World Development Vol. xx, pp. xxx–xxx, 2014 0305-750X/Ó 2014 Elsevier Ltd. All rights reserved. www.elsevier.com/locate/worlddev
http://dx.doi.org/10.1016/j.worlddev.2014.11.006
Foreign Aid Responses to Political Liberalization BERNHARD REINSBERG* University of Zurich, Switzerland Summary. — This paper analyzes the impact of political liberalization on receipt of foreign aid. It distinguishes different types of donors facing different constraints in rewarding democratization with foreign aid, notably bilateral donors, the World Bank, and the European Commission. Based on a sample of 174 recipient countries from 1995 to 2009, the paper jointly examines short-term dynamics and longterm effects of sustained liberalization. Except for the World Bank, donors react to regime change. Bilateral donors are found to reward political liberalization in the second year after transition. Ó 2014 Elsevier Ltd. All rights reserved. Key words — foreign aid, democratization, bilateral donors, multilateral donors, World Bank, European Union
1. INTRODUCTION
the best of my knowledge, both effects have not been studied together in a single econometric framework. To increase measurement precision, my results are not based on total aid, which might capture flows of aid that are inherently unpredictable or that cover expenditure in donor countries unrelated to recipient-country events. I rather use “country-programmable aid,” which more appropriately reflects the aid flows that are subject to aid agreements with the recipient government (OECD, 2013a). These refinements are important because existing empirical assessments of aid conditionality are inconclusive. Aid allocation does not seem to be primarily affected by good governance, although governance has become a more important criterion for some donors since the Cold War (e.g., Clist, 2011; Dollar & Levin, 2006; Wright, 2009). However, these studies typically analyze selectivity using levels of democracy; fewer studies examine liberalization episodes within recipient countries (Alesina & Dollar, 2000). Using more precise measures derived from theoretical considerations and advanced empirical methods, I am able to draw more refined conclusions on the characteristics of the aid response. Particularly, my study sheds light on the reasons why some donors may not be able to embrace political conditionality. While much work exists on the difficulties to impose aid sanctions (e.g., Crawford, 2001; Hakenesch, this issue; Molenaers, Gagiano, Smets, & Dellepiane, this issue), I am not aware of studies focusing on similar constraints with respect to aid rewards. In addition to its scientific contribution, this paper bears practical relevance. The recent wave of political reforms in many recipient countries begs the question what kind of response these countries can expect from various donors. To which donors would these countries appeal to leverage foreign aid for their own political development? In which year would the bulk of the additional aid be expected? My paper may inform questions along these lines. I proceed as follows. Section 2 summarizes the main debates in the democratization literature as well as the primarily empirical literature on aid allocation based on political conditions. Section 3 presents the theoretical argument on the
Do donors reward political liberalization? 1 Given the recent wave of democratic revolutions and the overall trend towards democracy across the globe, this question has continued relevance for developing countries. Countries that underwent democratization have higher economic growth (Persson & Tabellini, 2007). Similarly, and more important for this paper, foreign aid seems to be more effective if given to democracies or if disbursed under good policies (Kosack, 2003; Svensson, 1999). In this paper, I revisit the issue of ex-ante conditionality in the provision of foreign aid more specifically for transitions toward democracy. 2 In particular, I ask whether donors reward political reforms with foreign aid, and if so, how (and when)? Using a sample of countries receiving aid from OECD/DAC donors from 1995 to 2009, which includes 27 spells of sustained liberalization, I conduct non-linear multivariate analysis to study the responses of official donors in terms of aid flows. The results are robust to alternative indicators, additional control variables, linear panel regression methods, and a matching approach. My study goes beyond previous work in several ways. In particular, I distinguish among different donors facing different constraints in their use of political conditionality, notably bilateral donors, the World Bank, and the European Commission. After the Cold War, most donors have committed to support democratization with higher flows of aid (i.e., UNGA, 1993), and some donors vigorously embraced political conditionality in their aid allocation (e.g., Wright, 2009, p. 552). Among all donors, donor governments arguably are closest to domestic publics and therefore should have the strongest incitation to respond to political reforms within recipient countries. Direct accountability to voters equally implies that donor governments should respond to political liberalization within a short time horizon. In contrast, multilateral donors such as the World Bank are remote from electoral pressure and should thus not be responsive to political liberalization. Moreover, the World Bank is legally constrained from explicitly endorsing regime change with higher aid flows. The Commission as a mixed type donor combines features from those two types of donors. I also seek to disentangle the short-term impact of liberalization from the long-term effect of sustained liberalization, developing two distinct measures capturing these effects. To
* An earlier version has been presented at 43rd ECPR Joint Sessions, Mainz. I am grateful to participants of the ECPR Joint Sessions workshop for support, Jo¨rg Faust, Nadia Molenaers, Rainer Winkelmann, and three anonymous reviewers. Final revision accepted: November 1, 2014. 1
Please cite this article in press as: Reinsberg, B. Foreign Aid Responses to Political Liberalization, World Development (2014), http:// dx.doi.org/10.1016/j.worlddev.2014.11.006
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impact of political liberalization on aid flows across distinct types of donors. Section 4 entails the empirical analysis, including a discussion of key variables, data issues, main results, and robustness tests. Section 5 discusses the findings, and Section 6 concludes. 2. LITERATURE I proceed with a review of two relevant strands of literature. The first strand clarifies the conceptual underpinnings of democratization. The second strand summarizes literature on aid allocation based on recipient-country progress toward explicitly political objectives. (a) Democratization There are many definitions of democratization, as there are many definitions of democracy (Dahl, 2000). As commonly used, democratization additionally requires that the ensuing regime has institutionalized the essential traits of democracy, such as constitutionally guaranteed human rights and civil liberties, regular elections for assigning executive offices, and a working principal–agent relationship with the citizens (e.g., Dahl, 1971; Diamond, 2008; Murtin & Wacziarg, 2014; Sartori, 2001). 3 In contrast, a minimalist definition of democratization would require only a relative improvement of the institutional patterns of authority over a specified period of time (e.g., Mansfield & Snyder, 2002, p. 535). This minimal concept of democratization seems to be widely used among foreign aid donors. For example, the European Commission (EC) contends that “[f]ostering good governance requires a pragmatic approach based on the specific context of each country” (EC, 2006, p. 13). This suggests that donors may even reward relative improvements toward democracy. For the sake of clarity, however, relative improvements of political institutions should be called “political liberalization,” while the subset of political reforms leading to “coherent democracies” should be called “democratization.” Democratizations are complex processes that unfold their own dynamics. For analytical purposes, the process of democratization can be divided into three phases, notably liberalization, transition, and consolidation (Schneider & Schmitter, 2004). First, the phase of liberalization can be violent (e.g., Cederman, Hug, & Wenger, 2008). Liberalization increases political instability (Bremmer, 2007), because the lower opportunity costs for political offices increase the number of elites in the political contest. If institutions are weakly developed, elites mobilize along ethnic lines (Snyder, 2000), and sometimes ignite external war to rally their supporters (Mansfield & Snyder, 2002). Second, the phase of transition establishes a more democratic regime—sometimes the old leader becomes ousted, sometimes it enters into a power-sharing agreement with an oppositional leader. New regimes are typically installed by elections, oftentimes interpreted as a sign of democratization among donors (Collier, 2010; Crawford, 2001). However, the new political equilibrium remains fragile, and even though some fundamental rights may be formally guaranteed by a constitution, human rights violations may be commonplace. In some cases, especially post-conflict transitions, the state is too weak to protect its citizens, notably minorities. It turns out that many transitions become stuck in this phase, or even fall back to autocracy.
