## sgcecea ## Source details **Canonical URL:** [sgcecea](https://www.imf.org/-/media/files/publications/dp/2026/english/sgcecea.pdf) ## Other formats - [Markdown version](/-/media/files/publications/dp/2026/english/sgcecea.pdf.md) - [Structured JSON version](/-/media/files/publications/dp/2026/english/sgcecea.pdf.json) --- ### Executive summary — overview and context - Heightened global uncertainty, geoeconomic fragmentation, and trade tensions increase the importance of deepening economic ties to boost growth and resilience. - Focus: cross-cutting policies to expand and diversify trade and investment between the Gulf Cooperation Council (GCC) and the Caucasus and Central Asia (CCA). - Composition: - CCA: Armenia, Azerbaijan, Georgia, Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. - GCC: Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE. - Recent high-level engagement examples: summit between GCC and five Central Asian countries (July 2023); GCC and CA Foreign Ministers meeting (April 2024); GCC and CA Foreign Ministers met in Kuwait (April 2025); Azerbaijan–GCC economic forum (September 2024); bilateral meetings with Georgia and Armenia (May and June 2025). ### Key findings on trade structure and complementarities - Trade openness: GCC and CCA have higher trade openness than EMDEs and AEs. - Comparative advantages: hydrocarbons and other natural resources remain important; both regions show gradual reduction in hydrocarbons’ export share reflecting diversification. - Non-hydrocarbon trade: growing and relatively well diversified in both regions; GCC typically more diversified than CCA in non-hydrocarbon trade. - Complementarities: - Emerging bilateral investment activities. - Typical pattern: GCC exports capital while CCA imports capital. ### Trade- and investment-enabling environment — comparative strengths and weaknesses - GCC strengths relative to CCA: - Infrastructure and logistics. - Aggregate trade restrictions. - Governance. - Regulatory burden. - Product market policies. - Cross-border payment (XBP) systems. - CCA relative strengths: - Fewer nontariff measures (NTMs). - Lower state footprint in the economy. - Both regions: perform well in bilateral investment agreements but lag in trade agreements. ### Quantified potential impact of policy improvements on trade - Closing policy gaps to the level of the top 25 percent of global performers: - Logistics: could boost CCA trade in goods by about 150 percent. - Governance: could boost CCA trade in goods by about 120 percent. - Reducing CCA tariffs, aggregate trade restrictions, and regulatory burden would also enhance trade substantially. - GCC policy gaps smaller; closing them yields lower but still material gains (governance, logistics, regulatory burden). - Comparable magnitudes apply to trade in services when closing policy gaps. ### FDI: gains from structural reform - Comprehensive structural reform areas: institutional quality, trade liberalization, labor and product market reforms, financial sector development, human and physical capital. - Estimated FDI gains from closing policy gaps to the 25th percentile: - CCA: 0.7 percent of GDP. - GCC: 0.14 percent of GDP. - Larger CCA gains reflect larger policy gaps. - Investment treaties would help reduce binding constraints for private-sector FDI. ### Caution on complementary measures (SEZs, subsidies, PPPs, insurance) - SEZs, targeted subsidies, insurance schemes, and PPPs can help in limited circumstances; success mixed and bar high. - SEZ design principles: - Resolve a market failure better than alternatives. - Be time-bound, cost-effective, transparent. - Preserve macroeconomic stability, fiscal and external sustainability, and avoid negative cross-border spillovers. - Complement, not substitute for, broader structural reforms. ### Cross-border payments (XBPs): priorities and heterogeneity - XBPs are interdependent with trade and FDI; enhancements especially needed in the CCA. - G20 road map three priority themes: 1. Payment system interoperability and extension. 2. Legal, regulatory, and supervisory frameworks. 3. Data exchange and message standards. - Heterogeneity across countries implies tailored solutions. ### Cross-cutting policy recommendations - Improve governance, human capital, business environment, and FDI attractiveness aligned with national strategies. - Reduce tariffs, NTMs, and trade and exchange restrictions. - Liberalize product and labor markets and deepen the financial sector. - Expand trade agreements and consider bilateral investment treaties. - Improve infrastructure, logistics, and XBPs, prioritizing the CCA. - Use SEZs, subsidies, PPPs, insurance selectively and only when addressing clear market failures. *Source: Executive Summary, IMF Departmental Paper — Strengthening GCC–CCA Economic Cooperation.* --- ### 2. Current state of economic ties — trade in goods and services - Trade openness: higher in GCC and CCA than in EMDEs and AEs. - Goods dominate trade; services importance rising, notably in GCC where services account for almost one-third of non-hydrocarbon trade. - Excluding hydrocarbons, imports-to-non-hydrocarbon-GDP share higher in GCC and to a lesser extent CCA. - Comparative advantage highlights: - Both: minerals and fuels, stones and metals, basic manufacturing. - CCA: close to comparative advantage in textiles and agriculture. - GCC: near comparative advantage in chemicals and plastics. - Services: both have comparative advantage in transport, travel, and construction; GCC also in insurance and pension, government, and personal/cultural/recreational; CCA in telecommunication, computer, and information services. - Diversification and concentration: - Non-hydrocarbon trade relatively well diversified; GCC typically more diversified than CCA. - Herfindahl–Hirschman Index used (index ranges between 0 and 1). - GCC–CCA bilateral trade shares and hubs: - GCC (CCA) non-hydrocarbon goods exports to CCA (GCC) generally low; exception: 2023 CCA exports to GCC reached almost 4 percent of total exports due to stones, metals, and basic manufactures. - GCC exports to CCA increased significantly in 2022. - Services: GCC exports to CCA at 1 percent; CCA services exports to GCC close to 7 percent (mostly travel and transportation). - 2010–23: UAE accounted for close to 96 percent of GCC goods exports to CCA and 63 percent of GCC services exports to CCA; UAE accounted for close to 90 percent of GCC goods imports from CCA and 40 percent of GCC services imports from CCA. - UAE functions as transportation and trade hub; has signed CEPAs including with Georgia (2023, in force), and more recently with Azerbaijan and the Eurasian Economic Union. - Intra-regional goods exports as percent of total exports: - CCA: 8.9 percent. - GCC: 15 percent. - Comparators: ASEAN 23.6 percent; Europe 59 percent; MERCOSUR 13 percent; Central American Common Market 12.1 percent. ### 2. Current state — capital and financial flows - External investment dynamics: - GCC: current account surpluses; net provider of financing. - CCA: net recipient of financial flows, largely reflecting sustained FDI inflows. - GCC external investment composition: - Most outward investment are portfolio or other investments. - Sovereign wealth funds (SWFs) account for over 80 percent of total outward investment from the GCC. - Saudi Arabia and the UAE lead GCC outflows. - FDI inflows and trends: - FDI inflows to CCA dominated inward flows but declined after COVID-19; offset partially by deposits and external loans. - Realized FDI inflows 2019–23: GCC and CCA lag broader emerging market (EM) average. - Within GCC: Oman, Bahrain, and the UAE over-performed vs EMs; other GCC countries underperformed. - Within CCA: Georgia attracted inflows well above EMs during 2019–23; Uzbekistan, Turkmenistan, Kazakhstan, and Armenia below EMs. - Sectoral composition: - GCC inward FDI shifted from hydrocarbons to transportation and other services since early 2000s. - GCC outward FDI (led by SWFs): transportation, communication, manufacturing; increasing focus on renewable energy. - CCA FDI shifted from Kazakhstan-dominated resource investments to diversified landscape: Uzbekistan major destination (reforms, digital and energy projects); intra-regional investment among Kazakhstan, Uzbekistan, Azerbaijan increased. - GCC–CCA cross-border investment magnitudes: - GCC investment stock in CCA: accounts for 0.5 percent of the CCA’s GDP and 0.5 percent of total GCC FDI outflows during 2015–23. - GCC FDI inflows and commitments to CCA show diversification toward renewables, construction, and services (examples: Armenia renewables; Uzbekistan renewables and services; Kazakhstan construction and manufacturing). - CCA investments in GCC are very small (examples: Kazakhstan SWF investments; Azerbaijan SOCAR investments; private real estate investments from Kazakhstan, Azerbaijan, Uzbekistan). - Announced vs realized GCC investments in CCA (2015–23): data by activity (Renewables, Construction, Services, Manufacturing) reported in US$ million. --- ### 3. Trade and investment enabling environment — tariffs, NTMs, logistics, governance - Tariff patterns (2023): - Average tariff on CCA’s imports from the GCC: 4.5 percent. - Average tariff on CCA’s imports from AEs: 4.0 percent. - Average tariff on GCC imports from the CCA and AEs: 4.3 percent. - Average tariff on GCC imports from EMDEs: 3.4 percent. - NTMs: - NTMs more prevalent on imports; include SPS, TBTs, pre-shipment measures, quantity controls, price controls, finance measures, competition measures, trade-related investment measures. - Number of NTMs higher in GCC than CCA; high number of price-control measures in Bahrain, Oman, Qatar. - Impact of NTMs (AVEs) broadly similar across GCC, CCA, EMDEs—possibly due to better facilitation in GCC reducing enforcement cost. - Empirical AVE findings cited: - NTMs account for 70 percent of trade restrictiveness in 91 countries (Kee, Nicita, Olarreaga 2006). - AVEs of SPS on agricultural products range from 5 to 18 percent; AVEs of TBT on manufactured products range from 1.5 to 30 percent (Cadot, Gourdon, van Tongeren 2017). - Kravchenko and others (2022): average AVE 7.2 percent for technical measures and 6.1 percent for nontechnical measures. - Nicita and Koloskova (2025): AVEs range from less than 1 percent (construction, utilities, fossil fuels, mining) to 6–16 percent (food, forestry); regional AVEs range from 0.3 percent in Western Europe to 13.7 percent for Latin American and sub-Saharan exporters. - Logistics and trade facilitation: - Logistics Performance Index (LPI): GCC comparable to AEs; CCA closer to EMDE median with less variability. - Multimodal corridors under development: East–West Middle Corridor, North–South Corridor. - Azerbaijan, Kazakhstan, Kyrgyz Republic, Uzbekistan, and Türkiye ratified agreement to create a simplified customs corridor. - Policy priorities: streamline procedures, digitalize, harmonize standards, improve border agency cooperation. - Exchange, payments, trade restrictions: - CCA: significant aggregate trade payment restrictions (currency prescriptions, import financing requirements, import/export licenses, repatriation controls). - GCC: liberalized payment frameworks comparable to AEs. - Within CCA: Georgia liberalized; Turkmenistan highest number of restrictions. - Invisible transactions restrictions notable in