Institutional duration and growth in Africa

Institutional Duration and Growth in Africa*

Karen E. Ferree and Smita Singh

We argue that there are strong reasons to believe that continuous competitive, multiparty elections produce different growth dynamics than first competitive elections. We test this conjecture by looking at the effects of competitive elections and their endurance on growth rates in African countries from 1970 to 2001. We find that initial competitive elections do not offer a growth dividend over having no elections at all, although noncompetitive elections may result in a growth penalty. However, over time, countries that hold competitive elections slowly begin outperforming those without them-----especially those that hold noncompetitive elections. Africa's poor growth experience may therefore be related less to an unwillingness to experiment with democracy, than to an inability to consolidate democratic reforms once in place.

Introduction

M 'ul t iple studies have shown that Afr ica 's economic performance during .the past several decades has been dismal, even in comparison to most of

the rest of the developing world (Easterly and Levine, 1997; Sachs and Warner, 1997; Col l i e r and Gunn ing , 1999; G u i l l a u m o n t et al., 1999; A c e m o g l u , Robinson, and Johnson, 2001; and Hoeffier, 2002). In responding to this poor record of economic performance, a loose consensus emerged in the late 1980s, especially among international lending organizations, that political pluralism in the form of competitive elections would bring better economic management and per formance to Afr ica (Bates, 2005). Correspondingly , there has been enormous pressure for African countries to democratize, fol lowed by monu- mental changes in the openness of political competition in Africa over the last decade (Bratton and van de Walle, 1997; van de Walle, 2003; Lindberg, 2003).

Karen E. Ferree is assistant professor of political science at University of California, San Diego. She specializes in the study of elections in new democracies, especially those in Africa. Her work has examined the political economy of elections as well as the role of ethnicity in elections.

Smita Singh is Special Advisor to Global Affairs at the William and Flora Hewlett Foundation. Her research interests include the political economy of development and violence in Africa and Southeast Asia.

Studies in Comparative International Development, Winter 2006, Vol. 40, No. 4, pp. 30-54.

Ferree and Singh 31

In spite of the prevalence of the belief in the policy community that democracies grow faster than authoritarian regimes, empirical evidence for this link has been elusive. On one hand, scholarship suggesting that dictatorships are better at implementing the economic policies that improve growth performance has crumbled: Experience with economic reform initiatives has shown that authoritarian regimes are no more likely to liberalize economic policies suc- cessfully than democratic ones (Remmer, 1990; Geddes, 1995). On the other hand, there is little evidence that authoritarian regimes are worse than democracies in terms of growth either. All told, empirical evidence suggests a wash: no firm relationship either way between economic performance and regime type (Helliwell, 1994; Barro, 1996; Przeworski et al., 2000). t

Is the conventional wisdom of the policy community linking democracy to growth off base? Are African governments and their citizens placing unwar- ranted confidence in the power of elections to bring about "a better life for all?" We suggest that existing tests of the democracy/growth link have been incomplete because most have ignored the varying durability of electoral institutions. There is an implicit assumption that once a political institution-- like a particular electoral regime--is in place, its effects on growth will be immediate. As a result, most studies of democracy and growth use snap- shot, single-year measures of democracy, which treat countries that democratized last year and countries that democratized 30 years ago as the same. This may miss the main effects of democracy on economic performance, which we believe occur over time as democratic institutions consolidate and stabi- lize.

We test this conjecture by looking at the effects of competitive elections and their endurance on growth rates in sub-Saharan African countries from 1970 to 2001. Our results support the notion that the durability of democratic institutions matters for economic performance: In keeping with other studies of democracy and growth, we find that initial competitive elections do not offer a growth dividend (though noncompetitive elections may be associated with a growth penalty). However, we also find over the long term that countries with competitive elections slowly begin outperforming those without them.

Due to the simple econometric technology employed in this article, our results speak to correlations, not to causality. Others (notably Przeworski, Alvarez, Cheibub, and Limongi, 2001) have argued that democracies endure only when they deliver good economic performance. Indeed, Adam Przeworski (2004) suggests that institutions may be completely epiphenomenal to deeper structural forces. If true, this offers an alternative explanation for the pattern that we observe: one that sees institutional duration as the effect rather than the cause. While we cannot rule this out, we wish to suggest that there are good reasons for believing the relationship works in the opposite direction, from institutions to performance.

Issues of endogeneity aside, our analysis suggests that if there is a growth dividend to competitive elections, it is one that emerges over the long term, not in the immediate aftermath of a first election. Thus, African countries will see an economic payoff to their investment in democratic institutions only if these institutions endure. Africa's poor growth experience may be related less

32 Studies in Comparative International Development / Winter 2006

to an unwillingness to experiment with democracy than to an inability to consolidate democratic reforms once in place.

In the next section, we outline the empirical and theoretical reasons for focusing analytic attention on the duration of electoral regimes. In the third section, we describe our data and the specification used to test our hypothesis that longevity will condition the impact of electoral regimes on growth rates. Section four presents the results of our econometric tests, and section five offers a discussion of our findings. We conclude with unanswered questions and directions for future research.

The Missing Link? Growth, Political Competition, and Regime Duration

Institutions that govern how leaders are chosen and replaced are perhaps the most basic building blocks of political systems, upon which others, like judiciaries, are built. Indeed, one of the first steps in political reforms is insti- tuting competitive elections. Therefore, it is the competitiveness of electoral institutions that we emphasize in our analysis.

Electoral institutions have been far from static in the post-independence world of sub-Saharan Africa. After initially experimenting with democracy in the 1960s, much of sub-Saharan Africa abolished competitive elections in the 1970s--a fact that has not gone unnoticed by scholars trying to explain Africa's growth shortfall in the following decades (e.g., Collier and Gunning, 1999). 2 After this period of authoritarian rule, in the late 1980s and early 1990s, many African countries moved to allow multiparty competition in executive elections. In 1988, seven countries had a chief executive who had come to power in a competitive, multiparty election--Botswana, Gambia, Liberia, Mauritius, Senegal, Sudan, and Zimbabwe. By 2000, that number had jumped to 30. 3

However, snapshots miss much detail. Taking 1988 as an example, the seven countries with competitively elected executives differed vastly. Botswana and Gambia had been holding competitive, multiparty elections for 23 years; Mauritius, 21 years; Senegal, ten years; and Zimbabwe, eight years. In contrast, Liberia and Sudan first held competitive elections only in 1985.

The variability in duration applies to other types of regimes as well. In 1988, the chief executives in 14 sub-Saharan African countries were not elected at all. Some countries had been in this category for a long time (Congo and Swaziland, 20 years each), whereas others (Guinea, Nigeria, and Burundi) were relative newcomers. In 22 states, executives had come to power through noncompetitive single party elections. In some places, this represented politics as usual (e.g., C6te d'Ivoire, Kenya, Malawi, and Tanzania, where single party governance had been the norm for 20 years). In others, like Ethiopia and the Central African Republic, noncompetitive elections represented a de- parture.