Third, democratic consolidation occurs when the new regime stabilizes. The elites refrain from violence as the stakes from losing elections are lower (Przeworski, 1991), understandings of democratic principles become widespread (Schmitter, 1992, p. 424), and hence, democracy becomes the “only game in town” (Stepan & Linz, 1996). Institutional features conducive to consolidation are regularly held competitive elections, the alternation of political power, checks and balances, the rule of law, fundamental human rights, as well as participatory governance and a vibrant civil society (Collier, 2010; Deng, 2008; Diamond, 1994; Dahl, 1971; Przeworski, 1991; Putnam, 1993; Reynolds, 2010). Donors particularly consider elections to be a cornerstone of any consolidated democratic regime (e.g., Crawford, 2001; Diamond, 2008). Sustained democratization may have a positive impact on pro-poor development and economic growth (e.g., Haggard & Kaufman, 1995; Persson & Tabellini, 2007), mainly due to increased public accountability and enhanced checks and balances on executive power (Gibson & Boone, 2011). Democracies are more likely to deliver pro-poor policies and public goods since enfranchisement empowers poorer people (e.g., Meltzer & Richard, 1981; Plu¨mper & Martin, 2003). (b) Political conditions in aid allocation Conditionality can be ex ante, implying a selection of recipient countries; conditionality can also be ex post, responding to specific events in a given recipient country (see Koch, this issue). Empirical studies have addressed both types of conditionality related to the political governance of recipient countries. Most studies focus on the punitive side of conditionality, assessing whether donors punish human rights violations with aid withdrawal (Boulding & Hyde, 2008; Carey, 2007; Demirel-Pegg & Moskowitz, 2009; Doucouliagos & Paldam, 2011; Lebovic & Voeten, 2009; Molenaers et al., this issue). Conversely, some studies examine positive ex-ante conditionality, for example whether or not donors favor democracies in their aid allocation (Gates & Hoeffler, 2004; Hoeffler & Outram, 2011; Isopi & Mattesini, 2010; Svensson, 1999). Economic governance has similarly been made a condition for aid disbursement. Some studies establish that donors have increasingly favored well-governed countries (Dollar & Levin, 2006, p. 2044), especially after the end of the Cold War (Berthe´lemy & Tichit, 2004, p. 267; Scott & Steele, 2011, p. 53; Wright, 2009, p. 552), when bilateral donors have deemphasized other motives of aid allocation (e.g., Bearce & Tirone, 2010; Claessens, Cassimon, & Van Campenhout, 2009). However, more corrupt countries seem to have received more aid (Alesina & Weder, 2002; Easterly & Pfutze, 2008, p. 42). Overall, donor selectivity in favor of democratic polities and good governance remains low, without any significant improvement over the last two decades (Clist, 2011). Most ex-ante studies exploit cross-sectional variation among recipient countries, thereby establishing the general effect of democracy on the allocation of aid. Only a few studies examine ex-post political conditionality, notably whether donors reward democratization with more aid. Based on a sample of 77 countries from 1970 to 1994, a seminal study by two economists finds that political liberalization increases subsequent total aid flows by 50% over a threeyear period (Alesina & Dollar, 2000, p.34). A more recent study independently tests for the impact of improvements of two components of democracy; it finds that donors reward
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FOREIGN AID RESPONSES TO POLITICAL LIBERALIZATION
“contestation”, especially since the end of the Cold War, while even punishing greater ’inclusion’ (Wright & Winters, 2010, p. 64). These studies differ from the ex-ante conditionality studies because they employ panel data, thereby actually estimating a democratization effect from within-country variation. Nonetheless, aid allocation studies may generally be improved by further disaggregation. Notably, the temporal dynamics of potential aid responses to democratization are largely unexplored. In addition, heterogeneity of donors may be taken into account, as there may be differences between bilateral donors and multilateral donors (e.g., Neumayer, 2003). In general, while there exists plenty of work on the determinants of aid allocation (e.g., Clist, 2011; Dudley & Montmarquette, 1976; Hoeffler & Outram, 2011; Maizels & Nissanke, 1984; Neumayer, 2003) and particularly the relative importance of democracy among these determinants (e.g., Doucouliagos & Paldam, 2011), surprisingly little research exists on the potential reasons for donors to react to political reforms. Combining aid allocation studies with aid effectiveness literature suggests a potential avenue to account for such donor behavior. As argued by related studies, democratization may bring about tangible benefits for aid effectiveness. Democratization should boost pro-poor development because it enfranchises poor people. Indeed, an influential research paper suggests that foreign aid may only be effective when disbursed in good policy environments (Burnside & Dollar, 2000). Although the results are challenged on the grounds of sample sensitivity (Easterly, Levine, & Roodman, 2003), they seem to have been widely considered among donors (e.g., Chalker, 1991), leading to higher selectivity on governance (e.g., Boone, 1996; Dollar & Levin, 2006; Easterly, 2002). In addition, the strategic use of aid delivery channels and aid modalities represents further evidence that donors are concerned with aid effectiveness (e.g., Dietrich, 2013, p. 698). Besides aid amounts, donors can adapt aid modalities and aid channels in response to political changes in recipient countries. To the degree that different types of aid are differently valued by recipient countries, these donor policies are powerful devices of aid conditionality. On the one hand, donors shift among various types of aid, most notably in order to reduce the fiduciary risks of their aid transfers. Studies show that more democratic countries receive a larger share of program-based aid and general budget support (e.g., Amegashie, Ouattara, & Strobl, 2013; Clist, Isopi, & Morrissey, 2012; Cordella & Dell’Ariccia, 2007; Faust & Leiderer, 2012). To the degree that certain aid activities are less prone to corruption, donors also can shift to these modalities when facing less corrupt countries (Winters & Martinez, 2012). On the other hand, donors can choose their delivery channel, for example with a view to the effective implementation of foreign aid (e.g., Bermeo, 2008; Dietrich, 2013; Scott & Steele, 2011; Winters, 2010). Donor countries may use nongovernmental organizations as delivery channels to circumvent weak governments (Dietrich, 2013; Dreher, Mo¨lders, & Nunnenkamp, 2010). Recent studies focusing on the World Bank illustrate that the Bank differentiates among lending tools with a view on effective aid implementation (Winters, 2010) and that the Bank uses (economic) conditionality as an instrument of aid effectiveness (McLean & Schneider, 2013). Hence, most literature implicitly suggests that donors reward democratization due to an underlying concern for aid effectiveness (Doucouliagos & Paldam, 2011, p.5). Some studies also consider donor preferences to support democracy abroad through aid (e.g., Carothers, 1999; Finkel, Pe´rez-Lin˜a´n,
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& Seligson, 2007; Scott & Steele, 2011). However, the sources of these preferences are only loosely specified. In this paper, I offer a complementary view. Notably, public opinion favors democracy and political conditionality and thereby becomes a binding constraint for some donors in their aid allocation. Hence, my study seeks to contribute to several strands of literature, most notably aid allocation literature and its recent turn towards aid conditionality. It may also be relevant for aid effectiveness literature, given the interlinkages between donor behavior, recipient-country characteristics, and aid effectiveness. 3. AID RESPONSES BY DIFFERENT TYPES OF DONORS This section develops the theoretical argument. In a nutshell, I contend that donors must be able and willing to adapt their aid flows to political change, but they differ along both these dimensions. Some multilateral donors are legally prohibited to condition aid on explicitly political reforms, and all donor agencies seek to avoid the relatively risky support of political transition countries. However, especially bilateral aid agencies must be more responsive to political liberalization because they are more at risk of becoming “out of step” with their domestic voters being strong advocates of democracy as well as political conditionality. In the following, this argument is developed in greater detail. (a) Different ability to embrace political conditionality Donors vary in their ability to condition their aid on political events in recipient countries. In particular, donor governments are not legally constrained in their use of political conditionality. Indeed, especially after the Cold War, donor governments have publicly committed to reward political reforms with higher aid flows (e.g., Chalker, 1991; Hurd, 1990; UNGA, 1993). In contrast, the World Bank, like many other multilateral development organizations, is unable to impose political conditionality despite its historically strong commitment to economic conditionality. 4 Its Articles of Agreement explicitly state that it “[. . .] shall not interfere in the political affairs of any member; nor shall they be influenced in their decisions by the political character of the member or members concerned” (World Bank, 2012, p. 10). The agreement further stipulates that “[t]he Bank shall make arrangements to ensure that [. . .] loan[s] are used only for the purposes for which the loan was granted, with due attention to considerations of [. . .] efficiency and without regard to political [. . .] considerations” (World Bank, 2012, p. 7). Finally, the European Commission, being a rather odd type of donor, is able to impose political conditionality since the mid-1990s (e.g., Santiso, 2002, p. 118). “Democracy” and “respect for human rights” were made “essential conditions” in the aid partnerships with developing countries in the Lome´ IV Convention and the succeeding Cotonou Agreement (e.g., Pippan, 2002, p. 194). Since the Maastricht treaty, “a series of [EC] regulations elevated democracy promotion to [. . .] an overarching objective of foreign aid, not only for the [EC] but also for its member states” (Santiso, 2002, p. 111). In 1994, the European Parliament launched the European Initiative for Democracy and Human Rights (EIDHR), an EC-managed instrument to support democracy. Similarly, the EC uses budget support to incentivize political reforms (e.g., Faust & Leiderer, 2012, p. 73).
