Determinants of Democracy

Robert J. BarroHarvard University

Research Memorandum 9706

OCFEBEramus University RotterdamRoom H 7-25P.O. Box 17383000 DR RotterdamThe NetherlandsTel.: (31) 10 4082430Fax.: (31) 10 4089173Email: iwvdijk@few.eur.nlWWW: http://www.eur.nl/few/ocfeb

Table of contents

Abstract

1. The Measure of Democracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2. Framework for the Determination of Democracy . . . . . . . . . . . . . 3

3. Regression Results for Democracy: Standard of Living and Related Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

4. Additional Influences on Democracy . . . . . . . . . . . . . . . . . . . . . . 7

5. Civil Liberties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

6. Lon-Run Forecasts of Democracy . . . . . . . . . . . . . . . . . . . . . . . . 14

7. Concluding Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

ABSTRACT

A panel study of over 100 countries from 1960 to 1995 finds thatimprovements in the standard of living predict increases in democracy, as

measured by a subjective indicator of political freedom. Specifically, thepropensity for democracy rises with per capita GDP, primary schooling, and a

smaller gap between male and female primary attainment. For a given standardof living, democracy tends to falls with urbanization and with a greater reliance

on natural resources. Democracy has a weak positive relation to country size. Anincrease in the middle-class share of income predicts a rise in political rights.

The apparently strong relation of democracy to colonial heritage mostlydisappears when the economic variables are held constant. Similarly, the

allowance for these economic variables weakens the interplay between democracyand religious affiliation. However, negative effects from Muslim and non-religious

affiliations remain intact. The level of democracy tends to adjust over five yearsabout one-quarter of the way toward the target value determined by the standard

of living and the other explanatory variables. An expansion of political freedom - more democracy - has opposing effects

on economic growth. On the positive side, democratic institutions provide a checkon governmental power and thereby limit the potential of public officials to amass

personal wealth and to carry out unpopular policies. But, on the negative side,more democracy encourages rich-to-poor redistributions of income and typically

enhances the power of interest groups. Consequently, the net effect of democracyon growth is uncertain. (See Sirowy and Inkeles [1990] and Przeworski and

Limongi [1993] for surveys of theories that relate democracy to econonomicgrowth.)

My cross-country empirical work (Barro [1996]) finds a nonlinear effectof democracy on growth: growth is increasing in democracy at low levels of

political freedom, but the relation turns negative once a moderate amount offreedom has been attained. One way to interpret these results is that, in the

worst dictatorships, an increase in political rights tends to stimulate growthbecause the benefit from limitations on governmental power is the key matter.

But in places that have already achieved a moderate amount of democracy, afurther increase impairs growth because the dominant effect comes from the

intensified concern with social programs that redistribute resources.The focus of the present analysis is on the reverse channel; that is, the

impact of economic development on a country's propensity to experience

democracy. A common view since Lipset's (1959) research is that prosperity

stimulates democracy; this idea is often called the Lipset hypothesis. Lipset(1959, p. 75) credits the idea to Aristotle: "From Aristotle down to the present,

men have argued that only in a wealthy society in which relatively few citizenslived in real poverty could a situation exist in which the mass of the population

could intelligently participate in politics and could develop the self-restraintnecessary to avoid succumbing to the appeals of irresponsible demagogues." (For

a statement of Aristotle's views, see Aristotle [1932, book VII.) Theoretical models of the ellect of economic conditions on the extent of

democracy are not well developed. Lipset (1959, pp. 83-84) emphasizes increasededucation and an enlarged middle class as elements that expand "receptivity to

democratic political tolerance norms" (a phrase that I wish I understood). He alsostresses Tocqueville's (1835) idea that private organizations and institutions are

important as checks on dictatorship. This point has been extended by Putnam(1993), who argues that the propensity for civic activity is the key underpinning

of good government in the regions of Italy. For Huber, Rueschemeyer, andStephens (1993, pp. 74-75), the crucial concept is that capitalist development

lowers the power of the landlord class and raises the power and ability toorganize of the working and middle classes.

Boone (1996) develops a model in which the equilibrium amount offreedom depends on the net benefits of oppression to potential rulers. However,

in this type of setting, most effects turn out to be ambiguous. For example, anincrease in human capital raises the populace's ability to resist oppression but

also raises the ruler's benefits from subjugating them. Similarly, a rise inurbanization makes it easier for people to meet and communicate - which

presumably makes them harder to suppress - but also makes it easier for anautocrat to monitor and control activities.

Despite the lack of clear predictions from theoretical models, the cross-country evidence examined in the present study confirms that the

Lipset/Aristotle hypothesis is a strong empirical regularity. In particular,increases in various measures of the standard of living forecast a gradual rise in

democracy. In contrast, democracies that arise without prior economicdevelopment - sometimes because they are imposed by ex-colonial powers or

international organizations - tend not to last. Given the strength of this empiricalregularity, one would think that clearcut theoretical analyses ought also to be

attainable. (This seems to be a case where the analysis works better in practice

than in theory.)

See Gastil (1991) for a discussion of the methods that underlie his data series. Inkeles (1991)1

provides an overview of measurement issues on democracy. He finds (p. x) a ... high degree ofagreement produced by the classification of nations as democratic or not, even when democracyis measured in somewhat different ways by dillerent analysts." Bollen (1990) suggests that hismeasures are reasonably comparable to Gastills. It is difficult to check comparability directlybecause the two series do not overlap in time. Moreover, many countries-especially those inAfrica-clearly experienced major declines in the extent of democracy from the 1960s to the 1970s. Thus, no direct inference about comparability can be made from the higher average of Bollen'sfigures for the 1960s than for Gastills numbers for the 1970s.

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1. THE MEASURE OF DEMOCRACY

The definition of democracy in the present study is a narrow one thatfocuses on the role of elections. This concept accords with the one adopted by

Huntington (1991, p. 6): "The central procedure of democracy is the selection ofleaders through competitive elections by the people they govern." His inspiration

for this procedural definition of democracy comes from Schumpeter (1947, p.269): "The democratic method is that institutional arrangement for arriving at

political decisions in which individuals acquire the power to decide by means ofa competitive struggle for the people's vote."

More specifically, I use as a measure of democracy the indicator ofpolitical rights compiled by Gastil and his followers (1982-83 and subsequent

issues) from 1972 to 1995. A related variable from Bollen (1990) is used for 1960and 1965. The Gastil concept of political rights is indicated by his basic1

definition: "Political rights are rights to participate meaningfully in the politicalprocess. In a democracy this means the right of all adults to vote and compete

for public office, and for elected representatives to have a decisive vote on publicpolicies." (Gastil, 1986-87 edition, p. 7.) In addition to the basic definition, the

classification scheme rates countries (somewhat impressionistically) as lessdemocratic if minority parties have little influence on policy.

Gastil applied the concept of political rights on a subjective basis toclassify countries annually into 7 categories, where group 1 is the highest level

of political rights and group 7 is the lowest. The classification was made by Gastiland his associates based on an array of published and unpublished information

about each country. The original ranking from 1 to 7 was converted here to ascale from 0 to 1, where 0 corresponds to the fewest political rights (Gastills rank

The Gastil data cover more than 138 countries, but my sample is more limited to reflect the2

availability of other data.