several CCA countries. - Governance and regulatory burden: - CCA governance (average WGI) below EMDEs. - GCC and CCA perform well on regulatory burden (1 = burdensome to 7 = not burdensome scale). - Improving governance, especially in CCA, would support more trade and FDI. - Financial regulations, labor, product markets: - Financial regulations (2018–22): CCA generally perform well on net credit to private sector, interest rate controls, bank ownership, foreign currency accounts. - GCC: more developed financing sectors but retain interest rate controls for consumer and SME lending; better on foreign currency account openness. - Labor market (2018–22): GCC and CCA score broadly in line with AEs; GCC adopting measures to integrate nationals into private sector. - Product markets: GCC and CCA lag AEs and some EMs; GCC scores higher on protection of foreign assets, property rights, regulatory burden, bureaucratic costs; some CCA countries lag in impartial public administration and contract enforcement. - Trade policy and state footprint: - Both regions advanced performance over EMs on a trade policy index; lag AEs mainly due to capital account restrictions. - State footprint (2018–22): GCC score below EM and AE averages (higher state presence and SOEs); CCA score higher than EMs and AEs (lower state footprint); Armenia, Kazakhstan, Georgia score well above EM and AE averages. - Trade and investment agreements: all GCC and most CCA members (except Azerbaijan, Turkmenistan, Uzbekistan) are WTO members; both regions lag AEs in number of bilateral trade agreements (exceptions: Georgia, Armenia) but similar in bilateral investment agreements. --- ### Quantified policy impacts — gravity model and elasticities - Gravity model: bilateral and domestic trade for more than 150 countries, 2010–23; PPML estimation. - Key elasticities and model findings: - Trade agreements associated with an 80 percent increase in bilateral trade overall. - By sector: 128 percent in food products, 76 percent in mining, 63 percent in manufacturing. - Controlling for tariffs: signing a trade agreement associated with a 45 percent increase in trade. - Tariffs and NTMs reduce trade: - A 10 percent reduction in tariffs associated with a 5 percent increase in trade. - A 10 percent decline in the number of border NTMs improves trade by 0.3 percent. - Institutional and infrastructure improvements: - A 10 percent increase in logistics associated with a 48 percent increase in trade. - Improvements in governance associated with a 19 percent increase in trade. - A 10 percent reduction in regulatory burden associated with a 10 percent increase in trade. - A 10 percent reduction in aggregate trade restrictions associated with a 10 percent increase in trade. - Composite institutional indicator: improvement associated with an almost 1.7 percent increase in trade. - Regional potentials: - Intra-GCC and intra-CCA trade may be close to gravity-predicted potential. - Trade between GCC and CCA typically well below potential, suggesting scope to increase bilateral trade significantly. - GCC and CCA trade with China broadly at potential; CCA trade with Russia above potential; GCC trade with Russia below potential. - GCC trade with US at potential; CCA trade with US below potential. - Trade with EU and rest of world below potential for both regions. --- ### Policy simulation results — selected 10 percent changes and gap closures - Logistics LPI benchmark: 25th percentile of top performers has LPI = 3.4; GCC average = 3.3; CCA average = 2.5. - CCA-specific impacts from closing policy gaps to 25th percentile: - Closing logistics gap: improve trade by about 148 percent. - Closing governance gap: improve trade by about 122 percent. - Reductions in tariffs: boost trade by around 50 percent. - Reductions in aggregate trade restrictions (reflecting lower regulatory burdens): boost trade by around 6 percent. - GCC-specific impacts from closing policy gaps: - Reducing tariffs GCC exporters face: increase trade by about 58 percent. - Closing governance, logistics, regulatory burden gaps: lift trade by 15 to 30 percent. - Trade in services elasticities and impacts: - Trade agreements associated with a 45 percent increase in bilateral trade in services. - A 10 percent improvement in logistics associated with a 30 percent increase in trade in services. - A 10 percent improvement in governance or reduction in regulatory burden associated with a 15 percent increase in trade in services. - A 10 percent reduction in aggregate trade restrictions associated with a 7 percent increase in trade in services. - Overall, a 10 percent improvement in institutional quality associated with an almost 13 percent increase in trade in services. - CCA services impacts from closing gaps: - Closing logistics gap: improve trade in services by about 102 percent. - Closing governance gap: improve trade in services by about 93 percent. - Reducing regulatory burden and aggregate trade restrictions: boost trade in services by more than 40 percent. - GCC services impacts: - Improving governance and logistics associated with about 20 and 10 percent increases in trade in services, respectively. --- ### FDI model findings, drivers, and policy implications - Empirical approach: random-effects panel regressions for 86 economies, 2000–22. - Macroeconomic drivers: - A 1-percentage-point increase in GDP growth associated with an increase in FDI inflows of approximately 0.2 percent of GDP. - A 1-percentage-point increase in trade openness associated with about a 0.1 percent of GDP increase in FDI inflows. - Foreign GDP growth (US proxy) negatively associated with FDI inflows in many specifications. - Structural drivers: - FDIAI (FDI attractiveness index) positive and significantly associated with FDI inflows at the global level. - Smaller state footprint typically associated with higher FDI inflows globally and in CCA; in GCC the relationship reverses (FDI increases with larger state footprint). - Regional distinctions: - CCA: FDI driven by domestic growth and natural resources; product market efficiency matters; financial development and institutional quality show weak effects in some specifications. - GCC: FDI less driven by domestic growth; more linked to state-led initiatives and government projects. - Estimated FDI gains from closing structural policy gaps to 25th percentile: - CCA: FDI gains of 0.7 percent of GDP. - GCC: FDI gains of 0.14 percent of GDP. - Policy implications: - Strengthen FDI frameworks in CCA to attract capital from GCC (net capital exporters) and leverage GCC SWFs and private investors. - Coordinated structural reforms across institutional quality, trade liberalization, labor/product markets, financial sector, human and physical capital recommended. --- ### SEZs, XBPs, and cross-border payments — operational lessons and statistics - SEZs: - Mixed results for promoting GVCs, industrialization, and FDI (UNCTAD 2019). - Success factors: governance effectiveness, infrastructure quality, proximity to port, human capital availability (EBRD 2024). - Pitfalls: high fiscal costs, governance issues, harm to trading partners, breaches to international commitments, rent seeking, corruption. - GCC has several SEZs (UAE with higher number); GCC SEZs slightly larger and more logistics-focused; CCA SEZs more multi-activity. - Policy guidance: justify SEZs only if they resolve market failures better than alternatives; ensure time-bound incentives, cost-effectiveness, transparency, and mitigation of rent seeking. - Cross-border payments (XBPs) — role and frictions: - XBPs can take several days and cost up to 10 times more than domestic payments. - Number of correspondent banks fell by more than one-fifth between 2011 and 2022. - In GCC and CCA, all countries except Georgia saw a decline in number of counterparties abroad despite rising transaction volumes. - Fundamental XBP steps: validation, transmission, funding. - Common frictions: fragmented data formats; complex compliance checks; limited operating hours; legacy technology; high funding costs; weak competition. - More efficient arrangements: - Alternatives to correspondent banking: bilateral interlinking of domestic payment infrastructures (RTGS, fast payment systems), multi-jurisdictional platforms enabling direct PSP transactions. - Regional XBP innovations — facts: - AFAQ Gulf payment system: - Live: 2021 (Saudi Arabia and Bahrain); Kuwait joined 2022; UAE 2023; Oman 2024. - Values of transfer and financial settlements rose by 300 and 270 percent, respectively, in 2023 and 2024. - Buna platform: - Council decision 2018; went live 2020. - Transactions grew from less than 2,000 in 2022 to more than 110,000 in 2024. - Total value neared US$ 3.2 billion in 2024. - Participation: more than 15 countries and 100 institutions. - CBDC exploration status: - Bahrain, Georgia, Saudi Arabia, and UAE at advanced “proof-of-concept” stage. - Kazakhstan completed two pilot programs. - Policy recommendations for XBPs: - Use G20 road map themes: interoperability/extension; legal/regulatory/supervisory frameworks; data exchange and message standards. - For less advanced systems: modernize and digitalize domestic systems; analyze correspondent banking issues. - For advanced systems: consider interlinking or shared systems and CBDCs where prerequisites exist. - Leverage IMF and World Bank technical assistance. --- ### Conclusions and prioritized policy actions - Overall potential: significant scope to scale up trade and FDI between GCC and CCA with appropriate policies; reforms must be tailored to country heterogeneity. - Trade priorities: - CCA: prioritize logistics and governance improvements; reduce aggregate trade restrictions and regulatory burdens. - Both regions: tariff reductions, trade agreements, and NTM review; improve trade facilitation via simplified procedures, digitalization, harmonized standards, border agency cooperation. - FDI and structural reforms: - Implement coordinated reforms across institutional quality, trade liberalization, labor/product markets, financial sector, and human/physical capital. - GCC: strategic infrastructure upgrades; targeted interventions and partnerships to de-risk investments while deepening private sector participation. - CCA: address infrastructure gaps; strengthen rule of law to encourage private investment into non-hydrocarbon sectors. - Agreements and institutional tools: - Pursue trade and investment agreements consistent with WTO and existing regional arrangements (Eurasian Economic Union, GCC Customs Union). - Use SEZs, subsidies, PPPs, insurance selectively; ensure time-bounded, transparent, and market-failure–solving design. - De-risking support from international and regional financial institutions recommended to mitigate FDI risks. - Operational priorities for XBPs: - Prioritize interoperability, legal/regulatory frameworks, and data/message standardization per G20 road map. - Modernize domestic payment systems, analyze correspondent banking, consider interlinking and CBDCs where appropriate, and seek IMF/World Bank technical assistance. *Source: IMF staff calculations; IMF DEPARTMENTAL PAPERS • Strengthening GCC–CCA Economic Cooperation.