Please cite this article in press as: Reinsberg, B. Foreign Aid Responses to Political Liberalization, World Development (2014), http:// dx.doi.org/10.1016/j.worlddev.2014.11.006
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(b) Donor incentives against rewarding liberalization In general, all donor agencies want to avoid (fiduciary) risk (e.g., Amegashie et al., 2013, p. 279; Bauhr et al., 2013, p. 568; Dietrich, 2013, p. 700). Donor agencies fear media coverage on political capture of foreign aid, as it may give the impression that taxpayer money had not been wisely used and hence public support for aid might dwindle (Faust & Leiderer, 2012, p. 164; Bauhr et al., 2013, p. 570). Political transition, as it may sometimes lead to turmoil (e.g., Mansfield & Snyder, 2002), represents a time of increased (fiduciary) risk for any donor. Donors may also face other competing incentives that attenuate the role of liberalization as an aid allocation criterion. 5 Especially for the World Bank, responsiveness to political transition would severely challenge its self-image as a technocratic development institution (e.g., Chwieroth, 2007; Momani, 2007; Weaver, 2008, p. 76). However, the World Bank prefers to keep its technocratic reputation as it is a source of legitimacy and institutional power derived from delegated authority for tasks being defined as technical issues. Hence, the Bank should seek particularly low-risk tasks that perpetuate its technocratic reputation while avoiding politically tainted tasks (e.g., Allison & Zelikow, 1971; Barnett & Finnemore, 1999; Santiso, 2001). Hence, even when the donor community as a whole embraced political conditionality and pressures mounted for the Bank to “stretch its policy frontiers,” the World Bank considered “good governance” a technical issue and sought to avoid any reference to “democracy” (Santiso, 2001, p. 2). 6 To some degree, the preference for keeping a technocratic reputation similarly applies to the EC (Vaubel, 2006, p. 127). However, its political mandate as well as its infiltration by democratic values due to its exclusively democratic membership facilitates responsiveness to political change by the Commission (Santiso, 2002, p. 120). (c) Public opinion and voter proximity Why then would donors at all want to reward political reforms? This raises the issue about the supporters of democracy, notably in the realm of development cooperation. “Recipient merit” as an allocation criterion evolved within the elites after the Cold War. Following the “third wave of democratization” (Huntington, 1993), the international community pledged to support democratization in transition countries with higher flows of aid (UNGA, 1993). Political elites and development scholars alike emphasized its instrumental value for aid effectiveness (e.g., Doucouliagos & Paldam, 2011). In addition, domestic publics in Western donor countries have always been strong supporters of democracy. 7 Arguably, they may not be much interested in foreign aid, but they want democratic values and human rights to be respected. According to Eurobarometer surveys, European citizens consider “democracy” a priority for international development cooperation. 8 Furthermore, publics support aid, but only under the condition that the recipient government respects fundamental principles of democratic governance (see also, Bodenstein & Faust, 2014). This pattern is remarkably stable, with support for political conditionality exceeding 80%. 9 Against this background, I argue that donor agencies have an incentive to cater to public opinion, but the degree of responsiveness among the various donors depends on their distance to domestic publics.
Multilateral donors are at least one step farther away from domestic publics than bilateral donors. There is a long chain of delegation that prevents individual voters from holding these agencies accountable (e.g., Martens, Mummert, Murrell, & Seabright, 2002). The absence of direct parliamentary control increases the distance between individual voters and multilateral agencies and undermines agency accountability (Vaubel, 2006, p. 127). The literature on the politicization of international organizations also finds that the Bretton Woods institutions are among the most remote agencies in terms of institutionalized participation of civil society (Tallberg, Sommerer, Squatrito, & Jo¨nsson, 2013, p. 2; Woods, 2001, p. 83). Moreover, it is not very likely that multilateral agencies must fear strong accountability pressure through the member governments representing domestic publics. In fact, multilateral agencies insulate themselves against bilateral donor pressure, for example through adopting rulebased criteria aid allocation (Morrison, 2013). While some work finds bilateral donor influence on multilateral aid allocation (e.g., Dreher, Sturm, & Vreeland, 2009; Kilby, 2013; Stone, 2008), multilaterals are generally considered less politicized than bilaterals (e.g., Headey, 2008, p. 161; Keohane, Macedo, & Moravcsik, 2009, p. 1). In contrast, bilateral agencies are less distant to domestic publics. Voters are most familiar with their own national government (Anderson, 1998). Hence, national governments must fear that they will be the primary addressees “when something goes wrong” in aid allocation. In a similar vein, experiments have shown that voters are willing to punish their own government when words and deeds in foreign policy do not match (e.g., Chaudoin, 2014; Tomz, 2007). Publics do not need to know much about aid, since they receive cues from the elites (e.g., Berinsky, 2007), allowing them to make judgments along these lines. Hence, donor governments arguably want to demonstrate that they act consistently with public opinion (e.g., Aldrich, Gelpi, Feaver, Reifler, & Sharp, 2006), for example by supporting democratic values abroad. Aid may simply be an instrument to support these values. Similarly, donors want to avoid being accused of giving aid to ruthless dictators (e.g., Bader & Faust, 2014). Going one step further, it can be argued that donor governments may want to avoid any larger inconsistency of their own policies with public opinion especially at the time of domestic elections, assuming a preference for reelection of governments. Hence, the anticipated electoral accountability acts as a further constraint on donor government behavior, implying that donor governments will respond to regime change within a short period of time. The EC is not subject to direct electoral pressure, but the directly elected European Parliament co-decides on the European Union aid budget. While the Commission shares with the World Bank its technocratic approach to country development (e.g., Santiso, 2002, p. 120), its explicitly political mandate and the awareness of citizens of the European aid program as indicated by the Eurobarometer (EC, 2012e) imply relatively less insulation. Somewhat similar to bilateral donors, the Commission may want to ensure that it acts in accordance with its own commitments on political conditionality, repeatedly publicized at various occasions. In 2000, the EC together with the Council issued a statement that emphasized the key role of “democratic institutions, good governance, and the rule of law” as key conditions for effective aid (Santiso, 2002, p. 108). Following an EC Communication on Governance and Development (EC, 2003), the European Consensus on Development defined that EC aid would “have as its primary objectives the eradication of poverty [. . .] as well
Please cite this article in press as: Reinsberg, B. Foreign Aid Responses to Political Liberalization, World Development (2014), http:// dx.doi.org/10.1016/j.worlddev.2014.11.006
FOREIGN AID RESPONSES TO POLITICAL LIBERALIZATION
as the promotion of democracy, good governance, and respect for human rights” (EC, 2006, p. 8). It argued that “[p]rogress in the protection of human rights, good governance, and democratization is fundamental for poverty reduction and sustainable development” (EC, 2006, p. 13). Hence, as the EC reinforced its emphasis on political conditionality to counteract perceptions of its redundancy, it became more publicly exposed and hence general sensitivity to political change can be predicted, albeit to a lesser degree than bilateral donor governments. In sum, the above discussion leads to the following three hypotheses: Hypothesis 1 Bilateral donors are sensitive to political liberalization. Hypothesis 2 Multilateral donors are not sensitive to political liberalization. Hypothesis 3 Bilateral donors reward liberalization within a short period of time. These hypotheses are based on the mechanism that bilateral donors will cater to public support for political conditionality to a greater extent than more distant donors, particularly the World Bank and to a lesser degree the European Commission. The next section tests these hypotheses. 4. EMPIRICAL ANALYSIS This section proceeds with a discussion of key indicators, followed by data description. Subsequently, I visualize donor responses around political liberalization, followed by multivariate analysis. Finally, I run a series of robustness checks based on additional control variables, alternative indicators, and different estimation methods. (a) Key predictors of political liberalization Ideally, an analysis of donor responses to democratization would entail measures of these various events occurring over the course of transition. Facing feasibility constraints, a second-best option uses an indicator of democratization. However, choosing such an indicator involves the challenge that there exists a more fundamental disagreement about the appropriate measurement of democracy, the concept underlying democratization (Dahl, 2000, p. 3). Related measures of democracy abound, each having their pros and cons (Munck & Verkuilen, 2002). A key distinction refers to whether democracy is measured continuously (e.g., Bollen & Paxton, 2000; Dahl, 1971; Gates, Hegre, Jones, & Strand, 2006; Vanhanen, 2000), or binary (e.g., Huntington, 1993; Papaioannou & Siourounis, 2008; Przeworski, Alvarez, Cheibub, & Limongi, 2000). A binary indicator has the advantage of being more robust to measurement error, while continuous measures are able to capture variation in the intensity of democratization (Strand, Hegre, Gates, & Dahl, 2012, p. 7). Quasi-continuous index measures of democracy assume that a polity improvement has the same effect over its entire range. This may not be plausible, notably if donors reward improvements of an autocracy relatively more than an equally large improvement of a democracy. The possibility of “decreasing returns to democratization” could be captured by logarithmizing these polity indices, or by accounting for the initial level of the polity given an appropriate panel estimation method. Another distinction refers to the substantive definition of democracy built into the various polity indices. Principal component analysis shows that democracy has two distinct components, ‘contestation’ and ‘inclusion’ (Coppedge, Alvarez,
