monopoly rents and foreign direct investment in fixed assets

International Studies Quarterly (2018) 62, 341–356

Monopoly Rents and Foreign Direct Investment in Fixed Assets

JO S E P H W R I G H T A N D BO L I A N G ZH U

Pennsylvania State University

In the past two decades, much of foreign direct investment (FDI) in the primary sector has flowed to unconventional, politi-cally risky destinations. This presents a puzzle for theories that emphasize the ex post immobility of—and hence high potentialexpropriation risk for—fixed asset investment. Existing theories overlook one critical aspect of fixed assets: large capital re-quirements and high sunk costs act as entry barriers, resulting in market concentration and strong firm incentive for monopolyrent extraction. Personalist dictatorships, we posit, provide an attractive institutional environment for fixed asset investors. Insuch systems, the control of key economic sectors by the families of leaders, combined with a lack of institutional constraints,facilitate rent-seeking activities. We find that personalist dictatorships receive significantly more foreign investment in theprimary sector, and fixed-asset intensive industries in general, than other regimes. This study highlights the importance ofaccounting for heterogeneity among investors and political regimes to understand the politics of FDI.

The past two decades have seen a resurgence of foreigndirect investment (FDI) in the primary sector, mainly in theextractive industries; developing and transition economieshave become increasingly important investment destina-tions (UNCTAD 2007).1 Much of this investment flows tounconventional, politically risk destinations. For instance,the boom of foreign investment into Africa in the firstdecade of the new century mostly involves investments inthe extractive sector; top recipients include Sudan, Guinea,Chad, Tanzania, Ethiopia, Zambia, Uganda, Burundi,Madagascar, and Mali (UNCTAD 2007, 36).2 By contrast,investment in manufacturing industries in this region hasgrown slowly. In some sub-Saharan countries it has evendeclined (UNCTAD 2006). The large expansion of primarysector investment in the developing world represents arevival of global interest. It reverses the divestment trendduring the 1960s and 1970s that followed widespread na-tionalization and expropriation of foreign investment afterdecolonization and independence in many developingcountries (Kobrin 1984).

Joseph Wright is an associate professor of political science at the Pennsylva-nia State University. His research focuses on the comparative political economy ofdictatorships. His articles have appeared in the American Journal of Political Science,the Annual Review of Political Science, the British Journal of Political Science, Compar-ative Political Studies, International Organization, International Studies Quarterly, theJournal of Politics, Perspectives on Politics, Research & Politics, and World Politics.

Boliang Zhu is an assistant professor of political science and Asian studies atthe Pennsylvania State University. His research focuses on the politics of global-ization and development. His articles have appeared in the American Journal ofPolitical Science, Comparative Politics, and International Studies Quarterly.

Authors’ note: Earlier versions of the article were presented at the 2016 an-nual meetings of the American Political Science Association and InternationalPolitical Economy Society; the Politics of Multinational Firms, Governments, andGlobal Production Networks Conference at Princeton University; and a facultypaper workshop at the Pennsylvania State University. We are grateful to Lee AnnBanaszak, Liz Carlson, Sona Golder, Eddy Malesky, Bumba Mukherjee, EricaOwen, Pablo Pinto, Eric Plutzer, Stephen Weymouth, Vineeta Yadav, various con-ference and seminar participants, three anonymous reviewers, and the editorsof International Studies Quarterly for helpful comments and suggestions. We thankMinhyung Joo, Qing Deng, Boyoon Lee, and John Schoeneman for excellent re-search assistance. All errors remain our own.

1 The growth of global investment in extractive industries is closely related tothe changes of commodity prices, especially the commodity price hikes starting inthe early 2000s. Foreign investment in extractive industries dropped sharply afterthe 2008 Great Recession and started to recover recently. See UNCTAD (2015).

2 The ranking is based on FDI inflows in 2006.

Yet, the surge of primary sector FDI in the developingworld in general, and low-income authoritarian countriesin particular, seems puzzling. Observers generally see thesecountries as posing great political risk. Investments in theprimary sector typically involve a large amount of fixed as-sets and consequent high sunk costs. Once these invest-ments take place, they become an “obsolescing bargain” dueto their ex post immobility and, therefore, stuck under therisk of government expropriation (Vernon 1971, 1980). For-eign investors in fixed assets should, in turn, favor countrieswith high institutional constraints and strong property rightsprotection (for example, Henisz 2000; Jensen 2003, 2006; Liand Resnick 2003).

Given this, what drives fixed asset investors into politicallyrisky countries? Multinational corporations (MNCs) arerational actors. They weigh potential benefits against risks.While asset im(mobility) and expropriation risk remainimportant factors when MNCs make investment deci-sions, the recent political economy of FDI literatureoverlooks investors’ incentives for monopoly rent extrac-tion. These incentives are shaped by firm-specific assets,industry characteristics, and host countries’ institutionalenvironments.

We emphasize the role of fixed assets as entry barriersin shaping market dynamics and MNCs’ preferences forinstitutional environments. Large initial capital require-ments and consequent high sunk costs associated with fixedasset investments deter potential rivals. They thus limitmarket competition; market concentration in turn givesrise to opportunities for MNCs to extract monopoly oroligopoly rents. MNCs’ seeking of monopoly rents, however,depends on the host government’s policies and regulationsthat can either reinforce or weaken rent-seeking activi-ties. Compared with democracies, authoritarian countriesshould provide a favorable institutional environment; theyare more likely to tolerate MNCs’ monopoly or oligopolybecause they lack competitive elections and are less likelyto hold individual leaders accountable (Li and Resnick2003, 182–83). Yet, not all authoritarian regimes are alike(Geddes 2003). Rulers in personalist dictatorships typicallylack formal institutions that check their individual powerand these leaders’ families and close political allies oftencontrol key economic sectors. Thus, we posit that personal-ist dictatorships facilitate monopoly rent extraction and aretherefore attractive to fixed asset investors.

Wright, Joseph, and Boliang Zhu. (2018) Monopoly Rents and Foreign Direct Investment in Fixed Assets. International Studies Quarterly, doi: 10.1093/isq/sqy010© The Author(s) (2018). Published by Oxford University Press on behalf of the International Studies Association.All rights reserved. For permissions, please e-mail: [email protected]

Downloaded from https://academic.oup.com/isq/article-abstract/62/2/341/5049186by Pennsylvania State University useron 10 July 2018

mailto:[email protected]

342 Monopoly Rents and Foreign Direct Investment in Fixed Assets

Figure 1. Expropriations by regime and sector

To test this argument, following the “obsolescing bar-gain” literature (Vernon 1971, 1980), we proxy fixed assetintensity by sector of investment: primary sector as highfixed-asset intensive and secondary sector as low fixed-asset intensive. Utilizing sectoral FDI inflow data from theUnited Nations Conference on Trade and Development(UNCTAD) for developing countries over the period of1980–2010,3 we find that personalist dictatorships attractmore primary sector FDI as a share of gross domesticproduct (GDP) than other political regimes. We also showthat the correlation between personalist dictatorships andfixed asset investment goes beyond the primary sector andholds for fixed-asset intensive investment in general. Inother words, personalism correlates positively with FDI infixed-asset intensive industries, but this relationship turnsnegative in non-fixed-asset intensive industries. Further-more, we examine the underlying mechanisms and provideevidence that personalist dictatorships have less trans-parency and accountability, more corruption prosecutions,and higher market concentration in the primary sector.These findings show that personalist dictators tolerate mar-ket concentration and facilitate monopoly rent extraction.Taken together, our results suggest that foreign investorsin fixed assets, who seek to extract monopoly or oligopolyrents, favor institutional environments that restrict marketcompetition and lack transparency and accountability.

Our findings may seem counterintuitive at first glance.Due to the ex post immobility of fixed asset investment andits high sunk costs, MNCs should be primarily concernedabout host governments’ opportunistic behavior in person-alist regimes. Yet, nationalization and direct expropriationfollowing decolonization and independence of developingcountries largely ended by the late 1970s (Kobrin 1984;Wilson and Wright 2017), as shown in Figure 1.4 In thepast three decades, developing countries hold much morepositive attitudes toward, and display growing confidencein, dealing with MNCs. They increasingly embrace liberal-

3 In Appendix M, we provide additional results based on data of US majority-owned foreign affiliates.

4 Data on expropriations are from Kobrin (1984) and Hajzler (2012). Therewere twenty-five expropriations in the primary sector in the twenty-five years after1980; ten are agricultural assets, nine are petroleum, and six are mining.

ization, deregulation, and privatization (UNCTAD 2007).Their policies are heavily influenced by the prevailing neo-classical economic ideas and Washington Consensus advo-cated by the World Bank and International Monetary Fund.

Furthermore, MNCs are capable of protecting their as-sets, even in extractive industries, by leveraging a varietyof strategies such as forming joint ventures, establishingvertical linkages, diversifying assets across sectors, buildingtransnational alliances, exploiting issue linkages in negoti-ations, and lobbying their home governments (see Moran1973; Jenkins 1986; Eden, Lenway, and Schuler 2005; Post2014; Markus 2015; Johns and Wellhausen 2016; Post andMurillo 2016). These strategies help MNCs to lower de factopolitical risk in personalist regimes. For instance, BP is ableto protect itself from the Azerbaijani government’s expro-priation by cultivating an extensive relationship with lo-cal suppliers; this creates a “common roof” for protection(Johns and Wellhausen 2016, 46–47). In the past decadesthe risk of outright asset expropriation has been lowerthan during the immediate post-WWII decades. The in-centive for MNCs to seek institutional environments wheremonopoly rent extraction is greatest should therefore in-crease. Even if governments engage in “creeping expropria-tion” (Graham, Johnston, and Kingsley 2017), the incentiveto exploit monopoly rents may trump the risks associatedwith adverse government behavior that falls short of outrightasset seizure.5

It remains to be seen whether conditions alter in the fu-ture due to the recent rise of populism and nationalismthroughout the world and unfavorable legislation in somecountries. Yet, we believe large-scale nationalization and as-set expropriation are unlikely to occur, given the fundamen-tal changes of developing countries’ FDI policies and the dif-fusion of international investment and trade agreements inthe past decades. These practices significantly constrain gov-ernment’s policy discretion and provide credible investor

5 In Appendix K of the supplementary information, we show that personalistregimes have higher political risk scores, on average, even once we account forprior expropriation. This finding indicates that despite threats from creeping ex-propriation, the returns from exploiting monopoly power outweigh the costs ofadverse government behavior.


