Chinese Influence in International Organizations

A large literature has established that Western donors funnel aid for political influence in global international organizations like the UN (Kuziemko and Werker Reference Kuziemko and Werker2006; Vreeland and Dreher Reference Vreeland and Dreher2014; Dreher et al. Reference Dreher, Sturm and Vreeland2009), but efforts to replicable this finding to China have produced conflicting results (Lim and Kim Reference Lim and Kim2023; Stone et al. Reference Stone, Wang and Yu2022; Dreher et al. Reference Dreher, Fuchs, Parks, Strange and Tierney2018).Footnote ¹ In this paper, I focus on China’s efforts to buy influence at the regional level by targeting regional organizations. As China expands its global footprint, it has placed a strong emphasis on engaging countries regionally through regional organizations to secure legitimacy from the developing world. Consistent with these diplomatic practices, I argue that Beijing is likely to use money to cultivate political influence in regional organizations. Further, I argue that countries with greater influence in these organizations are more likely to be targeted by China and that one source of this influence comes from assuming the role of Chair.

Regional organizations offer several benefits for Beijing. First, Beijing identifies itself as the leader of developing countries, which are by and large organized around regional organizations. Just as how UNSC decisions can provide domestic and international legitimacy for Western governments (Vreeland and Dreher Reference Vreeland and Dreher2014), support from the developing world gives Beijing the legitimacy it seeks as it attempts to project the image of a responsible great power. China has a lot to gain in its reputation when regional organizations applaud Chinese behaviour or when they do not criticize certain Chinese actions. For instance, when African countries passed a ban on donkey trade during the 2024 African Union Summit, they made sure to de-emphasize how the issue is driven by Chinese demand. Attendants at regional meetings noted how African leaders took great care not to paint the issue as anti-China (Johnston Reference Johnston2024). The absence of public criticism regarding China’s involvement in the donkey trade, despite African representatives raising the issue privately with their Chinese counterparts, keeps this controversial issue out of mainstream news, enabling China to avoid heightened scrutiny.

Beyond the rhetorical support that regional organizations can provide, regional organizations in the developing world also play an important role in shaping regional development priorities, which is especially important during the BRI era. Since many BRI projects are regional in nature and require crossing the territories of multiple states, this increases the importance of regional organizations for China’s foreign policy agenda. For example, the Singapore-Kunming Rail Link (SKRL), which China rebranded into a BRI project, was originally a regional development initiative announced during the fifth ASEAN meeting in 1995. Southeast Asian states co-ordinate through an annual ASEAN working group to monitor progress and align national railway plans with ASEAN’s broader regional connectivity goals. Thus, whether and how ASEAN prioritizes railway development in a given year is critical to the project’s trajectory and progress. To the extent that China aims to shape the SKRL, it would be incentivized to seek influence in ASEAN.

I argue that countries who hold leadership positions in these organizations, such as the Chair, are especially likely to be targeted by China. First, countries who serve as Chair in a given year often speak on behalf of the organization and serve as a representative of the region on the international stage that year. Thus, funnelling money to Chair states can directly influence how that country frames China’s engagement with the continent, responds in the event of a controversy that involves China, and selects which Chinese activities to emphasize or avoid. In addition, the Chair holds important agenda-setting power in these organizations and plays a critical role in shaping policy outputs (Tallberg Reference Tallberg2010). This is especially true in emerging regional organizations, where in an effort to treat members equally, open access to the agenda can easily result in agenda overload, increasing the importance of the Chair in dictating what is discussed (Kufuor Reference Kufuor2007). Chairs can exclude proposals made by non-Chair states and prioritize agenda items that align with their strategic goals. For example, as a landlocked country, Laos often uses its Chairmanship years to prioritize regional connectivity. In 2016, it pushed through the launch of the Lao–Thailand–Malaysia–Singapore (LTMS) Power Integration Project (Lim and Kim Reference Lim and Kim2023). When it became Chair again in 2024, it helped revive stalled negotiations of the China-Thailand railway when it became Chair again in 2024 (Martinus and Lin Reference Martinus and Lin2024). These examples illustrate that the Chair can exercise considerable influence over the policy outputs of the organization in a given year. Thus, by extending more finance to the Chair, Beijing can influence the policy priorities the Chair country sets for the organization that year. In the case of ASEAN, for instance, this can shift the organization’s focus away from territorial disputes in the South China Sea and towards development and trade instead. Though China likely uses economic tools to influence non-Chair states as well, the Chair’s agenda-setting power creates additional incentives for Beijing to strategically use money to influence regional priorities.