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& Maldonado, 2007). Case studies (e.g., Collier, 2010; Crawford, 2001) as well as statistical analysis (Wright & Winters, 2010, p. 64) suggest that donors tend to emphasize “contestation,” notably competitive elections. Based on these considerations, I consider three measures for my analysis. First and foremost, I employ the Polity IV index (Gurr & Jaggers, 1995), given its conceptual proximity to ’contestation’ and the tendency of donors to respond to formal polity changes. The Polity IV measures checks and balances to executive power, thereby capturing the “formal patterns of authority.” It changes whenever a country promotes tangible institutional reforms, holds competitive elections, promulgates a new constitution, or adopts power-sharing agreements (Marshall, Gurr, & Jaggers, 2010). Polity IV tends to give less emphasis to political participation, which may lead to a high score coexisting with clientelism (Gates et al., 2006, p. 897). Second, the Freedom House index seeks to capture civil liberties and political rights (Freedom House, 2012). Donors may also reward these characteristics of ’inclusion’, independently of de-jure political institutions. While Freedom House and Polity IV do not need to be congruent, their sample correlation appears to be very high (q ¼ 0:9). I consider the Freedom House index with a view to assessing donor responses to democratic inclusiveness, despite potential weaknesses of the index (Munck & Verkuilen, 2002). Third, since both indices have the above-mentioned disadvantages of quasi-continuous measures, I additionally consider a dichotomous democracy indicator. If a country respects fundamental rights and if its executive positions are filled by regularly held competitive elections, it can be considered a democracy (Przeworski et al., 2000). Any of these three measures may capture the traits of a political regime. I take the Polity IV index without any adaptations, but for ease of representation, I rescale the Freedom House index to a 10-point scale from zero to 10, higher values indicating more democratic rights. The dichotomous indicator yields the effect of a discrete change from autocracy to democracy. Each indicator is lagged by one period throughout the multivariate analysis. The above indicators are not sufficient for my purposes. They also do not test whether donors reward democratization or whether they punish autocratization. In addition, the temporal dynamics of foreign aid responses cannot be assessed by using a single indicator. Therefore, I derive a political liberalization indicator that only takes the positive part of a polity change with base year t. Formally, it can be defined as ðp½t p½t 1Þþ :¼ maxf0; p½t p½t 1g; where p½t refers to the Polity score in period t. I add a battery of three temporal lags of this indicator. Previous research suggests that three lags are sufficient to capture short-term donor responses (Alesina & Dollar, 2000; Marshall et al., 2010). I also add a battery of indicators for “political closure,” defined as ðp½t p½t 1Þ :¼ minf0; ðp½t p½t 1Þg; in the above notation. Together with the set of liberalization indicators, these variables disentangle the direction of regime change as well as its temporal effects. Conceptually, I treat the political closure indicators as control variables. Finally, I want to know whether there is any long-term effect of political liberalization beyond the four-year interval captured by the above liberalization indicators. Yet, a long-term aid response would only be expected for sustained liberalization spells. Many political reforms are not durable (Figure 1). Sustained liberalizations—polity improvements that remain stable over a significant time period—may be different from unstable transitions. My indicator of sustained liberalization
Please cite this article in press as: Reinsberg, B. Foreign Aid Responses to Political Liberalization, World Development (2014), http:// dx.doi.org/10.1016/j.worlddev.2014.11.006
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Figure 1. Transitions with at least a six-point increase in the Polity IV. Source: Polity IV and own calculation based on Marshall et al. (2010). Column 4 gives the Polity score after transition that occurred in the year indicated by Column 2. Column 3 indicates the size of the transition. Column 5 indicates stable transitions.
requires at least a two standard deviations jump in the Polity IV score that must remain strictly within a two standard deviations band in a symmetric time interval of four years relative to the transition. For both criteria, the standard deviation has been based on the entire sample of countries. 10 Since donors only can observe “sustained liberalization” based on an evolution of the regime beyond the immediate transition period, I construct a step dummy that takes the constant value of one from the fourth year of transition until the end of the sample period. It captures any long-term effect of a liberalization that turned out to be stable. (b) Data and sample I assess my hypotheses using a sample of 174 OECD/DAC recipients of Official Development Assistance over the period
from 1995 to 2009. This choice is driven by data availability, but also by the fact that aid selectivity has increased since the end of the Cold War (e.g., Berthe´lemy & Tichit, 2004; Dunning, 2004; Hopkins, 2000). During this period, most transitions occurred in Sub-Saharan Africa, bringing patrimonial rule to an end (Mattes, 2010). A minority of transitions occurred in Europe and Central Asia, Latin America, and Asia. Figure 1 shows the distribution of democratic transitions. Twelve cases with Polity IV improvements by at least six points returned to autocratic rule, as indicated by the last column. In contrast, there were 27 spells of sustained democratization. Six spells thereof had at least a six-point Polity IV increase. I distinguish foreign aid commitments from three types of donors. The first group of donors comprises the European Union member states that are also members of the Donor Assistance
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FOREIGN AID RESPONSES TO POLITICAL LIBERALIZATION
Committee of the Organization of Economic Cooperation and Development (EU DAC donors). 11 Throughout the analysis, I estimate an average effect for these donors. This can be seen as appropriate under the premise that foreign aid responses of European donors to recipient-country policies are sufficiently homogeneous, for example because these donors regularly meet in the Council of Foreign Ministers of the European Union. I also provided anecdotal evidence from policy documents in the theory section, which focused on the EU. Finally, EU DAC donors jointly provide the highest flows of bilateral aid. 12 The next donor is the International Development Association (IDA), the concessional lending wing of the World Bank. It provides “foreign aid” in the strict sense, unlike its sister branch which gives out loans. 13 The last donor is the European Commission (EC). The EC has become a significant donor itself, most notably in the area of budget support. My choice of donors provides the opportunity to directly compare the aid responses to political liberalization between the European Commission and its member states. My dependent variable, country-programmable aid (CPA), refines the concept of Official Development Assistance (ODA), defined as “grants and loans to countries and territories [. . .] and to multilateral agencies which are: (a) undertaken by the official sector; (b) with promotion of economic development and welfare as the main objective; (c) at concessional financial terms [. . .]” (OECD, 2011). In contrast, CPA more directly captures the proportion of ODA that derives from government-to-government interactions between donors and recipients (OECD, 2013a). CPA deducts from ODA the following types of aid: humanitarian aid and debt relief due to their unpredictability, costs incurred in the donor country, and aid flows that do not form part of cooperation agreements with recipient governments (see Table A8). CPA is preferable to ODA because it does not include potential aid flows in response to confounding events, for example humanitarian disasters. Hence, there is no need to adjust for these confounders in the multivariate analysis, and aid data becomes much less noisy. The OECD makes available CPA data since 2000, but given that it is known how CPA is calculated from ODA (OECD, 2013a), missing values for the 1990s can be calculated using the respective aid categories from the Creditor Reporting System (OECD, 2013b). Following general practice as to official foreign aid data, I interpret missing values as zero commitments. The use of commitments rather than disbursements reflects my interest in donor motivations. When running linear models for robustness checks, I take the logarithm on positive aid amounts to remove skewness and heteroskedasticity (Lai, 2003). (c) Spell analysis First of all, I visually explore the average aid response pattern to a sustained liberalization. Figure 2 tracks the average donor response to the average sustained liberalization within five-year intervals around the peak year of transition. The figure has been produced based on the 27 spells of sustained liberalization. As a first step, I normalize aid flows to the value of one at the transition year, thus expressing preceding aid and subsequent aid in terms of the peak year of each spell. Transition spells are pooled, followed by local-polynomial fitting. For the local-polynomial regression, I choose a bandwidth parameter b ¼ 0:66, which turns out to smoothen out statistical noise without filtering out the important
7
Figure 2. Average relative flows of total aid around sustained liberalization events.