Thus, in 1988, the life span of existing regimes varied considerably. Since then, this heterogeneity has likely increased, given the significant democratic experimentation of the 1990s. Such diversity of electoral experience suggests that, if we are trying to understand how more competitive electoral systems influence growth rates, we ought to consider variation in the length of time

Ferree and Singh 33

that they have been functioning. Yet this temporal dimension of variation has been generally ignored in studies that explore the relationships between political factors and economic growth. When relating African economic outcomes to political institutions, studies have tended to treat these institutions as static, categorizing the nature of state institutions (neopatrimonialism) or both their historical antecedents (colonial rule). When democracy enters the right-hand side of the equation, it does so as a single-year measure. Little attention has been paid to how the durability of political institutions affects outcomes. Even time-series, cross-sectional studies relating aspects of political competition and growth over time have glossed over the impact of institutional longevity on growth? The temporal diversity underlying yearly snapshots of electoral institutions in sub- Saharan Africa belies this omission. By ignoring the impact of time, scholars dismiss the possibility that longer-lived political institutions produce different political and economic outcomes than shorter-lived ones.

Although this article is empirically motivated and our intention is not to provide a comprehensive review of the theoretical literature, it is worth high- lighting that many of the theoretical arguments in favor of democracy and political competition have an implicit temporal component. Below, we review general arguments about the link between democracy and growth, and then discuss how the duration of democratic institutions might affect them.

Numerous political economic models provide theoretical justifications for a link between growth and democracy. There are many versions of these models, but most hinge upon one of two linkages: first, how democratic political competition fosters accountability; and second, how competition brings a wider constellation of interests into the policymaking fold.

According to the first argument, accountability on the part of political agents requires that voters have a choice in leaders and the option to replace incum- b e n t s - i n other words, some modicum of competition. Although competition is far from a sufficient condition for accountability, it is a necessary one (Barro, 1973; Ferejohn, 1999).

The second mechanism linking democratic political competition to growth performance is the size of the minimum winning coalition. In one variant of this argument, put forth by Bueno de Mesquita et al. (2001), the larger the winning coalition required to stay in power, the more likely political agents will pursue policies that enhance the overall public welfare as opposed to providing private goods to a smaller subset of the population. The logic is simple: When faced with a small set of essential supporters (e.g., the military or key business people) needing to be "paid" for their support, it is cheaper for leaders to simply provide private goods. These private goods often take the form of corrupt practices and nepotism in awarding contracts or licenses, but include all those policies that accord differential access for essential supporters to the protection and spoils of the state. As leaders rely on progres- sively larger sets of essential supporters (a plurality of voters, for example), it becomes more expensive to provide private goods. At some level, providing public goods such as education, property rights, and other public welfare- enhancing policies becomes a more cost-effective means of garnering support.


Is there any reason to believe that such benefits of increased competition-- accountability and the size of the group to whom political agents are account- able--will appear immediately with the first election following a transition from authoritarian rule? We suggest that there are several specific mecha- nisms through which the duration of political competition may influence growth rates. We discuss three: property rights; stabilization of investment expectations; and development of performance-based voting. Each of these, we believe, offers reasons for linking economic performance to the duration of democracy, rather than the transition to democracy. Later in the article, we explore both the overall correlation between economic performance and the duration of competitive electoral institutions, as well as the first of the linkages we lay out below.

Property Rights

The first steps toward holding competitive elections may or may not be accompanied by the other institutions associated with democracies. These include a free press and courts to enforce laws, including election laws. An election, even a competitive one, may have little bearing on enforcing property rights. However, as argued by Mancur Olson (2000), the long-term endurance of competitive elections requires the protection of rights---economic and political. Furthermore, the same institutions and conventions (e.g., a dis- interested judiciary) that undergird political competition also protect individual property rights. Therefore, we should see a correlation between consistent competitive elections and the protection of property rights. Christopher Clague et al. (1996) find evidence of this relationship. Given the well-established link between the protection of property rights and productive investment, we should also expect to see a relationship between the duration of electoral institutions and economic performance.

Stabilization of Investment Expectations

In a related vein, we should expect that the institutions that protect property rights and hold predatory governments in check will function more effectively in conditioning the expectations of investors the longer they have been around. Countries with new democratic, competitive electoral systems are often plagued by uncertainty and instability, which hampers growth by fore- shortening the horizons of potential investors. When investors believe that existing institutions will continue to exist and behave predictably, they can invest more efficiently for the long run. Time affects this consolidation process because institutions of governance pass more "tests" of survival as time elapses. These are the moments that challenge the workings of the system, like the first time an incumbent is voted out of office and the courts uphold and enforce the result. As institutions survive these challenges, expectations that they will survive similar challenges in the future solidify. As their exist- ence is taken for granted, uncertainty lessens. Furthermore, as the political system deals with more "contingencies," it becomes more predictable and the

Ferree and Singh 35

distortion costs associated with unpredictable outcomes diminish. Institutions that have survived a long time and established a more encompassing set of precedents will provide more clearly defined contract and property rights than similar but new institutions (Clague et al., 1996: 247). Again, these conditions lead to greater allocative efficiency and more productive use of resources spurring growth.

Development of Performance-Based Voting

One of the basic arguments connecting democracy to growth focuses on how the threat of being voted out of office creates incentives for politicians to deliver good economic outcomes. For this to happen, voters must hold elites responsible for their performance in office. In new democracies, there are at least two barriers to this.

First, voters may not care about performance enough to factor it into their voting calculus. Perhaps they care about other things. Van de Walle (2003) suggests that African electorates are motivated primarily by ethnicity and pa- tronage, not by broad policy objectives. If so, African voters may not punish or reward incumbents based on the economic outcomes they deliver. Alternatively, the opposition might not present a viable enough alternative to the governing party to warrant a vote--even if their governing party is failing to perform. Afri- can transitions, in general, have been marked by weak and disorganized oppositions (Bmtton and van de Walle, 1997) and voters may feel they are not yet ready to govern. It is also possible that voters grant incumbents a honeymoon period after a transition, viewing poor performance as one of the legacies of the old regime, not the responsibility of the new one (Stokes, 2001). For many reasons, voters in a new democracy might not focus on performance--thereby reducing the ability of elections to act as an accountability mechanism.

Second, even if voters care about performance, they may not have the information they need to evaluate incumbents. As Fearon (1999) points out, performance-based voting models carry heavy informational burdens. Voters must be able to distinguish sufficiently between poor performance caused by bad decisions and poor performance caused by bad luck. In a new democracy, these informational demands may be particularly tough to meet. Africa's new voters operate in a relatively information-poor environment: there may be few independent newspapers; those that exist are often written in English or French rather than local languages; most people do not have access to alternative sources of information (television or Internet); and radio stations are often run by the government2 In this context, even performance-minded voters may struggle to use performance criteria to evaluate their leaders.