* ### Executive Summary.................................................................................................v ### Executive Summary ### Overview and context - Heightened global uncertainty, geoeconomic fragmentation, and trade tensions increase the importance of deepening economic ties to boost growth and resilience. - The paper focuses on cross-cutting policies to expand and diversify trade and investment between the Gulf Cooperation Council (GCC) and the Caucasus and Central Asia (CCA). - The Caucasus and Central Asia (CCA) comprises Armenia, Azerbaijan, Georgia, Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. The Gulf Cooperation Council (GCC) comprises Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE. - Recent high-level engagement examples: a summit between GCC and five Central Asian countries in July 2023; a high-level meeting of GCC and CA Foreign Ministers in April 2024; GCC and CA Foreign Ministers met in Kuwait in April 2025; an economic forum between Azerbaijan and the GCC in September 2024; high-level bilateral meetings between the GCC and Georgia and Armenia in May and June 2025, respectively. ### Key findings on trade structure and complementarities - The GCC and the CCA exhibit high trade openness and an important comparative advantage in hydrocarbons and other natural resources. - There has been a gradual reduction in the share of hydrocarbons in exports for both the GCC and the CCA, reflecting ongoing diversification policies. - The growing non-hydrocarbon trade (goods and services) of both regions is relatively well diversified. - Complementarities that could be leveraged include: - Emerging signs of bilateral investment activities. - Typical pattern of GCC exporting capital while the CCA imports capital. ### Trade- and investment-enabling environment: comparative strengths and weaknesses - The trade- and investment-enabling environment in the GCC is typically better than in the CCA on: - Infrastructure and logistics. - Aggregate trade restrictions. - Governance. - Regulatory burden. - Product market policies. - Cross-border payment (XBP) systems. - The CCA performs better in: - Having fewer nontariff measures (NTMs). - Having a lower state footprint in the economy. - Both regions perform well in bilateral investment agreements but lag in trade agreements. ### Quantified potential impact of policy improvements on trade - Improving policies to the level of top 25 percent of global performers in: - Logistics could boost CCA trade in goods by about 150 percent. - Governance could boost CCA trade in goods by about 120 percent. - Reducing CCA tariffs, aggregate trade restrictions, and regulatory burden would also enhance trade substantially. - GCC countries have generally smaller policy gaps; closing those gaps would yield lower but still material gains, notably in governance, logistics, and regulatory burden reduction. - Similar magnitudes of impact apply to trade in services when closing policy gaps. ### Foreign direct investment (FDI): gains from structural reform - A comprehensive structural reform strategy covering institutional quality, trade liberalization, labor and product market reforms, financial sector development, and human and physical capital improvement can boost FDI inflows to both regions. - Estimated FDI gains from closing the policy gaps: - CCA: 0.7 percent of GDP. - GCC: 0.14 percent of GDP. - Larger gains in the CCA reflect larger policy gaps in structural areas. - Investment treaties would help reduce binding constraints faced by private sector players undertaking FDI. ### Caution on complementary measures (SEZs, subsidies, PPPs, insurance) - Special economic zones (SEZs), targeted subsidies, insurance schemes, and public–private partnerships (PPPs) could help in limited circumstances, but success is mixed and the bar to get it right is high. - SEZs should: - Resolve a market failure better than alternatives. - Be time-bound, cost-effective, transparent. - Be consistent with preserving domestic macroeconomic stability, fiscal and external sustainability, and avoiding negative cross-border spillovers. - Complement broader structural reform efforts and not substitute for them. ### Cross-border payments (XBPs): priorities and heterogeneity - XBPs are important for facilitating trade and investment and are interdependent with trade and FDI. - Efforts are required to enhance XBPs, especially in the CCA. - The G20 road map on XBPs provides three priority themes to guide enhancements: 1. Payment system interoperability and extension. 2. Legal, regulatory, and supervisory frameworks. 3. Data exchange and message standards. - Heterogeneity of XBP systems across GCC and CCA countries implies that solutions must be tailored to country-specific circumstances. ### Policy recommendations (cross-cutting) - Improve governance, human capital, business environment, and FDI attractiveness, consistent with national development strategies. - Reduce tariffs, nontariff measures (NTMs), and trade and exchange restrictions. - Liberalize product and labor markets and deepen the financial sector. - Expand trade agreements and consider bilateral investment treaties to lift trade impediments and reduce investment constraints. - Improve infrastructure, logistics, and cross-border payment systems, with priority on the CCA where gaps are larger. - Use complementary tools (SEZs, subsidies, PPPs, insurance) selectively and only where they address clear market failures and conform to transparency and sustainability principles. *Source: Executive Summary, IMF Departmental Paper — Strengthening GCC–CCA Economic Cooperation.* ### 2. Current State of Economic Ties ### 2. Current State of Economic Ties ### A. Trade in Goods and Services - Trade openness (exports + imports of goods and services to GDP) is higher in the GCC and the CCA than in emerging market and developing economies (EMDEs) and advanced economies (AEs). - Goods account for most trade; services' importance has increased, especially in the GCC where services account for almost one-third of non-hydrocarbon trade. - Excluding hydrocarbons, the share of imports to non-hydrocarbon GDP is significantly higher in the GCC, and to a lesser extent the CCA, reflecting limited albeit improving diversification. - Export structure and comparative advantage: - Both regions have comparative advantage in minerals and fuels (hydrocarbons), stones and metals, and basic manufacturing. - The share of minerals and fuels in exports has gradually reduced for both regions. - CCA is relatively close to having a comparative advantage in textiles and agriculture. - GCC almost has a comparative advantage in chemicals and plastics. - Services exports are diversified; both regions have comparative advantages in transport, travel, and construction services. - GCC comparative advantages also include insurance and pension; government; and personal, cultural, and recreational services. - CCA comparative advantage includes telecommunication, computer, and information services. - Diversification and concentration: - Non-hydrocarbon trade in both regions is relatively well diversified; GCC is typically more diversified than the CCA in non-hydrocarbon trade. - CCA diversification is generally in line with EMDEs; GCC diversification is comparable to AEs except for non-hydrocarbon product exports. - For both regions, market concentration is lower than product concentration. - The Herfindahl–Hirschman Index is used (index ranges between 0 and 1). - GCC–CCA bilateral trade shares and hubs: - The share of GCC (CCA) non-hydrocarbon goods exports to the CCA (GCC) is relatively low, except in 2023 when CCA exports to the GCC reached almost 4 percent of its total exports due to a sharp increase in stones, metals, and basic manufactures. - GCC exports to the CCA increased significantly in 2022. - For services trade, GCC’s exports to the CCA are low at 1 percent; CCA’s services exports to the GCC are close to 7 percent (mostly travel and transportation services). - Over 2010–23, the UAE accounted for close to 96 (63) percent of GCC goods (services) exports to the CCA. - Over 2010–23, the UAE accounted for close to 90 (40) percent of GCC goods (services) imports from the CCA. - The UAE functions as a transportation and trade hub and has signed CEPAs including with Georgia (2023, in force), and more recently with Azerbaijan and the Eurasian Economic Union. - Scope to expand intra-regional trade: - Intra-regional goods exports as percent of total exports: CCA 8.9 percent; GCC 15 percent. - Comparators: Association of Southeast Asian Nations 23.6 percent; Europe 59 percent; MERCOSUR 13 percent; Central American Common Market 12.1 percent. - Import structure by region: - GCC non-hydrocarbon imports by region and CCA non-hydrocarbon imports by region show patterns across product categories (Agriculture and food products; Chemicals and plastics; Leather and hides; Wood and paper products; Textiles, footwear, and accessories; Stone, metals, and basic manufactures; Machinery and electronics; Transport and precision equipment; Arms, furniture, toys, and miscellaneous). - Services imports by region for GCC and CCA cover Manufacturing services, Maintenance, Transport, Travel, Construction, Insurance and pension, Financial, Intellectual property, Telecom/computer/info, Other business services, Personal/cultural/recreational, Government. ### B. Capital and Financial Flows - Complementary external investment dynamics: - GCC typically registers current account surpluses and is a net provider of financing to the rest of the world. - CCA is a net recipient of financial flows, largely reflecting sustained FDI inflows. - Composition and drivers of GCC external investment: - Most GCC investments abroad are portfolio investments or other investments. - Sovereign wealth funds (SWFs) account for over 80 percent of total outward investment from the GCC. - Saudi Arabia and the UAE lead GCC outflows; overall pattern of FDI outflows in other GCC countries resembles regional trends. - FDI inflows and recent trends: - FDI inflows to the CCA dominated inward flows but declined after the COVID-19 pandemic; decline was partially offset by an increase in other investment flows in the form of deposits and external loans. - Realized FDI inflows 2019–23: GCC and CCA overall lagged the broader emerging market (EM) average. - Within GCC, Oman, Bahrain, and the UAE over-performed compared to EMs; other GCC countries significantly underperformed. - Within CCA, Georgia attracted inflows well above EMs during 2019–23; Uzbekistan, Turkmenistan, Kazakhstan, and Armenia reported inflows well below EMs. - Sectoral composition and evolution: - GCC inward FDI historically skewed to hydrocarbon but shifted since early 2000s toward transportation and other services and away from financial services (deal-level information). - GCC outward FDI (led by SWFs) is primarily directed to transportation, communication, and manufacturing, with growing focus on renewable energy and new emerging markets. - CCA FDI shifted from resource-driven investments dominated by Kazakhstan to a more diversified and regionally balanced landscape: - Uzbekistan emerged as a major destination due to reforms and large-scale digital and energy projects. - Intra-regional investment surged among Kazakhstan, Uzbekistan, and Azerbaijan. - Region shifting toward diversification, renewable energy, and digital sectors. - GCC–CCA cross-border investment magnitudes and patterns: - GCC investment stock in the CCA accounts for 0.5 percent of the CCA’s GDP and represents 0.5 percent of the total stock of FDI outflows from the GCC during 2015–23. - GCC FDI inflows and investment commitments to CCA countries show diversification with increasing focus on renewable energy, construction, and services—especially in Armenia (renewable energy), Uzbekistan (renewable energy and services), and Kazakhstan (construction and manufacturing). - CCA investments in the GCC exist but are very small; examples include: - Kazakhstan’s SWF investments in energy, infrastructure, and banking sectors in the GCC. - Azerbaijan’s State Oil Company (SOCAR) investments in oil exploration and refining partnerships. - Private investors from Kazakhstan, Azerbaijan, and Uzbekistan making real estate investments in the GCC. - Announced versus realized GCC investments in the CCA (2015–23): - Announced and realized cumulative GCC investments by economic activity include Renewables, Construction, Services, Manufacturing (US$ million). - Announced and realized GCC investments show year-by-year flows from 2015 through 2023 (US$ million). *Source: sgcecea - 2. Current State of Economic Ties.