JO S E P H W R I G H T A N D BO L I A N G ZH U 343

protection (see Elkins, Guzman, and Simmons 2006; Bütheand Milner 2008; Kerner 2009; Allee and Peinhardt 2011).6

Our study extends the literature on political institu-tions and FDI in two crucial ways. First, we highlight theimportance of the heterogeneity of foreign investors inunderstanding MNCs’ preferences for institutional envi-ronments. Our research reflects scholars’ recent effortsto disaggregate FDI. For instance, Blanton and Blanton(2009) show that foreign investors with high skill levelsand intention for societal integration in the host favorcountries that respect human rights. This is because hu-man rights protection encourages citizens’ investment inhuman capital and facilitates firms’ cultivation of “sociallicense” (Blanton and Blanton 2009, 474). Kerner (2014)and Kerner and Lawrence (2012) suggest that institutionalconstraints are particularly attractive to the type of invest-ment that is vulnerable to political risk. MNCs differ widelyin their capital intensity, asset mobility, skill profiles, andso forth, which should drive their choice of investmentlocations—including the institutional environment—thatallow them to best capitalize on their firm-specific assets.

Second, the existing literature focuses primarily on thebroad distinction between democracy and autocracy in at-tracting foreign investment. This dichotomous conceptual-ization hides critical differences within each regime type.Dictatorships differ as much from each other as they dofrom democracies (Geddes 2003), and a large literature es-tablishes that the political institutions autocratic leaders em-ploy to build support coalitions and share power influencepolitical and economic outcomes in these regimes (for ex-ample, Gandhi and Przeworski 2006; Wright 2008; Gehlbachand Keefer 2012; Svolik 2012). One central message fromthis article is that different political regimes offer distinctinstitutional settings that are attractive to different types offoreign investors.

Our findings matter for governance both in autocraticcontexts and for the global economy. Foreign investors inthe primary sector are not necessarily deterred by high po-litical risk in personalist regimes (see Wilson and Wright2017). Instead, they invest in these regimes to extractmonopoly rents. This type of foreign investment likely stiflesmarket competition and results in more corruption that un-dermines governance (see Malesky, Gueorguiev, and Jensen2015; Pinto and Zhu 2016; Zhu 2017). Further, the rents ac-cruing to the leader help sustain a personalist rule that re-presses political freedom and civil liberties. These foreigninvestments in personalist regimes can thus lead to the de-terioration of citizens’ civil and political rights (for compar-ison, see Blanton and Blanton 2007; Mosley and Uno 2007).In these settings, strengthening regulations to improve gov-ernance from inside is likely to be difficult. Outside effortsto push for transparency and accountability of both MNCsand host governments, such as extraterritorial interventions(Kaczmarek and Newman 2011), are more likely to proveeffective.

Fixed Assets, Monopoly Rents, and Foreign Investment

One foci in the political economy of FDI literature iswhether democratic institutions attract more foreign in-vestment. Early work suggests that authoritarian leaders,in an effort to promote industrialization, safeguard MNCs’monopoly rents by suppressing wages, labor unions, and

6 Koivumaeki (2015) studies recent nationalizations in the oil sector in Boliviaand Venezuela and shows that BITs have little binding effect on leaders’ behaviorwhen the underlying economic conditions favor expropriation.

the populist demand for consumption (see, for example,O’Donnell 1978, 1988 on Latin America). While Oneal(1994) finds no evidence that authoritarian regimes attractmore US foreign investment, this study shows that returnsare higher in dictatorships.

More recently, scholars adopt a Neoinstitutionalist ap-proach to study the role of host countries’ political institu-tions in affecting FDI inflows. This literature starts with thepremise that footloose capital becomes relatively immobileex post, and thus a hostage to host governments (Vernon1971, 1980). To attract foreign investment, host govern-ments have ex ante incentives to minimize arbitrary inter-ventions and commit to liberal economic policies. Nonethe-less, a challenge remains insofar as it is difficult for hostgovernments to credibly commit to forgo opportunistic be-havior ex post, given foreign investment’s relative immobil-ity. Scholars thus posit that democratic institutions—suchas checks and balances, veto players, and audience costs—prevent the state’s predatory behavior by ensuring policy sta-bility and providing property rights protection, thereby at-tracting FDI (for example, Henisz 2000; Jensen 2003, 2006;Li and Resnick 2003). However, empirical studies providemixed evidence with regard to the relationship betweendemocracy and aggregate FDI inflows (see, for example,Resnick 2001; Jensen 2003, 2006; Li and Resnick 2003;Jakobsen and De Soysa 2006; Busse and Hefeker 2007; Yang2007; Li 2009; Asiedu and Lien 2011). Recent work suggeststhat aggregate FDI inflows may not be an appropriate mea-sure to capture the risk-mitigating role of democratic insti-tutions (Kerner 2014). Other firm-level studies suggest thatpolicy environments and specific institutional features suchas rule of law and property rights protection may be moreimportant than democracy itself (for example, Biglaiser andStaats 2010).

The existing literature focuses on one aspect of fixedassets—ex post immobility—and investors’ vulnerabilityto host governments’ opportunistic behavior. While asset(im)mobility, we believe, still remains important in analyz-ing MNCs’ investment strategies, the incidence of directexpropriation has been low since the end of the oil priceshocks in the 1970s and the start of the Washington Con-sensus in the 1980s.7 Nowadays, host governments are morelikely to engage in indirect or creeping expropriation suchas subtle changes in taxation and regulation or contractrenegotiation (see Graham et al. 2017; Post and Murillo2016). Compared to direct asset takeover, creeping expro-priation is arguably less damaging to fixed asset investors be-cause firms’ control rights of physical assets remain uncon-tested. We argue that emphasizing the ex post immobilityoverlooks another critical aspect of fixed asset investment:high initial capital requirements and the substantial sunkcosts that act as entry barriers to shape market dynamics andopportunities for monopoly rent extraction.

Fixed asset investments require the transformation oflarge amounts of capital into property, plant, machinery,and equipment. High capital requirements are beyond thereach of many firms and create entry barriers for potentialcompetitors (Bain 1956; Duetsch 1984; Geroski 1995). Firmexecutives consider high capital requirements as one of themost important entry barriers (Karakaya and Stahl 1989;Karakaya 2002). Furthermore, fixed asset investments incurhigh sunk costs that are not recoverable. Fixed assets thatbecome sunk costs ex post entail substantial economies of

7 See Figure 1 as well as Guriev, Kolotilin, and Sonin (2011) and Wilson andWright (2017).



scale (Bain 1956).8 New entrants must enter on a sufficientlylarge scale to avoid diseconomies (Scherer 1973; Harrigan1981). This increases the risk of entry because expectedprofits need to be higher than the sunk costs of entry forthe firm to be profitable, and these unrecoverable costs willbe lost if the entry fails (Baumol and Willig 1981, 418).

Therefore, large capital requirements and substantialeconomies of scale in sunk costs associated with fixed as-set investments constitute barriers for potential entrants, re-sulting in market concentration (Bain 1956; Baumol andWillig 1981; Harrigan 1981; Shafer 1994). For instance, inthe resource sector characterized by high fixed assets, thetop three companies control 74 percent of world iron oreproduction for export, and the largest ten companies ac-count for about 41 percent of global oil and gas produc-tion (UNCTAD 2007). Empirical studies show that capi-tal requirements are a significant determinant of firm size(Kumar, Rajan, and Zingales 1999) and market concentra-tion (Mitton 2008). When a few players dominate the mar-ket, it gives rise to opportunities for firms to extractingmonopoly or oligopoly rents, irrespective of their motiva-tion for investment (for example, market-seeking or export-oriented).

While high entry barriers in fixed-asset intensive indus-tries enhance MNCs’ incentive to pursue monopoly oroligopoly rents, actual rent extraction depends on host gov-ernments that regulate market entry and competition. Dueto natural entry barriers in fixed-asset intensive industries,market tends to be concentrated. Host governments can ei-ther strengthen or weaken market concentration and rent-seeking activities in these industries by enforcing regulationsto limit entrants or by strengthening antitrust policy. Mitton(2008) shows that strong institutions, such as rule of law andantitrust policy, have a particularly strong effect on reducingconcentration in industries with natural entry barriers.

Monopoly or oligopoly is not compatible with—and of-ten contradictory to—host governments’ policy objectivesfor redistribution, industrial protection, and antitrust reg-ulation. In democracies, governments tend to limit MNCs’exploitation of monopolistic or oligopolistic rents. Electoralcompetition, as well as a free press and the relatively lowcost of political mobilization, empower the public and in-cumbents (Dahl 1971). In consequence, democratic govern-ments have strong incentives to constrain MNCs’ monop-olistic or oligopolistic market positions that harm leaders’constituencies by hurting indigenous firms and reducingconsumers’ welfare if monopolists or oligopolists charge ahigher price (Li and Resnick 2003, 182–83).

In contrast, uncompetitive elections and limited politi-cal participation in autocracies mean that the political costof MNCs’ monopoly rent extraction is lower. However, notall authoritarian regimes are alike (Geddes 2003). We dis-tinguish personalist dictatorships from other autocracies toargue that personalist dictatorships are particularly attrac-tive to investors in fixed assets. Political rule in personalistregimes is less likely to be based on power-sharing agree-ments made credible through formal institutions and morelikely to depend on personal loyalties bought with imme-diate rewards and material benefits, often distributed viaan elite patronage network run through the leader’s family(Snyder 1992; Bratton and van de Walle 1994; Chehabi andLinz 1998). The ability of autocratic institutions to constrainthe leader hinges crucially on the distribution of power be-tween the leader and the support coalition (Svolik 2012,

8 Sunk costs cannot be recovered and remain even if a plant stops production.They are distinct from fixed costs because the latter do not vary with output andgo to zero as output drops.