There is anecdotal evidence that China actively engages countries economically during the years they serve as Chair. In July 2012, ASEAN failed to issue a joint communiqué for the first time in forty-five years when Cambodia, serving as the Chair, blocked it due to language that Vietnam and the Philippines added to criticize Chinese behaviour in the South China Sea. Two months later, during the Cambodian Prime Minister’s state visit to China, Beijing pledged more than $500 million in new loans/grants as an ‘appreciation for the part played by Cambodia as Chair of ASEAN to maintain good cooperation between China and ASEAN’ (Reuters 2012). Contrary to popular belief, Cambodia has not always had close ties with Beijing. Prime Minister Hun Sen had previously called China the ‘root of everything that is evil’ because of Beijing’s support of the Khmer Rouge regime (Hutt Reference Hutt2016). China spent a good decade courting Cambodia after Hun Sen launched his coup in 1997. It was only after this incident that Cambodia began to serve as China’s client-state in ASEAN, and bilateral relations cemented thereafter.

Relatedly, in January 2018, a French newspaper published allegations that China bugged the AU headquarters it built in Ethiopia, quoting anonymous sources that the organization overhauled its IT system after the hack was discovered a year earlier. When asked about the allegations, the newly assumed Rwandan Chair of the AU said he did not know anything about it, commenting instead that he ‘[doesn’t] think spying is the speciality of the Chinese’ (Maasho Reference Maasho2018). Two days later, Rwanda and China signed a co-operation agreement under which Beijing pledged a $32 million grant (Rwanda 2018). Though this cannot be interpreted as causal, it is consistent with Beijing’s broader efforts to court Rwanda that year, including selecting Rwanda as the first destination for the Chinese Foreign Minister’s annual trip to Africa as well as a personal state visit by Xi. This followed a visit to Beijing by the Rwandan President the previous year. A key motivation for Xi’s visit, similar to Indian Prime Minister Modi’s visit that year, was Rwanda’s goal of pushing the African Continental Free Trade Area through the AU, which aligns with Beijing’s long-standing support for a broad regional free trade agreement in Africa.

Forms of Chinese Development Finance

Beyond which venues Beijing chooses to exert influence over, there is the additional question of which economic instruments Beijing will use to do so. States that engage in economic statecraft can choose between various economic tools to advance their foreign policy priorities, and some instruments may be better suited for coercion than others. Existing studies of Beijing’s strategic use of development finance have studied this question by breaking down Chinese finance by its degree of concessionality, distinguishing China’s official development assistance (ODA) from other official flows (OOF). Scholars argue that aid (that is, ODA) is generally more politically motivated than commercially oriented OOF flows, though recent work has challenged this finding. While Dreher et al. (Reference Dreher, Fuchs, Parks, Strange and Tierney2018) find that Chinese ODA is guided by foreign policy considerations while OOF loans follow economic rationales in Africa, Lim and Kim (Reference Lim and Kim2023) find that both are politically motivated in Southeast Asia, going more to countries during years when they are ASEAN Chair. This suggests that the distinction between ODA and OOF may not be as great in the case of China’s development finance.

In this paper, rather than focusing on the ODA-OOF distinction, I provide a new way of disaggregating Chinese development finance based on which funding and recipient entities are involved in a given financial project. Chinese finance can be funded by Chinese government agencies, policy banks, or commercial banks. These funding entities can also extend finance directly to government agencies in the recipient country or to non-government entities such as state-owned enterprises, joint ventures, or private firms (see Figure 1). I contend that Chinese finance is most likely to reflect influence-buying motivations when the funding and recipient entities are directly tied to the Chinese or recipient state. Specifically, I hypothesize that financing from Chinese government agencies will be the most political since they are closely connected to arms of the Chinese government that are engaged in Chinese foreign policy. Similarly, finance received directly by government agencies in recipient countries is more likely to be used to buy influence than flows to non-government entities, seeing as it is the leadership’s support that Beijing aims to cultivate.

Figure 1. Funding and recipient entities of Chinese development finance.