2

7) and 1 to the most political rights (Gastills rank 1). The scale from 0 to 1

corresponds to the system used by Bollen.The solid line in Figure 1 shows the time path of the unweighted average

of the democracy index for the countries that I am considering for the years1960, 1965, and 1972-95. The number of countries covered rises from 99 in

1960 to 109 in 1965 and 138 from 1972 to 1995. The figure shows that the2

mean of the democracy index peaked at 0.66 in 1960, fell to a low point of 0.44

in 1975, and rose subsequently to 0.59 in 1995. Figure 1 also demonstrates thatthe main source of the decline in democracy after 1960 is the experience in Sub

Saharan Africa. The dotted line shows that the average of the democracyindicator in Sub Saharan Africa peaked at 0.58 in 1960 (26 countries), then (for

43 countries) fell to low points of 0.19 in 1977 and 0.18 in 1989 before rising to0.40 in 1995. This pattern emerges because many of the African countries began

with ostensibly democratic institutions when they became independent in theearly 1960s, but most evolved into one-party dictatorships by the early 1970s.

(See Bollen [1990] for further discussion.) The democratization in Africa since1989 has been substantial; whether it will be sustained is not yet known.

For countries outside of Sub Saharan Africa, the dashed line in Figure 1shows that the average of the democracy index fell from 0.68 in 1960 (73

countries) to 0.55 in 1975 (95 countries). It then returned to 0.68 in 1995.Some of the analysis also uses the Gastil indicator of civil liberties. The

definition here is "civil liberties are rights to free expression, to organize ordemonstrate, as well as rights to a degree of autonomy such as is provided by

freedom of religion, education, travel, and other personal rights" (Gastil [1986-87edition, p.7]). Otherwise, the subjective approach is the same as the one used for

the political rights indicator. The original scale for the civil liberties index from1 to 7 has again been converted to 0 to 1, where 0 represents the fewest civil

liberties and 1 the most. In practice, as observed by Inkeles (1991), the indicatorfor civil liberties is extremely highly correlated with that for political rights. This

high degree of correlation does not apply if the indexes of political rights and civilliberties are compared with measures of economic freedom, such as Knack and

3

Keefer's (1995) indicator for maintenance of the rule of law (see below).

The democracy indicator takes on only seven discrete values between zero and one, but the3

linear specification on the right-hand side does not take this pattern into account. In practice,the most negative:fitted value turned out to be -0.02 for Indonesia in 1972, and the highest fittedvalue was 1.09 for the United States in 1995. Some improvement might be obtainable byadopting a nonlinear specification in which the dependent variable was constrained to theinterval (0,1).

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2. FRAMEWORK FOR THE DETERMINATION OF DEMOCRACY

Inspection of the cross-country data suggests that countries at low levelsof economic development typically do not sustain democracy. For example, the

political freedoms installed in most of the newly independent African states in theearly 1960s did not tend to last. Conversely, nondemocratic places that

experience substantial economic development tend to become more democratic.Examples include Chile, South Korea, Taiwan, Spain, and Portugal. Moreover, the

countries of central and eastern Europe - which have been reasonably advancedeconomically for some time, especially in terms of education eventually became

more democratic. Thus, a casual view of the data tends to confirm theLipset/Aristotle hypothesis.

To assess this hypothesis formally, I consider systems of the form

(1) DEMOC = a + a DEMOC + a DEMOC + a Z + u ,it 0 1 i,t-T 2 i,t-2T 3 i,t-T it

where i is the country, t is the time period, and T is a time lag, usually taken tobe five years. DEMOC is the indicator for democracy; Z is a vector of variables,

such as per capita GDP and education, that influence the extent of democracy;and u is an error term. The idea in equation (1) is that - if a >0, a > and 0<a +a <1 2 1 2

1 - then the extent of democracy in a country converges gradually over timetoward a (moving) target that is determined by the Z variables. In practice, the3

Z variables are themselves highly persistent over time.Operationally, I use a panel setup in which the dependent variable,

DEMOC , is observed at most six times for each country: 1972, 1975, 1980,it

1985, 1990, and 1995. (The year 1972 is the initial date of the Gastil sample.)

The variables Z refer to observations roughly five years prior to these dates,i,t-T

and DEMOC and DEMOC refer, respectively, to (approximately) five- andi,t-T i,t-2T

The empirical results turn out to be virtually the same if contemporaneous values of the Z4

variables are entered into equation (1) (that is, if the lag T is set to zero), but lagged values of theZ variables and the lags of democracy are used as instruments.

The GDP data are from Summers and Heston (1991, 1995) Descriptions of these and other5

variables are in the Barro-Lee data set, which is available on request.

The data on years of schooling are updated values described in Barro and Lee (1996).6

The IMF definition includes countries whose net oil exports represent a minimum of two-thirds7

of total exports and are at least equivalent to approjdmately one percent of world exports of oil. Adefinition based on OPEC membership would add Ecuador and subtract Bahrain and Oman.

5

ten-year lags of the dependent variable. (The values for DEMOC are for 1965,4t-T

1972, 1975, and so on.)

3. REGRESSION RESULTS FOR DEMOCRACY: STANDARD OF LIVING AND RELATED

VARIABLES

The basic regression results are in column 1 of Table 1. This system

contains the five-year and ten-year lags of democracy as regressors. Theexplanatory variables also include the log of real per capita GDP and measures5

of educational attainment. These indicators are observed roughly five years priorto the dependent variable. The schooling figures that turn out to have the most

explanatory power are the average years of attainment at the primary level forpersons aged 25 and over and the gap in average years of primary attainment

between males and females aged 25 and over.6

A dummy for oil-exporting countries, as designated by the IMF, is also7

included as a rough adjustment of GDP for the contribution of natural resources.That is, the income generated from natural resources such as oil may create less

pressure for democratization than income associated with the accumulation ofhuman and physical capital.

The specification includes some other possible influences on democracythat have been proposed in the political-science literature that began with Lipset

(1959); see Lipset, et al (1993) and Lipset (1994) for discussions. Theurbanization rate is often mentioned as a determinant of democracy, although the

sign of this influence is not clear on theoretical grounds. Some observers arguethat the rural population has limited ability to organize and is therefore easy for

The figures on urbanization are the standard ones reported by the World Bank.8

School attainment of persons aged 25 and over has slightly more explanatory power than9

attainment of persons aged 15 and over.

6

a dictator to suppress. But one could also argue that a less dense, rural

population is harder for the central authority to monitor and control. The simplecorrelation between democracy and urbanization is strongly positive, but

urbanization is also positively related to real per capita GDP and the othermeasures of the standard of living that are included as regressors. In any event,

the system includes as an explanatory variable the rate of urbanization observedfive years prior to the dependent variable.8

The system also contains a measure of country size, the log of the five-year earlier level of population. It is, however, not apparent a plod whether a

larger place is more or less likely to be democratic. One problem of interpretationis that country size is endogenous, as argued by Alesina and Spolaore (1995).

Places that are too large to be manageable are likely to have split apart sometimein the past.

The first observation from column 1 of Table 1 is that the estimatedcoefficient on the five-year lag of democracy is 0.61 (s.e.=0.04) and that on the

ten-year lag is 0.10 (0.04). Thus, democracy is highly persistent over time, butabout 25% of the adjustment to a target position (determined by the other

variables) occurs over 5 years and nearly 70% occurs over 20 years.The results are broadly highly supportive of the idea that more

prosperous places are more likely to be democratic. The estimated coefficients onlog(per capita GDP) and the level of primary schooling are each significantly

positive, 0.058 (0.016) and 0.013 (0.006), respectively. Thus, the target level ofdemocracy is increasing in these indicators of the standard of living.9

Democracy is also negatively and signfficantly related to the gap betweenmale and female primary attainment, with an estimated coefficient of -0.047

(0.013). That is, more equal educational opportunity across the sexes raises thetarget level of democracy. One possibility is that the gap between male and

female attainment is a proxy for general inequality of schooling and income.However, the inclusion of explicit measures of educational and income inequality

(discussed below) does not eliminate the explanatory power of the gap between

The value for 1970 enters into the first two equations, that for 1975 in the next two, and that10

for 1985 in the last two.