* ### 3. Trade and Investment Enabling Environment ### 3. Trade and Investment Enabling Environment ### Tariffs and Nontariff Measures (NTMs) - Tariff patterns (2023): - Average tariff on CCA’s imports from the GCC: 4.5 percent. - Average tariff on CCA’s imports from AEs: 4.0 percent. - Average tariff on GCC imports from the CCA and AEs: 4.3 percent. - Average tariff on GCC imports from EMDEs: 3.4 percent. - Intra-regional tariffs are low in the GCC due to the customs union; applied tariffs on agricultural, textile, and footwear products remain much higher than on other goods. - NTMs overview: - NTMs are more prevalent on imports than on exports and include SPS measures, TBTs, pre-shipment measures, quantity controls, price controls, finance measures, competition measures, and trade-related investment measures. - The number of NTMs is higher in the GCC than in the CCA (Figure 10), including a high number of price-control measures in Bahrain, Oman, and Qatar for customs inspection, processing, servicing fees, merchandise-handling or storage fees, and import license fees. - Although the GCC records more NTMs, their impact on trade (as measured by AVEs) is broadly similar to that in the CCA and EMDEs (Figure 11), possibly because better trade facilitation in the GCC reduces the cost of enforcing NTMs. - Empirical findings on AVEs and NTMs (from the literature cited): - NTMs account for 70 percent of the trade restrictiveness of policies in 91 developing and developed countries (Kee, Nicita, and Olarreaga 2006). - AVEs of SPS on agricultural products range from 5 to 18 percent; AVEs of TBT on manufactured products range from 1.5 to 30 percent (Cadot, Gourdon, and van Tongeren 2017). - Kravchenko and others (2022) find average AVEs of 7.2 percent for technical measures (SPS, TBTs, pre-shipment inspection) and 6.1 percent for nontechnical measures. - Nicita and Koloskova (2025) report AVEs ranging from less than 1 percent on construction, utilities, fossil fuels, and mining products to 6 to 16 percent on food and forestry products, and AVEs from 0.3 percent in Western Europe to 13.7 percent for Latin American and sub-Saharan exporters. ### Logistics, Infrastructure, and Trade Facilitation - Logistics Performance Index (LPI): - GCC performs at a level comparable to AEs on the World Bank LPI (scale 1 = low to 5 = high). - CCA countries are closer to the EMDE median and show much less variability within the region. - LPI subindicators include tracking and tracing, logistics competence and quality, ease of arranging competitively priced international shipments, efficiency of clearance process, timeliness of shipments, and quality of trade and transport-related infrastructure. - Connectivity projects and corridors: - CCA and partners are developing multimodal transport infrastructure, including the East–West Middle Corridor and the North–South Corridor. - Azerbaijan, Kazakhstan, the Kyrgyz Republic, Uzbekistan, and Türkiye have ratified an agreement to create a simplified customs corridor. - Policy priorities to enhance trade facilitation: - Streamline procedures and enhance digitalization. - Harmonize standards and improve border agency cooperation. ### Exchange, Payments, and Trade Restrictions - Aggregate trade payment restrictions: - CCA countries typically have significant aggregate trade payment restrictions (Figure 13), including prescriptions on currency requirements, financing requirements for imports, import licenses, repatriation of export proceeds, export licenses, and controls on trade and investment payments. - Payments, exchanges, and transfers in the GCC are facilitated by a liberalized policy framework comparable to AEs. - Within the CCA there is wide variation: Georgia has a liberalized framework, whereas Turkmenistan has the highest number of restrictions in the region. - Invisible transactions (services, income, transfers) are an important area of restrictions in several CCA countries. ### Governance, Regulatory Burden, and Institutional Quality - Governance: - CCA governance (average of World Bank Governance Indicators for government effectiveness, regulatory quality, rule of law, control of corruption) is below that of EMDEs. - GCC and CCA both perform well on regulatory burden (Figure 15). - Regulatory burden (2022): - Measured on a 1 = burdensome to 7 = not burdensome scale; both GCC and CCA record favorable scores relative to EMDEs. - Implication: - Improving governance would benefit all countries and support more trade and FDI, especially in the CCA where governance lags. ### Financial Regulations, Labor Markets, and Product Markets - Financial regulations (average 2018–22): - CCA countries generally perform well on measures capturing net credit to the private sector, interest rate controls, bank ownership, and foreign currency bank accounts. - GCC countries have more developed financing sectors but retain significant interest rate controls, especially for consumer and SME lending. - GCC performs better on foreign currency account openness due to globally integrated financial systems. - Labor market (average 2018–22): - GCC and CCA labor market regulatory frameworks score broadly in line with AEs and outperform EMs on the index that incorporates minimum wage policies, hiring and firing regulations, centralized wage determination, and human capital indicators. - GCC countries are adopting measures to integrate nationals into the private sector while maintaining labor market flexibility. - Product markets (average 2018–22): - GCC and CCA lag AEs and some EMs on the product market index, which captures impartial public administration, bureaucracy costs, regulatory burden, protection of foreign assets, property rights, business environment, and contract enforcement. - GCC scores higher on protection of foreign assets, property rights, regulatory burden, and bureaucratic costs; some CCA countries lag in public sector impartiality and contract enforcement. ### Trade Policy, State Footprint, and Investment Agreements - Trade liberalization: - Trade liberalization efforts in both the GCC and the CCA have advanced performance above the average for EMs on a trade policy index that captures tariffs, NTMs, financial openness, and capital controls. - Both the CCA and the GCC lag AEs, primarily because of capital account restrictions and, in some cases, limited financial openness. - Within the GCC, the UAE and Bahrain are close to AEs on the trade policy index. - Within the CCA, Georgia stands out for its liberal trade regime (low tariffs, limited NTMs, relatively open capital account); other CCA countries maintain elevated tariff levels and rely more on capital controls. - State footprint (average 2018–22): - State footprint is a composite of government consumption, government investments, and state ownership in the economy; a greater footprint corresponds to a lower index score. - On average, GCC countries score below both EM and AE averages, reflecting higher state presence and dominant SOEs, particularly in energy sectors (though Bahrain outperforms EMs). - CCA countries score higher on average than EMs and AEs, indicating a lower state footprint; Armenia, Kazakhstan, and Georgia score well above EM and AE averages. - Literature: a large state footprint can deter FDI when it creates an uneven playing field, but targeted government intervention can catalyze investment by addressing market failures. - Trade and investment agreements: - All GCC countries and most CCA countries (except Azerbaijan, Turkmenistan, and Uzbekistan) are members of the WTO. - The GCC and the CCA lag well behind AEs in the number of bilateral trade agreements (except Georgia and Armenia), though they have a similar number of bilateral investment agreements as AEs. - The CCA lacks a regional trade agreement or customs union covering all countries, though there are many bilateral trade agreements and some subregional arrangements (e.g., Armenia, Kazakhstan, Kyrgyz Republic in the Eurasian Economic Union). ### Key Policy Implications and Priorities (drawn from analysis) - Reduce trade costs and barriers: - Lower tariffs where appropriate and rationalize NTMs to limit trade-restricting measures while preserving legitimate SPS and TBT objectives. - Enhance trade facilitation and connectivity: - Invest in multimodal infrastructure, simplify customs procedures, accelerate digitalization, harmonize standards, and strengthen border agency cooperation. - Liberalize payments and exchange frameworks: - Reduce aggregate trade payment restrictions in the CCA to facilitate invisible transactions and cross-border trade and investment. - Strengthen governance and institutional quality: - Improve government effectiveness, regulatory quality, rule of law, and control of corruption to attract FDI and bolster trade competitiveness. - Calibrate state footprint and SOE roles: - Where SOEs dominate, ensure a level playing field and consider targeted reforms to encourage private investment while preserving strategic objectives. - Deepen trade and investment integration: - Pursue trade agreements and liberalize capital accounts progressively to enhance attractiveness for FDI and integration into GVCs. *Italic: Source—IMF DEPARTMENTAL PAPERS • Strengthening GCC–CCA Economic Cooperation, Chapter 3.