Resource nationalism: the intersection of politics and economics

The paper addresses why and when resource nationalism arises across heterogeneous resource-rich countries amid growing global demand for critical minerals. It situates resource nationalism within cycles of high mineral prices and geopolitical tensions, noting that governments intervene in rent distribution for political and economic gains. Despite the “resource curse” literature showing adverse growth effects of resource endowments, more than 200 national-level actions since 2000 suggest persistent incentives. The study proposes a transnational perspective using two-level (international–domestic) game theory to explain how international price shocks interact with domestic political economy to produce resource-nationalist policies. It posits three hypotheses: (1) rising global resource prices trigger resource nationalism; (2) domestic political games intrinsically drive such policies; (3) economic dependence on resource rents in host countries underpins resource nationalism.

The authors synthesize research on historical waves of resource nationalism (1960s–70s nationalizations; 2000s metals super-cycle), linkages to geopolitics and price cycles, and political-economic determinants (ideology, elections, fiscal dependence, corruption, governance). They note conflicting findings on ideology’s role (e.g., across Latin America vs. Bolivia’s social movements), and emphasize that contemporary resource nationalism often replaces expropriation with fiscal, ownership, export, and local content tools. The literature highlights resource curse mechanisms (institutional weakness, elite capture), cyclical patterns with commodity booms, and heterogeneous national trajectories (e.g., Indonesia vs. Bolivia). The authors frame resource nationalism as an outcome of multi-actor bargaining equilibria shaped by rents, political competition, and social movements, motivating their two-level game approach and cross-national quantitative test.

Conceptual framework: Two-level game theory models the government’s simultaneous bargaining with international resource firms over rents and with domestic interest groups over distribution and legitimacy. Rising global metal prices alter payoffs, prompting policy shifts toward resource nationalism when new domestic equilibria emerge.

Data construction: The authors assemble a global resource nationalism incident dataset drawing primarily from USGS Minerals Yearbook (International, Volume III), supplemented by ICMM/IUCN reports, academic papers, newspapers, government publications, and other sources. They define 35 event types in six dimensions (export controls; property rights uncertainty; operational interventions; geopolitical/permit constraints; fiscal/local content measures; environmental/social disruptions). A country-year is coded RN=1 if any listed event occurs. They track 83 countries (with at least one year of non-forest natural resource rents ≥5% of GDP during 2000–2019 per World Bank WDI), extract 1,494 texts, and identify 261 RN events (1990 onward). Macroeconomic, political, and social indicators come from WDI/Our World in Data; the globalization index from KOF.

Empirical strategy: Binary Choice Model (panel logit via MLE) with pooled, fixed, and random-effects specifications. Dependent variable RN_it ∈ {0,1}. Core regressors: global metal price index (metal.price); host-country political variables (rule of law, government effectiveness, democratization index, party ideology indicators, party rotation); economic conditions (lagged real GDP growth, national income level), and resource dependence (natural resource rents/GDP, its square; oil/ore/metal exports share). Interaction models examine politico-economic mechanisms (e.g., ideology × party change; ideology × government effectiveness; ideology × growth; ideology × resource rents). Robustness: (i) Restrict sample to countries with at least one RN event to test selection; (ii) Machine learning (XGBoost) variable importance on panel data with entity-level splits into training/test/validation to preserve independence, ranking predictors’ contributions.

Key variables summary (Table 2): RN mean 0.05; metal.price mean 0.65 (min 0.37, max 1.13); governance indicators (ROL mean −0.42; GE mean −0.31); resource dependence (RRT mean 0.11; MEOX mean 0.46).