A country's land area is insignificant if it is added to the regressions as another indicator of11

country size.

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male and female schooling. Perhaps more promising is the idea, reminiscent of

Tocqueville (1835), that expanded educational opportunity for females goes alongwith a social structure that is generally more participatory and, hence, more

receptive to democracy.The oil-country dummy is significantly negative, -0.094 (0.031), thereby

indicating that the high level of per capita GDP associated with oil productiondoes not have the usual positive linkage with democracy. It seems plausible that

this result would extend to natural-resource availability more generally. To testthis idea, I introduced the measure of natural-resource intensity suggested by

Sachs and Warner (1995), the ratio of primary-product exports to total exports.10

However, this variable is insignificant if added to the system shown in column 1

of Table 1, -0.022 (0.033), and the oil dummy remains significant, -0.090 (0.035).One problem with the export-ratio variable is that it reflects a country's choices

on which production activities to focus on. Possibly a better measure ofexogenous natural-resource availability would outperform the oil dummy.

The urbanization rate enters negatively in the system shown in column1 of Table 1; the estimated coefficient is -0.095 (0.048). Thus, once indicators of

the standard of living are held constant, the association between urbanizationand democracy switches sign and becomes negative. That is, for a given standard

of living, it is not true that more rural places are less likely to be democratic.The estimated coefficient on the log of population is positive and

marginally significant, 0.0080 (0.0044). Thus, there is some indication that11

larger places are more likely to be democratic. However, as mentioned before, this

result might reflect the endogeneity of country size.The system shown in column 1 of Table 1 allows for different intercepts

in each of the equations; that is, for 1972, 1975, and so on. The estimatedcoefficient for each date - expressed as a deviation from the (unweighted) average

intercept - is shown in column 1 of Table 2. The second column of the tableshows the unweighted mean of the democracy indicator at each date for the

The pattern for the estimated intercepts in column 1 of Table 2 differs from that of mean12

democracy in column 2 because of the dynamic relation between democracy and the explanatoryvariables. In particular, a permanent downward shift in the intercept would reduce democracycontemporaneously and would imply further declines in democracy in future periods.

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observations that are included in the regression sample.

The pattern of estimated intercepts suggests, in the language ofHuntington (1991, p. 16), a wave whereby world democracy declined in the early

1970s, then rose in the early 1980s and again in the early 1990s. Note that12

these results apply for given values of the explanatory variables, which can also

generate patterns in world democracy. For example, positive trends in per capitaGDP and schooling would imply an upward trend in democracy. This result

seems reasonable because - when evaluated in terms of the Gastil concept ofpolitical participation - there have not been many full democracies in the world

until the twentieth century. Huntington (1991, p. 16) dates the first long wave ofdemocratization as 1828-1926.

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4. ADDITIONAL INFLUENCES ON DEMOCRACY

Table 3 considers some other possible determinants of democracy, manyof which have been proposed in the political-science literature. These additional

variables are entered one set at a time into the six-period regression systemdescribed in column 1 of Table 1.

1. Health IndicatorsThe first line of Table 3 adds a measure of health status - the log of life

expectancy at birth - as another indicator of the standard of living. The estimatedcoefficient is positive but only marginally significant, 0.13 (0.08). With life

expectancy included, the estimated coefficients of log(per capita GDP) andaverage years of primary attainment become less significant; the estimated

coefficients are now 0.042 (0.018) and 0.011 (0.006), respectively. Thus, it isdifficult to sort out precisely the measures of standard of living that matter for

democracy.Similar results apply if the infant mortality rate is used instead of life

expectancy as a measure of health status. Line 2 of Table 3 shows that theestimated coefficient of the infant mortality rate is -0.44 (0.30).

2. Upper-Level SchoolingThe third regression in Table 3 includes two additional schooling

variables: the average years of attainment for persons aged 25 and over at thesecondary and higher levels and the gap between male and female attainment for

persons aged 25 and over at these levels. These variables are individually andjointly insignificant, as shown, whereas the estimated coefficients on primary

schooling remain significant (0.014 [0.006] for years of attainment and -0.051[0.016] for the gap between males and females). Hence, it appears to be early

education that matters for democratization. Similar results apply to thedetermination of fertility rates and health status. However, as discussed in Barro

(1996), rates of economic growth and investment relate far more to secondary andhigher schooling than to primary education.

3. Inequality of Income and SchoolingRegression 4 of the table includes measures of income inequality, as

gauged by Gini coefficients for the distribution of income. (A higher Ginicoefficient signifies more inequality.) The data come from the careful compilation

The regressions use their "high-quality" observations, which exclude observations based on13

incomplete geographical coverage or incomplete measures of income. I have added to their high-quality set some observations that involve approximations but cover full income on a nationalbasis.

10

of information assembled recently by Deininger and Squire (1996). The13

underlying values were categorized as applying around 1970, 1980, and 1990and were entered accordingly into the regression system (see the notes to Table

3). Because of the limited availability of income-distribution data, the inclusionof the Gini coefficient substantially reduces the number of observations - to 51

for the 1972 equation, 56 for 1975, 60 for 1980 and 1985, and 68 for 1990 and1995. Within this truncated sample, the estimated coefficient on the Gini

coefficient is negative but only marginally significant, -0.15 (0.09). However, inthis small sample, some of the variables from the basic specification are also

statistically insignificant - average years of primary schooling, urbanization rate,the log of population, and the oil dummy. In any event, there is some indication

that - for given measures of the standard of living - greater income inequalitypredicts less democracy.

Some researchers stress a positive interaction between the size of themiddle class and the extent of democracy. To check this relation, regression 5 of

Table 3 includes in the regression system the share of income accruing to themiddle three quintiles (also complied from Deininger and Squire [1996]). Because

of the more severe limitation on data by quintile shares, this sample was evensmaller than that for the Gini coefficient. (With the middle-class variable

included, the numbers of observations for the various dates are 38, 40, 51, 51,65, and 65.) The estimated coefficient of the middle-class share is positive, 0.26

(0.15), but only marginally significant. However, in this sample, the estimatedcoefficients of average years of primary attainment, urbanization rate, the log of

population, and the oil dummy are even less significant.If the Gini coefficient is entered along with the middle-class share, then

the estimated coefficients are 0.05 (0.24) for the Gini (the "wrong" sign) and 0.32(0.38) for the middle-class share. The middle-class variable also appears to be the

more important indicator of inequality when it is entered jointly with the shareof the lowest or highest quintile. Thus, there is some evidence that the weight of

The value 1 can be thought of as the effective years of eduational human capital possessed by14

a person with no formal schooling.

Most of the data come from Miklukho-Maklaya Institute (1964), as reported in Taylor and15

Hudson (1972, Table 4.15). See Mauro (1995) for a discussion.

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the middle class is the aspect of inequality that matters most for democracy.

Another possibility is to use recently assembled data on educationalattainment at seven levels to construct measures of schooling inequality (see n.

6 above). Regression 6 of Table 3 uses as an independent variable the standarddeviation of log (l+years of schooling) for the population of both sexes aged 1514

and over. This variable is observed for 1965, 1970, and so on. The estimatedcoefficient is close to zero, -0.008 (0.046). The estimated coefficients of primary

schooling remain significant here, 0.013 (0.006) for average years of attainmentand -0.046 (0.016) for the male-female gap. If the Gini coefficient for years of

schooling is used as an alternative measure of educational inequality, then thefindings are similar. Hence, these results indicate that the primary enrolment

variables - and specifically the male-female gap - do not enter the regressionsmerely as proxies for educational inequality.