101). Because power is consolidated in the hands of thedictator, power-sharing through formal institutions in per-sonalist regimes lacks credibility. Political institutions suchas legislatures do not constrain the leader; rather, they arevenues to distribute patronage and identify potential oppo-nents (Wilson and Wright 2017, 4).

Political loyalty in these contexts therefore depends onthe rewards accrued from clientelistic practices and not onformal institutions that enable the dictator to make crediblepromises about future behavior or that allow broad access todecision-making (Wright 2008). Leaders in personalist dic-tatorships maintain their power by extracting rents from theeconomy to pay supporters. These leaders thus have strongincentives to limit market competition to create businessnetworks conducive to rent extraction.

Personalist dictators’ interest in extracting rents to sus-tain their rule aligns with fixed asset investors’ incentive toexploit oligopolistic or monopolistic positions.9 Dictators inthese regimes have personal control of policy decisions andaccess to office (Geddes 2003). The lack of institutional con-straints and the prevalence of family control of economicsectors in these regimes, on the one hand, imply high poten-tial political risk for investors; on the other hand, they makeit easier for MNCs to bribe or collude with host governmentsto guarantee privileged access and strike exclusive deals.10

Despite weak rule of law and high corruption (Chang andGolden 2010), personalist regimes provide an attractive en-vironment that facilitates monopoly or oligopoly rent ex-traction. For example, O’Neill (2014, 183) notes that Chi-nese fixed asset investment in Cambodia occurs only withthe direct approval of an unchecked leader: “Hun Sen hasthe final say on all such [investment] projects regardless ofwhether they have been approved or rejected by govern-ment ministries.”11

In such cases, MNCs’ incentives for monopoly rent extrac-tion outweigh concerns of political risk, including the riskof contract renegotiation. This is especially the case dur-ing an era in which neoliberal economic ideas prevail andthe incidence of direct expropriation is relatively low (Edenet al. 2005; Wilson and Wright 2017, 9). Indeed, O’Neill(2014, 184) concludes that Chinese firms—particularlystate-owned enterprises with fixed assets—invest in Cambo-dia despite the political risks: “[t]he political risk, weak ruleof law, and high corruption resulting from Cambodia’s po-litical institutions create a poor investment environment.”12

The case of a manganese mine in Burkina Faso illus-trates both why MNC investors enter markets in personalistregimes and how they succeed in securing rents despite thepolitical risks endemic to such regimes. Under Compaoré’spersonalist rule, one MNC investor ousted another to takecontrol over the Tambao mine in 2012. Despite the fact

9 Dictators could rely on national firms to extract rents. Many developingcountries, however, still lack the financial resources, technology, and risk manage-ment skills to succeed in capital-intensive investments without resorting to MNCs(Shafer 1994; UNCTAD 2007, 92).

10 The regime’s durability could be a concern when MNCs make investmentdecisions. Compared with other dictatorships, personalist regimes are not partic-ularly short-lived. During the sample period, the average duration of personalistregimes is fourteen years, longer than average duration for democracy (thirteen)or military regimes (ten), but shorter than that for monarchies (seventy-one) anddominant party regimes (thirty-six).

11 Hun Sen’s personalist rule is based on “family ties, constructed througharranged marriages” that form “Cambodia’s somewhat opaque ruling coalition”(O’Neill 2014, 183).

12 Private Chinese firms in the secondary sector also invest in Cambodia. How-ever, O’Neill (2014, 191–92) argues that “investment in Cambodia’s garment sec-tor is unique within China’s global FDI portfolio,” in part, because in markets out-side Cambodia “Chinese companies do not enjoy the type of cultural and linguis-tic ties with large local Chinese communities that facilitate Chinese investment inCambodia’s garment sector.”



that the Burkinabé government had reached an agreementwith a Dubai-based mining consortium in 2007, the head ofthe privately owned Pan African Minerals, Frank Timis, lob-bied the regime leader’s wife and allegedly paid his brothermore than $8 million in bribes to secure access to the mine(Madsen 2015; Prince 2015; Werthmann 2016). The “openinternational tender” was cancelled, and Timis was grantedthe rights (Madsen 2015). The government paid an addi-tional $15 million to compensate the ousted MNC after thelatter sued the government in international court.

When Compaoré’s regime fell after the 2014 uprisings,the newly elected government struck down the agreementwith Timis, forcing his mining operations to a halt. Timisinitially sought $385 million in arbitration but is now askingfor more than $1 billion in court (Farge 2016; West AfricaNewsletter 2017). The difference in the size of the damages(between $385 million and $1.2 billion) sought by Timis andthe damages ($15 million) and bribes ($8 million) paid tosecure the contract provide some evidence of the expectedrent extraction on the part of the MNC investor. Further, acommission established to assess resource contracts handedout during the Compaoré regime “concluded that the Burk-inabé state suffered from a loss . . . of almost a billion USdollars through fraud, lack of taxation, and nonpayment offees” (Werthmann 2016). This again suggests that the sizeof the extracted rents accruing to MNC’s in this case vastlyoutweighed the costs associated with bribes and adverse gov-ernment behavior.

In nonpersonalist dictatorships, a single leader does notcontrol decisions about policy and personnel; instead, thedominant party in party regimes, juntas in military regimes,and a royal family in monarchies play a critical role (Geddes2003; Geddes, Wright, and Frantz 2014). Military and partyregimes rely more on a productive economy to sustain au-thoritarian rule and on formal institutions for power shar-ing (Wright 2008). These political institutions facilitate thecollective action of regime supporters including domesticinvestors (Gehlbach and Keefer 2012). The diversity of eliteinterests and regime supporters’ capacity to act collectivelyin nonpersonalist regimes limit leaders’ discretion in offer-ing privileges to or striking exclusive deals with MNCs thatseek monopoly rents.

The pattern of antitrust regulations across differentregimes helps to illustrate our point. According to the WorldEconomic Forum’s Global Competitiveness Report, in de-veloping countries from 2007 to 2010, the average antitrusteffectiveness score for personalist regimes is 3.37 in a rangefrom 1 (least effective) to 7 (most effective). It is the lowestcompared to other regimes (3.54 for military regimes, 3.83for party regimes, 4.17 for monarchies, and 4.22 for democ-racies).13 The effectiveness of antitrust policy across regimesis consistent with our argument that personal dictatorships,because of the lack of institutional constraints and leaders’families’ control of key economic sectors, tolerate marketconcentration and facilitate rent extraction. Therefore, wehypothesize the following:

H1: All else being equal, compared to other regimes, personalist dic-tatorships are more attractive to foreign investors with high fixedassets.

Conversely, this argument suggests that non-fixed-asset in-tensive investors should not necessarily favor personalist dic-

13 The index is constructed based on executives’ responses to the followingquestion in the World Economic Forum’s Executive Opinion Survey: “in yourcountry, how effective are antimonopoly policies at ensuring fair competition?”

tatorships. Non-fixed-asset intensive investments involve lowsunk costs, and thus lower entry barriers. Given low entrybarriers, there are more incumbent firms and potential en-trants, contributing to greater market competition. In thissense, opportunities for firms to exploit oligopolistic or mo-nopolistic market positions are low. Investors with low fixedassets still retain substantial bargaining power ex post byleveraging exit options. Therefore, these investors shouldfavor an institutional environment that protects propertyrights and constrains government’s opportunistic behavior.Thus we expect that personalist dictatorships should not at-tract more non-fixed-asset intensive FDI than other politicalregimes.

Empirical Analysis

To test the hypothesis, we follow the “obsolescing bargain”literature (Vernon 1971, 1980) and proxy FDI’s fixedasset intensity by sector of investment—primary versussecondary.14 The central argument of the “obsolescingbargain” model is that high fixed asset investments in theextractive industry become sunk costs ex post and thus ahostage to the host government. On the contrary, MNCs inthe manufacturing sector characterized by relatively highmobility, changing technology, and global integration pos-sess substantial bargaining power and are less likely to turninto an obsolescent bargain (Kobrin 1987). On average,investments in the primary sector should require highercapital expenditures than those in the secondary sector.For instance, in 2013 the net value of property, plant, andequipment accounts for about 46 percent of total assets ofmajority-owned foreign affiliates of US MNCs in the miningsector, compared to 17 percent in the manufacturing sec-tor.15 Thus, sectoral investment should be a good proxy forfixed asset intensity.

We utilize sectoral FDI inflow data from UNCTAD. Thedata span the years from 1980 to 2010. There are two draw-backs to using this data. First, the data coverage is poor. Asoverall FDI to developing countries increased from the early1980s through the 2000s, countries became more likely toreport sectoral FDI data. This means many low FDI obser-vations have missing data, particularly in the 1980s. We ad-dress this issue by using multiply imputed data for missingvalues for the sixty-one countries that have a least one obser-vation of sectoral FDI in the time series.16 Imputing missingdata in country-series with at least one observation of sec-toral FDI data should allay concerns about bias arising fromdropping observations from the estimating sample early incountry time series, particularly when FDI inflows are low.

The geographic coverage of the data series is also poor. Asubstantial number of countries in a sample with availabledata on total FDI (109 countries) have missing data for theentire time series for sectoral data (forty-eight countries).If the dropped countries are those with high primary FDIbut low personalism or with low primary FDI but high per-sonalism, excluding them would bias our estimates upward.

14 The primary sector includes both the agricultural and extractive industries.Fixed asset intensity varies within the agricultural industries. Large industrial plan-tation production such as tea and rubber is characterized by capital intensity andoligopoly; by contrast, small cash crop production such as coffee has low entrybarriers and high market competition (Shafer 1994). Our results are consistentand robust if we exclude agricultural FDI from primary FDI. We later produceresults at a more disaggregated industry level, which show that personalism cor-relates positively with FDI in fixed-asset intensive industries in general, but therelationship turns negative in non-fixed-asset intensive industries. See Figure 8.

15 Calculation is based on data from the US Bureau of Economic Analysis.16 We do not impute data for countries that the entire time series of sectoral

FDI is missing because we are concerned that doing so may introduce more bias.



This is because these omitted observations would indicatea negative relationship between personalism and primaryFDI.