* ### 1. Number of Trade Agreements ### 1. Number of Trade Agreements ### Trade and Investment Agreements: counts and patterns - Median number of trade agreements by region (2023) shown for: GCC, CCA, AEs, EMDEs. (Figure data labels present but exact medians not listed in the text excerpt.) - Number of Bilateral Investment Agreements: latest available data, median number by region (figure presented; exact medians not listed in the text excerpt). - Sources: BACI (Base pour l’Analyse du Commerce International) database from CEPII; UNCTAD Investment Hub; and IMF staff calculations. - Note: AEs = advanced economies; CCA = Caucasus and Central Asia; EMDEs = emerging market and developing economies; GCC = Gulf Cooperation Council. - WTO accession start years: Uzbekistan started its WTO accession process in 1994, Azerbaijan in 1997, and Turkmenistan in 2022. ### Global Value Chains (GVCs): backward and forward participation - Average 2010–20 measures show: - Backward participation (share of foreign value-added in a country’s export) is relatively higher for CCA hydrocarbon importers compared to hydrocarbon exporters. - Hydrocarbon exporters display relatively low backward integration and higher forward participation (their exports used in other countries’ exports). - Most GCC and CCA hydrocarbon exporters have experienced a decline in backward participation since the 1990s and an increase in forward participation. - Backward participation in both the GCC and the CCA is below that of emerging markets and middle-income countries (EMMIs). - Policy implication: Greater integration in value chains in the CCA and the GCC, and possibly GCC–CCA value chains, would help raise productivity while enhancing growth and resilience. - Data sources for GVCs: EORA Global Supply Chain Database; and IMF staff calculations. ### Special Economic Zones (SEZs): experience and design lessons - SEZs have had mixed results in promoting GVCs, industrialization, and attracting FDI (UNCTAD 2019). - Typical objectives vary by development level: - Developing countries: support industrialization, attract FDI, promote exports and GVC integration. - More developed economies: transition to service and high-tech industries, develop logistics hubs, and promote innovation. - SEZs that produced relatively better results shared factors including: - Effectiveness of governance. - Quality of infrastructure. - Proximity to a port. - Availability of human capital (EBRD 2024). - Common pitfalls and costs: high fiscal costs including forgone revenues, significant governance issues, potential harm to trading partners, breaches to international commitments, rent seeking, and corruption. - Regional observations: - The GCC and the CCA countries have several SEZs, with the UAE having a higher number than other countries (Figure referenced). - GCC SEZs appear slightly larger than in the CCA and are slightly more focused on logistics hubs; CCA SEZs are more multi-activity. - Policy guidance: SEZs should be justified only if they resolve a market failure better than alternatives, provide time-bound incentives, be cost-effective and transparently deployed, mitigate rent seeking and corruption, and avoid inflicting harm on trading partners. ### Cross-Border Payments (XBPs): systems, gaps, and the G20 road map - XBPs are fund transfers for which senders and recipients are located in different jurisdictions; they include retail and wholesale segments. - Challenges for XBPs: cost, speed, access, and transparency due to transaction/account/compliance fees, FX conversion fees, liquidity prefunding, dependence on multiple correspondents, cutoff times, lack of interoperability, non-harmonized messaging/processing standards, and limited user information on costs and timing. - Regional payments landscape: - Use of digital payments (fast/instant payment systems) is highly prevalent in GCC countries but less so in the CCA; some CCA countries still rely heavily on cash transactions. - GCC countries use advanced XBP systems including bilateral interlinking of domestic payment infrastructures; CCA countries rely more on correspondent banking. - Central bank digital currencies (CBDCs) exploration status: - Bahrain, Georgia, Saudi Arabia, and the UAE are at the more advanced “proof-of-concept” stage. - Kazakhstan completed two pilot programs. - G20 road map (launched 2020; quantitative targets endorsed in 2021 with the goal of achieving most by 2027) identifies three cross-cutting priority themes: - Payment system interoperability and extension: improve interoperability/interlinking, extend real-time gross settlement operating hours, and enhance payment system access to shorten transaction chains, reduce costs, and increase transparency and speed. - Legal, regulatory, and supervisory frameworks: promote efficient frameworks while maintaining safety, efficiency, and integrity; mitigate unintended frictions (including improving consistency of AML/CFT and sanctions controls); enhance transparency on total transaction costs and expected delivery times. - Data exchange and message standards: facilitate cross-border data exchange and increase use of standardized message formats such as ISO 20022; harmonize APIs used for account validation, compliance screening, message repairs, and investigations. ### Drivers of Trade and Investment — Trade in Goods (gravity model results) - Model: Structural gravity model estimated using bilateral international and domestic trade for more than 150 countries from 2010 to 2023; main-text results based on total exports. - Key model findings and elasticities: - Trade agreements have been associated with an 80 percent increase in bilateral trade overall. - By sector: 128 percent trade increase in food products, 76 percent in mining products, and 63 percent in manufactured products. - When controlling for tariffs, signing a trade agreement is associated with a 45 percent increase in trade. - Tariffs and NTMs reduce trade: - A 10 percent reduction in tariffs is associated with a 5 percent increase in trade. - A 10 percent decline in the number of border NTMs improves trade by 0.3 percent. - Institutional and infrastructure improvements: - A 10 percent increase in logistics is associated with a 48 percent increase in trade. - Improvements in governance are associated with a 19 percent increase in trade. - A reduction in the regulatory burden of 10 percent is associated with a 10 percent increase in trade (text states “reduction in the regulatory burden (10 percent)” in context of relative impact). - A reduction in aggregate trade restrictions of 10 percent is associated with a 10 percent increase in trade (text lists “reduction in aggregate trade restrictions (10 percent)” among impacts). - Composite institutional indicator: - Improvement in the institution’s composite indicator is associated with an almost 1.7 percent increase in trade (constructed via principal component analysis from World Bank Governance Indicators, Fraser Institute regulatory burden, Logistics Performance Index, and an index of aggregate trade restrictiveness). - Regional potentials and gaps: - Intra-GCC and intra-CCA trade may be close to their potential as predicted by the gravity model. - Trade between the GCC and the CCA is typically well below model-predicted potential, suggesting scope to increase bilateral trade significantly. - Trade with other partners: - GCC and CCA trade with China is broadly at potential. - CCA trade with Russia is above potential; GCC trade with Russia is below potential. - GCC trade with the United States is at potential; CCA trade with the United States is below potential. - GCC and CCA trade with the European Union and the rest of the world is below potential. - Policy implications: - Signing trade agreements, reducing tariffs and NTMs, improving governance and logistics, and reducing regulatory burdens and aggregate trade restrictions are key priorities to improve trade performance. - Increasing FDI is associated with greater trade openness and a comprehensive, integrated reform strategy across markets, institutions, and governance. *IMF DEPARTMENTAL PAPERS • Strengthening GCC–CCA Economic Cooperation — 1. Number of Trade Agreements* ### 1. Trade Agreement2. Selected Policies (10 percent change) ### 1. Trade Agreement2. Selected Policies (10 percent change) ### Trade in Goods — key findings and impacts - Policy priorities to improve trade differ between the GCC and the CCA due to different policy gaps; logistics LPI benchmark: 25th percentile of top performers has an LPI of 3.4 while GCC average is 3.3 and CCA average is 2.5. - Trade agreements (bilateral or RTAs) are recommended to strengthen trade between the GCC and the CCA; RTAs can cover competition, subsidies, SOEs, services, investment, and intellectual property rights. - Open, stable, and transparent trade policies and nondiscriminatory agreements that cover a broad set of areas are preferable and must be fully consistent with WTO requirements and existing trade and customs agreements. - Review and reform of NTMs is recommended; NTMs likely have a significant impact on prices and trade volumes even if nominal trade results indicate a limited impact. Suggested improvements: streamline procedures, enhance digitalization, harmonization of standards, and border agency cooperation. - CCA-specific impacts from closing policy gaps (to reach the 25th percentile of top performers): - Closing logistics gap would improve trade by about 148 percent. - Closing governance gap would improve trade by about 122 percent. - Reductions in tariffs would boost trade by around 50 percent. - Reductions in aggregate trade restrictions (reflecting lower regulatory burdens) would boost trade by around 6 percent. - GCC-specific impacts from closing policy gaps: - Reducing tariffs GCC exporters face could increase trade by about 58 percent. - Closing policy gaps in governance, logistics, and regulatory burden could lift trade by 15 to 30 percent. - Notes on interpretation: - Predicted trade gains are estimated using average trade elasticities derived from a gravity model and the country’s policy gap; elasticities are not country specific and estimates should not be interpreted as forecasts. - The boost to trade from a reduction in tariffs and NTMs would require policy actions from importers. ### Trade in Services — key findings and impacts - A gravity model indicates trade agreements are associated with higher bilateral trade in services by 45 percent. - Policy-dependent factors—governance, logistics, regulatory burden, aggregate trade restrictions—are important drivers of trade in services. - Policy elasticity examples: - A 10 percent improvement in logistics is associated with a 30 percent increase in trade in services. - A 10 percent improvement in governance or a reduction in the regulatory burden is associated with a 15 percent increase in trade in services. - A 10 percent reduction in aggregate trade restrictions is associated with a 7 percent increase in trade in services. - Overall, a 10 percent improvement in institutional quality is associated with an almost 13 percent increase in trade in services. - CCA-specific impacts from closing policy gaps for services: - Closing logistics gap would improve trade in services by about 102 percent. - Closing governance gap would improve trade in services by about 93 percent. - Reducing regulatory burden and aggregate trade restrictions would boost trade in services by more than 40 percent. - GCC-specific impacts for services: - Improving governance and logistics would be associated with about 20 and 10 percent increases in trade in services, respectively. - For aggregate trade restrictions, the median GCC country is already at or above the 25th percentile of top performers; hence those results may not be shown. - Recommendation: - To improve bilateral trade in services between GCC and CCA, consider signing trade agreements specifically including services or economic integration agreements that address regulatory harmonization and mutual recognition of standards and qualifications. ### Foreign Direct Investment — drivers and impacts - Empirical approach: random-effects panel regressions at global and regional levels; structural indicators and an FDI attractiveness index (FDIAI) constructed as a simple