4. Ethnolinguistic FractionalizationThe population's degree of heterogeneity with respect to ethnicity,

language, and culture may also matter for democracy. The usual idea is thatmore heterogeneity makes it more difficult to sustain democracy. A standard

measure of a population's heterogeneity is its ethnolinguistic fractionalisation, ameasure of disparity of languages and ethnicity within a country. The variable15

runs between 0 and 1 and is intended to measure the probability that tworandomly chosen persons in a country will come from different groups. Hence,

0 is the most homogeneous, and 1 is the most heterogeneous.Regression 7 of Table 3 shows that the estimated coefficient of the

fractionalisation variable (observed once per country) is negative and marginallysignificant, -0.055 (0.028). Thus, there is some indication that more ethnically

diverse countries are less likely to sustain democracy.One possibility is that ethnic diversity reduces democratic tendency by

contributing to inequality. To test for this possibility, I included the middle-classshare of income along with the fractionalisation variable. The result was that the

The indicator was initially measured in 7 categories on a 0 to 6 scale, with 6 the most16

favorable. The scale has been revised here to 0 to 1, with 0 indicating the worst maintenance ofthe rule of law and 1 the best.

12

estimated coefficient of fractionalisation was essentially zero, 0.002 (0.036),

whereas that on the middle-class share was 0.24 (0.15), similar to that found inregression 5 of Table 3. It turns out, however, that the result does not reflect a

high correlation between the fractionalisation variable and the middle-class share(a correlation that is negative but small in magnitude) but rather the truncation

of the sample. Within the limited sample for which data on the middle-class shareare available, the estimated coefficient of the fractionalisation variable is

essentially zero even if the middle-class variable is omitted from the system.

5. The Rule of Law

Knack and Keefer (1995) discuss a variety of subjective country indexesof economic rights that have been prepared for fee-paying international investors

by International Country Risk Guide. The concepts covered include quality of thebureaucracy, political corruption, likelihood of government repudiation of

contracts, risk of government expropriation, and overall maintenance of the ruleof law. (The various time series cover 1982 to 1995 and are available for a fee

from Political Risk Services of Syracuse, New York.) The general idea is to gaugethe attractiveness of a country's investment climate by considering the

effectiveness of law enforcement, the sanctity of contracts, and the state of otherinfluences on the security of property rights. Although these data are subjective,

they have the virtue of being prepared contemporaneously by local experts.Moreover, the willingness of customers to pay substantial amounts for this

information is perhaps some testament to their validity.Among the various series available, the indicator for overall maintenance

of the rule of law seemed a priori to be the most relevant for investment and16

growth. My previous empirical work (Barro [1996]) confirms that this indicator

of economic rights is an important predictor of economic growth.The connection between political and economic rights is unclear, as

stressed by Sirowy and Inkeles (1990) and Przeworski and Limongi (1993). Thesimple correlations between the democracy and rule-of-law indicators are 0.64

in 1982, 0.55 in 1985, and 0.60 in 1990, and 0.49 in 1995. These correlations

13

are much smaller that those between the democracy and civil-liberties indexes

(see below).Regression 8 of Table 3 checks out the relationship between political

freedom and the rule of law by entering lagged values of the rule-of-law index intothe equations for democracy. Since the data on the rule of law begin in 1982, this

system includes only the equations for democracy for 1985, 1990, and 1995.(The second lag of the dependent variable is excluded here.) The values for the

rule of law in this system apply to 1982, 1985, and 1990. The result is that theestimated coefficient on the rule-of-law variable is positive but insignificant,

0.031 (0.057). Thus, holding fixed the measures of standard of living, there is notmuch timing evidence that better maintenance of the rule of law promotes

political freedom.The rule-of-law measure can also be viewed as the dependent variable in

a system where the independent variables are its own lags and the lags of theother variables, including the democracy index. (Three equations - for 1985,

1990, and 1995 - are used here.) In this setting, democracy turns out to enterwith a positive coefficient, 0.023 (0.026), which is not statistically significant.

Thus, there is also not strong timing evidence that political freedom stimulatesthe maintenance of the rule of law.

6. Colonial HistoryColonial heritage would be important for democracy if countries inherit

tendencies for more or less political freedom from their previous rulers. Forexample, Lipset, et al (1993, p. 168) argue that British rule provided a crucial

learning experience for subsequent democracy. In Table 4, a non-colony isdefined to be a country that was independent prior to and since 1775 (so that the

United States is treated as a former possession of Britain). Each former colonyis attributed to its most recent occupier; for example, the Philippines is

associated with the United States rather than Spain, Rwanda and Burundi areattached to Belgium rather than Germany, and several Caribbean countries are

related to Britain rather than Spain. The classification treats as non-coloniesplaces such as South Korea, Taiwan, Hungary, and Poland, which were occupied

by a foreign power for some periods.The first section of Table 4 shows that the 32 non-colonies are more likely

to be democratic (average value for the democracy indicator from 1975 to 1995

The underlying data, from the World Christian Encyclopedia (Barrett [1982]) are estimates of17

professed affiliation in 1970 and 1980. (Figures are also available for 1900.) This informationtakes no account of regularity of church attendance or amounts spent on religious activities. Thedata provided in the encyclopedia are compiled from the most authoritative local sources,published or unpublished, including government censuses of religion. A large part of the datawere collected directly by the editors, who visited virtually all of the countries over the years1965-75. The basic concept of a religious adherent is that the person professes to believe in thereligion when government censuses or public opinion polls ask the question, "What is yourreligion?" Each person is considered to have at most one religious affiliation. Further work oncross-country religion data is ongoing.

14

of 0.69) than are the colonies (average value of 0.46). Within the colonies, the

former possessions of Britain and Spain are substantially more democratic thanare those of France, Portugal, or other countries. (The former Spanish colonies

in Latin America would, however, look less democratic at some earlier dates.)In the statistical analysis, with the measures of standard of living held

constant, regression 9 of Table 3 shows that a dummy variable for colonial status(1 for former colony, 0 for non-colony) is negative, but statistically insignificant,

-0.018 (0.018). Moreover, regression 10 shows that a breakdown among British,French, Spanish, Portuguese, and other colonies fails to generate any significant

coefficients. The p-value for joint significance of the five colony dummies is 0.33.These results, in conjunction with Table 4, suggest that the influence of former

colonial status on democratic tendency mostly works indirectly through effectson the standard of living, as measured here particularly by per capita GDP and

primary schooling. These indirect links with colonial history are worth furtherstudy.

7. ReligionReligious affiliation has also been stressed as an important determinant

of democracy; see Huntington (1991, pp. 71-85), Lipset (1994, p. 5), and Boone(1996, pp. 25-28). (The theory of the interplay between religion and political

structure is even less developed than are other aspects of the theory ofdemocracy.)

To check for a connection between religion and political freedom, I usedata compiled by Jong-Wha Lee on the fractions of a country's population in

1970 and 1980 affiliated with nine major groups: Catholic, Muslim, Protestant17

(including Anglican, eastern orthodox, and some other Christian groups), Hindu

The system allows for some variation over time in religious affiliation in that the 1970 religion18

figures appear in the first three equations for democracy, and the 1980 figures enter into the lastthree equations. However, in most cases, the variations in religious affiliation between 1970 and1980 are minor. If the 1970 values are included in all seven equations, then the results arevirtually indistinguishable from those shown in regression 11 of Table 3.