To assess this possibility, we examine whether the sixty-one countries in the estimating sample differ along key di-mensions from the forty-eight countries excluded from theestimating sample. We chose not to impute missing data forthe latter forty-eight countries because they had no obser-vations with any sectoral FDI data. Figure 2 plots averagelevel of three variables—total FDI from all sectors, oil rents,and GDP per capita—for each regime type in the data forthe sixty-one countries in the estimating samples (includedcountries) and for the forty-eight countries not in the sample(excluded countries).

The top panel shows that, among the included countries(left plot) personalist regimes have, on average, more to-tal FDI than military regimes or monarchies but less thandemocracies or dominant party regimes. However, amongexcluded countries (right plot) personalist regimes havemore total FDI. If aggregate FDI is more likely to be com-posed of primary FDI in personalist regimes among the ex-cluded countries, then the top panel suggests the estimatesfor personalism using only the included countries might bebiased downward.

The middle panel shows that, while included countrieshave more oil rents, on average, than those excluded fromthe sample, the pattern ranking regimes by oil wealth re-mains consistent across the two groups of countries. In bothgroups, personalist regimes have roughly the same averagelevel of oil rents as military regimes and democracies butless oil rents than monarchies and party regimes. Finally, thebottom panel again shows similar patterns between the twogroups of countries: monarchies are the richest and person-alist dictatorships the poorest.

Our next approach assesses whether the two groups ofcountries differ in the change over time in total FDI in a waythat might suggest bias from estimates that only include thesixty-one countries with sectoral data. Figure 3 plots the timetrend in total FDI for countries included in the estimatingsample and those excluded from it. The left panel showsthat the FDI trend in the two groups of countries is nearlyidentical for nonpersonalist regimes. This indicates that,in nonpersonalist dictators and democracies, changes intotal FDI over time are roughly the same. For both groupsof countries, FDI inflows respond to global shocks afterthe Asian financial crisis (1998) and the Great Recession(2008).

The time trend for each group of countries with per-sonalist regimes, plotted in the right panel, shows a similarpattern, but with two exceptions.17 In the early 1980s, whenoverall FDI inflows to the developing world are low, theexcluded personalist regimes have higher total inflows.Second, the responses to the commodity boom of the 1990sand 2000s—as well as the attendant dips in 1998 and 2008resulting from global shocks—are stronger in the groupof included personalist regimes than in those excluded.Finally, total FDI inflows in personalist regimes appear to bemore responsive to commodity prices—and the respectiverecessionary dips—than the group of nonpersonalist coun-tries. This pattern is consistent both with our argument thatpersonalist regime receives more FDI inflows in resourceextraction sectors and with the documented dependenceof personalist regimes on nontax revenue, particularly fromforeign resource investment (Wright 2008).

17 The confidence intervals on the local area estimate are larger in right plotbecause there are fewer personalist regimes than nonpersonalist ones.

Appendix F in the supplementary information describestwo more tests that address concerns about bias resultingfrom excluding forty-eight countries from the estimatingsample. We show, first, that in a model of total FDI (ratherthan sectoral FDI), personalist regime has a similar effect inboth groups of countries. Second, we show that an indicatorof being an included country is not systematically correlatedwith either total FDI inflows or personalist regime. Whilethese tests cannot rule out potential bias, they nonethelessdo not raise any strong concerns about bias.

We address missingness in the time series for the sixty-one countries in the estimating sample by imputing themissing data (King et al. 2001; Honaker and King 2010).18

After imputing missing data, the main estimating samplecontains 1,782 observations from sixty-one developing coun-tries, from 1980 to 2010.19

A second empirical issue that arises when using sectoralFDI data is the highly skewed distribution of FDI inflows.Inference from skewed distributions may be heavily influ-enced by the presence of outliers. To address this issue, weconstruct the dependent variable as the cube root of pri-mary sector FDI as a share of GDP.20

Since we argue that personalist dictatorships offer a par-ticularly attractive institutional environment for fixed assetinvestors, we use an indicator for personalist regime as theindependent variable (Geddes et al. 2014). The personal-ism indicator measures whether the leader of the autocracyhas consolidated control over policy and personnel appoint-ments at the expense of the supporting political party (ifthere is one) and military and internal security institutions(Geddes 2003). The questions used to code this variabledo not address investment, either domestic or foreign, butrather informal power politics among regime elites.21 Thereference category is all other polities, including other typesof autocracies (Party, Military, and Monarchy) and democ-racy.22

The main model specification includes potential con-founders that influence FDI inflows: economic develop-ment (GDP per capita, log), market size (population, log),trade openness (total trade as a percentage of GDP, log),economic growth, regime durability, civil violence, naturalresource endowments, and total FDI inflows into the de-veloping world. The latter accounts for the strong calen-dar time trend in the FDI inflow data. Data on GDP per

18 In the imputation, we include two extra variables—total FDI inflows as ashare of GDP and oil rents—and a cubic polynomial of time. The sixty-one coun-tries in the estimating sample are listed in Table F-1 of the supplementary infor-mation. In these countries, data are missing for roughly three-quarters of possibleobservations from the 1980s, roughly half the observations from the 1990s butless than 20 percent from the 2000s. We impute data for ten datasets and aver-age model estimates from these ten datasets. See Figure F-4 in the supplementaryinformation for results that use listwise deletion instead of multiply imputed data.

19 The country panels are slightly unbalanced: nine post-Soviet countries havet = 19; all others have t = 31.

20 We address distributional issues in the FDI variable in Appendix B of thesupplementary information. We account for negative values by using the fol-lowing formula: F DIGDPs,i,t = (|F DIs,i,t /GDPi,t |)(1/3), where s is the sector, i isthe country, and t is the calendar year. We then multiply F DIGDPs,i,t by –1 when F DIs,i,t is less than 0. The cube root transformation handles nega-tive values without changing the underlying distribution of the original variable.Results are robust to different transformations of the dependent variable (seeAppendix B in the supplementary information).

21 Robustness tests in Figures A-1 and D-3 of the supplementary informationshow that the result is robust to including a measure of political constraints(Henisz 2002), indicating that the finding for personalist regime is not simplythe result of lack of formal institutional constraints (for example, opposition inthe legislature) in these regimes.

22 Robustness tests show that the finding for personalist regime remains whenincluding party, military, and monarchy indicators, leaving democracy as the ref-erence category.



Figure 2. Structural features of countries in estimating sample



Figure 3. Total FDI time trend in estimating sample

capita, population, trade openness, economic growth rates,total FDI into developing countries are from the WorldBank’s World Development Indicators. Regime duration is thenatural log of the years the regime has been in power,from Geddes, Wright, and Frantz (2017). Civil conflict in-cidence data come from the Uppsala Conflict Data Program(UCDP) Peace Research Institute Oslo (PRIO) Armed Con-flict Dataset (Gleditsch et al. 2002; Themnér and Wallen-steen 2014). The specification also includes a measure ofpast expropriation, from Kobrin (1984) and Hajzler (2012).This variable measures the number of expropriations in theprior eight years using an exponentially weighted moving av-erage, such that more recent expropriations are given moreweight.23

To account for natural resource endowments, which in-fluence both personalist rule and sectoral FDI, we include ameasure of the mean level of oil reserves in a country priorto the start of the sample period. The data are from Haberand Menaldo (2011). By design, this variable cannot be en-dogenously determined by observed FDI during the sampleperiod and does not reflect a posttreatment effect becauseit measures reserves prior to the observation of regime type.We believe it is a plausible cross-sectional measure of re-source endowments. Finally, the specification also includesgeographic region effects.24

We employ a linear estimator with country-random ef-fects (REs); because the data show serial correlation, weemploy a random effects estimator that allows for autore-gressive errors.25 Since we report results from ten multiplyimputed datasets, we aggregate the estimate from each im-puted dataset into one reported estimate using the rules out-lined in Rubin (1987).26

23 Using a six- or ten-year weighted moving average lag does not change theresults (see replication materials).

24 The region effects are the following: Americas, Asia, East Asia, and sub-Saharan Africa, with the Middle East as the reference category. We omit resultsfor these effects in the figures below.

25 A Wooldridge test for serial correlation rejects the null of no autocorrela-tion at the 0.10 level in seven of ten imputed datasets.

26 The reported coefficient estimates are the average estimates from ten mod-

els from ten datasets with imputed data: β̄ =∑mi=1 βim , where m = 10. The vari-

Figure 4. Primary sector FDI

Foreign Investment in Fixed Assets: Primary Sector FDI

Figure 4 reports the results of the baseline model of primarysector FDI. It displays point estimates and confidence inter-vals (95%, 90%) for each covariate, saving the region dum-mies. The estimate for personalist is positive and statisticallysignificant at the 1 percent level. Substantively, comparedto other regimes, personalist dictatorship is associated with0.06 units more of primary FDI. This is 48 percent of thestandard deviation of the dependent variable. As expected,the estimates for oil reserves and regime longevity also cor-relate positively with primary FDI. In contrast, past expropri-ations, economic development, and civil conflict are associ-ated with less primary FDI.

Results in the supplementary information show that thepositive association between personalist regime and pri-mary FDI is robust to specification changes, to differentoperationalizations and transformations of the dependent

ance estimates are the variances from within each of the ten imputed datasets,plus the sample variance in the coefficient estimates across the ten datasets, mul-

tiplied by a factor that corrects for m < ∞ : s2 =∑mi=1 u

2i

m + s2i (1 + 1m ), where

s2i =∑mi=1 (βi−β̄)2

m−1 .



Figure 5. Divided seizure predicts personalist regime

variable, to different approaches to modeling oil and gaswealth, and when dropping influential observations or onegeographic region at a time. We also show that personalistdictatorships receive more primary sector FDI than democ-racies, while other types of dictatorships such as monarchiesand dominant party regimes attract less. We further showthat the result is not driven by increasing Chinese invest-ment after China adopted the “Go Out” policy in 2001.

Addressing Endogeneity

A positive correlation between personalist regimes and pri-mary sector FDI might reflect an endogenous relationship:FDI flows may shape the behavior of dictators, such as theappointment of family relatives to positions of high officeor the facilitation of the development of corrupt resourcemanagement; such information is then used to distinguishpersonalist dictatorship from other types of autocratic rule.