Although performance-based electorates may not automatically accompany democratic transitions, there are good reasons for believing that they could develop over time as democracy endures. In a cogent analysis, Gerring, Bond, and Barndt (2004) introduce the concept of "political capital," which measures the relative health of a polity--trust in political institutions, low corrup- tion, high capacity, consensus, stability, and good leadership. They suggest that political capital accrues over time as part of a "learning process" between


elites and masses. In this process, voters learn how to recognize good policy, reward good performance, and resist succumbing to populist temptations; elites learn to be concerned with their party's economic record. The longer democracy is in place, the greater the degree of learning. Indeed, Bratton, Mattes, and Gyimah-Boadi (2005) emphasize the importance of learning in the formation of African public opinion. Block, Ferree, and Singh (2003) show that political business cycles are strongest in founding elections and diminish after that--perhaps indicating the development of a more sophisticated, less populist electorate.

Beyond this, democratic duration may also nurture a viable and attractive opposition. In Africa, the absence of organized oppositions at transition does not imply that oppositions will remain permanently small and fractured. In Botswana, the development of a strong opposition has been a slow and gradual process (Keineetse, 2004). Other African democracies may follow suit, giving performance-oriented electorates real choices. Finally, the information environment may become richer over time as new media grow and develop and government control over information weakens. Keineetse (2004) documents a gradual opening of the media in Botswana in the past decade, with the ruling party relying less on heavy-handed methods to control the independent media, and even the state run media is slowly softening its line on printing opposition viewpoints. In sum, even if performance-oriented electorates do not accompany democratic transitions, they may develop over time. This suggests that, if elections are to create incentives for incumbents to deliver good performance, they are only likely to do so as democracy endures.

We have briefly surveyed several paths through which the duration of electoral competition could affect economic performance. We intend our survey to be suggestive not comprehensive, and we present it to reinforce our con- tention that variation in the longevity of electoral regimes may be as important as the nature of the regime itself in explaining its impact on economic performance. Econometric work that compares economic growth under conditions of greater and lesser electoral competition without taking into account the durability of political institutions is most likely misspecified. In fact, our discussion suggests that we expect to see a salutary impact from increased political competition on growth rates only after competitive electoral institutions have functioned for a while. We should not expect an immediate growth dividend after electoral reforms that allow political competition. Our discussion also suggests that Przeworksi (2004) may be too hasty when he sees institutions as purely derivative. While the possibility remains that good economic performance contributes to democratic survival, we should not be too quick to dismiss the possibility that the relationship works the other way as well.

Data and Model: Measuring Executive Electoral Regimes, Duration, and Growth

In our analysis we employ three types of independent variables--political, temporal, and economic--and one dependent variable, growth rates. We describe each category of variables below.

Ferree and Singh 37

Political Variables: Capturing Electoral Competition

Our political variables are based on a scale that captures the extent of competition allowed in the selection process for chief executives. We constructed the scale for 45 sub-Saharan African countries for each year between 1970 and 1995. Afterward, the World Bank collected a similar measure from 1975 to 2000 . 6 Combining these measures, we have 30 years of data for most countries in sub-Saharan Africa. This data is summarized in Table 1. We define six theoretical levels in the scale: Countries that fall under level 1 had no identifi- able executives--these are the countries often referred to as "collapsed states." Countries at level 2 had chief executives who came to power through coups or succession but not through popular elections. Level-3 countries are those where executives are "elected," but face no challengers during the election-- these are mostly the single party states so prevalent in post-colonial, sub- Saharan Africa. Level-4 countries allow a modicum of political competition: they hold an election for the chief executive whereby more than one candidate is allowed to run, but opposition parties are banned. Countries at level 5 have executives that are elected in competitive contests in which opposition parties are legal but remain inactive. Finally, level 6 consists of countries that hold competitive, multiparty elections. 7

As is apparent from Table 1, only three levels of the scale have much de- scriptive relevance for the types of executive electoral regimes found in sub- Saharan Africa. Almost all of our observations fall in categories two, three, or six: countries that held no elections, noncompetitive elections, or competitive multiparty elections, respectively. (This is even truer for the sample actually used in our models, as the third column of Table 1 shows.) In our model, we use dummy variables for each of these levels (dropping the two level-1 observations in our sample and ignoring the theoretically interesting but empiri-

Table 1 The Executive Scale

Level Frequency Characteristics of Electoral Institutions

Total In Sample

Level 1 17 2

Level 2 402 218

Level 3 488 243

Level 4 21 10

Level 5 3

Level 6* 399 207

No executive exists

Nonelected executive

Executive elected, but was the only candidate

Executive elected, more than one candidate competed for the office, but multiple parties not legal

Multiple parties legal but did not compete in elections

Candidates from more than one party competed for the executive elections

* Between 1996 and 2000, an additional level (Level 7) was coded for cases where the winning party won less than 75 percent of the vote. These were folded into the level-6 cases.


cally irrelevant level-5 category). We also use a dummy for level 4, but do not expect it to yield results due to the small number of cases in the category. In the specifications that follow, we treat level 6 as the reference category as we anticipate that it should be different from levels 2 and 3.

Temporal Variables: Accounting for the Durability of Electoral Competi- tion. We are interested in how institutional longevity mediates the impact of executive electoral regimes on growth performance. To test our temporal hy- potheses, we created a duration variable by counting how many years each country had been at its current level of the scale. (During years of institutional change, the duration variable is zero.)

Taking all the countries over the entire period for which data was collected (but looking only at the actual sample used in our regressions), the mean value of the endurance variable is around eight years; its maximum value is 36 years. 8 Thirty-five percent of electoral regime country-years lasted between zero and four years; 19 percent between five and nine years; 19 percent between ten and 14 years; 14 percent between 15 and 19 years; and 14 percent endured at least 20 years. We emphasize that our variable does not record the tenure of particular leaders per se, but rather the durability of executive selection institutions. Therefore, models relating long-term, growth-oriented policies to the time horizons of leaders (for example, Bienen and van de Walle, 1991) are not relevant to our analysis.

Deconstructing this distribution by levels (see Table 2), we find that the average (in sample) duration of countries with no elections (level 2) was around 11 years, with a maximum value of 36. The average (in sample) duration of countries with non-competitive elections (level 3) was also around 11 years, with a maximum value of 29 years. Finally, the (in sample) duration of countries with competitive, multiparty elections (level 6 or higher) was around eight years, with a maximum value of 30 years. Overall, the yearly duration data sketches a portrait of temporal diversity.

We do not expect durability to produce similar growth impacts across the range of electoral regimes. Therefore, we created interaction terms multiply- ing the duration variable for a particular country-year by the corresponding scale level dummy variable. We created these for four scale levels: 2, 3, 4, and 6.

