oil exports as a % of GDP

7 7

% in which regime failure is observed

3 3

% Dictatorships 56 54 % 1970s 27 25 % 1980s 27 31 % 1990s 35 37 % 2000s 11 6 Sub-Saharan Africa 22 17 Middle East and North Africa

17 17

Latin America and Caribbean

31 33

Europe and Central Asia 12 13 South Asia 5 7 East Asia and Pacific 13 13 High Income (non-OECD) 9 12 Upper Middle Income 25 25 Lower Middle Income 39 38 Low Income 27 26 Region and income codings are by the World Bank. Conclusion

A fundamental question in the study of democratization is whether theories developed

in one part of the world apply to other parts of the world (Bunce 2000). The recent statistical

works on the relationship between oil and political regime have been excellent examples of

the importance of testing the broader validity of an �area study� theory. This paper will

hopefully be seen in this tradition as well. However, instead of focusing only on the area

studies literature focused on oil (and therefore mainly the Middle East), this paper also builds

on literature that has examined the impact of foreign aid on regime change�a literature that

24

studies different regions of the world. My underlying hypothesis has been that these types of

revenue sources have similarities that cause them to have certain effects on different types of

political regimes.

In examining this underlying hypothesis, this paper has made four principal

contributions. First, it has pointed to the fact that a sizeable portion of government revenue�

non-tax revenue�remains largely ignored in political science, despite its overall importance

in the revenue strains of many governments. In fact, in the sample of countries and years

studied here, it accounted for an average of more than a third of government revenue. Our

theories of government size have very little to say about this portion of government revenue,

and this clearly is a gap in our understanding of the public sector.

Second, this paper has begun to flesh out a theory of revenue and regime stability,

based on approaches to political regimes that focus on the regime�s role in resource allocation

and re-allocation. As the important recent works in this tradition build off work on the size of

the public sector�which have, as just mentioned, ignored the difference between tax and

non-tax revenue�it is not surprising that these theories have ignored the potential role of

non-tax revenue. My analysis has indicated that since the dynamics driving redistribution in

dictatorships and democracies are different, the effect of non-tax revenue on these regimes

should also be different. Specifically, non-tax revenue should not affect redistribution and

regime stability in democracies, but it should diminish redistribution and increase regime

stability in dictatorships.

Third, the preceding analysis indicates that the answer to the question that opened this

paper��What is so peculiar about oil?��may be that so much of it is produced by successful

state-owned enterprises, particularly in dictatorships. This is certainly not to argue that

25

theories that link oil-wealth to authoritarianism based on taxation dynamics (e.g. Boix 2003)

are not useful. However, it may be the case that taxation dynamics are more relevant to the

effects of privately held oil resources. And since so much of the world�s oil resources are in

public hands (as discussed above), we need to consider the effects of this public ownership on

the effects of oil in different political regimes.

Finally, while the focus of the discussion in this paper has been on oil, it should also

be noted that this paper has implications for the effect of foreign aid on regime stability, a

topic that has received surprisingly little attention in the literature. The results that we do

have are inconsistent. Goldsmith (2001) finds a small but significant positive correlation

between level of democracy in Africa and aid as a percentage of GNP, and Knack (2004)

finds no correlation between improvements in level of democracy and aid as a percentage of

either GNP or government spending. The analysis here indicates that aid�s effects are

conditional on the political regime in place.

While the results presented here are illuminating, much work remains to be done on

this topic. First, a formalization of the argument presented in the second section of this paper

would enable a useful direct comparison of the formal treatments of regime change in Boix

(2003) and Acemoglu and Robinson (2005).5 Second, a broader range of tests of the effects

of non-tax revenue and redistribution and regime stability would be illuminating. And third,

some in-depth case studies might improve our on-the-ground understanding of the linkages

between redistribution and regime stability, which remain rather slim. Enlightening case

studies do exist, such as those by Boix (2003) and Rueschemeyer et al. (1992), but they

remain rather few. And none of them (that I know of) examine the effect of non-tax revenues

on this relationship. Of course, as discussed above, case studies on certain types of non-tax 5 I have formalized this argument for dictatorships in Morrison (2005).

26

revenues and regime stability do exist, but none of these have studied these revenues in an

overarching framework, which would hopefully shed light on the similarities between oil

income and other types of non-tax revenue.

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