To address this issue, we use information on how the dic-tatorship arose in the first place in a two-stage model. Howthe first leader of a new dictatorship seizes power is corre-lated with the personalist regime indicator: these dictator-ships are more likely to arise from uprisings and when ademocratically elected leader, such as Peru’s Alberto Fuji-mori, grabs power by closing democratic institutions. Thesescenarios—uprisings and power-grabs—indicate situationsin which the new dictator is likely to bargain over initialpower-sharing with a relatively divided military or a weak po-litical party (Geddes et al. 2017). Alternatively, leaders of dic-tatorships that seize power in an armed rebellion are likelyto bargain with a unified military or a cohesive revolution-ary party. Similarly, leaders of regimes established by coupsled by senior military officers are likely to face a unified mil-itary. More initial bargaining power for the dictator leads tothe concentration of political power in his hands—in otherwords, a personalist, or “consolidated,” dictatorship (Svolik2012; Geddes et al. 2017). Importantly, the information onhow the regime seizes power (divided seizure) is chronolog-ically prior to the behavior of the dictator once in power.Using information on seizure of power as an excluded in-strument thus alleviates concerns about reverse causation, inwhich foreign investment shapes autocratic behavior oncein power.

Figure 5 shows the results of a “first-stage” equation (RE,clustered errors) that uses divided seizure as the excluded in-strument. The F-statistic for this variable is 46, indicating astrong excluded instrument.

To estimate a two-stage model, we adopt two approaches.First, we employ Baltagi’s error component two-stage least

Figure 6. 2SLS results

squares (EC2SLS) random-effects estimator. It is more effi-cient than a generalized 2SLS estimator.27 We also reportestimates from an ordinary least squares (OLS) random ef-fects model with clustered errors but no autocorrelation correc-tion for direct comparison with the two-stage results.

Second, we report results from fixed effects (FEs) esti-mators that model autoregressive (AR[1]) process: OLS-FE with AR(1) errors, OLS-FE with heteroscedasticity-autocorrelation-consistent (HAC) errors, and 2SLS-FE withHAC errors.28 Models with HAC errors assume an AR(1)process (that is, Newey-West) and correct for arbitrary het-eroskedasticity. While we believe the RE approach withAR(1) errors is preferable to the FE estimator, the lattermore easily models serial correlation in a 2SLS framework.Further, a Hausman test indicates that the RE and FE mod-els yield similar coefficient estimates.

The top estimate for personalist in Figure 6 is the RE es-timate with AR(1) errors—the same as reported in Figure4. Next is the RE estimate with clustered errors. The lat-ter yields a slightly smaller coefficient estimate and slightlylarger error bands. The third estimate is from the 2SLS-REmodel with clustered errors. The point estimate is slightlylarger than the OLS-RE estimates, but with larger errorbands. The next three estimates are from the FE models.While the OLS-FE estimates are slightly smaller than the REestimates, the 2SLS-FE estimator with HAC errors yields alarger point estimate.

Overall, the 2SLS estimates are similar to the OLS esti-mates. This indicates that—if we believe that how the regimeseizes power does not cause foreign investment apart frominfluencing political regime type—the estimates for person-alist regime can be interpreted as causal. We discuss thisassumption in detail in Appendix D of the supplementaryinformation, but note that the 2SLS result is robust to mod-eling additional potential confounders, such as covert inter-ventions from superpower countries that might prop up per-sonalist dictatorships that are friendly to foreign investors.

FDI in the Other Sectors

Our main expectation states that FDI in the primary sectorshould be higher in personalist dictatorships than in otherregimes, including democracies. A further implication ofthe argument suggests that personalist dictatorships should

27 All variance components are estimated with the Baltagi-Chang estimator.We report cluster-robust standard errors.

28 Note that with FE models, the time-invariant covariates drop from the spec-ification: pre-1980 oil reserves and the region dummies.



Figure 7. Estimates for sectoral FDI and from oil-rich and oil-poor countries

not receive more FDI in sectors characterized by low levels offixed assets. We test this proposition by repeating the mainmodel specification but with secondary sector FDI, insteadof primary sector investment.

We also report a test for tertiary FDI, but view this typeof FDI as a less compelling proxy for asset immobility be-cause investment in this sector yields both mobile and im-mobile assets. Investment in the construction and energysupply and transportation sectors, for example, is classifiedas tertiary FDI but yields a relatively immobile asset. In con-trast, financial or information technology investments alsocount as tertiary FDI, but the asset remains relatively mo-bile. If tertiary FDI in our sample tends to flow to immobileassets such as construction or resource extraction services,then this variable may better reflect investments in immo-bile assets.

The left panel of Figure 7 shows the estimates for person-alist regime from the sectoral models. The top estimate isthe same as the one from Figure 4, with primary FDI as thedependent variable. The next two estimates are from mod-els with secondary and tertiary FDI as the outcomes, respec-tively. Both estimates are close to zero and neither is statis-tically significant. This suggests that personalist regimes donot have more secondary and tertiary sector FDI than otherregimes. This result is consistent with theoretical expecta-tions.

Oil Rich and Oil Poor Countries

A final test examines whether the main finding holds in bothoil rich and in oil poor countries. If primary FDI simply flowsto countries where resources are located and if personalistregimes are more likely to arise in countries with large nat-ural resource endowments, then a finding indicating thatpersonalist regimes attract more primary FDI than otherregimes may be spurious. We have already addressed thiscounterargument by directly accounting for resource en-

dowment in the regression analysis (see especially AppendixC in the supplementary information). Further, the fixed ef-fects estimates (shown in Figure 6) compare periods of per-sonalist rule with other types of government within the samecountry, directly accounting for cross-country differences infixed resource endowments.

The right panel of Figure 7 shows estimates from a split-sample model. We divide the sixty-one countries in the sam-ple in two categories: low oil countries and high oil countries.The cut-point distinguishing the two is whether the max-imum value of logged oil reserves (per capita) is greaterthan 1.29 Of the sixty-one countries in the sample, thirty-five are in the high oil category and twenty-six are in thelow category. In each category, just over 25 percent of thecountries have had a personalist regime during the sampleperiod (1980–2010).

The top estimate in the right panel of Figure 7 is the mainmodel that pools information from all sixty-one countries(reported in Figure 4). The next two split the sample intothe two categories. The estimates for personalist regime arepositive and statistically significant in both models. Theseresults suggest that the main finding is not the product ofsome unobserved relationship between resource wealth andpersonalism.30

Industry-Level FDI

In the previous model specifications, we focus on the broaddistinction between the primary and secondary sector asproxies for high and low fixed-asset intensive investments,

29 The countries with the highest maximum value are Saudi Arabia,Venezuela, and Iran, whereas twenty-three countries—from all regions of theworld—have a maximum value of 0. Using this cut-point, the countries with thehighest value in the low oil bin are Ethiopia, Morocco, and Bangladesh. The coun-tries with the lowest value in the high oil category are Tajikistan, Pakistan, andJordan.

30 See Appendix L in the supplementary information for more tests.



Figure 8. Estimated coefficients of personalism across industriesNote: Plot of regression coefficients of personalism across industries. Vertical lines represent 95 percent and 90 percentconfidence intervals. The dark dashed line is the fitted regression line of estimated coefficients over fixed asset intensity(fixed capital expenditures/output, log) at the industry level.

respectively. Yet, levels of fixed assets also vary within the pri-mary and secondary sector. In this section, we explore theindustry-level variation to assess the relationship betweenpersonalism and foreign investment. According to our the-ory, we should expect a positive relationship between per-sonalist dictatorships and high fixed asset investments butnot between the former and low fixed asset investments.

We regress FDI in each of the eighteen primary and sec-ondary industries on personalism and covariates,31 and thenplot the coefficients against industry-level fixed asset inten-sity.32 As shown in Figure 8, the coefficient of personalismis positive and significant in fixed-asset intensive industries,such as mining, quarry and petroleum, and electricity, gasand water. It becomes much smaller and turns negative in in-dustries with low levels of fixed assets, such as textiles, cloth-ing and leather.33 The correlation between the estimatedcoefficients and our measure of fixed asset intensity for theeighteen industries is 0.65.

31 Coefficients plotted in Figure 8 are based on imputed data. Appendix Gin the supplementary information presents regression results from both nonim-puted and imputed datasets.

32 Industry-level fixed asset intensity is measured by the ratio of annual fixedcapital expenditures to gross output. This measure is calculated using data fromUS Bureau of Economic Analysis, averaged over the period of 2001–2010. Al-though level of fixed asset intensity of one particular industry varies across coun-tries, the intensity ordering of different industries does not change too much.Industry characteristics are largely determined by technology. In other words, thesame industries are always more fixed-asset intensive than others across differentcountries. See Nunn and Trefler (2014, 274). In this article, we examine whetherthe relationship between personalism and foreign investors differs in high andlow fixed-asset intensive industries. Thus, we are interested in the relative order-ing of industrial-level fixed asset intensity rather than its absolute level. Anotheradvantage of using US data is that they are exogenous for developing countries.

33 Primary FDI is comprised of investment in two industry categories: agricul-ture and mining. The estimate in Figure 8 for mining, quarrying, and petroleum isthe largest positive estimate, while the estimate for agriculture, hunting, forestry,and fishing is much smaller and not statistically significant. This suggests that themain result is driven by mining FDI and not agricultural FDI.

These results suggest that the correlation between fixedasset investors and personalist dictatorships is not confinedto the primary sector only and holds in fixed-asset intensiveindustries in general.

Mechanisms: Corruption, Governance, and Market Dynamics

We have shown that personalist dictatorships receive moreforeign investment in fixed-asset intensive industries thanother political regimes. Our theory suggests that this rela-tionship is driven by a favorable institutional environmentthat facilities MNCs’ monopoly or oligopoly rent extrac-tion, despite high political risk. Accordingly, we should ob-serve lower transparency and accountability, more corrup-tion, and higher market concentration in fixed-asset inten-sive sectors in personalist regimes. In the following sections,we examine these underlying mechanisms.