Disaggregating Chinese finance by the actors involved is important because it is more closely aligned with the ways in which the Chinese state classifies its own development assistance programme. Existing studies that focus on differences between Chinese ODA and OOF overlook the fact that researchers estimate classifications of Chinese commitments as aid or loans based on Western standards since China does not adhere to OECD-DAC standards itself. As such, any of the above-mentioned lending and recipient entities can finance ODA projects in existing datasets, even though Beijing considers only its government ministries as true aid agencies. In other words, the ODA-OOF distinction does not accurately correspond to how Beijing perceives its financial commitments. Focusing on the level of concessionality is therefore likely to mask important insights about how Beijing politicizes its development finance based on the actors involved.

To illustrate this point, a simple explanation reconciling the conflicting findings of Lim and Kim (Reference Lim and Kim2023) and Dreher et al. (Reference Dreher, Fuchs, Parks, Strange and Tierney2018) is that OOF projects feature more prominently in Chinese government agencies’ financing portfolios in Southeast Asia (15 per cent) than in Africa (5 per cent). Because Chinese government agencies finance more on market terms in Southeast Asia than in Africa, this explains why Lim and Kim (Reference Lim and Kim2023) find that both ODA and OOF are strategically used in Southeast Asia, while Dreher et al. (Reference Dreher, Fuchs, Parks, Strange and Tierney2018) find this to be true only for ODA in Africa. As the analysis below shows, their conflicting findings can be reconciled by differentiating Chinese flows based on the actors involved. The following sections consider how the incentives of each set of actors may differ and how this affects the politicization of the given or received financial commitment.

Chinese Funding Entities

Various Chinese entities participate in lending abroad, each with varying degrees of ties to the state and differing lending rationales. The first group of actors consist of government agencies such as the Ministry of Commerce, the Ministry of Foreign Affairs, the People’s Liberation Army, and various subnational governments. Among these, the Ministry of Commerce plays a leading role in administering China’s zero-interest loan and grant programmes for developing countries (Bräutigam Reference Bräutigam2009). Many of these agencies are also directly engaged in China’s diplomatic and trade relations, increasing the likelihood that their financial commitments align with China’s foreign policy objectives. I hypothesize that development finance provided by Chinese government agencies is the most likely used for political purposes, as these agencies are more closely connected to the parts of the Chinese government engaged in foreign policy.

Most of China’s development finance is provided by state-owned policy banks (that is, the China Development Bank (CDB) and the Export-Import Bank of China (China Eximbank)) and state-owned commercial banks, which include the ‘Big Four’ banks in China. These banks are driven more by economic rationales compared to state agencies. However, policy banks are likely to be more strategic in their lending compared to their commercial counterparts. This is because CDB and China Eximbank were established to support China’s ‘Going Out’ strategy, an outward economic strategy designed to address domestic economic challenges like industrial overcapacity and resource dependence (Malik et al. Reference Malik, Parks, Russell, Lin, Walsh, Solomon, Zhang, Elston and Goodman2021). Nonetheless, because these banks are also simultaneously expected to generate financial returns, their loans must also incorporate commercial criteria.

Commercial banks, on the other hand, are more likely to be purely commercially oriented, and their allocation decisions likely reflect traditional sovereign creditor incentives. As China’s government plays a central role in managing the country’s economic growth, it has a vested interest in the return on investments made by its state-owned banks. As Dreher et al. (Reference Dreher, Fuchs, Parks, Strange and Tierney2022) note, many of China’s state-owned banks behave like private sector banks in the USA and Western countries. Although Chinese commercial banks are more willing to lend to countries with poor credit ratings than OECD creditors, they compensate for the higher repayment risk by charging interest rates above market levels (Malik et al. Reference Malik, Parks, Russell, Lin, Walsh, Solomon, Zhang, Elston and Goodman2021).

Table 1 shows the value of Chinese development finance projects by ODA, OOF, and funding entities across the five United Nations regional groups. Importantly, it highlights the value of decomposing Chinese development finance by actor rather than flow class, the latter of which is estimated by researchers. While it is commonly assumed that aid projects are primarily associated with Chinese government actors and OOF projects with commercial actors, Table 1 demonstrates that ODA and OOF cannot be directly equated with government and commercial Chinese lenders (for example, column 1 does not equal column 3). As Beijing’s true aid agencies, Chinese government ministries naturally make up most of the projects classified as ODA, but they only account for 44 per cent of the total ODA value during 2000–2017. Additionally, studies relying solely on ODA-OOF as the main explanatory variable may exclude many projects where concessionality levels cannot be determined, whereas my approach does not. Indeed, columns 3 through 5 of Table 1 add up to more than the total ODA and OOF amounts in columns 1 and 2.