average of structural indicators. - Macroeconomic drivers: - A 1-percentage-point increase in GDP growth is associated with an increase in FDI inflows of approximately 0.2 percent of GDP. - A 1-percentage-point increase in trade openness is associated with about a 0.1 percent of GDP increase in FDI inflows. - Foreign GDP growth (proxied by US growth) is negatively associated with FDI inflows. - Domestic and foreign policy rates, global fuel prices, the natural resource index, and the global volatility index do not exhibit statistically significant effects in the baseline global model. - Structural drivers: - The FDIAI is positive and significantly associated with FDI inflows at the global level, indicating coordinated structural reforms can enhance investment appeal. - A smaller state footprint (higher values indicate less government involvement) is typically associated with higher FDI inflows in the global and CCA models. - In the GCC model, the relationship reverses: FDI increases with a larger state footprint, reflecting the GCC state-led development model and state-directed large-scale projects. - Regional differences in determinants: - CCA: FDI mainly driven by domestic growth and natural resources; product market efficiency matters; weak effects for financial development and institutional quality suggest lingering reform credibility concerns. - GCC: FDI less driven by GDP and more linked to state-led initiatives; state footprint effect positive for attracting FDI in the GCC context. - Estimated FDI gains from closing structural policy gaps to the 25th percentile of top FDIAI performers: - CCA: FDI gains of 0.7 percent of GDP. - GCC: FDI gains of 0.14 percent of GDP. - Policy implication: strengthening FDI frameworks in the CCA can attract capital from GCC countries (net exporters of capital) and leverage GCC SWFs and private investors. ### Conclusions and policy recommendations - Overall potential: With appropriate policies, there is significant potential for scaling up trade and FDI between the GCC and the CCA; reform priorities differ by region and must be tailored to country heterogeneity. - Trade policy recommendations: - Prioritize logistics and governance improvements in the CCA; reduce aggregate trade restrictions and regulatory burdens. - Both GCC and CCA can benefit from tariff reductions on their exports, potentially via expanded trade agreements. - Review NTMs and improve trade facilitation through streamlined procedures, digitalization, harmonization of standards, and border agency cooperation. - FDI and structural reform recommendations: - Implement coordinated structural reforms covering institutional quality, trade liberalization, labor and product market reforms, financial sector development, and human and physical capital. - GCC: pursue strategic infrastructure upgrades; encourage targeted government interventions and partnerships to de-risk investments while deepening private sector participation. - CCA: address larger infrastructure gaps and bolster rule of law to encourage private sector investment and FDI into non-hydrocarbon sectors. - Trade and investment agreements: - Consider trade agreements and investment treaties consistent with WTO and existing regional arrangements (Eurasian Economic Union, GCC Customs Union) to reduce binding constraints and uncertainty for private-sector entrants. - Complementary measures (conditional and carefully managed): - SEZs, targeted subsidies, insurance schemes, and public–private partnerships can complement—but not substitute for—broader reforms; if pursued, they should resolve market failures, be time-bound, cost-effective, transparent, and limit fiscal risks. - De-risking support from international and regional financial institutions could mitigate FDI-associated risks. - Cross-border payments (XBPs) and operational recommendations: - Use the G20 road map themes: (1) payment system interoperability and extension; (2) legal, regulatory, and supervisory frameworks; (3) data exchange and message standards. - For less advanced payment systems: modernize and digitalize domestic payment systems and analyze correspondent banking issues. - For more advanced systems: consider interlinking or shared systems and central bank digital currencies where prerequisites are in place. - Leverage IMF and World Bank technical assistance for enhancing XBPs. *Source: IMF staff calculations; IMF DEPARTMENTAL PAPERS • Strengthening GCC–CCA Economic Cooperation* ### Annex 1. Facilitating Cross-Border Payments ### Annex 1. Facilitating Cross-Border Payments (XBPs) between the Gulf Cooperation Council (GCC) and the Caucasus and Central Asia (CCA) ### Role and challenges of XBPs - XBPs are indispensable for facilitating international trade and capital flows. - XBPs build upon domestic payment systems but face additional challenges: diverse national legal and regulatory frameworks, transactions in multiple currencies, varying time zones, involvement of multiple intermediaries, and financial market infrastructures. - These factors contribute to higher costs, longer execution times, and limited accessibility for economic agents. - XBPs can take several days to process and may cost up to 10 times more than domestic payments. - Correspondent banking relation (CBR) is one of the most common methods to facilitate XBPs; its network has been shrinking due to more efficient alternatives, AML/CFT challenges, low profitability, and reputational risk from financial integrity issues. - Globally, the number of correspondent banks fell by more than one-fifth between 2011 and 2022. - In the GCC and CCA, all countries except Georgia saw the number of counterparties abroad decline, even though transaction volumes and values generally increased. ### Fundamental XBP processing steps (each intermediary performs these) - Validation: gathering data on the parties to the payment; confirming legitimacy and regulatory (including AML/CFT) compliance; checking format and content of the payment message; verifying sufficient availability of funds. - Transmission: identifying the next recipient in the chain and transforming the data for onward sending to the next recipient. - Funding: receiving incoming funds and changing the currency if needed; releasing funds to the next recipient. ### Common frictions and root causes - Fragmented and truncated data formats: payment messages vary across jurisdictions, systems, and message networks; some formats allow only Latin characters or differing data capacities, forcing translations and inconsistencies. - Complex processing of compliance checks: uneven implementation of sanctions screening and financial crime regimes means repeated checks and higher costs; different banks may use different data sources, increasing false flags and manual interventions. - Limited operating hours: settlement systems’ operating hours constrain account updates; uncertainties in FX rate timing drive up costs as banks overfund positions. - Legacy technology platforms: reliance on batch processing, lack of real-time monitoring, and low data processing capacity create delays, trapped liquidity, and interoperability barriers across legacy infrastructures. - High funding costs: banks must provide funding in advance across multiple currencies or access FX markets, creating capital and liquidity strains and leading to overfunding. - Weak competition: barriers to entry for nonbank PSPs and opacity in true payment initiation costs limit end-user choice and dampen investment in modernization. ### More efficient XBP arrangements and regional examples - Alternatives to CBRs include bilateral interlinking of domestic payment infrastructures (RTGS and fast payment systems) and multi-jurisdictional platforms that allow PSPs in different jurisdictions to transact directly. - These arrangements can substitute for or operate alongside traditional CBRs, reducing intermediaries and potentially lowering cost and time. Annex Box 1.1 — GCC innovations (key facts) - AFAQ Gulf payment system: - Connects RTGS systems of GCC member states; offers instant processing with same-day settlement finality and irrevocability. - 2016: GCC leaders endorsed a plan to link GCC payment systems, leading to establishment of the GPC (owned and funded by GCC central banks). - AFAQ went live in 2021, starting with Saudi Arabia and Bahrain; Kuwait joined in 2022; the UAE in 2023; Oman in 2024. - Use of AFAQ services saw values of transfer and financial settlements rise by 300 and 270 percent, respectively, in 2023 and 2024. - Buna platform (operated by the ARPCSO under the AMF): - Centralized cross-border multicurrency payment system enabling direct settlement between banks in the Arab region; offers wholesale and retail services plus liquidity and FX management tools. - Council decision in 2018; Buna went live in 2020. - Initial currencies: the UAE dirham, Egyptian pound, Saudi riyal, and the US dollar; recently added the Jordanian dinar and the euro. - Transactions grew from less than 2,000 in 2022 to more than 110,000 in 2024. - Total value of transactions neared US$ 3.2 billion in 2024. - More than 15 countries and 100 institutions were participating in the Buna platform. - Success factors cited: common high-level vision, robust security measures, standardized processes (payment formats, cutoff times, delivery times), and adherence to international standards. ### Domestic payment system gaps and regional comparison - XBP frictions often stem from domestic payment system weaknesses: infrastructure, governance, and legal/regulatory frameworks. - Need for modernization is especially pronounced where financial development is lower, competition is weak, or state-owned banks dominate. - Based on a composite indicator, CCA countries generally lag behind GCC countries in financial development, especially on financial institutions’ depth and financial markets (Annex Figure 1.2). - Governance gaps may include underdeveloped formal frameworks for central bank oversight of payments and qualitative dimensions not captured well by existing payment surveys. ### Key statistics and indicators (preserved as in source) - Correspondent banks fell by more than one-fifth between 2011 and 2022. - XBPs can cost up to 10 times more than domestic payments. - AFAQ: - Live in 2021 (Saudi Arabia and Bahrain), Kuwait (2022), UAE (2023), Oman (2024). - Values of transfer and financial settlements rose by 300 and 270 percent, respectively, in 2023 and 2024. - Buna: - Decision by Council of Governors in 2018; went live in 2020. - Transactions: less than 2,000 in 2022 to more than 110,000 in 2024. - Total value neared US$ 3.2 billion in 2024. - Participation: more than 15 countries and 100 institutions. - Annex Figure 1.2 describes Financial Institutions and Markets Development on an index level, 0-1 (simple averages), and metrics for bank state ownership prevalence, sovereign-bank nexus, and profitability (Percent; medians; 2022) comparing GCC and CCA. *IMF Departmental Papers — Strengthening GCC–CCA Economic Cooperation: Annex 1. Facilitating Cross-Border Payments* ### Annex 2. Trade Model, Data and Results ### Annex 2. Trade Model, Data and Results ### Structural gravity model: formulation and interpretation - The structural gravity model is expressed by equations (1)–(3) where: - Xijt is the bilateral trade flow between exporter i and importer