Corruption We provide two pieces of evidence that suggestpersonalist dictatorships enable monopoly rent extractionand thus more corruption in the fixed-asset intensive re-source sector. Firms’ corruption activity is directly linkedto the level of rents they extract. High rents not only rein-force firms’ ability to internalize the cost of corruption, butalso increase government officials’ incentives to engage inthe quid pro quo of their “control rights” for bribes (Adesand Di Tella 1999). Extant literature shows that, in the cross-section, personalist dictatorships have higher levels of over-all corruption, as measured by survey data on perceptions ofcorruption (Chang and Golden 2010).

Instead of relying on data for corruption that cover allmarkets in a domestic economy, we examine the relation-ship between personalism and corruption in the resourcesector, focusing on two new measures. The first is the Re-source Governance Index (RGI), which captures the level oftransparency and accountability in the oil, gas, and mining



Figure 9. Personalism and resource governance (RGI)

sectors in fifty-eight resource-rich countries (Revenue WatchInstitute 2013). A lack of transparency and accountabilityfacilitates rent-seeking activities. We expect that personal-ist regimes should score lower in the RGI compared withother regimes. The second is the incidence of prosecutionsfor bribery in the oil and gas sectors under the US ForeignCorrupt Practices Act (FCPA). The data come from Mahdavi(2015).

Resource governance First, we examine the cross-sectionalcomposite RGI. This index combines information from fourcomponent areas: the institutional and legal setting, report-ing practices, safeguards and quality controls, and the en-abling environment.34

The RGI data only exist for the year 2013, and the data onpersonalism only extend to 2010. Therefore, we construct ameasure of the mean level of personalism for each coun-try. We begin with cross-section, time-series data on four fea-tures of personalism in dictatorships (Geddes et al. 2017):(1) whether appointment to high office in the governmentdepends on a personal relationship with the regime leader(office personal); (2) whether the regime leader appoints fam-ily relatives to position of high office in the government ormilitary (leader relative); (3) whether the regime leader cre-ated his own political party during a democratic electionand then subsequently “authoritarianized” the regime (cre-ate party); and (4) whether the regime leader is a personalrelative of the prior leader (family succession) in contexts—such as Haiti (Duvalier family), North Korea (Kim family),and Syria (Assad family)—where there is no formal hered-itary succession rule (i.e., nonmonarchies). These variablescapture two aspects of personalism central to our argument:whether individual personal relations with the dictator andhis family structure elite behavior (i.e., personal cronyism)and whether the supporting political party acts as a checkon the leader’s behavior.35

34 Further tests in Appendix H of the supplementary information indicate thatfindings for the composite measure extend to each of the component scores ex-cept enabling environment.

35 When dictators such as Alberto Fujimori or Hugo Chavez create personalpolitical machines to campaign for office, they typically retain control over high-level appointments to the party, and the parties therefore rarely constrain the waythe leader relates to other elites. In contrast, supporting parties that arise as part

To construct a cross-country index of personalism, we firsttake a linear combination of the four items (office personal,leader relative, create party, and family succession) and then cal-culate the country-mean of this variable for all autocraticyears up to 2010. Finally, we weight this country-mean by theshare of years from 1980 (or independence) that the coun-try had a nondemocratic regime. This means that the rawVenezuela personalism index is weighted less because thecountry is only coded as nondemocratic from 2005, whileCambodia’s score is weighted more because it was coded asnondemocratic for all years from 1980 to 2010.

The left panel of Figure 9 plots the composite RGI scoreagainst the personalism index; there is a strong negativecorrelation. Dominant-party dictatorships such as China,Mexico, Mozambique, and Vietnam as well as long-lastingdemocracies such as Colombia and India have low personal-ism scores and high values of resource governance. In con-trast, personalist dictatorships, such as the Democratic Re-public of Congo, Gabon, and Libya, have high personalismscore and poor resource governance.36

Because the values of the RGI index are bounded at 0and 100, we divide it by 100 and then test a generalized lin-ear model with logit link function. The right panel showsthe conditional correlation between the personalism indexand the transformed RGI score. The estimate is conditionedon cross-sectional measures of GDP per capita (log) andoil rents (log), as well as a binary indicator of whether themain resource in the country is hydrocarbons. A secondmodel adds a variable capturing whether the oil industry

of rebel groups or independence movements, such as the Vietnamese CommunistParty or the Tanzanian TANU (later CCM), structure leader and elite interactions.In the former, the dictator selects the party; in the latter, the party selects theleader.

36 We note two countries that stand out in this pattern: Myanmar and Turk-menistan. Like many other post-Soviet autocracies in Central Asia, Turkmenistaninherited its ruling political party from the Soviet era; the leader therefore didnot create a new party. However, unlike other autocracies in the region, the firstpostindependence leader was an orphan and thus did not have an extensive fam-ily to appoint to high office. Therefore, the only item in the personalist index thatindicates this regime is personalist is office personal, lowering the overall personal-ist score. In Myanmar, the military junta that ruled during the sample period didnot create a new political party until 1993, and there was no family succession ofleaders. When we exclude these two cases, the results are substantially strongerthan those reported in Figure 9.



Figure 10. Personalism and FCPA corruption cases

is governed by a regulatory nationalized oil company(NOC).37 In both tests the estimate for the personalist indexis negative. This suggests a negative cross-sectional correla-tion between personalism and resource governance, evenonce we account for some of the other explanations forresource corruption in the literature (Luong and Weinthal2010).

Corruption prosecutions in the resource sector In this section, weexamine whether personalism is associated with bribery inthe oil and gas sectors, using data on prosecutions under theFCPA. According to our argument, personalist dictatorshipstend to tolerate market concentration and facilitate MNCs’monopoly rent extraction. When rents are high, we shouldobserve a high frequency of corruption involving foreigninvestment in fixed assets in these regimes. The FCPA waspassed in 1977, granting authority to the US Security andExchange Commission and the US Department of Justice toprosecute US companies or foreign organizations that tradesecurities in the United States for bribing foreign govern-ment officials and politicians. Mahdavi (2015) collects dataon FCPA prosecutions in the oil and gas sectors. All but twoof the FCPA prosecutions occur after 1996, so we examineforty-six oil-producing countries from 1997 to 2010. We testa kernel regression model but show in Appendix I that thetime-varying results remain in conditional logit, random ef-fects logit, and rare events logit tests as well.

The left panel of Figure 10 shows the cross-sectioncorrelation among the ninety-five individual regimes; thedependent variable is a binary indicator of whether theregime (either a specific autocratic case or democracy)faced prosecution. The specification reported in the top es-timate has only two control variables: GDP per capita andpopulation. The second set of estimates is from a specifica-tion that adds oil-related covariates (oil rents per capita and

37 The hydrocarbon indicator is from Revenue Watch Institute (2013), andthe indicator of regulatory NOC is from Mahdavi (2015). The NOC variable isonly available for thirty-one oil-producing countries, reducing the sample size.

regulatory NOC), while the last estimates are from a specifi-cation that includes measures of US military and economicaid. The structural covariates and foreign aid variables arethe regime-mean. We test a model with foreign aid to ac-count for the possibility that US prosecutions are less likelyfor US allies; however, we find the opposite. This may re-flect more corruption scrutiny for foreign governments thatreceive high amounts of US aid. In all specifications, we findthat FCPA prosecutions in the oil sector are more likely totarget regimes with a higher personalism score.

The right panel of Figure 10 reports results from a seriesof models with time-varying data on all variables, includingthe personalism index. The results are similar to those re-ported in the left panel: personalism, GDP per capita, popu-lation, oil rents, and regulatory NOCs are all associated witha higher likelihood of corruption prosecution. However, theaid variables do not yield consistent results. Overall, the find-ings in Figure 10 suggest that prosecution for corruptioncases in the oil sector are more likely to target personalistdictatorships.

Export Concentration To examine whether personalist dic-tators tolerate monopolistic or oligopolistic market struc-tures, ideally we would like detailed firm-level data acrossdifferent industries for a large sample of countries. How-ever, such data is extremely difficult to come by. Alterna-tively, we utilize a country’s export profile as a proxy forits market structure. Note that a lack of export diversity isnot a direct measure of market concentration. Nonethe-less, it likely reflects the underlying market dynamics inthe country, especially in extractive industries in which gi-ant MNCs typically dominate and production in develop-ing countries is primarily for export (UNCTAD 2007). Weobtain detailed commodity trade data from the UnitedNations Comtrade database and calculate the Herfindahl-Hirschman Index (HHI) of each country-year’s primaryand secondary exports using two-digit commodity export



Figure 11. Personalism and export concentration

data.38 We use the two HHI indicators as a measure of ex-port concentration in the primary and secondary sector,respectively.

Because this index is bounded by 0 and 1, we logit trans-form it for use in a linear model. Tests indicate the pres-ence of autocorrelation in the panel data, so we employ amodel with an AR1 error structure. The reported specifica-tions control for the size of the market (log population) aswell as GDP per capita and trade openness. We also con-dition the estimates on current oil rents per capita to cap-ture the effect of past investment—which yields current re-source production—and thus influences the compositionof exports. To account for unmodeled time-invariant dif-ferences between economies from different geographic re-gions, such as distance to advanced economy markets, weinclude region effects.

Figure 11 reports the results for export concentrationmodels in the primary and secondary sectors. The top es-timate for each variable is for the primary sector, while thebottom estimate is for the secondary one; the thick lines rep-resent the 90 percent confidence intervals and the thin linesindicate the 95 percent confidence intervals.39 For the pri-mary sector, personalist regimes have higher average exportconcentration than other regimes. In the secondary sector,the estimate for personalist regimes is roughly zero. Finally,oil rents correlate positively with export concentration inboth sectors but more so in the primary sector. The findingindicating higher primary export concentration in personal-ist dictatorships remains when we model fixed effects, dropcontrol variables, or estimate various lagged dependent vari-ables. These results are consistent with our argument thatpersonalist dictatorships tolerate more market concentra-tion in the primary sector than other regimes.