15

(including Jains and Sikhs), Buddhist, miscellaneous eastern religions (Chinese

folk religions, Shinto, Confucianism, and new-religionists), Jewish, no professedreligion (including atheists), and other religious groups (such as Parsis, Bahais,

Spiritists, tribal religions, and indigenous third-world Christians).The second section of Table 4 verifies that differences in a country's

primary religious affiliation relate strongly to democracy. When countries aresorted in accordance with their most popular religion in 1980, the average of the

democracy indicator from 1975 to 1995 is 0.86 for Jewish (1 country), 0.78 forProtestant (24 countries), 0.66 for Hindu (5 countries), 0.61 for Catholic (49

countries), 0.56 for Buddhist (4 countries), 0.46 for miscellaneous easternreligions (3 countries), 0.29 for other religions (17 countries), and 0.26 for

Muslim (32 countries). China is the only place in which non-religion is the mostcommon affiliation, and the average of the democracy index in this case is 0.10.

The mean value of democracy for all 136 countries with data on religion is 0.51.A prominent aspect of this breakdown is that Protestant countries are

nearly always highly democratic, whereas Muslim countries are usually notdemocratic. Only 4 of the 32 Muslim countries have democracy indicators that

averaged at least 0.5 for 1975-95: Gambia (0.70), Senegal (0.50), Malaysia (0.57),and Turkey (0.62).

Regression 11 of Table 3 shows the results when eight religious affiliationvariables are entered into the equations for democracy. (The omitted18

characteristic is chosen arbitrarily to be Catholic, the most prevalent religionwhen countries are weighted equally.) The regressions indicate that the most

significant religion coefficients are for Muslim, -0.004 (0.026); non-religion, -0.26(0.09); and other religion, -0.104 (0.049).

The p-value of 0.001 indicates that the eight religion coefficients aresignificant overall. However, some of this significance hinges on the presence of

a few outlier observations. For example, the positive coefficient on Hindu mainlyindicates that India and Mauritius are surprisingly democratic, given their

The 1980 value of non-religion for China is 0.71. The other values that exceed 0.1 are 0.35 for19

Uruguay; 0.29 for Sweden; 0.17 for Yugoslavia; 0.16 for Italy, Hungary, and France; 0.15 forAustralia; 0.14 for Hong Kong; and 0.12 for the Netherlands and Japan.

A formal test rejects equality of the coefficients in the systems for democracy and civil liberties. 20

Viewed individually, however, the only estimated coefficients that are found to differ significantlyat the 5% critical level are those for the lagged dependent variables, log of population, and theconstant terms.

16

indicators of the standard of living. If these two places are omitted from the

sample, then the estimated coefficient on Hindu falls to 0.002 (0.063). Thesignificance of the negative coefficient on non-religion depends on the inclusion

of China, the one country for which this affiliation exceeds 0.5. If China is19

omitted, then this coefficient becomes -0.25 (0.13). Probably the most interesting

finding is the significantly negative coefficient on the Muslim variable, even whenthe measures of standard of living and the other explanatory variables are held

constant.The estimated coefficients understate the potential consequence of

religion for democracy because of the potential effects of religion on some of theexplanatory variables, especially the gap between male and female education and

the indicators of the standard of living. In fact, the main effects of religion ondemocracy are likely to work through these indirect channels. Given the striking

patterns that emerge in Table 4, these linkages are worth further investigation.

5. CIVIL LIBERTIES

The democracy indicator is a narrow procedural measure that focuses onpolitical rights, specifically on the role of elections. In contrast, the Gastil index

of civil liberties is a broader concept that covers freedoms of speech, press, andreligion, and also considers a variety of legal protections. In practice, however,

the civil-liberties variable is highly correlated with the democracy index: 0.86 in1972, 0.93 in 1980, 0.94 in 1990, and 0.92 in 1995.

Given this high degree of correlation, it is not surprising that results withthe civil-liberties index as the dependent variable - shown in column 2 of Table

1 - look similar to those found for the democracy index. This result suggests20

that the economic and social forces that promote political rights are similar to

17

those that stimulate civil liberties.

More precisely, the model shows how initial democracy and the values of the other explanatory21

variables influence the probabilities of transition over time among the seven discrete rankings ofdemocracy.

The projected value equals [1/(1 - coefficient of first lag of democracy - coefficient of second lag22

of democracy)] * (estimated value based on explanatory variables other than lags of democracy).

18

6. LON-RUN FORECASTS OF DEMOCRACY

The estimated relation from column 1 of Table 1 implies a gradualadjustment of democracy toward the values determined by the explanatory

variables aside from lagged democracy. In a full system, the dynamics of these21

explanatory variables would also be determined. In practice, the level of per

capita GDP and the other variables are highly persistent over time, although theyevolve gradually in line with the process of economic development, some of which

has been studied in previous research in terms of rates of economic growth.One simple way to relate the current level of democracy to its long-run

target is to compute at each date the estimated level of democracy that wouldarise asymptotically if all the right-hand-side variables (aside from the lags of

democracy) were held fixed at their current values. For example, in 1975, thelong-run level of democracy is calculated from the 1970 values of the regressors

included in column 1 of Table 1. The resulting projected values for 1975 and22

1995 are shown along with the actual values in Table 5. The gap is the difference

between the current level of democracy and its long-run target. Values of the gapthat exceed 0.33 in magnitude are shown in boldface.

In 1975, out of 101 countries with the necessary data, 5 were below thelong-run target for democracy by at least 0.33, and 21 were above by at least

0.33. In 1995, out of 100 places with the required data, 16 were below target byat least 0.33, and 5 were above target by at least 0.33.

One striking observation is that no countries appear with the same signon both lists (although Yugoslavia came close). With an estimated rate of

convergence for democracy of about one-quarter per five-year period (from thecoefficients on the lags of democracy in column 1 of Table 1), a lot of reversion

to the mean occurs over 20 years.Among the Sub Saharan African countries, Botswana, Gambia, and

Mauritius (if Mauritius is classed with Africa) looked "too democratic" in 1975,

19

but the situation for Gambia changed with a coup in 1994. Botswana and

Mauritius were still above target for democracy in 1995 but by much smalleramounts than in 1975.

A surge of democratization since the late 1980s meant that many of thecountries in Sub Saharan Africa became more democratic than predicted by

1995. This group includes Benin, Central African Republic, Guinea-Bissau,Malawi, Mali, Niger, and Zambia. In some of these cases, the democratization

may be explicable from the pressures and rewards exerted by internationalorganizations, such as the IMF and the World Bank. (The recent U.S. efforts in

Haiti are analogous.) In any case, the regression analysis predicts that, as withthe African experience of the 1960s, democracy that gets well ahead of economic

development will not last. As a possible indicator of this process, Niger had amilitary coup in January 1996 and then became nondemocratic.

Some Sub Saharan African countries still had below-target levels ofdemocracy in 1995. Prominent here are Cameroon, Kenya, Rwanda, Sierra Leone,

Sudan, and Swaziland. (Nigeria and Somalia would likely be included in thiscategory but have missing data and are therefore excluded from Table 5.)

For Latin America in 1975, several countries were surprisinglynondemocratic, including Panama, Chile, and Ecuador. All of these places

subsequently experienced sharp increases in political freedom. In 1995, Boliviahad more democracy than would be predicted from its economic situation. Mexico

and Peru were below target in 1995 and are predicted to become moredemocratic.

Among Asian countries, surprisingly low democracy prevailed in 1995 inChina, Hong Kong, Indonesia, Singapore, and Syria. The model predicts increases

in democracy in these cases, but the model has not been informed of HongKong's post-1997 relationship with China. It will be especially interesting to see

whether prosperous Singapore joins South Korea and Taiwan in their markeddemocratizations.