Table 2 Duration at Different Levels

Duration at:

Level 2

Level 3

Level 4

Level 6

Total

Average Maximum

8.6 36

9.3 29

3.8 10

7.1 30

Average

10.8

11.2

2.7

7.8

In Sample

Maximum

36

29

6

30

Ferree and Singh 39

Control Variables: Determinants o f Growth. We use a set of economic variables standard in the growth literature as a base for all of our regressions. Our goal is not to est imate these relationships p e r se, but to control for whatever effects they may have on the dependent variable. We try various permutations of them to ensure that the results for our political variables are robust to different configurat ions. In particular, we use:

�9 Lagged log of per capita income. This variable captures conditional "convergence effects" where countries at lower initial levels of income are expected to grow faster than countries at higher initial levels of income (Barro, 1996). We expect the sign on this variable to be negative (NY.GDP.PCAP.KD from World Development Indicators).

�9 Lagged government consumption as a percentage of gross domestic product (GDP). This variable is used "to approximate the outlays that do not enhance productivity" (Barro, 1996: 9). It is considered nonproductive spending and is expected to reduce growth (NE.CON.GOVT.ZS from World Development Indicators).

�9 Lagged change in government consumption as a percentage of GDP. Because we consider short-term growth, we include a measure for changes in government consumption. We expect this variable to have a negative effect on growth.

�9 Lagged real investment as a percentage of GDP. Following most prior work on growth, we expect investment to be positively related to growth (Barro and Sala-i- Martin, 1995). As a measure for this, we use gross domestic fixed investment as a percentage of GDP (NE.GDI.FrOT.ZS from World Development Indicators).

�9 Lagged change in real investment as a percentage of GDP. Because we consider short-term growth, we expect changes in investment to be at least as important as the level of investment. We anticipate that increases in investment should lead to higher growth.

�9 Lagged life expectancy. We use this as a proxy for human capital, which is widely viewed as a necessary ingredient for growth. We opt for life expectancy instead of a schooling measure because it offers better data coverage, and because we suspect that it has less measurement error than other human-capital variables. 9 We expect a positive relationship with growth. As measures of life expectancy typically occur every second or third year (thus producing a gappy dataset), we used data imputa- tion to fill in intervening years (SP.DYN.LE00.IN from World Development Indica- tors).

�9 Lagged labor force. Following Baum and Lake (2003) and Prezworski et al. (2000), we use this as a measure of the labor component of growth. We expect a positive relationship with growth (SL.TLETOTL.IN from World Development Indicators).

�9 Eighties. A dummy variable indicating the 1980s. We anticipate a positive relationship with growth (relative to the 1990s).

�9 Seventies. A dummy variable indicating the 1970s. We anticipate a positive relationship with growth (relative to the 1990s).

Dependen t Variable: Annual Growth Rates. Most econometr ic studies looking at the determinants of growth rates are interested in long-run growth pat- tems and use five- or ten-year average growth rates. Because we are interested specifically in distinguishing the temporal impact of electoral institutions, we do not wish to average out and obscure the possibil i ty o f different ial short- term impacts. Thus, the dependent variable in our analysis is the annual growth rate of per capita GDP in each o f the 45 sub-Saharan Afr ican countries cov- ered in our dataset f rom 1970 to 2001.


Model Specification. We use the following pooled time-series, cross-sectional model of growth:

ln(Yu ) - ln(Y;.,_~ ) = ~ ln(Yu_~)+ W;.,_,6 + E;.,

where Yuis real per capita income for country i in period t, W;.,_~is a row vector of determinants of economic growth observed in country i for period t-r. (the lagged independent variables discussed earlier), and ei. , is the error term. Be- cause our dependent variable is annual growth rates, z = 1.

We employ this equation as the foundation for our specification and esti- mate it through ordinary least squares. Following Nathaniel Beck and Jonathan Katz (1995), we calculate panel-corrected standard errors to deal with prob- lems caused by contemporaneous correlation of errors, panel heterogeneity or both. To deal with the possibility of country-specific effects (i.e., unspeci- fied factors particular to a country that systematically affect its growth rate), we ran two additional models: a random-effects model and a fixed-effects model. Each of these models is associated with certain costs and benefits. Random-effects model country-specific effects through the error term and require the estimation of only two additional parameters. This makes them relatively efficient in exploiting the information in the dataset. However, they make the (large) assumption that the country-specific effects in the error term are not correlated with the other independent variables in the model. Fixed- effects model difference out country-specific effects (either directly or through country dummies). This involves a significant loss of information--in particular, it removes much of the cross-sectional variation and estimates effects based on variation within a country over time. This can be problematic if much of the variation in the dataset is cross-sectional in nature. ~~ Because none of these models is clearly superior, we run and report estimations based on all three, l

A l though the above speci f ica t ion does not al low us to control for endogeneity, we have lagged our independent variables behind our dependent variables, appealing to the standard logic that an event at time t cannot cause an event at time t-1. We explore endogeneity further in brief case studies of Botswana and Mauritius later in the article.

Results

Our results (Tables 3 and 4) support our hunch that time matters. Without taking into account the longevity of an electoral system, we found mixed results for the effects of competition: countries with competitive elections outperformed countries with uncompetitive elections (primarily Africa's single- party states), but did not outperform countries with no elections at all (Table 3). We also found that more competitive electoral systems seem to be associated with better growth performance than less competitive systems over the long term. This is especially true for our OLS (ordinary least squares-) and random-effects models (columns 1 and 2 of Table 4). ~2 When using a fixed-

Ferree and Singh 41

effects model (column 3 of Table 4), the story is less clear, but institutional duration continues to be important.

Controls. Before delving into our core results, we will briefly review our control variables. Most perform as expected. We find evidence of convergence, with countries at lower initial per capita incomes growing at higher rates than with countries at higher initial per capita incomes (this is true across specifications, but the size of the coefficient is smaller in the fixed-effects model). Both the level of investment and changes in investment have large, well-estimated, positive relationships with growth (also true across specifications). Both the level of government spending and changes in government spending have consistently negative effects (as expected) that are significant in most specifications. Life expectancy has a positive relationship with growth in the OLS pcse (panel corrected standard errors) and random-effects mod- e l s - b u t not in the fixed-effects model. Due to the slow rate of change in this variable (and therefore a minimal amount of within country over time variation), the lack of significance in the fixed-effects model is not surprising. Lagged labor force had a negative, weakly significant relationship with growth in the OLS pcse and random-effects models, but not in the fixed-effects model. Fi- nally, the decade dummies perform as anticipated (and are consistent across specifications), whereby the 1970s and 1980s show higher levels of growth than the 1990s. The coefficient on the 1970s is particularly large, and demon- strates the general decline in economic performance in Africa over the past three decades. J3

Competitive Electoral Regimes and Growth. We turn now to the relationship between level of competition in executive elections and growth rates (Table 3). If political competition has a beneficial, duration-invariant impact on growth, countries at level 6 (multiparty competition) should be associated with better economic performance than those at levels 2 (no elections) and 3 (noncompetitive elections). Yet we find only partial evidence for this. Across specifications, the level-two dummy never approaches significance, while the level-three dummy is consistently significant and negative. ]4 This tells us that there appears to be a growth penalty to holding noncompetitive elections, but no reward to holding competitive ones versus having no elections at all. In view of arguments extolling the accountability benefits of more competitive electoral systems and the restraining effects of democratic institutions, these results may seem surprising. They also help explain why, in spite of all the democratic reforms of the late 1980s and 1990s, African growth performance has declined relative to the 1970s.