Taken together, these results provide strong support toour argument that personalist regimes have poorer gover-nance, more corruption, and higher market concentration

38HHI =N∑

i=1s2i , where si the export share of commodity i in the primary or

secondary sector.39 For ease of interpretation, we omit estimates of region indicators and time

trend variables.

in the primary sector. Personalist dictatorships thereforeprovide a favorable institutional environment for foreign in-vestments in fixed assets that seek monopoly or oligopolyrents.

Conclusion

The past decades have witnessed a boom of foreign invest-ment in the primary sector, especially since the commod-ity price hikes in the 1990s. Much of the investment haspoured into unconventional, politically risky destinations.This seems to contradict arguments in the recent politicaleconomy of FDI literature, which holds that the immobil-ity of fixed assets—and their vulnerability to host govern-ment’s expropriation—should deter foreign investment insuch countries. But, as we show, fundamental regulatorychanges since 1980s—both in developing countries and atthe international level—have greatly reduced MNC fears ofnationalization and asset expropriation. Existing literaturealso overlooks another critical aspect of fixed assets: highinitial capital requirements and substantial sunk costs act asentry barriers. This gives rise to opportunities for monopolyrent extraction. Personalist dictatorships provide a particu-larly favorable institutional environment for this type of in-vestor because of a lack of de facto institutional constraintsand because leaders’ families control key economic sec-tors. We find strong evidence that, compared with otherregimes, personalism correlates strongly with more FDI infixed-asset intensive industries. We also find that personal-ist dictatorships have lower transparency and accountability,more corruption prosecutions, and higher market concen-tration in the resource sector. This suggests that personalistdictatorships provide an attractive institutional environmentfor monopoly rent extraction.

We believe it is fruitful to move this research agenda for-ward in two directions. First, future research can exploreadditional dimensions of foreign investment and variationin political contexts. In addition to fixed asset intensity,multinationals differ widely in technology sophistication, re-search and development (R&D) expenditures, skill profiles,marketing and advertising intensity, and so forth. These fac-tors influence their preferences for institutional environ-ments where firms can make the most use of firm-specificassets. High-tech and R&D intensive MNCs, for instance, arelikely to favor political institutions that provide strong prop-erty rights protection and encourage citizens’ investmentin human capital, two factors crucial to capitalize on thesetypes of investments.

Second, it is important to examine the political andeconomic consequences of primary sector FDI in devel-oping countries. Foreign investments in extractive indus-tries tend to have limited backward and forward link-ages, as well as a small effect on employment creation,compared to investment in the manufacturing sector.Many important questions remain to be explored, suchas how primary sector FDI influences leader and regimesurvival in authoritarian countries and whether the en-try and presence of rent-seeking MNCs may result inthe deteriorate governance or even fuel political violence(see Pinto and Zhu 2017).

Supplementary Information

Supplementary information is available at the authors’ web-sites and the International Studies Quarterly data archive.



References

ADES, ALBERTO, AND RAFAEL DI TELLA. 1999. “Rents, Competition, and Corrup-tion.” American Economic Review 89 (4): 982–93.

ALLEE, TODD, AND CLINT PEINHARDT. 2011. “Contingent Credibility: The Im-pact of Investment Treaty Violations on Foreign Direct Investment.”International Organization 65 (3): 401–32.

ASIEDU, ELIZABETH, AND DONALD LIEN. 2011. “Democracy, Foreign Direct In-vestment, and Natural Resources.” Journal of International Economics 84(1): 99–111.

BAIN, JOE STATEN. 1956. Barriers to New Competition, Their Character, and Conse-quences in Manufacturing Industries. Cambridge, MA: Harvard UniversityPress.

BAUMOL, WILLIAM J., AND ROBERT D. WILLIG. 1981. “Fixed Costs, Sunk Costs,Entry Barriers, and Sustainability of Monopoly.” Quarterly Journal ofEconomics 96 (3): 405–31.

BIGLAISER, GLEN, AND JOSEPH L. STAATS. 2010. “Do Political Institutions Af-fect Foreign Direct Investment? A Survey of US Corporations in LatinAmerica.” Political Research Quarterly 63 (3): 508–22.

BLANTON, SHANNON LINDSEY, AND ROBERT G. BLANTON. 2007. “What Attracts For-eign Investors? An Examination of Human Rights and Foreign DirectInvestment.” Journal of Politics 69 (1): 143–55.

——. 2009. “A Sectoral Analysis of Human Rights and FDI: Does IndustryType Matter?” International Studies Quarterly 53 (2): 469–93.

BRATTON, MICHAEL, AND NICOLAS VAN DE WALLE. 1994. “Neopatrimonial Regimesand Political Transitions in Africa.” World Politics 46 (4): 453–89.

BUSSE, MATTHIAS, AND CARSTEN HEFEKER. 2007. “Political Risk, Institutions, andForeign Direct Investment.” European Journal of Political Economy 23 (2):397–415.

BÜTHE, TIM, AND HELEN V. MILNER. 2008. “The Politics of Foreign Direct In-vestment into Developing Countries: Increasing FDI Through Interna-tional Trade Agreements?” American Journal of Political Science 52 (4):741–62.

CHANG, ERIC, AND MIRIAM A. GOLDEN. 2010. “Sources of Corruption in Author-itarian Regimes.” Social Science Quarterly 91 (1): 1–20.

CHEHABI, HOUCHANG E., AND JUAN J. LINZ. 1998. Sultanistic Regimes. Baltimore:Johns Hopkins University Press.

DAHL, ROBERT A. 1971. Polyarchy: Participation and Opposition. New Haven, CT:Yale University Press.

DUETSCH, LARRY L. 1984. “Entry and the Extent of Multiplant Operations.”Journal of Industrial Economics 32 (4): 477–87.

EDEN, LORRAINE, STEFANIE LENWAY, AND DOUGLAS A. SCHULER. 2005. “From theObsolescing Bargain to the Political Bargaining Model.” In Interna-tional Business and Government Relations in the 21st Century, edited byRobert E. Grosse, 251–72. New York: Cambridge University Press.

ELKINS, ZACHARY, ANDREW T. GUZMAN, AND BETH A. SIMMONS. 2006. “Competingfor Capital: The Diffusion of Bilateral Investment Treaties, 1960–2000.”International Organization 60 (4): 811–46.

FARGE, EMMA. 2016. “Timis Companies Seek $385 Million from Burkina Fasoin Mining Dispute.” Reuters, December 6. Accessed November 15, 2017.http://reut.rs/2AeQtwh.

GANDHI, JENNIFER, AND ADAM PRZEWORSKI. 2006. “Cooperation, Cooptation, andRebellion Under Dictatorships.” Economics & Politics 18 (1): 1–26.

GEDDES, BARBARA. 2003. Paradigms and Sand Castles: Theory Building and Re-search Design in Comparative Politics. Ann Arbor: University of MichiganPress.

GEDDES, BARBARA, JOSEPH WRIGHT, AND ERICA FRANTZ. 2014. “Autocratic Break-down and Regime Transitions: A New Data Set.” Perspectives on Politics12 (2): 313–31.

GEDDES, BARBARA, JOSEPH WRIGHT, AND ERICA FRANTZ. 2018. How DictatorshipsWork. New York: Cambridge University Press.

GEHLBACH, SCOTT, AND PHILIP KEEFER. 2012. “Private Investment and the Insti-tutionalization of Collective Action in Autocracies: Ruling Parties andLegislatures.” Journal of Politics 74 (2): 621–35.

GEROSKI, PAUL A. 1995. “What Do We Know about Entry?” International Journalof Industrial Organization 13 (4): 421–40.

GLEDITSCH, NILS PETTER, PETER WALLENSTEEN, MIKAEL ERIKSSON, MARGARETA SOL-LENBERG, AND HÅVARD STRAND. 2002. “Armed Conflict 1946–2001: A NewDataset.” Journal of Peace Research 39 (5): 615–37.

GRAHAM, BENJAMIN A. T., NOEL P. JOHNSTON, AND ALLISON F. KINGSLEY. 2017.“Even Constrained Governments Take.” Journal of Conflict Resolution:1–13.

GURIEV, SERGEI, ANTON KOLOTILIN, AND KONSTANTIN SONIN. 2011. “Determinantsof Nationalization in the Oil Sector: A Theory and Evidence fromPanel Data.” Journal of Law, Economics & Organization 27 (2): 301–23.

HABER, STEPHEN, AND VICTOR MENALDO. 2011. “Do Natural Resources Fuel Au-thoritarianism? A Reappraisal of the Resource Curse.” American PoliticalScience Review 105 (1): 1–26.

HAJZLER, CHRISTOPHER. 2012. “Expropriation of Foreign Direct Investments:Sectoral Patterns from 1993 to 2006.” Review of World Economics 148 (1):119–49.

HARRIGAN, KATHRYN RUDIE. 1981. “Barriers to Entry and Competitive Strate-gies.” Strategic Management Journal 2 (4): 395–412.

HENISZ, WITOLD J. 2000. “The Institutional Environment for MultinationalInvestment.” Journal of Law, Economics, & Organization 16 (2): 334–64.

——. 2002. “The Institutional Environment for Infrastructure Investment.”Industrial and Corporate Change 11 (2): 355–89.

HONAKER, JAMES, AND GARY KING. 2010. “What to Do about Missing Values inTime-Series Cross-Section Data.” American Journal of Political Science 54(2): 561–81.

JAKOBSEN, JO, AND INDRA DE SOYSA. 2006. “Do Foreign Investors Punish Democ-racy? Theory and Empirics, 1984–2001.” Kyklos 59 (3): 383–410.

JENKINS, BARBARA. 1986. “Reexamining the ‘Obsolescing Bargain’: A Study ofCanada’s National Energy Program.” International Organization 40 (1):139–65.

JENSEN, NATHAN M. 2003. “Democratic Governance and Multinational Corpo-rations: Political Regimes and Inflows of Foreign Direct Investment.”International Organization 57 (3): 587–616.

——. 2006. Nation-States and the Multinational Corporation: A Politi-cal Economy of Foreign Direct Investment. Princeton, NJ: PrincetonUniversity Press.

JOHNS, LESLIE, AND RACHEL L. WELLHAUSEN. 2016. “Under One Roof: SupplyChains and the Protection of Foreign Investment.” American PoliticalScience Review 110 (1): 31–51.