trends. Confidence intervals are obtained by bootstrapping. 14 It can be seen that total aid exhibits an upward trend, and its growth accelerates exactly after the peak year of transition. Though it is difficult to visually assess whether aid growth remains sustainably higher after political liberalization, it seems that total aid returns to its canonical trend after three years (Figure 2). For more distant years after the liberalization event, aid flows are more likely to be influenced by confounding factors. Therefore, I partial out the effect of potential confounders by obtaining residuals of a Poisson quasi-maximum likelihood estimation of total aid on the entire set of controls (except liberalization), including country-fixed effects and a linear time trend (see the next section for a discussion of the method). The residuals obtained from this estimation represent the unexplained part of foreign aid. If democratization did not affect foreign aid receipt, the residual plot should be a flat line. I standardize the residuals by centering them around their peak-year value and dividing by the standard deviation of foreign aid in order to facilitate cross-donor comparisons. The results are insightful. Average aid is significantly higher two years after democratization, even after having controlled for other factors accounting for short-term aid dynamics (Figure F1, see Appendix). Consistent with the interpretation of Figure 2, this also suggests that there is no long-term effect of political liberalization. In addition, I repeat the residual analysis with disaggregated foreign aid for the three main donors. For the EU DAC donors, bilateral aid is somewhat lower than predicted immediately before the transition, but higher shortly after transition, before falling back to pretransition levels; these effects are not statistically significant (Figure F2). World Bank aid residuals are virtually flat, possibly even lower than predicted after transition (Figure F3). For the European Commission, unexplained aid flows at lowest at the peak of transition and otherwise indistinguishable from zero (Figure F4). To see whether these spell dynamics are driven by political liberalization, I explicitly test for these events using multivariate analysis.
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(d) Multivariate analysis Using the entire sample of recipient countries, I conduct multivariate analysis to estimate short-term dynamics and long-term effects in a single framework. In particular, I employ Poisson quasi-maximum likelihood estimation (PQMLE), with fixed effects on recipient countries to mitigate potential omitted variable bias. While being rarely used, PQMLE offers considerable advantages over its alternatives, notably when the data have many zeros and standard errors are heteroskedastic. 15 PQMLE has three advantages, each of them being relevant for my own analysis. First, zeros in the dependent variable are dropped when using a log-linear model, while PQMLE fully considers the semi-continuous nature of the dependent variable (Santos Silva & Tenreyro, 2011). Second, PQMLE is robust to misspecification of the distributional form of the dependent variable, as long as its conditional mean is correctly specified (Gould, 2011). Third, Monte Carlo simulations have shown that PQMLE outperforms both Ordinary Least Squares and the Tobit estimator in the presence of heteroskedasticity and many zero observations (Santos Silva & Tenreyro, 2011). The generic specification of PQMLE reads as Eðy it j y it > 0; Z it ; ci Þ ¼ ci expðZ it bÞ, where Z it collects the covariates, including a constant, the main predictors, and the controls, and ci being the fixed effect. In the fully specified dynamic model, the main predictors include a sustained liberalization indicator, a political liberalization indicator along with three lags, and a political closure indicator along with three lags. 16 In the following, I conduct baseline PQML models using country-fixed effects and polynomial time trends. When replacing the polynomial trend by a battery of idiosyncratic year effects, the results are virtually unaffected. To avoid the restrictive variance specification of the Poisson model, I calculate robust standard errors clustered on countries (Gould, 2011). Goodness-of-fit measures for PQMLE are computed using McFadden’s pseudo-R2 , which subtracts from unity the share of the log-likelihood of a model over a null model on the same number of observations. The null model includes only fixed effects on recipient countries. Table 1 assesses aid responses by bilateral donors to political changes. The contemporaneous Polity IV score is positively
Polity IV
(2) EU CPA
Quadratic trend Cubic trend N ll ll0 Pseudo-R2
Polity IV
(3) IDA CPA
0.05 (0.04)
0.10 (0.07) 0.01 (0.01) 0.45 (0.38)
0.10 (0.07) 0.01 (0.01) 0.46 (0.37)
0.19* (0.11) 0.10 (0.07) 0.01 (0.01) 0.46 (0.37)
878 21,276 22,277 0.05
996 22,364 23,066 0.03
993 22,343 23,007 0.03
Binary democracy indicator Time trend Quadratic trend Cubic trend N ll ll0 Pseudo-R2
PQMLE with country-fixed effects, clustered standard errors. p-values: ***, .01; **, .05; *, .1.
(1) EC CPA
0.13*** (0.04) 0.02*** (0.00) 0.59*** (0.17)
0.12*** (0.04) 0.01*** (0.00) 0.55*** (0.18)
0.15** (0.07) 0.12*** (0.04) 0.01*** (0.00) 0.48*** (0.18)
1739 19,375 21,839 0.11
2045 22,667 25,968 0.13
2030 22,897 25,802 0.11
(2) EC CPA
0.07** (0.03)
0.32*** (0.08)
0.26** (0.12) 0.32*** (0.08)
0.03*** (0.01) 1.09*** (0.39) 1942 20,978 24,253 0.14
(0.01) 1.03*** (0.40) 1926 20,892 24,239 0.14
Binary democracy indicator Time trend Quadratic trend textsuperscript*** Cubic trend N ll ll0 Pseudo-R2
(3) EC CPA
0.03** (0.01)
Freedom House
0.07*** (0.03)
PQMLE with country-fixed effects, clustered standard errors. p-values: ***, .01; **, .05; *, .1.
(2) IDA CPA
0.03** (0.01)
Freedom House (rescaled)
Polity IV
Binary democracy indicator Time trend
(1) IDA CPA
(3) EU CPA
0.03*** (0.01)
Freedom House (rescaled)
Table 2. World Bank aid responses to polity changes
Table 3. Aid responses by the commission to polity changes
Table 1. Bilateral aid responses to polity changes (1) EU CPA
correlated with foreign aid by bilateral donors (Model 1). This results equally holds for the Freedom House index instead of the Polity IV index (Model 2), as well as the dichotomous democracy indicator (Model 3). From the PQMLE, I can calculate the factor changes in the outcomes by exponentiating the predicted marginal effect of the key variables. A one-unit polity improvement increases bilateral aid (EU CPA) by about 3%. Hence, major transitions of six points would affect EU CPA by 18% on average. A one-unit change in the Freedom House index roughly yields a seven-percent change of aid in the same direction, or, 22% for a one standard deviation change. Finally, switching from autocracy to democracy in a dichotomous world increases aid flows by 16%. 17 Table 2 assesses World Bank aid in response to political changes. In fact, World Bank aid even negatively reacts to a Polity IV improvement, by 3% on average for each unit. There is no significant effect when using the Freedom House index
0.35*** (0.10) 0.04 0.03*** (0.01) 1.18*** (0.44) 1658 19,879 23,178 0.14
PQMLE with country-fixed effects, clustered standard errors. p-values: ***, .01; **, .05; *, .1.