Electoral Regimes, Institutional Durability, and Growth: Duration Effects. We set out to test the hypothesis that a positive relationship between greater electoral competition and growth (if there is one) will only emerge in the long term. These effects are captured in the lagged duration and three lagged duration, interaction terms (for levels two, three, and four) in Table 4.

The story that emerges through these variables depends on the specification used. For the OLS pcse and random-effects models, we find the expected relationships. Duration of electoral institutions has a positive, well-estimated effect on growth. However, duration at either level 2 or level 3 is associated


Table 3 Growth Models with Scale Level--Standard Errors in Parentheses

Dependent Variable: Growth OLS with PCSEs Random Effects Fixed Effects

(1) (2) (3) Lagged Per Capita -.0103"* -.0103"** -.0717"** Income (.0052) (.0040) (.0160)

Lagged Investment .0015"** .0015"** .0013'** (.0003) (.0003) (.0004)

Lagged Change in .0273"** .0273"** .0240"* Investment (.0101) (.0100) (.0099)

Lagged Government -.0008** -.0008* -.0021"** Spending (.0003) (.0004) (.0007)

Lagged Change in -.0320** -.0320** -.0156 Government Spending (.0133) (.0134) (.0143 )

Lagged Life Expectancy ,0016 * * * .0016* * * .0007 (.0005) (.0005) (.0010)

Lagged Labor Force -7.10e- 10'* -7.10e- 10* * 1.96e-09 (3.54e- 10) (3.56e- 10) (1.82e-09)

Eighties .0138"* .0138'** .0194"** (.0066) (.0052) (.0060)

Seventies .0225** .0225*** .0272*** (.0099) (.0083) (.0102)

Lagged Level 2 -.0003 -.0003 .0010 (.0067) (.0066) (.0083)

Lagged Level 3 -.0258*** -.0258*** -.0182"* (.0062) (.0065) (.0081)

Lagged Level 4 -.0303 -.0303 -.0010 (.0312) (.0202) (.0225)

N 678 678 678 R-Squared .14 .14 .00

(within .07, between ,60) (within.12, between .02)

* < .10; ** <.05; *** <.01

with a growth penalty. The coefficient on level 3 is especially large. This is more-or-less the story we anticipated: over time, countries with competitive elections begin to outperform countries without these elections, even if initially there is no growth dividend to democratization. 15 We did not expect to see a difference between duration at level 2 versus level 3. We discuss expla- nations for this below.

Because it is difficult to understand the total effect of different variables in the presence of multiple interaction terms, we fo l low the sage advice in Brambor, Clark, and Golder (2005) and provide fitted values for growth in Table 5.16 The tables show the fitted values for each level of the scale and for

Ferree and Singh

Table 4 Growth Models with Level and Durat ion--Standard Errors in Parentheses

43

Dependent Variable: Growth OLS with PCSEs Random Effects Fixed Effects

(1) (2) (3) Lagged Per Capita -.0125"* -.0125"** -.0827*** Income (.0054) (.0041) (.0171)

Lagged Investment .0015"** .0015"** .0013"** (.0003) (.0003) (.0004)

Lagged Change in ,0284"** .0284"* * .0242"* Investment (.01) (.0096) (.0099)

Lagged Government -.0006** -.0006 -.0020*** Spending (.0003) (.0004) (.0007)

Lagged Change in -.0314** -.0314"* -,0131 Government Spending (.0132) (.0134) (.0142)

Lagged Life Expectancy .0018 * * * .0018 * * * .0010 (.0005) (.0005) (.0010)

Lagged Labor Force -6.08e- 10* -6,08e- 10" 1.96e-09 (3.47e- 10) (3.55e- 10) ( 1.81 e-09)

Eighties .0126" .0126"* .0184"** (.0066) (.0052) (.0061)

Seventies .0212"* .0212"* ,0229'* (.0097) (.0085) (.0106)

Lagged Level 2 .0143 .0143 0.0161 (.0097) (.0095) (.0106)

Lagged Level 3 -.0024 -.0024 .0134 (.0094) (.0100) (.0116)

Lagged Level 4 -.0565 -.0565** -.0302 (.0440) (.0312) (.0324)

Lagged Duration .0009** .0009* .0009 (.0004) (.0005) (.0009)

Lagged Duration at -.0016'* -.0016"* .0006 Level 2 (.0007) (.0007) (.0011)

Lagged Duration at -.0023*** -.0023*** -.0037"** Level 3 (.0006) (.0007) (.0012)

Lagged Duration at .0146 .0146 .0092 Level 4 (.0162) (.0098) (.0099)

N 678 678 678 R-Squared ,16 .16 .00

(within .09, between .60) (within. 14, between .02)

* < .10; ** <.05; *** <.01

44 Studies in Comparative International Development [ Winter 2006

l, 10, 20, and 25 years of duration, with 95 percent confidence intervals in parentheses. Table 5 shows that scale level has only a negligible and not well- estimated effect at low levels of duration: countries without elections (level 2) have marginally higher growth rates than those with either competitive (level 6) or noncompetitive (level 3), but the confidence intervals of all three estimates are intersecting. Over time, the performance of level-6 countries gradu- ally improves, while the performance of countries at levels 2 and 3 deteriorates. If a level-2 country starts with a growth rate of around .03 in year 1, by year 25, its growth rate has declined two percentage points to .01 (note that the confidence intervals are fairly wide). In contrast, if a level-6 country starts off in year 1 with a growth rate of .015, at the end of 25 years it has a growth rate of nearly .04, an increase of over two percentage points (again, with wide confidence intervals). And finally, for a level-3 country starting at about the same place as the level-6 country, the effect of duration is to reduce its growth rate by around four percentage points. The difference between level 6 and level 3 is significant at the 95 percent level by a duration of 20 years (the confidence intervals are completely nonoverlapping). The difference between level six and level two displays more uncertainty (the lower confidence interval for level 6 is still between the upper and lower limits for level 2). The lower certainty for the estimates of level 6 and level 2 (versus level 3) most likely reflects the distribution of our data--we have nine cases of level-3 countries enduring for 20 years or more, but only three each of level-2 and level-6 countries enduring this long. We address this issue more below.

For the fixed-effects specification (Table 4, column 3), the variables tell a somewhat different story. Here, the duration variable is not significant (though the coefficient is exactly the same as the earlier specification, the estimated standard error is larger). The duration/level-2 interaction is also not significant. However, the duration/level-3 interaction remains highly significant and negative, and an F-test of all the duration variables together is significant at the .003 level. Overall, this tells us that duration has no impact on countries

Table 5 Fitted Values for Different Levels and Durations--

with 95 % Confidence Intervals (Random-Effects Model)

Duration Level 2 Level 3 Level 6

1 year .030 .013 .015 (.011,.048) (-.007,.033) (-.004,.035)

10 years .023 .001 .023 (.007,.038) (-.017,.015) (.005,.041)

20 years .016 -.015 .032 (-.003,.035) (-.034,.004) (.013,.064)

25 years ,013 -.022 ,039 (-.010,.036) (-.05,.001) (.013,.064)

Values are generated by holding other variables at means.