On the other side, democracy was higher than predicted in 1975 forIndia, Indonesia, Malaysia, Sri Lanka, and Thailand. However, with the decline

in Gastills measure of democracy (in 1991 and 1993), India no longer looked likean outlier in 1995. Indonesia, Malaysia, Sri Lanka, and Thailand were all below

target in 1995.

20

Because of lack of data, only three countries from central or eastern

Europe are represented in the sample: Hungary, Poland, and Yugoslavia. In eachof these cases, democracy was strikingly below its target level in 1975. Two

countries in western Europe - Portugal and Spain - were also somewhat belowtarget. By 1995, all of these countries except Yugoslavia had - as predicted -

become far more democratic. The model forecasts a large increase of democracyin Yugoslavia, which should perhaps now be identified with Serbia. The model

also predicts substantial democratization for Turkey, which was surprisinglynondemocratic in 1995.

21

7. CONCLUDING OBSERVATIONS

The positive relation between democracy and prior measures of prosperity- the Lipset/Aristotle hypothesis - is well established as an empirical regularity.

Given the strength of this association, it is surprising that convincing theoreticalmodels of the relation do not exist. Thus, development of such a theory is a

priority for future research.At the empirical level, it would be especially interesting to investigate

further the relation of democracy to inequality, colonial status, and religion.Hopefully, the development of satisfactory theories of the determination of

democracy will suggest additional empirical linkages that ought to be explored.

22

REFERENCES

Alesina, Alberto and Enrico Spolaore (1995). "On the Number and Size ofNations," unpublished, Harvard University, October.

Aristotle (1932). Politics, translated by H. Rackham, Cambridge MA, HarvardUniversity Press.

Barrett, David B., editor (1982). World Christian Encyclopedia, Oxford, OxfordUniversity Press.

Barro, Robert J. (1996). "Democracy and Growth," Journal of Economic Growth,1, 1 (March), 1-27.

Barro, Robert J. and Jong-Wha Lee (1996). "International Measures of SchoolingYears and Schooling Quality," Amedcan Economic Review (May).

Bollen, Kenneth A. (1990). "Political Democracy: Conceptual and MeasurementTraps," Studies in Comparative International Development, Spring, 7-24.

Boone, Peter (1996). "Political and Gender Oppression as a Cause of Poverty,"unpublished, London School of Economics, April.

Deininger, Klaus and Lyn Squire (1996). "Measuring Income Inequality: A NewData-Base," unpublished, The World Bank, March.

Easterly, William and Ross Levine (1996). "Africa's Growth Tragedy," presentedat the HIID Economic Growth Conference, Harvard University, May.

Gastil, Raymond D. and followers (1982-83 and other years). Freedom in theWorld, Westport CT, Greenwood Press.

Gastil, Raymond D. (1991). "The Comparative Survey of Freedom: Experiencesand Suggestions," in Alex Inkeles, ed., On Measuring Democracy, New

Brunswick NJ, Transaction Publishers.Huber, Evelyne, Dietrich Rueschemeyer, and John D. Stephens (1993). "The

Impact of Economic Development on Democracy," Journal of EconomicPerspectives, 7, Summer, 71-85.

Huntington, Samuel P. (1991). The Third Wave: Democratization in the LateTwentieth Century, Norman, Oklahoma, University of Oklahoma Press.

Inkeles, Alex (1991). On Measuring Democracy., New Brunswick NJ,Transaction Publishers.

Knack, Stephen and Philip Keefer (1995). "Institutions and Economic

23

Performance: Cross-Country Tests Using Alternative Institutional

Measures," Economics and Politics, 7, 207-227.

Lipset, Seymour Martin (1959). "Some Social Requisites of Democracy: EconomicDevelopment and Political Legitimacy," American Political Science Review,

53, 69-105.Lipset, Seymour Martin (1994). "The Social Requisites of Democracy Revisited,"

American Sociological Review, 59 (February), 1-22.Lipset, Seymour Martin, Kyoung-Ryung Seong, and John Charles Torres (1993).

"A Comparative Analysis of the Social Requisites of Democracy,"International Social Science Journal (May), 155-175.

Mauro, Paolo (1995). "Corruption, Country Risk, and Growth," Quarterly Journalof Economics, 110 (October).

N.N. Miklukho-Maklaya Institute of Ethnography of the Academy of Sciences(1964). Atlas Narodov Mira, Moscow, Department of Geodesy and

Cartography of the State Geological Committee of the USSR.Przeworski, Adam and Fernando Limongi (1993). "Political Regimes and

Economic Growth," Journal of Economic Perspectives, 7, Summer, 51-69.Putnam, Robert D., with Robert Leonardi and Raffaella Y. Nanetti (1993). Making

Democracy Work, Civic Traditions in Modern Italy, Princeton NJ,Princeton University Press.

Sachs, Jeffrey D. and Andrew M. Warner (1995). "Natural Resource Abundanceand Economic Growth, " unpublished, Harvard Institute for International

Development, December.Schumpeter, Joseph A. (1947). Capitalism, Socialism, and Democracy, 2nd

edition, New York, Harper.Sirowy, Larry and Alex Inkeles (1990). "The Effects of Democracy on Economic

Growth and Inequality: a Review," Studies in Comparative InternationalDevelopment, 25, Spring, 126-157.

Summers, Robert and Alan Heston (1991). "The Penn World Table (Mark 5): AnExpanded Set of International Comparisons, 1950-1988,11 Quarterly

Journal of Economics, 106, 2 (May), 327-368.Summers, Robert and Alan Heston (1995). "Penn World Tables, Version 5.6,"

available on diskette from the National Bureau of Economic Research,

24

Cambridge MA. Taylor, Charles Lewis and Michael C. Hudson (1972).

World Handbook of Political and Social Indicators, 2nd edition, NewHaven, Yale University Press.

Tocqueville, Alexis de (1835). Democracy in America, translated by Henry Reeve,London, Saunders & Otley.

25

Table 1:

Regressions for Democracy and Civil-Liberties Indexes

dependent variable: (1) democracy (2) civil liberties

independent variable:

five-year lag of dependent 0.608 0.536

variable (0.041) (0.041)

ten-year lag of dependent 0.102 0.148

variable (0.040) (0.039)

log (GDP) 0.058 0.054

(0.016) (0.014)

years of primary schooling 0.0134 0.0143

(0.0059) (0.0051)

gap between male and female - 0.047 - 0.043

primary schooling (0.013) (0.011)

urbanization rate - 0. 095 - 0.075

(0.048) (0.041)

log(population) 0.0080 0.0012

(0.0044) (0.0038)

oil-country dummy - 0.094 - 0.096

(0.031) (0.027)

R 2 .62, .76, .67 .63, .81, .77

.76, .76, .56 .82, .75, .70

number of observations 76, 88, 102 76, 88, 102

102, 103, 100 102, 103, 100

Note: The systems have six equations, where the dependent variables are the values of the

democracy or civil-liberties indexes for 1972, 1975, 1980, 1985, 1990, and 1995. The five-year lag

is for 1965, 1972, 1975, and so on. The ten-year lag is for 1960, 19659 1972, etc. The variables GDP

(real per-capita GDP), primary schooling (years of attainment for persons aged 25 and over at the

primary level), the gap between male and female primary schooling, urbanization rate, and population

refer to 1965, 1970, etc. The oil dummy equals 1 for countries designated as oil exporting by the IMF

and 0 otherwise.