Please cite this article in press as: Reinsberg, B. Foreign Aid Responses to Political Liberalization, World Development (2014), http:// dx.doi.org/10.1016/j.worlddev.2014.11.006
FOREIGN AID RESPONSES TO POLITICAL LIBERALIZATION Table 4. Dynamic analysis using the Polity IV index
Sustained liberalization ðP ½t P ½t 1Þþ ðP ½t 1 P ½t 2Þþ ðP ½t 2 P ½t 3Þþ ðP ½t 3 P ½t 4Þþ ðP ½t P ½t 1Þ ðP ½t 1 P ½t 2Þ ðP ½t 2 P ½t 3Þ ðP ½t 3 P ½t 4Þ Time trend Quadratic trend Cubic trend N ll ll0 Pseudo-R2
(1) EU CPA
(2) IDA CPA
(3) EC CPA
0.00 (0.10) 0.01 (0.01) 0.01 (0.02) 0.02** (0.01) 0.00 (0.01) 0.02 (0.02) 0.04** (0.02) 0.04** (0.02) 0.04** (0.02)
0.04 (0.19) 0.02 (0.02) 0.03** (0.02) 0.02 (0.02) 0.04** (0.02) 0.04 (0.03) 0.01 (0.03) 0.01 (0.01) 0.05*** (0.01)
0.11 (0.12) 0.02 (0.03) 0.04 (0.03) 0.04 (0.02) 0.01 (0.02) 0.06** (0.02) 0.03 (0.03) 0.05* (0.03) 0.07** (0.03)
0.13*** (0.04) 0.01*** (0.00) 0.54*** (0.18)
0.08 (0.06) 0.01 (0.01) 0.39 (0.34)
0.37*** (0.09) 0.04*** (0.01) 1.19*** (0.40)
1770 22,818 26,158 0.13
896 21,262 24,951 0.15
1690 20,914 22,652 0.08
PQMLE with country-fixed effects, clustered standard errors. p-values: ***, .01; **, .05; *, .1.
instead. Moving from autocracy to democracy reduces estimated World Bank aid by about 20%, but the effect is barely significant. Table 3 assesses the response of European Commission aid. EC CPA significantly responds to Polity IV changes (Model 2), as well as changes in the Freedom House index (Model 2). The effects are in the same order of magnitude as for the bilateral donors. Reactions to discrete changes toward democracy are even more pronounced (Model 3). In particular, EC CPA changes by 30% when the regime type of a recipient country has switched. All effects are statistically significant at the five-percent level. The subsequent models examine the temporal dynamics of the aid responses to political liberalization. 18 Using the liberalization indicator, I must also include “autocratization” as another control variable in order to avoid omitted variable bias. Table 4 shows a positively significant effect of political reforms on EU CPA, notably in the second year after transition. A sixpoint polity improvement increases EU CPA by 12%. This effect is statistically significant (p < 0.05). Yet, bilateral donors to not respond to sustained liberalization (Model 1). For the World Bank, there tends to be a slightly negative effect of political liberalization with respect to its aid commitments after two years from transition; interestingly, the negative effect becomes more significant by the last year of the short-term transition horizon. Again, there is no significant effect of sustained liberalization on World Bank aid (Model 2). Finally, the last column tests the impact of liberalization on EC aid. None of the short-term liberalization indicators reaches significance. Similarly, there is no long-term impact of sustained liberalization.
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In addition, the above specification highlights whether donors respond to different directions of political change, given that both the liberalization dummies and the autocratization dummies are included. It turns out that bilateral donors significantly punish political closure starting after the first year of such event (Model 1). The Commission reacts even more promptly, decreasing its aid in the year of autocratization and again after three years (Model 3). For both types of donors, aid amount reductions tend to be more pronounced than aid amount increases following liberalization. For example, a six-point decrease in the polity score would reduce aid by almost 35%. Lastly, the World Bank does not initially respond to political closure, but then even increases its aid commitment after three years. (e) Robustness checks For robustness tests, I introduce additional control variables, alternative estimation methods, and alternative indicators for liberalization events. (i) Control variables By running fixed-effects estimations throughout my analysis, I have already eliminated the impact of possible confounders that do not vary over time. Aid allocation literature points to a number of time-varying control variables that may confound the relationship between political liberalization and foreign aid. In particular, donors are known to allocate their aid according to the “four P’s”—population, proximity, poverty, and policies (Clist, 2011). These characteristics are measured for the recipient countries. Population size reflects the importance of the recipient in terms of both development need and donor proximity. Some studies report a small-population bias (Harrigan & Wang, 2011; Hoeffler & Outram, 2011; Maizels & Nissanke, 1984; Neumayer, 2003). I include the logarithm of population, sourced from the World Development Indicators (WDI) (World Bank, 2011). Gross domestic product per capita indicates the level of development. Recipient-country wealth indicates developmental need (Dollar & Levin, 2006) as well as the opportunity costs for potential aid-for-policy deals (Bueno de Mesquita & Smith, 2009). It also proxies institutional capacity, which is a prerequisite for certain types of aid. Further variables to capture recipient need include the number of battle deaths as a proxy for political violence (World Bank, 2011), as well as the costs for natural disasters sourced from the EM-DAT database (CRED, 2011). My dependent variable should not contain emergency aid flows, but I do not know the coding quality of the aid data and thus include these emergency events as control variables. Donor proximity can be captured by variables indicating economic relations with the recipient countries. I use total trade flows as a percentage of gross domestic product. In addition, I use overall foreign direct investment as a percentage of gross domestic product. Both indicators are sourced from WDI (World Bank, 2011). To deal with missing data, I pre-process the recipient variables with multiple imputation (using the Amelia II package) (Honaker, King, & Blackwell, 2011). Imputed variables are characterized in the outputs with a super-scripted empty circle. Values on aid, democratization, autocratization, and similar indicators are not imputed. In addition, there are a number of time-varying donorspecific controls. These variables may interfere with the willingness of donors to reward democratization with foreign aid.
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For bilateral donors, I include the annual unemployment rate as well as the consumer price index to capture economic hardship in donor countries. Everything else equal, I expect rising unemployment and rising consumer prices to reduce the fiscal space to provide aid. I apply a twice-year lag to both indicators. Data are sourced from the OECD website, and simple averages are taken across donor countries. Lacking an equivalent measure for multilateral donors, I include their own multilateral inflows received from OECD/DAC countries, lagged by three years. Higher multilateral budgets might be expected to increase disbursements of multilateral agencies with a time lag. Data comes from the DAC tables (OECD, 2013b). Turning to the general sensitivity of donors to political changes in recipient countries, the main results are robust when adding control variables (Table A1, see Appendix). Bilateral donors consistently react to political changes, especially when the estimates are based on the Polity IV index and the Freedom House index (Model 1). The binary indicator of democratization stays positively significant, albeit at a lower level of precision (p < 0.10). Possibly, some control variables such as country wealth, trade flows, and foreign direct investment may absorb some variation that should be attributed to democratization. The World Bank does not respond to political change, which is even negatively related to aid (Model 2). In contrast, EC aid significantly responds to political changes, except for the Polity IV index (Model 3). In sum, the main results are recovered under a fully specified model. Turning to the dynamic analysis, the control variables do not significantly affect the estimates of interest (Table A2, see Appendix). Some political liberalization events apparently coincide with periods of declining inflation, which slightly reduces the positive effect of liberalization for bilateral aid (Model 1). Higher inflation strongly predicts a reduction of bilateral aid. Key results for the other donors are not affected by the control variables. The World Bank tends to decrease its exposure to politically liberalizing countries (Model 2), whereas the Commission does not alter its aid at all (Model 3). (ii) Linear specifications I have argued before that PQMLE models are appropriate when dealing with zero-inflated aid data and heterogeneous panels. As sensitivity check, I present results from log-linear models. Table A3 (see Appendix) combines estimates from several models, each using a specific indicator for political change once at a time. Consistent with my hypothesis, bilateral donors consistently respond to political reforms, particularly giving more aid when the regime becomes more democratic (Model 1). There is no reaction whatsoever of World Bank aid to any political reform indicator (Model 2). Finally, the Commission significantly responds to an improvement of inclusiveness and full-fledged democratization, while it does not seem to respond to changes in the Polity IV score (Model 3). Table A4 (see Appendix) shows linear panel estimations with the battery of polity change indicators. As before in the main results, there is no long-term effect of sustained liberalization. In fact, the only significant result as regards liberalization is the positive short-term response of EU DAC donors to political liberalization two years after transition (Model 1). In the linear specification, none of the other donors rewards political liberalization. (iii) Alternative indicators of liberalization As previously discussed, polity indices have the disadvantage that the type of events to which donors react cannot easily be assessed. Hence, I assess whether the significant