Table 1. Chinese Development Finance by Flow Class and Funding Entity (in Billions of Constant USD 2017)

Source: AidData Global Chinese Development Finance Dataset, V2.0 (Dreher et al., Reference Dreher, Fuchs, Parks, Strange and Tierney2022)

¹ Countries in Western Europe receive very little ODA and OOF from China, given that most are developed countries. With the exception of Turkey and Malta, none are eligible for ODA under OECD criteria. China has given some ODA to Turkey, and only Turkey and Israel have been recipients of Chinese OOF loans during the entire 2000–2017 period.

Focusing on ODA and OOF alone, therefore, makes it difficult to understand the extent to which politicization of development finance is driven by heterogeneity in donor incentives. Although ODA is certainly more attractive than OOF for recipient countries, it is not immediately clear whether all Chinese funding entities use either aid or loans to pursue the same objectives. From an influence-buying perspective, it is easiest for Beijing to rely on its government agencies’ own financial commitments to pursue foreign policy objectives, especially since many of these agencies are also directly involved in China’s diplomatic relations. On the other hand, relying on the allocation decisions of lending from China’s policy banks or commercial banks is more costly since this invites more actors to the table that can delay or obstruct the process. Thus, when China is engaging in influence-buying, we should expect flows that originate from Chinese government agencies to react most to Beijing’s strategic needs.

Recipient Entities

Chinese development finance can be directed to several types of recipient entities. In the pre-BRI era, Chinese finance was primarily extended to recipient governments in the form of aid or sovereign loans. However, by 2013, many countries had accumulated substantial debt, forcing Chinese banks to lend to other official sector institutions such as state-owned enterprises (SOEs), project companies known as special purpose vehicles (SPVs) or joint ventures (JVs), or even to private companies (Malik et al. Reference Malik, Parks, Russell, Lin, Walsh, Solomon, Zhang, Elston and Goodman2021). SPVs, in particular, have become common borrowers of Chinese loans. These entities are established on a temporary basis for a specific project and can only engage in activities or incur debt related to that project. Unlike sovereign loans, loans to SPVs can generally be repaid using revenue generated from the project only and not assets of the borrowing government (Malik et al. Reference Malik, Parks, Russell, Lin, Walsh, Solomon, Zhang, Elston and Goodman2021). Setting up SPVs to receive financing can be advantageous for developing countries, as it allows them to borrow more without negatively impacting their balance sheets. However, from an influence-buying perspective, the isolated financial structure of SPVs makes it difficult for politicians to divert funds for personal use.

I argue that financial commitments more easily captured by elites are more likely to be used by donors to extract policy concessions. Thus, I hypothesize that Beijing is more likely to extend financing to recipient government agencies as a tool for influence compared to flows directed to non-government entities. Loans to state agencies are more prone to political capture, as leaders have greater access to funds allocated to agencies within their control. These funds can then be appropriated as private goods or diverted into patronage networks to secure political support. Financing to other official sector borrowers, such as state-owned enterprises (SOEs), may also be at risk of being diverted, but this depends critically on SOE governance structures in host countries. By contrast, SPVs are more difficult to take from, seeing as they are designed to be project-specific. Financing to SPVs can instead be used to reward countries more generally off-balance sheet. Finally, I hypothesize that flows to wholly private firms, which are accountable to non-government stakeholders, are the least likely to be used for political purposes.

Table 2 shows the value of Chinese development finance by recipient entity and region. Governments are the primary recipients of Chinese finance in Africa and Latin America, with Asia following closely behind. Eastern European governments do not receive much financing from China; instead, state-owned enterprises in the region are the largest recipient type. SPVs and private enterprises receive much more Chinese development finance in Asia than in other regions.

Table 2. Chinese Official Financing by Recipient Entity (in Billions of Constant USD 2017)

Source: AidData Global Chinese Development Finance Dataset, V2.0 (Dreher et al., Reference Dreher, Fuchs, Parks, Strange and Tierney2022)

Comparing Tables 1 and 2 further highlights the importance of decomposing by actor. For example, in Africa, the total value of government-received Chinese finance is $142.40 billion, which is much larger than the value of total ODA commitments to Africa during this time period. In other words, most Chinese finance to Africa is received by host governments regardless of concessionality and funding entity. Comparing financing across lender-recipient pairs is therefore likely to provide important insights about which financial transactions reflect strategic motives.