j. - Yit is the total value of production in exporter i. - Ejt is the total value of expenditure in importer j. - Yt is global production. - Πit is the outward multilateral resistance. - Pjt is the inward multilateral resistance. - σ is the elasticity of substitution between goods from different countries. - Equation (1) decomposition: - Size term: Yi Ej / Y captures hypothetical frictionless trade. - Trade-cost term: (tij / Πi Pj) captures the wedge between realized and frictionless trade. - Multilateral resistance terms (Πi and Pj) capture how isolated countries are from the rest of the world; changes in trade costs between any two countries affect all other countries. - Econometric specification used: - Xijt = exp InS it + InM jt + Zijt() + eijt (equation (4)), where: - S it is an origin-time fixed effect (exporter-year). - M jt is a destination-time fixed effect (importer-year). - Dij is a country-pair fixed effect. - Zijt includes bilateral trade-related variables (e.g., regional trade agreements). - PPML (Poisson pseudo maximum likelihood) is used to estimate the model to account for zero trade flows and heteroscedasticity. ### Data coverage and variable construction - Sample coverage: - More than 150 countries over the period 2010–23. - Bilateral trade flows aggregated at three levels: - Total trade. - Three sectors: agriculture, mining, and manufacturing. - 10 sectors (see Annex Table 2.2 for HS chapter groupings). - Relevant policy and control variables: - Binary variable for bilateral trade agreement. - Trade-weighted tariffs (World Integrated Trade Solution (WITS)). - Number of border NTMs (as defined in Nicita and Koloskova 2025; UNC TAD). - Quality of governance: simple average of WGI government effectiveness, regulatory quality, rule of law, and control of corruption (World Bank, WGI). - Quality of logistics/infrastructure: Logistics Performance Index ranging from 1 to 5 (World Bank). - Regulatory burden (Fraser Institute). - Measure of aggregate trade restrictions (IMF’s AREAER, following Estefania-Flores and others 2022). - Composite index of institutional quality: first principal component of correlated governance/logistics/regulatory/trade restriction indicators. ### Gravity model results for goods - Findings consistent with the literature (Annex Table 2.3): - Distance, contiguity, common language, and colonial ties are highly statistically significant with expected signs. - Border dummy (equal to one if trade flows across an international border) is negative and highly significant, reflecting a home bias effect; domestic trade tends to be much larger than international trade. - Trade agreements significantly and positively impact bilateral trade. - Tariffs and NTMs negatively impact trade. - Policy-variable interactions: - Domestic policy indicators are introduced as interaction terms between the policy variable and the border dummy. - Governance, logistics, regulatory burden, and aggregate trade restrictions were introduced individually (columns 4–7) due to high correlation; all are highly significant with expected signs. - When policy variables are included simultaneously (column 8), governance impact on trade turns negative and remains significant, highlighting correlation among policy variables. - Composite index of institutional quality is positive and statistically significant. - Sector-specific results (Annex Tables 2.4–2.6): - NTMs have their most adverse impact on manufacturing and agricultural products and the least impact on mining products. - Quality of logistics affects trade of manufacturing products the most. - Governance and the composite index of institutional quality have their greatest impact on manufacturing and mining products. - Regulatory burden has its greatest impact on trade of manufacturing and agricultural products. - Robustness: - Results appear robust to: - Different fixed-effects specifications (Annex Table 2.8): no fixed effects; exporter, importer, and year fixed effects; sector fixed effects; exporter-year and importer-year fixed effects. - Different subcategories of NTMs (Annex Table 2.9): sanitary and phytosanitary measures, technical barriers measures, nontechnical measures, price controls, and other measures. - Different broad measures of NTMs (Annex Table 2.10). - Note: Nicita and Koloskova (2025) find that AVEs are highest for agricultural products and lowest for commodities. ### Gravity model results for services - Data source: - WTO–OECD Balanced Trade in Services (BaTiS) dataset: balanced matrix for over 200 countries by 26 sectors for 2005–23; bilateral trade flows reconciled where exports mirror imports (WTO 2025; WTO Stats 2025). - Estimation challenges and approach: - Domestic trade flows are not available for services, so exporter-year and importer-year fixed effects would absorb GDP and country-specific time-varying variables. - Constructed exporter and importer remoteness indices to proxy multilateral resistance terms where fixed effects cannot be used; remoteness indices are functions of bilateral distance and GDP of trade partners. - Remoteness indices (logarithms of expenditure and output weighted averages of bilateral distance) may not be theoretically consistent and can lead to biased estimates. - Results (Annex Table 2.11): - Column 1 (no fixed effects): exporter GDP and importer GDP positively associated with bilateral trade; distance negatively correlated; common language, colonial links, and trade agreements strongly associated with trade; contiguity coefficient insignificant. - Column 2 (exporter-year and importer-year fixed effects): qualitatively similar; contiguity becomes positively and significantly associated with bilateral trade. - Column 3 (includes remoteness indices): exporter remoteness index is positive and significant; importer remoteness index is not significant, suggesting distance-based remoteness may matter less for services. - Institutional policy variables (columns 4–9): - Better governance, logistics performance, regulatory quality, and lower aggregate trade restrictiveness are positively associated with bilateral trade in services. - Quantified associations reported in the model: - Column 4: "a 1 percent improvement in governance in importer or exporter indicator is significantly associated with a 1 to 1.5 percent increase in bilateral trade." - Logistics performance: "a 1 percent improvement could be associated with a 2.5 to 3 percent increase in bilateral trade in services." - Regulatory quality (column 6): "a 1 percent increase in regulatory quality is associated with a 1.2 to 1.7 percent increase in bilateral trade." - Aggregate trade and exchange restrictiveness (column 7): "lowering trade and exchange restrictiveness by 1 percent could be correlated with 0.5 to 0.7 percent higher bilateral trade." - Composite institutional indicator (column 9): "Improvement in the composite indicator is associated with an almost 1 to 1.3 percent increase in trade." ### Annex Tables and data definitions (selected) - Annex Table 2.1: Gravity Model Data (selected variables and sources) - International trade in goods: BACI by CEPII; values in thousand current US$; data at six-digit HS level, aggregated into 10 sectors (see Annex Table 2.2). - Domestic trade in goods: TradeProd by CEPII; internal trade flows obtained by subtracting exports from gross production; sectoral for 10 sectors. - Trade in services: OECD–WTO BaTiS; values in million US$; 12 sectors listed. - Distance: Population-weighted average distance between most populated cities, arithmetic mean, in km bilateral (CEPII). - Contiguity, Common language, Colonial links, Free trade agreement: CEPII. - Tariff: Effectively applied weighted average tariff (WITS). - NTMs: Total number of NTMs (UNC TAD); border NTMs per Nicita and Koloskova (2025); NTM subcategories specified. - Governance: simple average of selected WGI (World Bank, WGI). - Regulatory burden: Fraser Institute. - Infrastructure: Logistics Performance Index ranging from 1 to 5 (World Bank). - Measure of aggregate trade restrictions: IMF’s AREAER (per Estefania-Flores and others 2022). - Annex Table 2.2: Goods classification by HS chapter groupings into 10 sectors: - 10: 1–24 Agriculture and Food Products (Live Animals, Food, and Beverages) - 22: 25–27 Minerals and Fuels (Incl. Crude Oil, Coal, and Salt) - 32: 28–40 Chemicals and Plastics - 44: 41–43 Leather and Hides - 54: 44–49 Wood and Paper Products - 65: 50–67 Textiles, Footwear, and Accessories - 76: 68–83 Stone, Metals, and Basic Manufactures - 88: 84–85 Machinery and Electronics - 98: 86–92 Transport and Precision Equipment - 10: 93–97 Arms, Furniture, Toys, and Miscellaneous *Source: Annex 2. Trade Model, Data and Results (sgcecea - Annex 2. Trade Model, Data and Results).* ### Annex Table 2.3. Gravity Model Estimates—Aggregate Trade ### Annex Table 2.3. Gravity Model Estimates—Aggregate Trade ### Main estimated coefficients (column (1)) - Log of distance: −0.512*** (0.0278) - Contiguity: 0.581*** (0.108) - Common language: 0.264*** (0.0832) - Colonial ties: 0.402*** (0.0958) - Trade agreements: 0.586*** (0.0599) - Border: −2.996*** (0.102) - Log of tariff: −0.452*** (0.0361) - Observations: 277,415 - Exporter-year fixed effect: Yes - Importer-year fixed effect: Yes *Source: Authors’ calculations.* --- ### Annex Table 2.4. Gravity Model Estimates—Agriculture ### Main estimated coefficients (column (1)) - Log of distance: −0.602*** (0.0347) - Contiguity: 0.779*** (0.114) - Common language: 0.240*** (0.0870) - Colonial ties: 0.398** (0.164) - Trade agreements: 0.825*** (0.0642) - Border: −4.130*** (0.116) - Log of tariff: −0.343*** (0.0244) - Observations: 228,849 - Exporter-year fixed effect: Yes - Importer-year fixed effect: Yes *Source: Authors’ calculations.* --- ### Annex Table 2.5. Gravity Model Estimates—Mining ### Main estimated coefficients (column (1)) - Log of distance: −0.875*** (0.0580) - Contiguity: 0.538*** (0.140) - Common language: 0.188 (0.122) - Colonial ties: 0.193 (0.135) - Trade agreements: 0.567*** (0.0946) - Border: −1.644*** (0.223) - Log of tariff: −0.403*** (0.0699) - Observations: 153,470 - Exporter-year fixed effect: Yes - Importer-year fixed effect: Yes *Source: Authors’ calculations.* --- ### Annex Table 2.6. Gravity Model Estimates—Manufacturing ### Main estimated coefficients (column (1)) - Log of distance: −0.587*** (0.0277) - Contiguity: 0.449*** (0.0885) - Common language: 0.139* (0.0806) - Colonial ties: 0.641*** (0.127) - Trade agreements: 0.490*** (0.0618) - Border: −0.737*** (0.147) - Log of tariff: −0.340*** (0.0505) - Observations: 268,336 - Exporter-year fixed effect: Yes - Importer-year fixed effect: Yes *Source: Authors’ calculations.* --- ### Annex Table 2.7. Gravity Model Estimates—10 Sectors ### Main estimated coefficients (column (1)) - Log of distance: −0.536*** (0.0279) - Contiguity: 0.543*** (0.107) - Common language: 0.233*** (0.0837) - Colonial ties: 0.400*** (0.0954) - Trade agreements: 0.552*** (0.0612) - Border: −3.014*** (0.104) - Log of tariff: −0.459*** (0.0335) - Observations: 2,027,129 - Exporter-year fixed effect: Yes - Importer-year fixed effect: Yes - Sector fixed effect: Yes *Source: Authors’ calculations.