Ferree and Singh 45

without elections (level 2) or countries with multiparty elections (level 6), but it has a large negative impact on countries with noncompetitive elections (level 3). These results suggest that duration mat ters- -but not exactly in the way expected. Democracy never brings benefits (at least relative to countries without elections), but it does help avoid the penalties associated with some regime types (those with noncompeti t ive elections). We did not anticipate a difference between countries without elections and countries with noncompetitive elections, and we speculate on this relationship in the discussion section of the article.

Fitted values provide a window into these results (Table 6). Because of the high standard errors on the scale level coefficients, differences across columns should not be emphasized. Yet, the severe effect of duration on level- three countries is evident: these countries lose about seven percentage points in growth in 26 years, and this effect is well estimated. Both level-6 and level- 2 countries gain marginally over time, but this effect is not well estimated.

Given the different substantive stories told by the models, which is the most accurate? We believe there are strong reasons to favor the random-effects/ OLS results. First, as already discussed, fixed-effect models level out cross- sectional variation. This means ignoring most of the information in variables that do not change much over time. Our substantive variables of interest change over time (duration in particular), but the amount information in single countries about the effects of duration at different levels of the scale is by nature limited. Given the 30-year span of our sample, few countries can simulta- neously experience 20 years at level 6 and 20 years at level 2.17 Consequently, we can only learn about the effects of our interaction term by harnessing across country variation. But this is precisely what fixed-effects models difference out, so the price of the fixed-effect cure is very high for our data.

Second, the importance of country-specific effects (and cures for them) increases the more unalike the units of analysis. Our sample, composed en- tirely of African cases, is more homogeneous than samples pooling disparate

Table 6 Fitted Values for Different Levels and Durat ions- -

with 95% Confidence Intervals (Fixed-Effects Model)

Duration Level2 Level3 Level6

1 year .024 .022 .008 (.003,.046) (.000,.043) (-.013,.030)

10 years .027 -.006 .017 (,010, .045) (-.025, .012) (-.007, .040)

20 years .031 -.034 .026 (.008, .054) (-.060, -.008) (-.011, .062)

25 years .033 -.048 .031 (.004, .062) (-.080, -.016) (-.015, .077)

Values are generated by holding other variables at means.


regions of the world. As African countries share a similar geography, a similar general history, a similar type of cleavage structure, a similar export profile, a similar level of development, and so on, comparing them is perhaps more akin to comparing Mclntosh apples with Fuji apples than it is to comparing apples with oranges. 18 If this is true, the cure of the fixed-effects model may be worse than the disease! For these reasons, we attach greater weight to the random-effects/OLS specification, but provide the fixed-effects results for those unconvinced by our arguments. If nothing else, the fixed-effects results provide a lower confidence interval on our results. 19

Exploring Property Rights. In our theoretical section, we speculated on several causal paths that might link the duration of competitive electoral institutions to growth. One of these paths involved property rights. Earlier work by Clague et al. (1996) suggested that stable property rights emerge only after democratic institutions have been in place for an extended time. If this is true, then the duration of democratic institutions should also have an impact on growth, one that works through the stabilization of property rights. To test the plausibility of this conjecture, we conclude our empirical work with a final set of regressions.

If duration works through property rights, then two things should be true: first, property rights should have a significant relationship with growth; and second, controlling for property rights should reduce or eliminate the direct effects of institutional duration. Our results again depend on whether we use the fixed-effects specification. 2~ Table 7, column 1, repeats the random-effects model in Table 4, but adds a measure of lagged property rights. 21 In this model, we find the expected result: the coefficient on lagged property rights is positive and significant, indicating that greater respect for property rights is associated with higher levels of growth, and including it eliminates the significance of the duration variables. The fixed-effects specification (second column, Table 7) tells a different story since the remarkably persistent negative effects of duration at level 3 (noncompetitive elections) emerges again-- indeed the coefficient is the same as in the third specification, which does not include property rights. This suggests that the negative effects of duration at level 3 do not work through property rights, but this interpretation is conditional on accepting the fixed-effects specification as the correct one.

In sum, conclusions about the relationship between institutional duration, property rights, and economic outcomes depend on how we model country- specific effects. If we adopt the random-effects model, then our results, com- bined with the evidence in Clague et al. (1996), offer tentative support that the duration of democratic institutions is associated with higher property rights, which are in turn associated with better economic performance. Yet we wish to emphasize that the fixed-effects model tells a different story (one that does not see duration working through property rights) and that limitations of our data (the questionable nature of the property rights measure, the severe loss of observations from its inclusion) preclude attaching too much significance to these findings. We believe they are suggestive, but hardly definitive. The other causal avenues we posited earlier--in particular, the development of perfor-

Ferree and Singh

Table 7 Exploring Property Rights--Standard Errors in Parentheses

47

Dependent Variable: Growth Random Effects Fixed Effects

(4) (5) Lagged Per Capita -.0123 * * -. 1432 * * * Income (.0060) (.0346)

Lagged Investment .0013"* .0019* (.0005) (.0010)

Lagged Change in .0334*** .0210 In vestment (.0120) (.0134)

Lagged Government -.0010* -.0037"** Spending (.0006) (.0012)

Lagged Change in -.0214 .0063 Government Spending (.0153 ) (.0179 )

Lagged Life Expectancy .0010 -.0006 (.0008) (.0018)

Lagged Labor Force -4.60e- 11 9.90e- 10 (-4.76e-10) (3.32e-09)

Eighties .0215"** .0242"** (.0063) (.0078)

Lagged Property rights .0121"** .0128"** (.0032) (.0049)

Lagged Level 2 .0028 .0048 (.0123) (.0150)

Lagged Level 3 -.0133 .0239 (.0140) (.0182)

Lagged Level 4 -.0513 -.0675 (.0391) (.0425)

Lagged Duration -.0001 .0004 (.0007) (.0014)

Lagged Duration at .0006 .0048 Level 2 (.0001) (.0150)

Lagged Duration at -.0010 -.0037' * Level 3 (.0010) (.0017)

Lagged Duration at .0153 .0134 Level 4 (.0391) (.0104)

N 315 315 R-Squared .21 .02

(within .16, between .50) (within .22, between .01)

* < .10; ** <.05; *** <.01

48 Studies in Comparative International Development ! Winter 2006

mance based voting--may also be critical. We leave to future work the task of operationalizing and testing this avenue.

Sorting Out Causality: A Brief Look at Botswana and Mauritius

Our results demonstrate a correlation between growth and duration at different levels of competition. We posit a particular direction of causality (from institutional duration to performance) and several avenues through which this causality could operate. But the possibility remains that we have the story backwards, that enduring democracies have high growth rates because growth promotes endurance, not the other way around. To gain purchase on this thorny issue, we look more closely at Botswana and Mauritius, two cases that are especially important to our results.