Each system contains a different constant for each time period. The estimation, by the SUR

technique, weights countries equally but allows for different error variances in each period and for

26

correlation of these errors over the periods. Standard errors of the estimated coefficients are shown

in parentheses. The R 2 values apply to each period individually.

27

Table 2:

Variations in Democracy over Time

Year (1) (2)

Estimated constant term Sample mean of

(relative to average) democracy index

1972 -0.092 (0.024) 0.54

1975 -0.047 (0.019) 0.47

1980 0.043 (0.020) 0.54

1985 0.035 (0.016) 0.58

1990 0.023 (0.017) 0.59

1995 0.038 (0.022) 0.64

Note: Column 1 shows the estimated constant term for the indicated date from the system in

column 1 of Table 1. The estimate is expressed as a deviation from the average of the constants over

the six periods. The standard error of the coefficient estimate is shown in parentheses. The p-value

for the hypothesis of equal constant terms is 0.0000. Column 2 is the mean of the democracy index

over the sample included in the regression system for the indicated date.

28

Table 3

Additional Determinants of Democracy

independent variables regression

coefficients

1. log(life expectancy at birth) 0.129 (0.079)

2. infant mortality rate -0.44 (0.30)

3. years of upper schooling -0.008 (0.011)

gap between male and female 0.010 (0.024)

upper schooling p-value=0.76

4. income inequality (Gini coefficient) -0.15 (0.09)

5. share of middle class in income 0.26 (0.15)

6. educational inequality (standard deviation of log[l+years of -0.008 (0.046)

schooling for population aged 15 and over)

7. ethnolinguistic fractionalisation -0.055 (0.028)

8. rule-of-law index 0.031 (0.057)

9. dummy for former colony -0.018 (0.018)

10. dummy for British colony -0.031 (0.018)

dummy for French colony -0.020 (0.026)

dummy for Spanish colony 0.007 (0.022)

dummy for Portuguese colony 0.022 (0.048)

dummy for other colony -0.032 (0.034)

p-value=0.33

11. Muslim religion fraction -0.094 (0.026)

Protestant religion fraction 0.025 (0.030)

Hindu religion fraction 0.054 (0.050)

Buddhist religion fraction 0.011 (0.047)

Miscellaneous eastern religion fraction -0.075 (0.073)

Jewish religion fraction 0.049 (0.073)

Non-religion fraction -0.256 (0.092)

Other religion fraction -0.104 (0.049)

p-value=0.001

29

Notes to Table 3:

The indicated groups of explanatory variables are added, one at a time, to the system for the

democracy index shown in column 1 of Table 1. (Case 8 applies only to the three periods that start

with the value of the democracy index for 1985.)

Life expectancy at birth applies to 1965-69, 1970-74, etc. The infant mortality rate applies

to 1965, 1970, etc. Upper schooling (from Barro and Lee [1996]) is the years of secondary and higher

schooling for persons aged 25 and over in 1965, 1970, etc. The Gini coefficient for income inequality

and the income share of the middle class (the three middle quintiles of income) are from Deininger

and Squire (1996) and apply around 1970 in the first two equations, around 1980 in the next two

equations, and around 1990 in the last two equations. A higher number for the Gini coefficient

signifies more inequality. Educational inequality.(from Barro and Lee [1996]) is the standard

deviation of log(l+years of schooling) for the population aged 15 and over in 1965, 1970, etc. The

ethnolinguistic fractionalisation variable, which runs between 0 and 1, is a measure of heterogeneity

of language and ethnicity. The number, observed once for each country, represents the probability

that two randomly selected persons will come from different groups; hence, a higher value signifies

more heterogeneity. See lauro (1995) for a discussion of these data. The rule-o _ law index discussed

by Knack and leefer (1995) and available for 1982-95 from Political Risk Services, is a subjective

'indicator of the extent of maintenance of the rule of law. The variable runs from 0 to 1, with a higher

value indicating a more favorable environment.

Colony is a dummy for countries that are former or present colonies, where any country that

was independent before 1776 is designated as a non-colony. In case 10, dummies for former British,

French, Spanish, Portuguese, and other colonies are added together to the system from column 1 of

Table 1. Colonial status is based on the most recent ruler; for example, the Philippines is attributed

to the United States, rather than Spain.

In case 11, the fractions of the population affiliated with eight major religious groups are

entered together into the system from column 1 of Table 1. The left-out religion category is Catholic.

The religion data are for 1970 (in the first three eq ' uations) and 1980 (in the last three equations)

and come from Barrett (1982). The Protestant group includes Anglicans, eastern orthodox, marginal

Protestants (Jehovahls Witnesses, Normons, new-age cults), and cryto-Christiansu@secret believers

in Christ not professing publicly). Eastern religions incl e Chinese folk religions, Shinto,

Confucianism, and new-religions. The non-religion category comprises those professing no religion

and atheism. Other rell ions in lude Parsis, Spiritists, tribal religions, indigenous third-world ristians

not of western importation, and Bahais. Jains and Sikhs are classed with Hindus.

30

Table 4:

Democracy in Relation to Colonial Status and Religion

I. Colonial Status

Colonial status Number of countries Democracy indicator

(average 1975-95)

non-colony 32 0.69

colony 106 0.46

British colony 53 0.54

French colony 23 0.26

Spanish colony 16 0.60

Portuguese colony 5 0.30

Other colony 9 0.36

all countries 138 0.52

II. Religious affiliation

Primary religious affiliation in Number of countries Democracy indicator

1980 (average1975-95)

Catholic 49 0.61

Muslim 32 0.26

Protestant 24 0.78

Hindu 5 0.66

Buddhist 4 0.56

Misc. eastern religions 3 0.46

Jewish 1 0.86

non-religious 1 0.10

other religion 17 0.29

all countries with data on religion 136 0.51

Note: See the discussion in the text and Table 3 for definitions of colonial status and religious

affiliation. Section II shows averages for 1975-95 of the democracy measure for groups of countries

in which the most common religious affiliation in 1980 is of the indicated type.

31

32

Table 5:

Actual and Long-Run Values of Democracy

Country Democ.7 Democ. Democ. Democ. Democ.9 Democ.9

5 75 75 95 5 5

actual projected gap actual projected gap

Algeria 0.17 (-0.14) (0.31) 0.17 0.26 -0.09

Benin 0.00 0.23 -0.23 0.83 0.36 0.47

Botswana 0.83 0.26 0.57 0.83 0.75 0.09

Cameroon 0.17 0.08 0.08 0.00 0.44 -0.44

Cent. Afr. Rep. 0.00 0.03 -0.03 0.67 0.21 0.45

Congo 0.33 -- -- 0.50 0.56 -0.06

Egypt 0.17 0.15* 0.01 0.17 0.48 -0.31

Gambia 0.83 0.06* 0.78 0.00 0.33 -0.33

Ghana 0.00 0.09 -0.09 0.50 0.33 0.17

Guinea-Bissau 0.17 -- -- 0.67 0.33** 0.33

Kenya 0.33 0.04 0.30 0.00 0.40 -0.40

Lesotho 0.33 0.32 0.01 0.50 0.81 -0.31

Liberia 0.17 0.08 0.09 0.00 -- --

Malawi 0.00 (-0.03) (0.03) 0.83 0.28 0.55

Mali 0.00 0.03 -0.03 0.83 0.34 0.49

Mauritius 0.83 0.20 0.63 1.00 0.79 0.21

Mozambique 0.17 0.33 -0.17 0.67 0.40 0.27

Niger 0.00 0.19 -0.19 0.67 0.36 0.31

Rwanda 0.00 0.19 -0.19 0.00 0.39 -0.39

Senegal 0.17 0.14 0.03 0.50 0.44 0.06

Sierra Leone 0.17 0.20 -0.03 0.00 0.38 -0.38

South Africa 0.50 0.55 -0.05 1.00 0.78 0.22

Sudan 0.17 0.22 -0.06 0.00 0.47 -0.47

Swaziland 0.17 0.37 -0.20 0.17 0.65 -0.48

Tanzania 0.17 0.08** 0.09 0.33 0.33** 0.00

33

Togo 0.00 0.06 -0.06 0.17 0.22 -0.05

Tunisia 0.17 0.14 0.03 0.17 0.53 -0.37

Uganda 0.00 0.10 -0.10 0.33 0.34 -0.01

Zaire 0.00 (-0.01) (0.01) 0.00 0.16 -0.16

Country Democ.7 Democ. Democ. Democ. Democ.9 Democ.9

5 75 75 95 5 5

actual projected gap actual projected gap

Zambia 0.33 0.01 0.32 0.67 0.16 0.51

Zimbabwe 0.17 0.18 -0.02 0.33 0.49 -0.15

Barbados 1.00 0.65 0.35 1.00 1.00 0.00

Canada 1.00 0.82 0.18 1.00 (1.23) (-0.23)

Costa Rica 1.00 0.49 0.51 1.00 0.85 0.15

Dominican 0.50 0.31 0.19 0.50 0.62 -0.12

Republic

El Salvador 0.83 0.21 0.62 0.67 0.62 0.05

Guatemala 0.50 0.32 0.18 0.50 0.66 -0.16

Haiti 0.17 0.16 0.01 0.33 0.28 0.06

Honduras 0.17 0.27 -0.11 0.67 0.62 0.04

Jamaica 1.00 0.49 0.51 0.83 0.75 0.08

Mexico 0.50 0.32 0.18 0.50 0.89 -0.39

Nicaragua 0.33 0.35 -0.02 0.50 0.49 0.01

Panama 0.00 0.44 -0.44 0.83 0.82 0.01

Trinidad & 0.83 0.64 0.20 1.00 0.96 0.04

Tobago

United States 1.00 0.95 0.05 1.00 (1.30) (-0.30)

Argentina 0.50 0.57 -0.07 0.83 0.87 -0.04

Bolivia 0.17 0.15 0.02 0.83 0.51 0.32

Brazil 0.50 0.43 0.07 0.83 0.82 0.01

Chile 0.00 0.49 -0.49 0.83 0.79 0.04

Colombia 0.83 0.36 0.48 0.50 0.82 -0.32

Ecuador 0.00 0.36 -0.36 0.83 0.76 0.08

Guyana 0.50 0.40 0.10 0.83 0.66 0.17

34

Paraguay 0.33 0.30 0.04 0.50 0.71 -0.21

Peru 0.17 0.29 -0.12 0.33 0.61 -0.28

Uruguay 0.33 0.50 -0.17 0.83 0.82 0.02

Venezuela 0.83 0.21 0.62 0.67 0.51 0.15

Bahrain 0.17 -- -- 0.17 0.47 -0.30

Bangladesh 0.00 0.25 -0.25 0.67 0.55 0.11

China 0.00 0.12* -0.12 0.00 0.54 -0.54

Hong Kong 0.67 0.12 0.54 0.50 0.92 -0.42

India 0.83 0.10 0.74 0.50 0.48 0.02

Country Democ.7 Democ. Democ. Democ. Democ.9 Democ.9

5 75 75 95 5 5

actual projected gap actual projected gap

Indonesia 0.33 (-0.19) (0.53) 0.00 0.38 -0.38

Iran 0.17 0.11 0.06 0.17 0.31 -0.14

Iraq 0.00 0.05 -0.05 0.00 0.04 -0.04

Israel 0.83 0.50 0.33 1.00 0.96 0.04

Japan 0.83 0.76 0.07 1.00 (1.21) (-0.21)

Jordan 0.17 0.02 0.14 0.50 0.45 0.05

South Korea 0.33 0.25 0.08 0.83 0.94 -0.10

Malaysia 0.67 0.13 0.53 0.50 0.77 -0.27

Nepal 0.17 0.22 -0.05 0.67 0.45 0.22

Pakistan 0.33 0.16 0.17 0.67 0.50 0.17

Philippines 0.33 0.44 -0.11 0.83 0.86 -0.03

Singapore 0.33 0.01 0.32 0.33 0.79 -0.45

Sri Lanka 0.83 0.30 0.54 0.50 0.81 -0.31

Syria 0.17 0.13 0.04 0.00 0.57 -0.57

Taiwan 0.17 0.25 -0.08 0.67 0.96 -0.30

Thailand 0.83 0.35 0.48 0.67 0.95 -0.28

Austria 1.00 0.68 0.32 1.00 (1.07) (-0.07)

Belgium 1.00 0.83 0.17 1.00 (1.16) (-0.16)

Cyprus 0.50 0.36 0.14 1.00 0.93 0.07

35

Denmark 1.00 0.83 0.17 1.00 (1.20) (-0.20)

Finland 0.83 0.93 -0.10 1.00 (1.30) (-0.30)

France 1.00 0.76 0.24 1.00 (1.12) (-0.12)

West Germany 1.00 0.91 0.09 1.00 (1.26) (-0.26)

Greece 0.83 0.45 0.38 1.00 0.79 0.21

Hungary 0.17 0.80 -0.64 1.00 (1.01) (-0.01)

Iceland 1.00 0.56 0.44 1.00 0.97 0.03

Ireland 1.00 0.68 0.32 1.00 (1.10) (-0.10)

Italy 1.00 0.70 0.30 1.00 (1.05) (-0.05)

Malta 1.00 0.30 0.70 1.00 -- --

Netherlands 1.00 0.75 0.25 1.00 (1.09) (-0.09)

Norway 1.00 0.80 0.20 1.00 (1.12) (-0.12)

Poland 0.17 0.62 -0.46 1.00 (1.04) (-0.04)

Country Democ.7 Democ. Democ. Democ. Democ.9 Democ.9

5 75 75 95 5 5

actual projected gap actual projected gap

Portugal 0.33 0.44 -0.10 1.00 0.94 0.06

Spain 0.33 0.61 -0.27 1.00 (1.06) (-0.06)

Sweden 0.83 0.70 0.13 1.00 (1.11) (-0.11)

Switzerland 1.00 0.86 0.14 1.00 (1.20) (-0.20)

Turkey 0.67 0.28 0.39 0.33 0.75 (-0.42)

United Kingdom 1.00 0.77 0.23 1.00 (1.19) (-0.19)

Yugoslavia 0.17 0.44 -0.27 0.17 0.81 -0.64

Australia 1.00 0.83 0.17 1.00 (1.18) (-0.18)

Fiji 0.83 0.33 0.50 0.50 0.83 -0.33

New Zealand 1.00 0.81 0.19 1.00 (1.13) (-0.13)

Papua New 0.67 0.34 0.33 0.83 0.54 0.29

Guinea

Note: Projected values are based on the estimated system shown in Table 1, column 1. The 1975

projection is [1/(l-coeff. of first lag of democracy-coeff. of second lag of democracy)]*(estimated value

based on other variables included in the 1975 equation). The 1995 projection is formed analogously.

Values in parentheses are linearly fitted values that lie outside the range (0,1). Values shown in bold

36

have a magnitude of at least 0.33.

* Projected value for 1975 uses 1975 schooling values because of missing data for 1970.

** Projected value based on estimated schooling value for persons aged 25 and over based on

available data for persons aged 15 and over.