KACZMAREK, SARAH C., AND ABRAHAM L. NEWMAN. 2011. “The Long Arm of theLaw: Extraterritoriality and the National Implementation of ForeignBribery Legislation.” International Organization 65 (4): 745–70.

KARAKAYA, FAHRI. 2002. “Barriers to Entry in Industrial Markets.” Journal ofBusiness & Industrial Marketing 17 (5): 379–88.

KARAKAYA, FAHRI, AND MICHAEL J. STAHL. 1989. “Barriers to Entry and MarketEntry Decisions in Consumer and Industrial Goods Markets.” Journalof Marketing 53 (2): 80–91.

KERNER, ANDREW. 2009. “Why Should I Believe You? The Costs and Conse-quences of Bilateral Investment Treaties.” International Studies Quarterly53 (1): 73–102

——. 2014. “What We Talk About When We Talk About Foreign Direct In-vestment.” International Studies Quarterly 58 (4): 804–15.

KERNER, ANDREW, AND JANE LAWRENCE. 2012. “What’s the Risk? Bilateral Invest-ment Treaties, Political Risk and Fixed Capital Accumulation.” BritishJournal of Political Science 44 (1): 107–21.

KING, GARY, JAMES HONAKER, ANNE JOSEPH, AND KENNETH SCHEVE. 2001. “Analyz-ing Incomplete Political Science Data: An Alternative Algorithm forMultiple Imputation.” American Political Science Review 95 (1): 49–69.

KOBRIN, STEPHEN J. 1984. “Expropriation as an Attempt to Control ForeignFirms in LDCs: Trends from 1960 to 1979.” International Studies Quar-terly 28 (3): 329–48.

——. 1987. “Testing the Bargaining Hypothesis in the ManufacturingSector in Developing Countries.” International Organization 41 (4):609–38.

KOIVUMAEKI, RIITTA-ILONA. 2015. “Evading the Constraints of Globalization:Oil and Gas Nationalization in Venezuela and Bolivia.” Comparative Pol-itics 48 (1): 107–25.

KUMAR, KRISHNA B., RAGHURAM G. RAJAN, AND LUIGI ZINGALES. 1999. “What De-termines Firm Size?” National Bureau of Economic Research Working PaperSeries No. 7208. http://www.nber.org/papers/w7208.pdf.

LI, QUAN. 2009. “Democracy, Autocracy, and Expropriation of Foreign DirectInvestment.” Comparative Political Studies 42 (8): 1098–127.

LI, QUAN, AND ADAM RESNICK. 2003. “Reversal of Fortunes: Democratic Institu-tions and Foreign Direct Investment Inflows to Developing Countries.”International Organization 57 (1): 175–211.

LUONG, PAULINE JONES, AND ERIKA WEINTHAL. 2010. Oil Is Not a Curse: OwnershipStructure and Institutions in Soviet Successor States. New York: CambridgeUniversity Press.

MADSEN, MICHELLE. 2015. “Liberia’s Offshore Oil Blocks Owners Operationsin Turmoil.” Front Page Africa, December 7. Accessed November 15,2017. http://allafrica.com/stories/201512071901.html.

MAHDAVI, PAASHA. 2015. “The Politics of Oil Nationalizations.” PhD disserta-tion, University of California, Los Angeles.

MALESKY, EDMUND J., DIMITAR D. GUEORGUIEV, AND NATHAN M. JENSEN. 2015.“Monopoly Money: Foreign Investment and Bribery in Vietnam,


http://reut.rs/2AeQtwh

http://www.nber.org/papers/w7208.pdf

http://allafrica.com/stories/201512071901.html


a Survey Experiment.” American Journal of Political Science 59 (2):419–39.

MARKUS, STANISLAV. 2015. Property, Predation, and Protection: Piranha Capitalismin Russia and Ukraine. New York: Cambridge University Press.

MITTON, TODD. 2008. “Institutions and Concentration.” Journal of DevelopmentEconomics 86 (2): 367–94.

MORAN, THEODORE H. 1973. “Transnational Strategies of Protection and De-fense by Multinational Corporations: Spreading the Risk and Raisingthe Cost for Nationalization in Natural Resources.” International Orga-nization 27 (2): 273–87.

MOSLEY, LAYNA, AND SAIKA UNO. 2007. “Racing to the Bottom or Climbing tothe Top? Economic Globalization and Collective Labor Rights.” Com-parative Political Studies 40 (8): 923–48.

NUNN, NATHAN, AND DANIEL TREFLER. 2014. “Domestic Institutions as a Sourceof Comparative Advantage.” In Handbook of International Economics, vol.4, edited by Gopinath Gita, Helpman Elhanan, and Ken Rogoff, 263–315. Amsterdam, NL: Elsevier.

O’DONNELL, GUILLERMO A. 1978. “Reflections on the Patterns of Change inthe Bureaucratic Authoritarian State.” Latin American Research Review13 (1): 3–38.

——. 1988. Bureaucratic Authoritarianism: Argentina, 1966–1973, in Compara-tive Perspective. Berkeley: University of California Press.

ONEAL, JOHN R. 1994. “The Affinity of Foreign Investors for AuthoritarianRegimes.” Political Research Quarterly 47 (3): 565–88.

O’NEILL, DANIEL. 2014. “Playing Risk: Chinese Foreign Direct Investment inCambodia.” Contemporary Southeast Asia: A Journal of International andStrategic Affairs 36 (2): 173–205.

PINTO, PABLO M., AND BOLIANG ZHU. 2016. “Fortune or Evil? The Effect of In-ward Foreign Direct Investment on Corruption.” International StudiesQuarterly 60 (4): 693–705.

PINTO, PABLO M., AND BOLIANG ZHU. 2017. “Brewing Violence: Foreign Invest-ment and Civil Conflict.” http://dx.doi.org/10.2139/ssrn.2998123.

POST, ALISON E. 2014. Foreign and Domestic Investment in Argentina: The Poli-tics of Privatized Infrastructure. Cambridge, MA: Cambridge UniversityPress.

POST, ALISON E., AND MARÍA VICTORIA MURILLO. 2016. “How Investor PortfoliosShape Regulatory Outcomes: Privatized Infrastructure After Crises.”World Development 77(C): 328–45.

PRINCE, ROB. 2015. “Manganese: Burkina Faso’s New Resource Curse.” For-eign Policy in Focus, December 29. Accessed November 15, 2017.http://fpif.org/manganese-burkina-fasos-new-resource-curse/.

RESNICK, ADAM L. 2001. “Investors, Turbulence, and Transition: DemocraticTransition and Foreign Direct Investment in Nineteen DevelopingCountries.” International Interactions 27 (4): 381–98.

REVENUE WATCH INSTITUTE. 2013. The 2013 Resource Governance Index: A Measureof Transparency and Accountability in the Oil, Gas, and Mining Sector. NewYork: Revenue Watch Institute.

RUBIN, DONALD B. 1987. Multiple Imputation for Nonresponse in Surveys. NewYork: Wiley.

SCHERER, FREDERIC M. 1973. “The Determinants of Industrial Plant Sizes inSix Nations.” Review of Economics and Statistics 55 (2): 135–45.

SHAFER, D. MICHAEL. 1994. Winners and Losers: How Sectors Shape the Developmen-tal Prospects of States. Ithaca, NY: Cornell University Press.

SNYDER, RICHARD. 1992. “Explaining Transitions from Neopartimonial Dicta-torships.” Comparative Politics 24 (4): 379–99.

SVOLIK, MILAN. 2012. The Politics of Authoritarian Rule. New York: CambridgeUniversity Press.

THEMNÉR, LOTTA, AND PETER WALLENSTEEN. 2014. “Armed Conflicts, 1946–2013.” Journal of Peace Research 51 (4): 541–54.

UNITED NATIONS CONFERENCE ON TRADE AND DEVELOPMENT (UNCTAD). 2006.FDI from Developing and Transition Economies: Implications for Development.New York: United Nations.

——. 2007. Transnational Corporations, Extractive Industries and Development.New York: United Nations.

——. 2015. World Investment Report: Reforming International Investment Gover-nance. New York: United Nations.

VERNON, RAYMOND. 1971. Sovereignty at Bay: The Multinational Spread of U.S.Enterprises. New York: Basic Books.

——. 1980. “The Obsolescing Bargain: A Key Factor in Political Risk.” InThe International Essays for Business Decision Makers, edited by Mark B.Winchester, 281–86. Houston, TX: Center for International Business.

WERTHMANN, KATJA. 2016. “The Lost Gold of Burkina Faso—A ParliamentaryInquiry Into the Mining Sector.” Resource Worlds, December 15. Ac-cessed November 15, 2017. http://resourceworlds.org/2016/12/15/the-lost-gold-of-burkina-faso-a-parliamentary-inquiry-into-the-mining-sector/.

WEST AFRICA NEWSLETTER. 2017. “Frank Timis Claims Up to $1.2 Billion forthe Loss of the Tambao Mine Contract.” West Africa Newsletter (763),November 2. Accessed November 15, 2017. http://bit.ly/2iWsiyt.

WILSON, MATTHEW CHARLES, AND JOSEPH WRIGHT. 2017. “Autocratic Legislaturesand Expropriation Risk.” British Journal of Political Science 47 (1): 1–17.

WRIGHT, JOSEPH. 2008. “Do Authoritarian Institutions Constrain? How Legis-latures Affect Economic Growth and Investment.” American Journal ofPolitical Science 52 (2): 322–43.

YANG, BENHUA. 2007. “Autocracy, Democracy, and FDI Inflows to the Devel-oping Countries.” International Economic Journal 21 (3): 419–39.

ZHU, BOLIANG. 2017. “MNCs, Rents, and Corruption: Evidence from China.”American Journal of Political Science 61 (1): 84–99.


http://dx.doi.org/10.2139/ssrn.2998123

http://fpif.org/manganese-burkina-fasos-new-resource-curse/

http://resourceworlds.org/2016/12/15/the-lost-gold-of-burkina-faso-a-parliamentary-inquiry-into-the-mining-sector/

http://bit.ly/2iWsiyt

monopoly rents and foreign direct investment in fixed assets

Documents