Botswana democratized in 1965 and has held multiparty elections in five- year intervals ever since. 22 When it democratized, the country was dirt poor (with a per capita income of around $600 annually). In 2001, per capita income exceeded $4,500 annually. Its growth in the 1970s was not exceptional (many African countries had similar growth paths). But its phenomenal growth in the late 1980s and more moderate but still impressive growth in the late 1990s contrast significantly with the experience of most of the continent. The country clearly did not transition to democracy because of its prior performance, but did the presence and consolidation of democracy contribute to this spectacular growth rate (especially its ability to keep growing in the oth- erwise depressing African landscape of the 1990s), or did growth ensure democracy's survival?

Although it is impossible to sort this out conclusively, several factors suggest that this is not only a story of economic performance begetting democratic survival. First, Botswana's economic performance was not independent of its governance decisions. As one country expert put it, the government made "superb economic choices" in its stewardship of the country (Stedman, 1993: 5), for example, plowing mineral revenues back into development projects rather than shipping them to personal bank accounts in Switzerland. The government also refrained from violating property rights, creating a stable and attractive environment for investment (Botswana scores very high on the measure of rule of law/property rights used in the last section). Because of these choices, the economy has grown in spite of severe exogenous shocks like the persistent droughts of the 1980s. When the rest of Africa stopped growing in the 1980s and 1990s, Botswana kept going.

Second, there is some evidence that some of Botswana's good governance decisions were related to it being a consolidated democracy--especially in the early 1990s when its economy experienced a leveling off. About the same time, opposition parties (previously very small and quiet) began attracting larger numbers of votes. In the 1994 election, the ruling Botswana Demo- cratic Party (BDP) won only a slim majority (53 percent of the vote) rather than its customary landslide. Economic growth has since resumed and the BDP has stayed in power, but the specter of the opposition (and the possibility that it will benefit from an economic downturn) remains. We cannot know if

Ferree and Singh 49

fear of being voted out kept the BDP in line through its long tenure, but the rise of the opposition in the mid-1990s at least raises this possibility.

In sum, the presence of opposition parties, which did not flourish immediately in the aftermath of the first election but took decades to cohere, may have aided in keeping the government concerned about performance--at least in recent decades. Furthermore, the decisions of the government were important in putting Botswana on a high growth path and keeping it there in spite of exogenous economic shocks like droughts and a faltering regional economy. Although this does not prove that democratic endurance caused good performance, it does suggest that we should not automatically assume that the relationship runs the other way.

Like Botswana, Mauritius is another of Africa's economic success stories and one of its most stable democracies. In 1968, when it gained independence, it had a per capita income well under $1,000 and an economy based almost exclusively on sugar. By 2002, per capita income was close to $5,000 and the economy had diversified into manufacturing and service industries (Bowman, 1991). Aside from a brief period in the early 1970s when elections were delayed (from 1972 to 1976), the country has held regular competitive multiparty elections over this entire period. Mauritius thus raises the same questions as Botswana: did democratic consolidation pave the way for development or did development facilitate democracy?

Again, several factors suggest this is not only a story of economics influ- encing politics. First, like Botswana, Mauritius did not transition to democracy because of development: it was poor when it had its first elections. Second, most of the country's growth occurred after democracy had already endured significant economic shocks. Mauritius experienced a brief period of moderate growth in the early 1970s, but this was followed by a period of economic crisis in the late 1970s and early 1980s. This crisis, which saw rising unem- ployment and inflation, and led to the introduction of IMF austerity measures, tested but did not derail Mauritian democracy (Bowman, 1991). After 1983, the economy began its sharp upward climb---even as economies in the rest of Africa were faltering. Thus, it is difficult to argue that development preserved democracy: democracy persisted through some dark economic days.

Finally, Mauritian voters have tended to vote out incumbents presiding over bad economic periods and keep in incumbents presiding over good ones. The crisis of the early 1980s produced two democratic alternations in power: in 1982 when the Mouvement Militant Mauricien (MMM) and Parti Socialiste Mauricien (PSM) coalition took power from the Labor Party (LP), and in 1983 when the Mauritian Socialist Movement (MSM) alliance took power from the MMM/PSM. Following 1983, the MSM and its various alliance partners have converted strong economic performance into electoral dominance (Bowman, 1991). The behavior of Mauritian voters thus created incentives for Mauritian parties--many of which were socialist--to focus on delivering positive economic performance.

In sum, neither Botswana nor Mauritius offers a simply story of economic growth that begets or even preserves democracy. Both countries transitioned when poor, staved off economic challenges while remaining democratic, and


posted especially impressive growth performances several decades after the initial introduction of democracy. Furthermore, electorates in both countries have punished poor economic performance. All of this supports the notion that democratic endurance, not simply democratic transition, is what matters in explaining different paths of economic development.

Discussion

We anticipated that any positive relationship between democratic competition and growth would only appear as competitive electoral institutions endured because only over time did the institutional infrastructure--both within the state and in society--develop to protect rights, predictable administration of those rights, and viable policy and opposition alternatives. Our results suggest support for this hypothesis.

We did not foresee that electoral regime durability would affect countries with noncompetitive electoral systems adversely, nor did we expect a difference in the influence of institutional durability on growth rates in level-two and -three countries, both of which did not competitively elect their executives. These results--which are consistently our strongest--are provocative, and merit some discussion about the causal dynamics they suggest.

If we take seriously the arguments of Bueno de Mesquita et al. (2001) about the breadth of interests represented in more competitive electoral systems, we would expect leaders from level-2 countries to rely on the smallest set of supporters---officers who backed the coup, for example. Executives from level- 3 countries, although they faced no competition in the elections that brought them to power, must still secure the support of their party infrastructures to ascend to candidacy. With both sets of regimes, the support base required is unlikely to be large enough to encourage leaders to provide public goods rather than private goods. Since a larger group must be "bought oft" in level- 3 countries, patron-client networks are probably more extensive and more growth inhibiting. Over time, as these networks accrue, they eventually strangle the productive capacity of the state, thereby yielding the patterns we observe in our data. These are, of course, merely speculations. If nothing else, our results reinforce the need for further research to disentangle the growth dynamics of different types of authoritarian systems.

Conclusion

We end as we began: by considering the implications of our analysis for the growth prospects of poor countries. Our results contradict recent work that concludes that regimes do not matter for growth. We show that the effects of regimes are tempered by the longevity of those regimes. More competitive electoral systems only appear to yield growth dividends in the long run (if at all), while noncompetitive electoral systems exact a growth penalty in the long run. These results leave us with intriguing questions about the survival dynamics of democracies.