Empirical Strategy

I test my hypotheses in the context of Southeast Asia and Africa. Both regions are of high strategic importance for China’s security and economic policy. Southeast Asia is not only the primary ground for strategic competition between the USA and China, but Beijing itself faces a number of territorial disputes in the South China Sea with its regional neighbours. Economically, Chinese ties to the region are also significant and increasing, with ASEAN states overtaking the USA as China’s largest trading partner for the first time in 2020. Outside of Asia, Chinese engagements with Africa have been the most notable. Beijing has become a major player in closing the continent’s industrialization gap, and continued African resource exports are critical to China’s search for energy security. Beyond economics, China has maintained close political ties to Africa going as far back as the decolonization period. Their long-standing engagement takes the form of mutual support on the international stage, especially on human rights issues. Beijing is also careful to prioritize African states’ preferences on regional issues in international forums and has at times been willing to shift away from its non-interference principle to support the AU’s position, such as on the issue of Sudan.

In both Southeast Asia and Africa, regional organizations – ASEAN and the African Union – have played important roles in shaping the region’s response to China’s rise. In Southeast Asia, the region’s preference for multilateralism has allowed ASEAN to play a central role in regional relations with the world. For these reasons, Beijing has actively engaged ASEAN through a number of initiatives, including an annual China-ASEAN summit that has taken place since 1997. Similarly, China has maintained close relations with the AU since its establishment in 2002. In 2011, the AU was admitted as a full member of the Forum on China-Africa Cooperation, which is the primary institution for co-ordinating cooperation between China and Africa, especially on the issue of development finance. Since the AU plays an important role in shaping the region’s development priorities every year, China holds regular consultations with the AU to discuss how its development finance can best serve the region’s development goals and how the AU can facilitate the implementation of the BRI on the continent.

I leverage the institutional structure of the Chair position in ASEAN and the AU, which rotates annually among the institutions’ members, to study how regional leadership affects Chinese development finance. Within ASEAN, the Chair rotates annually based on the alphabetical order of members’ English names. The AU Chair, on the other hand, rotates annually among the five geographic regions of the continent – East, North, Southern, Central, and West Africa – and from each region, the Chair is selected either by consensus or two-thirds majority if consensus cannot be reached.Footnote ²

Rotating leadership offers both theoretical and empirical benefits for this study. Theoretically, compared to elected chairs, rotating leadership in international institutions creates incentives for logrolling within the organization (Tallberg Reference Tallberg2010; Lim and Kim Reference Lim and Kim2023). The Chair’s annual rotation allows states to take turns in exploiting the Chair’s agenda-setting power for their own interests. This also results in member states trading favours with one another, as each is expected to assume this position in the future.Footnote ³ In addition, the fact that member states cannot be punished electorally for assuming the Chair opens the door for external players like China to exert influence. Methodologically, since the position rotates in a way that is uncorrelated with Chinese financing, it addresses the identification concern that Chairmanship is endogenously determined by China’s strategic interests.

The main dependent variable in this analysis is Chinese development finance commitments. The data comes from AidData’s Global Chinese Development Finance Dataset Version 2.0, which covers 13,427 development projects across 165 countries from 2000–2017 (Dreher et al. Reference Dreher, Fuchs, Parks, Strange and Tierney2022).Footnote ⁴ Of these, 10,849 projects worth $843 billion are active or completed.Footnote ⁵ This data critically includes details about the funding and recipient entities for each project. Of the 5,753 projects directed to AU and ASEAN countries, all include information about the funding entity and 4,410 (77 per cent) contain details on the recipient entity. Roughly 600 projects directed to countries that have served as Chair at least once are missing recipient entity information. Nearly all projects missing recipient entity information are financed by Chinese government agencies.Footnote ⁶

Following convention, I focus on project commitments instead of disbursements. One potential downside of doing so is that this ignores delays in fund disbursements, as projects may be announced but not disbursed until later years. One might argue that if China knows preemptively who will become Chair, like in the case of ASEAN, then it could theoretically commit the year before a country becomes Chair and disburse funds the following year. However, disbursements during the year a country is Chair can be problematic as China loses its leverage over the recipient country once the loan has sunk. Thus, it is more optimal for China to commit projects to a country when they are Chair and wait to disburse until after the country follows through on certain promises. In the case of the African Union, since the country that will assume Chair is not always known beforehand, commitments the year of is the only option. In addition, while project commitment value is collected by AidData, annual disbursement value is not. I would therefore have to impute these values based on the average delay between commitment and completion years among a small fraction of projects where completion date is known. This would require making assumptions about how funds are disbursed over this period (for example, linearly), creating additional noise that would lead to less precisely estimated coefficients.