• Rising metal prices are the primary trigger of RN events: The metal price index significantly and positively predicts RN incidence across logit models (Table 3), corroborated by ML importance ranking (Figure 4).
• Domestic political dynamics matter: The year after a party rotation exhibits elevated RN probability. However, an indicator for explicitly nationalist ruling parties (execnat) is not significant, implying tactical, game-driven behavior rather than fixed ideology.
• Governance effects are mixed: Stronger rule of law reduces RN likelihood, whereas higher government effectiveness increases it—efficient governments more readily capitalize on mineral price windfalls via flexible policy tools.
• Resource dependence drives RN: Higher natural resource rents (RRT) and its nonlinearity (RRT^2) indicate greater RN propensity in more resource-dependent economies, supporting Hypothesis 3.
• Economic context: Higher lagged real GDP growth is associated with more RN, consistent with RN as a strategy to capture excess rents during favorable conditions rather than a crisis tool.
• Politico-economic interactions: Left-wing parties are more inclined to introduce RN around elections and in high-effectiveness administrations; when large economic dividends are at stake, both left- and right-wing groups may converge on RN to gain political advantage (Table 4).
• Heterogeneity: RN probabilities are higher in low-income countries and regions central to mineral supply (Southeast Asia, South America, Sub-Saharan Africa), rising markedly during the 2000s super-cycle and retrenching post-2012 (Figures 2–3). Non-energy minerals show increasing RN likelihood compared to energy minerals; clean energy metals (lithium, cobalt, copper) exhibit notable increases after 2008.
• Robustness: Results persist when restricting to countries with recorded RN events (Table 5). XGBoost ranks metal price, government effectiveness, and GDP growth as top predictors, with rule of law and resource rents also influential (Figure 4).

Findings support a two-level game logic: international price booms expand producer surplus, reshaping domestic bargaining among governments, firms, and social groups and prompting RN to reallocate rents. RN is not purely zero-sum; while it reduces multinational firms’ windfall capture, repeated interactions and mobility of capital constrain outcomes toward equilibria where excess profits are still shared, albeit with altered splits. Contemporary RN tends toward “soft” instruments (taxes, royalties, equity stakes, export controls, local content) that leave space for negotiation. Strategically, international resource firms should anticipate RN during booms and hedge (e.g., strategic reserves, flexible contracting) to manage rent-sharing games. The study interprets RN as an attempt by resource-rich states to secure fairer gains from endowments amid an imbalanced global value chain where upstream suppliers bear environmental and social burdens while downstream centers capture higher value. Thus, RN also expresses resistance to structural inequities in the world trading system and aspirations for industrial upgrading and greater domestic spillovers.

The study advances a transnational, two-level game explanation for contemporary resource nationalism and constructs a novel global dataset of RN events. Empirically, it validates three hypotheses: (1) global metal price increases are the main trigger; (2) domestic political games intrinsically drive policy choices; (3) economic dependence on resource rents underlies RN incidence. Governance quality shapes RN directionally—rule of law dampens while government effectiveness amplifies RN—and left–right dynamics interact with elections and administrative capacity. Spatially, RN concentrates in lower-income, resource-dependent regions and intensified during the early-2000s super-cycle, especially for clean-energy metals. Policy implications include preparing for cyclical RN through strategic reserves and negotiated rent-sharing, and pursuing more resilient global resource governance that balances development goals with supply chain stability. Future work can refine and expand standardized RN event tracking, enhance early-warning systems linking price signals to political economy indicators, and assess long-run welfare and investment impacts of specific RN instruments.

• Data constraints: No pre-existing standardized global database for RN; events compiled from diverse sources (USGS Minerals Yearbook, industry associations, academic and government reports) with text-based extraction may introduce measurement and classification challenges.
• Scope and coding: Broad 35-category event definition (ranging from expropriation to minor tax changes or CSR demands) may conflate heterogeneous policy intensities within a single RN indicator (RN=1), obscuring gradations of intervention.
• Sample selection: Country coverage focuses on those with ≥5% resource rents (non-forest) of GDP (2000–2019), potentially limiting generalizability to less resource-dependent states.
• Heterogeneity: Cross-country differences in institutions, extractive histories, and ideology complicate identification of a single optimal strategy; some effects may be context-specific.
• Model limitations: Use of aggregate metal price index and annual country-year panels may miss commodity- or project-level dynamics and within-year policy shifts.