relationships can be explained by specific events that should strongly correlate with changes in the Polity IV index (see Table A8 in the Appendix for an explanation on all variables used in this sub-section). First, I check whether bilateral donors respond to executive elections, as previous literature has suggested (e.g., Collier, 2010; Crawford, 2001). Using the full dynamic specification with control variables as the baseline model (Table A5, see Appendix), I insert an indicator of executive elections. Indeed, the significant coefficient of political liberalization vanishes, and execution elections tend to have a positive effect on aid commitments (Model 2). Similarly, I check whether incumbent change affects the relationship between political liberalization and bilateral aid. Again, the alternative indicator fully absorbs the original effect (Model 3). Second, using the same approach, I corroborate that the World Bank does not reward political liberalization (Table A6, see Appendix). In fact, neither executive elections (Model 2) nor incumbent change (Model 3) affect the original findings on liberalization. Is the World Bank sensitive to political (in)stability? The ICRG index for political stability strongly positively relates to World Bank aid, and it also mitigates some of the previously negative aid response (Model 4). Conversely, “good governance” as indicated by better control of corruption tends to have an independent effect unrelated to political liberalization (Model 5). Third, virtually no changes occur when including pathway variables in the baseline specification for EC CPA. The Commission seems to punish incumbent change with less aid, while it rewards better control of corruption. However, these events are unrelated to liberalization (Table A7, see Appendix). (iv) Reverse causality Extant research addresses the possibility that foreign aid can affect the likelihood of regime change. Notably, “[a]id may [. . .] be endogenous to the process of democratization, wherein donors observe movement towards democratization and reward this behavior with more aid” (Wright, 2009, p. 565). Even though earlier empirical studies using total aid do not find any effect (Al-Momani, 2003; Bermeo, 2011; Boone, 2011; De Hennin & Rozema, 2011; Goldsmith, 2001; Knack, 2004), there are pertinent arguments in favor of some endogeneity. On the one hand, foreign aid, particularly democracy aid, can facilitate democratization, for example by relaxing the budget constraint of the incumbent (De Hennin & Rozema, 2011), or by giving a patient leader the necessary non-tax revenue for increasing public expenditure before an election (Collier, 2006; Wright, 2009). Donor intent and aid modalities are key to make regime change happen, since only democracy aid tends to be able to bring about regime change (e.g., Carothers, 1999; Finkel et al., 2007; Kalyvitis & Vlachaki, 2012; Scott & Steele, 2011), for example through buying reforms from incumbents (Crawford, 2001) or supporting the opposition (Dietrich & Wright, 2011). On the other hand, foreign aid may also inhibit democratization, even unintended by donors (e.g., Limpach & Michaelowa, 2010; Cruz & Schneider, 2012). Recipient-country leaders may use aid to prolong their autocratic rule (Licht, 2010), by paying bribes to elites (Svensson, 2000), by financing a state security apparatus (Kalyvitis & Vlachaki, 2012), or by tactically providing public goods (Bueno de Mesquita & Smith, 2010). Foreign aid also weakens the accountability of the incumbent to its own citizens (Bra¨utigam & Knack, 2004; Djankov, Montalvo, & ReynalQuerol, 2008; Morrison, 2009) and to the other branches of
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FOREIGN AID RESPONSES TO POLITICAL LIBERALIZATION
government (Bra¨utigam, 2000), thereby fostering corruption (Alesina & Weder, 2002) and delaying political reforms (Kalyvitis & Vlachaki, 2012). I cannot exclude the possibility that foreign aid increases the chances of democratization, which would be a reason for concern if also foreign aid was highly persistent. To address these concerns, I employ several empirical remedies throughout the paper. Notably, predictors of interest are lagged, and the estimates are derived from unobserved heterogeneity models to eliminate the effect of time-invariant factors that jointly determine democratization and foreign aid (e.g., Wooldridge, 2002, p. 247). Beyond these standard remedies, I explore panel estimations, adjusted for potential covariate imbalance in order to address the problem that “control units” might be far outside the range of “treated units”. 19 Careful model specification becomes more important in the case of little overlap in the covariates. Robust estimation ideally requires elimination of any relationship between the treatment and the covariates through matching (e.g., Ho, Imai, King, & Stuart, 2007, p. 211). In my case, there does not appear to be a lack of overlap; however, as a final robustness test, I go on to obtain imbalance-corrected estimates (see the Appendix for technical details). It turns out that the previous findings are robust even when applying these sophisticated methods. Besides empirical remedies, case-study evidence may help assessing causally meaningful directions. Studies have assessed the potential impact of budget aid on democratic reforms. For example, Tanzania, a large recipient of budget aid, has failed to become more democratic despite huge amounts of budget aid, and many observers emphasize the critical role of domestic drivers of change (Frantz, 2004, p. 14). Other assessments emphasize that parliamentary participation has not improved, civil society failed to be a change agent (Gould & Ojanen, 2003), and patronage networks continued to prevail (Cooksey, 2003). These judgments suggest that aid flows are not a key determinant of political changes within recipient countries. 5. DISCUSSION AND IMPLICATIONS The above results provide a nuanced picture on the sensitivity of various donors to political change in recipient countries. In particular, my study has revealed the temporal dynamics of foreign aid flows in the event of political liberalization by three types of donors. First and foremost, EU DAC donors are sensitive to political changes. They most consistently react to liberalization among the three types of donors as they jointly reward political reforms two years after transition with approximately 12% higher country-programmable aid. Analysis of specific liberalization events has shown that these donors react to genuinely political events such as an executive election. This finding echoes earlier work on the importance of elections (Collier, 2010; Crawford, 2001; Reynolds, 2010). In addition, consistent with some earlier studies, bilateral donors punish political closure (e.g., Boulding & Hyde, 2008). Second, the World Bank does not significantly respond to political changes. It even tends to reduce its exposure in the event of transitions: Measured by the Freedom House index, political liberalization does not affect World Bank aid, while it exerts a negative effect when proxied by the Polity IV index. In the dynamic analysis of liberalization events, World Bank aid tends to decrease shortly after transition. The fact that this reaction partially relates to the political instability from regime
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transition lends support to the theoretical claim that the World Bank seeks to avoid risk while being at enough distance from political pressure to support regime change with higher aid (see Section 3). The findings also are consistent with previous literature showing that the World Bank responds to economic governance (Burnside & Dollar, 2000, p. 863). Third, EC aid is sensitive to regime change. However, this result does not hold under all specifications, which suggests that the EC responds less consistently than EU DAC countries. The dynamic analysis shows that the Commission does not reward liberalization. Conversely, it promptly punishes autocratization, and this reaction can be related to the lower quality of recipient-country governance in the event of transition. While previous studies leave an inconclusive picture as regards aid selectivity on democracy by the Commission (e.g., Dollar & Levin, 2006, p. 2044; but see Baumann, Berthe´lemy, & Michaelowa, 2013), these studies have not examined whether EC aid responds to liberalization within recipient countries. My findings shed light on the debate about the identity of the Commission as a donor. Some recent empirical evidence suggests that the EC behaves rather like a development donor than a democracy promoter (Del Biondo, this issue). In fact, the EC might so promptly cut aid in the event of autocratization possibly because it honors the Cotonou Agreement, which forces the EC to do so; conversely, there is no comparable legal obligation to reward liberalization. Despite this “technocratic approach” to development, “contrary to the apolitical mandate of the [World Bank]—EC aid [. . .] has explicitly political objectives” (Santiso, 2002, p. 120). By consistently punishing autocratization, the Commission embraces political conditionality, similarly as its member states when rewarding liberalization. It hence is functionally closer to a bilateral donor, given also its relative proximity via European Parliament involvement compared to the World Bank. None of the donors actually rewards sustained liberalization over the long term. This implies that donors possibly fail to reward the countries that are genuinely progressing toward democracy, while opening the purse for short-term political liberalization that may reverse to autocracy after a few years. These response patterns can be explained by political economy considerations. I have argued that bilateral donors are more compelled to cater to public opinion and hence anticipate a potential electoral threat. To the degree that multilateral organizations are relatively more insulated from public pressure, they will not reward liberalization with higher aid. Are there any alternative explanations for the empirical patterns? I do not claim that my arguments are the only possible explanation. However, any alternative theory must account for the heterogeneous response patterns identified in the empirical section. In particular, consider the alternative that donors impose political conditionality whenever they are both able and willing to do so, and “willingness” would be measured by donor rhetoric. This would explain the different responsiveness by bilateral donors and the World Bank, but not the Commission, which also announced to reward political reforms in its official documents. Similarly, a theory that assumes that all donor agencies respond to their institutional self-interest to avoid fiduciary risk cannot explain different aid responses to the same risky events. Finally, a theory focusing on the characteristics of transition cannot account for different aid responses either. In fact, my analysis has shown that the interplay between legal constraints and domestic political economy considerations determines political conditionality patterns across different donors.