I estimate the following model:

(1) $$log({\rm{commitments}}_{it} + 1) = \alpha + \tau \rm{Chair}_{it} + {\boldsymbol X}'{\beta _{i,t - 1}} + {\gamma _t} + {\delta _i} + {\varepsilon _{it}}$$

where $commitments$ is the value of committed projects in constant 2017 USD, indexed by $i$ , the recipient country, and $t$ , the year. The main independent variable of interest is $Chair$ , a binary variable that takes 1 if country $i$ is Chair of ASEAN or the AU in year $t$ .Footnote ⁷ The model includes year fixed effects ( ${\gamma _t}$ ) to account for common shocks that drive Chinese aid and investment decisions as well as country fixed effects ( ${\delta _i}$ ) to absorb time-constant country characteristics. For robustness, Table A7 in the Appendix reports results using pooled OLS (without country fixed effects) to exploit variation across recipient countries.

X is a set of time-varying economic and political control variables that may affect Chinese financial commitments. To control for recipient countries’ need for development finance, I include countries’ level of development (logged GDP per capita), market size (logged population), natural resources rent (per cent of GDP), GDP growth rate, and logged national income.Footnote ⁸ I also control for the logged value of bilateral trade to capture Chinese economic interests in a country.Footnote ⁹ All prices are converted to constant 2017 USD. Further, to account for potential lending risks, covariates related to countries’ governance and institutional quality are added. These include: Control of Corruption scores from the World Bank’s Worldwide Governance Indicators project, which captures the extent to which public goods can be funneled for private gains, that is, the risk of elite capture of foreign aid; and level of democracy using the polity2 variable from Polity V.

In addition, several covariates are included to account for political motivations beyond regional organization leadership. I control for geopolitical alignment with Beijing by including host countries’ UNGA ideal point distance from China.Footnote ¹⁰ Since UNGA resolutions likely consist of many low-salience issues, I check that results are robust to subsets of votes that may be important to China, including those related to human rights issues, that the US Department of State labels as important, and where China and the USA disagree. Voting more closely with Beijing on these votes is likely to signal greater alignment to China over the USA. I also add a binary indicator variable for temporary membership on the UN Security Council, and another to indicate recognition of the Taiwanese government, which typically makes countries ineligible for Chinese aid (Bräutigam, Reference Bräutigam2011; Kersting and Kilby Reference Kersting and Kilby2014). Lastly, to capture potential competition among donors, the residuals of an ordinary least squares regression (OLS) of logged ODA from DAC donors (in constant 2017 USD) on all explanatory variables are included, following the approach in Dreher et al. (Reference Dreher, Fuchs, Parks, Strange and Tierney2018). All covariates are lagged following previous studies. Descriptive statistics for right hand side variables are in Table A1.

The main coefficient of interest, $\tau $ , is identified by the exogenous rotation of the Chair position in ASEAN and the AU. In the generalized difference-in-differences (TWFE) setup described above, identification relies on the assumption that financing to Chair and non-Chair states follow parallel trends prior to Chair years. Since rotating Chairmanship involves both staggered adoption and treatment reversal, I examine the parallel trends assumption for the main outcome variables of interest using an event study approach, where I interact the regional organization Chair dummy with indicators for years relative to when a country serves as Chair. Given that some countries hold the Chair position more than once during the sample period, I generate the relative period index by assuming a one-year carryover period. In other words, all intermediate periods between Chair years are treated as pre-periods, except for the year immediately following a Chair year, which is treated as a post-period. This assumption reflects concerns that Beijing could theoretically provide increased financing as a reward for pro-China behavior when the country served as Chair, rather than commit more finance during the Chair year itself. This concern is likely most relevant in the $t + 1$ period. The $t - 1$ period is treated as the baseline year in these models. Figure A2 in the Appendix plots dynamic treatment effects for four periods leading up to the treatment year. These four pre-periods correspond to one full round of AU Chair rotation (since the Chair rotates among the continent’s five regions) and half of ASEAN’s rotation cycle (since there are 10 ASEAN members). None of the coefficients in these pre-periods are statistically significant, either individually or jointly, providing greater confidence that identifying assumptions hold.