Ferree and Singh 51

D o o n l y t h o s e c o m p e t i t i v e , m u l t i p a r t y s y s t e m s s u r v i v e tha t p e r f o r m w e l l

e c o n o m i c a l l y ? O r is i t the o t h e r w a y a r o u n d ? O n l y t h o s e c o m p e t i t i v e , m u l t i - p a r t y s y s t e m s tha t s u r v i v e b e g i n to p e r f o r m w e l l e c o n o m i c a l l y ? T h e s e q u e s - t ions p i n p o i n t a focus for fu ture work . O t h e r w i s e , we are lef t w i th a d e m o c r a t i c s t r a i t j a c k e t : I f , as r e c e n t w o r k c o n c l u d e s , i t is the c a s e t ha t d e m o c r a c i e s a re m o r e s ens i t i ve to p o o r g r o w t h p e r f o r m a n c e , then o n l y t h o s e d e m o c r a c i e s tha t g r o w s u r v i v e . Yet , d e m o c r a c i e s m a y n e e d to s u r v i v e to p e r f o r m w e l l . W e sugges t tha t work , w h i c h e x p l i c i t l y c o n s i d e r s the t e m p o r a l i m p a c t s o f po l i t i c a l i n s t i tu t ions and re l a t e s those i m p a c t s b a c k to the fu r the r d e v e l o p m e n t o f those i n s t i t u t i ons , s h o u l d be an i n t e g r a l pa r t o f the c o n t i n u i n g r e s e a r c h p r o g r a m in the p o l i t i c a l d e t e r m i n a n t s o f g r o w t h .

N o t e s

* We wish to thank Robert Bates for support and advice at all stages of this project. Thanks also to Macartan Humphries, Naunihal Singh, two anonymous reviewers, and the editors at Studies in Comparative and International Development for helpful comments.

1. Baum and Lake (2003) provide an interesting exception to this general trend: they argue that democracy works on growth indirectly through the avenue of higher human capital. According to their results, democracies outperform nondemocracies in terms of public health and education, making an important impact on growth levels.

2. For an excellent discussion of elections during this earlier period, see Collier (1982). 3. We are not claiming here that these countries are fully "democratic," but that they have increased the

degree of competition in the executive selection mechanism, a change that we expect should have wide- ranging implications. See van de Walle (2004) and Lindberg (2004) for empirical investiga- tions of the quality of African elections. Although African elections are frequently painted as being uniformly poor in quality, more careful analysis has suggested that this view is too pessimistic.

4. One very recent exception is Gerring, Bond, and Barndt 2004. The only other study we are aware of that explicitly considers regime duration is Clague et al., 1996, although their dependent variable is not growth but protection of property rights.

5. See Schaffer (1998) for a rich account of the informational environment of Senegalese elections, and Keineetse (2004) for a discussion of the news media in Botswana.

6. The World Bank measure is called the executive index of electoral competition (EIEC) and is part of the Database of Political Indicators. See Beck et al. (2001) for a description. We use our original data for 1970 through 1995 and the World Bank data for 1996 through 2000. The measures correlate at a level above .8 for the overlapping years.

7. In the World Bank data, a seventh level is distinguished for countries with competitive, multiparty elections in which the winning party won Jess than two-thirds of the vote. For this analysis, we merge together levels six and seven for the five years of World Bank data we use.

8. The maximum value of the duration variable (Ethiopia at level two) exceeds the total number of years in the dataset (30 years) because electoral regime duration does not start at zero in 1970 for most countries. Rather it records the number of years that the electoral institutions had already been in place by 1970.

9. See Burro and Lee (1993) for a discussion of human capital measures. 10. For more on each of these models, see Greene (1993). 11. We initially included a lagged value of the dependent variable to control for serial correlation, but

were able to drop it as it proved to be highly insignificant across all specifications. This step did not change the coefficients on any of the other variables. Dropping the lag freed up an extra degree of freedom and allowed us to use a fixed-effects model without introducing an inconsistency problem. For these reasons, there is little need to resort to more complicated fixes for country-specific effects like the Generalized Method of Moments (GMM) method.

12. Note, OLS with pcse and random-effects models will produce the same coefficient estimates as regular OLS. This is because both models make their corrections to the error term, which affects the size of the estimated standard errors, not the size of the estimated coefficients.

52 Studies in Comparative International Development ] Winter 2006

13. We also experimented with other temporal variables, including ones that are more historically relevant. Thus, we tried a dummy variable for the post-Berlin Wall era (which we code as 1990 onward). When included, this has a negative, significant effect on growth. We also tried a dummy for the 1979 oil shock (we arbitrary set this as 1980-1984). This also bad a negative, significant effect on growth. Using these instead of the decade dummies had no impact on our variables of interest. For simplicity, we just report the results with the decade dummies but the other results are available upon request.

14. Note, level- l countries (only two country years in the sample) are dropped and level 6 is left out of the specification, so the results should be interpreted as relative to level 6. A positive coefficient on the level-2 dummy is therefore evidence that level 2 countries outperform level 6 countries. We leave level 6 out of the equation (or more accurately, relegate its effects to the constant) because levels 2 and 3 should be similar to one another, but different from level 6. This is merely an issue of presentation-estimation of coefficients is not affected by which level is left out.

15. The interaction for level six and duration is left out. The coefficient on the straight duration term can therefore be interpreted as the effect of duration at level six. For a specific effect for the other duration/level interactions, the coefficient on duration must be added to duration/level interaction in question.

16. To generate the fitted values in the table and charts, all other variables were held at their means. 17. This can only happen if the country entered the sample with a substantial duration at one level,

transitioned early on, and then spent the rest of the time at the second level�9 18. Clearly, we do not mean to imply that African countries are undifferentiated. There are large

differences between Sudan, on the one hand, and Benin or Botswana on the other, and we do not mean to minimize them. However, we would argue these countries share more in common with each other than they do with, say, Germany or China, and that this makes them more comparable. The challenge in cross-national work is to find samples with enough variation to permit inferences, yet composed of countries similar enough to permit comparisons. We believe that Africa offers the possibility of doing this, making it an excellent laboratory for cross-national research.

19. A separate but equally important methodological question concerns the role of outliers-particularly Botswana and Mauritius. Both countries grew well during the period examined here. Both are also long-term democracies. Are we simply capturing the "Botswana/Mauritius" effect in our results? When we drop both countries, our results for duration at level 6 and level 2 evaporate and the results on level three weaken considerably (the coefficient stays the same but the standard error grows, producing a p value above .10). The fixed-effects results for level 3 persist. Thus, these cases are very influential to the result that democratic duration matters. However, this speaks to the sparseness of our data, not to the implausibility of our conjectures. Indeed, the cases support our conjectures. It would be nice to have richer data-more cases of democracy enduring for 30 years- but we have to work with what history gives us.

20. We should note that inclusion of the property rights variable severely reduces the cases in our sample (the measure starts in the 1980s, hence the 1970s fall out of the model). The results should be interpreted with care.

21. Our measure of the rule of law comes from the International Country Risk Guide (ICRG) and is based on an experts panel of investors. Although commonly used, this measure is not flawless. See Davis (2004) for a critical discussion of rule of law measures, including the one used here.

22. For a useful review of Botswana's electoral history, see Keineetse (2004).

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Documents

Institutional duration and growth in Africa