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6. CONCLUSION In this paper, I have examined whether or not donors actually reward political liberalization with higher aid flows, and I have identified the interplay between legal constraints and domestic political economy considerations as the key driver of the use of political conditionality across different donors. Theoretically, I have distinguished bilateral donors and multilateral donors. These types of donors should respond differently to political reforms, because they operate under different legal rules, and they face different constraints to act upon a public opinion that strongly favors democracy and aid allocation conditional upon political reforms. Notably, since donors vary in their proximity to domestic publics, the constraint from public opinion should be strongest for bilateral donors, as opposed to the World Bank (or, to a lesser degree, the European Commission). Conceptually, I treat the European Commission as a mixed-type donor with an explicitly political mandate, which faces lower electoral pressure than donor governments but whose aid allocation decisions are politicized. Empirically, I have employed advanced econometric techniques. Moreover, I have developed more fine-grained measures to capture the relevant relationships. In particular, I have disentangled the two possible directions of political change, including them into a dynamic analysis of short-term aid responses. I also developed an indicator of sustained liberalization to capture any potential long-term effect of sustainable political reforms. Finally, I have used countryprogrammable aid in order to reduce unwarranted noise in the response variable. For a sample of 174 foreign aid recipients from 1995 to 2009, multivariate exponential regression has shown that among all donors, bilateral donors most consistently respond to contemporaneous regime change. Moreover, I have found that bilateral donors reward political liberalization two years after transition. A major transition would imply about 12% more bilateral aid. In fact, these donors react to explicitly political events such as executive elections or an incumbent change. None of the other donors shows any positively
significant short-term response to political liberalization. World Bank aid even tends to decrease in the event of liberalization. Across all donors, democratization does not have long-term benefits in terms of higher aid receipts—a result that survives many robustness checks such as the use of alternative indicators, more conventional estimators, and yet more advanced data pre-processing methods. In sum, these findings are consistent with my theoretical argument, while being difficult to explain by any alternative theory. The results are relevant for the wider debate about the role of foreign aid in leveraging democratic transitions and to the policy dilemmas involved in this process (e.g., Buchanan, 1975). My results speak to previous studies that have found democratization to be followed by instantaneous increases in foreign aid (Alesina & Dollar, 2000), albeit I have obtained smaller effect sizes. Moreover, the skepticism of previous studies suggesting that democracy tends to be a second-order allocation criterion seems to be justified (Carey, 2007; Clist, 2011; Doucouliagos & Paldam, 2011). If democracy does not imply higher aid, it is possibly not surprising that steps towards democratization do not increase aid flows in the long term. However, my results clearly show that bilateral donors do react to democratization, and future research would be needed to identify the exact underlying causes. My analysis of specific events has explored some proximate political reform characteristics, while my theory rests on donor-specific arguments. Future work may combine these two sets of features to develop a unified model of donor responses to political liberalization. Such analyses may also include other forms of donor reactions, for example changes in the modalities of allocation over the course of transition. Indeed, I have not examined the possibility that political change may alter the strategic composition of donor portfolios, notably as to different aid modalities (e.g., Amegashie et al., 2013; Cordella & Dell’Ariccia, 2007), aid sectors (e.g., Winters, 2010), and aid channels (e.g., Bermeo, 2008; Dietrich, 2013). These instruments establish a new dimension of aid conditionality, to the degree that recipient countries have a preference not only for more aid transfers but also for specific types of transfers.
NOTES 1. In general, I define liberalization as any political reform that implies an improvement in the respective Polity IV score. However, several measures of political liberalization are used throughout the empirical analysis. 2. Ex-ante conditionality is also known as aid selectivity (see Koch, this issue). 3. Democratization can be seen as processes of “moving from autocratic regimes with low popular participation in political decision-making and weak constraints on the exercise of executive power, to more democratic regimes with broader political participation and greater limits on the exercise of political power” (Murtin & Wacziarg, 2014). 4. For example, the Bank championed economic reforms in exchange for structural adjustment loans since the 1980s (e.g., Pincus & Winters, 2002). 5. In this respect, consider the vast literature on idiosyncratic donor interests (e.g., Bueno de Mesquita & Smith, 2009).
6. Skeptics may contend that “good governance” and “democracy” actually are synonymous (e.g., Easterly, 2011), but others argue that both concepts are not identical since “governance” is about effectiveness and “democracy” is about legitimacy, and both objectives can be independently strengthened (Bøa˚s, 2001, p. 5). 7. In the list of the three most important personal values, “democracy” is mentioned by 24% of all respondents, following “respect human life” (44%), “peace” (40%), and “human rights” (40%). Other values such as “rule of law”, “equality”, or “solidarity” are less frequently mentioned (EC, 2012e). 8. Asked about global priorities for EU development cooperation, respondents mention “democracy” more frequently (27%) than “climate change” (25%) or “global health” (22%) (EC, 2012e). 9. In 1991, 91% of respondents favored the use of conditions before giving aid to developing countries, among which “respect for human rights” (94%) and “democracy” (72%) were frequently mentioned, slightly
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FOREIGN AID RESPONSES TO POLITICAL LIBERALIZATION less than the condition that aid “help reaches its intended purpose” (97%) and “national ownership” (97%) (EC, 2012a). In 1998, 86% wanted African aid to be linked to progress on democracy (EC, 2012b). In 2004, 84% of respondents agreed that the level of foreign aid should be linked to recipient-country efforts to encourage democracy (EC, 2012c). Note that not all waves include information on conditionality (e.g., EC, 2012d). 10. The use of four years as time window length balances the tradeoff that sustainability can only be judged ex post and the associated drop of available data. Using two standard deviations as cutoff ensures that only significant political reforms are identified. The Polity IV codebook considers a significant transition if the score improves by at least six points (Marshall et al., 2010, p. 35). Indeed, my own set of “sustainable transitions” has significant overlap with the Polity IV transitions. 11. Notably, these twelve donors include Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, and the United Kingdom. 12. Amalgamating aid flows from EU DAC donors and non-EU DAC donors may serve as a robustness check. 13. Data on the dependent variable are not available for the International Bank for Reconstruction and Development.
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14. I implemented this procedure using the loess-function in R. A bandwidth of 0.66 implies that two thirds of the data are used at each focal point for smoothing. 15. Studies using PQMLE have addressed trade flows (e.g., Arvis & Shepherd, 2013) or individual health behaviors (e.g., Neelon & O’Malley, 2013), but surprisingly not yet aid allocation. 16. Estimates are obtained using the xtpqml-package of STATA (Simcoe, 2008). The model requires the weak exogeneity assumption Eðy it jZ i;1 ; . . . ; Z i;t ; ci Þ ¼ ci expðZ it bÞ in order to eliminate the fixed effect (Gourieroux, Monfort, & Trognon, 1984). 17. For small values only can the coefficients be interpreted as percentage changes, otherwise expðbÞ 1 gives the true effect. 18. Dynamic models always include a set of political liberalization dummies (that capture short-term aid responses irrespective of the sustainability of the regime change), an indicator of sustained liberalization (that shows whether aid remains higher in years other than the set of four years when the Polity IV score first increases, and that captures sustained transitions), and an indicator of autocratization (the mirror component of political liberalization, to avoid omitted variable bias). 19. In my case, treatment refers to undergoing a sustained liberalization.
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APPENDIX A. SUPPLEMENTARY DATA Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. worlddev.2014.11.006.
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Please cite this article in press as: Reinsberg, B. Foreign Aid Responses to Political Liberalization, World Development (2014), http:// dx.doi.org/10.1016/j.worlddev.2014.11.006