* --- ### Annex Table 2.8. Gravity Model Estimates—Fixed Effects ### Selected estimated coefficients (columns shown) - Log GDP (origin): 0.604*** (0.0496) (col (1)) - Log GDP (destination): 0.680*** (0.0368) (col (1)) - Log of distance: −0.149 (0.143) (col (1)) - Contiguity: 1.128*** (0.175) (col (1)) - Trade agreement: 0.382*** (0.130) (col (1)) - Log of tariff: −0.310*** (0.0434) (col (1)) - Log of NTM: −0.0175 (0.0197) (col (1)) - Border: −9.016*** (0.840) (col (1)) - Observations: 120,450 (columns (1) and (2) reported) - Exporter fixed effect: No (col (1)); Yes in col (3) - Importer fixed effect: No (col (1)); Yes in col (3) - Year fixed effect: No (col (1)); Yes in col (2) - Exporter-year / Importer-year fixed effect: Yes in col (4) *Source: Authors’ calculations.* --- ### Annex Table 2.9. Gravity Model Estimates—Granular types of NTMs ### Main estimated coefficients (columns shown) - Log of distance: −0.532*** (0.0251) (col (1)) - Contiguity: 0.540*** (0.0938) (col (1)) - Common language: 0.252*** (0.0755) (col (1)) - Colonial ties: 0.387*** (0.0949) (col (1)) - Trade agreements: 0.118* (0.0645) (col (1)) - Log of tariff: −0.377*** (0.0366) (col (1)) - Border: −2.068*** (0.125) (col (1)) - Log of NTM (aggregate): −0.0322*** (0.00985) (col (1)) - Log of NTM A: −0.0369*** (0.0108) (col (3)) - Log of NTM B: −0.0332*** (0.0106) (col (3)) - Log of NTM E: −0.0888*** (0.0142) (col (4)) - Log of NTM F: 0.00457 (0.0146) (col (5)) - Observations: 156,381 - Exporter-year fixed effect: Yes - Importer-year fixed effect: Yes *Source: Authors’ calculations.* --- ### Annex Table 2.10. Gravity Model Estimates—Nontariff Trade Measures ### Selected estimated coefficients (columns shown) - Log of distance: −0.532*** (0.0251) (col (1)) - Contiguity: 0.540*** (0.0938) (col (1)) - Common official language: 0.252*** (0.0755) (col (1)) - Colonial links: 0.387*** (0.0949) (col (1)) - Regional trade agreement: 0.118* (0.0645) (col (1)) - Log of tariffs: −0.377*** (0.0366) (col (1)) - Log of NTM: −0.0322*** (0.00985) (col (1)) - Log FRA NTM for the importer side: −2.096*** (0.131) (col (1)) - Border: −2.068*** (0.125) (col (1)) - Observations vary by specification: 156,381; 133,834; 233,699; 135,574; 133,834 (cols reported) - Exporter-year fixed effect: Yes in some specifications - Importer-year fixed effect: Yes in some specifications *Source: Authors’ calculations.* --- ### Annex Table 2.11. Gravity Model Estimates—Trade in Services ### Selected estimated coefficients (representative columns) - Log of origin GDP: 0.796*** (0.0233) (col (1)) - Log of destination GDP: 0.787*** (0.0231) (col (1)) - Log of distance: −0.645*** (0.0346) (col (1)) - Contiguity: −0.126 (0.120) (col (1)) - Common language: 0.778*** (0.112) (col (1)) - Colonial links: 0.287** (0.135) (col (1)) - Trade agreement: 0.366*** (0.0714) (col (1)) - Log of governance of exporter: 1.484*** (0.100) (col (1)) - Log of governance of importer: 1.071*** (0.112) (col (1)) - Log of Logistics Performance Index of exporter: 3.332*** (0.213) (col (1)) - Log of Logistics Performance Index of importer: 2.591*** (0.248) (col (1)) - Log of regulatory burden of exporter: 1.719*** (0.117) (col (1)) - Log of regulatory burden of importer: 1.279*** (0.134) (col (1)) - Log of trade and exchange restrictiveness of exporter: −0.734*** (0.0626) (col (1)) - Log of trade and exchange restrictiveness of importer: −0.491*** (0.0646) (col (1)) - Log of composite index for institutional quality of exporter: 1.320*** (0.0913) (col (1)) - Log of composite index for institutional quality of importer: 0.933*** (0.0991) (col (1)) - Constant (col (1)): −20.61*** (0.652) - Observations (various specifications): 282,722; 286,582; 282,722; 268,974; 255,782; 257,438; 274,420; 237,678; 237,678 (as reported) - Exporter-year fixed effect: Yes in some specifications (col (2) shows Yes) - Importer-year fixed effect: Yes in some specifications (col (2) shows Yes) *Source: Authors’ calculations.* ### Annex 3. Foreign Direct Investment ### Annex 3. Foreign Direct Investment (FDI) Model, Data and Results ### Model and Methodology - Empirical approach: random-effects panel regression model for 86 advanced and emerging market developing economies over the period 2000–22, supported by the Hausman test. - Baseline specification: - FDI_i,t = α_i,h + δ_h SR_i,t + β X_i,t + ε_i,t - FDI_i,t denotes net FDI inflows as percentage of GDP. - SR denotes a set of structural indicators. - X_i,t denotes control variables capturing key macroeconomic and external conditions. - Control variables include domestic and foreign GDP growth; domestic and foreign policy rates; VIX index; global fuel prices; trade openness; natural resource index. ### Structural Indices (construction and components) - Indices constructed by standardizing subindicators to vary between 0 and 100, taking unweighted averages, and scaling the score to 100; higher value shows favorable conditions to attract FDI inflows. - Data sources: World Development Indicators, UNCTAD database, Fraser Institute database (period 2000–22). - Indices and key constituent variables: - State footprint index: government consumption as percent of total consumption; government investment as percent of total investment; size of state-owned enterprises. Higher index values indicate less government intervention. - Institutions index: six Worldwide Governance Indicators (voice and accountability; political stability; government effectiveness; regulatory quality; rule of law; control of corruption). - Product market index: impartial public administration; bureaucratic costs; regulatory burdens; asset protection for nonresidents; market distortions; property rights protection (Fraser database). - Labor market index: flexibility in labor market; human capital quality (World Bank); labor market restrictions and collective bargaining (Fraser Institute). - Financial regulations index: depth and development of financial sector; credit market regulations; foreign currency bank accounts; ownership of banks; interest rate controls. - Trade index: capital controls; financial openness; nontariff trade barriers; mean tariff rate (Fraser Institute). ### Data and Variable Definitions - Foreign GDP growth proxied by US real GDP growth. - Foreign policy rate proxied by the effective federal funds rate. - Trade openness measured as sum of exports and imports as share of GDP. - Natural resource index is a dummy: 1 for resource-rich countries, 0 otherwise. - Control and structural variable descriptions (selected): - Domestic GDP growth: Percentage change in real GDP (WEO). - Volatility index: VIX (Haver). - Global fuel prices: Brent (Haver). - Multiple Fraser Institute and World Governance Indicators variables used for structural indices. - Note: Fraser indicators may not fully capture recent reform efforts in some regions. ### Main Empirical Results — Global Model (Annex Table 3.2) - Strong and robust macro determinants: - Openness: 0.054*** (0.013) in column 1; consistently 0.054***–0.056*** across columns 1–8. - Domestic GDP growth: positive and significant in many specifications, e.g., 0.211** (0.085) in column 1; 0.264*** (0.088) in column 3; other columns: 0.168**, 0.242***, 0.217***, 0.198***, 0.214***, 0.199***. - Foreign GDP growth: negative and significant in many specifications, e.g., −0.290** (0.138) in column 1; −0.228* (0.122) in column 2; other columns: −0.292**, −0.269**, −0.231**, −0.243**, −0.239**, −0.262**. - Structural index findings: - FDI attractiveness index: 0.061** (0.031) when included alone (column 4). - State footprint index: 0.082** (0.035) in column 5; 0.052* (0.029) in column 6 when included separately. - Financial development index: 0.018 (0.015) in column 6; 0.014 (0.021) in column 7. - Labor market index and product market index show mixed/insignificant effects in separate specifications. - Institutional quality index: 0.026 (0.036) in column 7; −0.082 (0.068) in column 8. - Limited influence of short-term variables: - Volatility index coefficients small and not statistically significant across most specifications (e.g., −0.04 (0.039) in column 1). - Global fuel prices small and mostly insignificant (e.g., −0.01 (0.007) in column 1). - Other reported model summary lines (as printed): - Constant terms: −3.013 (2.615), −0.917 (1.784), −1.821 −2.626 (2.072), −0.48 (3.196), −6.196* (2.338), −1.056 (1.824), −0.322 (3.068), −3.814 - Observations line (as printed): 11621396128212881448152813951162 - Number of Countries line (as printed): 7183788282868471 - R2 (Overall) line (as printed): 0.307 0.2940.291 0.284 0.275 0.2640.280.314 - Random-Effect line (as printed): Ye sYe sYe sYe sYe sYe sYe sYe s - Significance notation in table: *p < .1, **p < .05, ***p < .01. ### Regional Results - CCA model (Annex Table 3.3) — key coefficients and findings: - Domestic GDP growth: strongly positive and significant across specifications, e.g., 0.383*** (0.027) in column 1; 0.437*** (0.073) in column 2; 0.423*** (0.053) in column 3; other values include 0.448***, 0.401***, 0.421***, 0.428***, 0.1390 (0.244). - Foreign GDP growth: negative and occasionally significant, e.g., −0.396* (0.225) in column 1; other columns show mixed significance. - Foreign policy rate: large negative and significant in several specifications, e.g., −1.947*** (0.596) in column 1; −1.346*** (0.512) in column 2; −1.233*** (0.270) in column 3; values across columns include −1.333**, −1.4070, −1.1070, −1.346***, −1.466***. - Volatility index: more negative and sometimes significant than in the global model, e.g., −0.2080 (0.148) in column 1; −0.251* (0.137) in column 5; −0.220** (0.108) in column 6. - Openness: positive and significant, e.g., 0.198** (0.100) in column 1; other columns show 0.103*, 0.1100, 0.100*, 0.1070, 0.106*, 0.103*, 0.280**; associated standard errors and some negative numbers are printed adjacent in the table layout (e.g., −0.1000 −0.0550 −0.0740 −0.0530 −0.0870 −0.0560 −0.0570 −0.1430). - Natural resource index: strongly positive and significant in many specifications, e.g., 2.199*** (0.718) in column 1; 3.413*** (0.965) in column 2; 3.854* (1.974) in column 3; additional values include 3.650***, 5.290*, 5.042**, 3.072**, 3.6880 (3.398). - GCC model (summary from text and tables): - In the GCC, FDI is not significantly driven by domestic growth or fuel prices. - Reducing state dominance has a negative impact on FDI in GCC regional models (counterintuitive relative to global findings), possibly reflecting the prominence of government-led projects and SWFs. - Openness shows a strong positive effect in the GCC model. ### Robustness Checks and Additional Specifications - Alternative definitions of the state footprint variable: tested using different combinations of size of government, state ownership, and public investment (Annex Table 3.5). - Excluding the UAE from GCC regional models to assess influence of UAE-specific structural features. - Inclusion of regional dummy variables to account for unobserved heterogeneity across geographic blocs. - Use of a country’s share of global FDI as an alternative dependent variable. - Separate models estimated for hydrocarbon-exporting and resource-rich countries to test heterogeneity in drivers of FDI (Annex Table 3.6). - Across these specifications, results remain stable and statistically robust. ### Interpretation and Policy-Relevant Findings - Market fundamentals and integration matter: - Domestic GDP growth and trade openness are robust pull factors for FDI globally and regionally. - External conditions can divert capital: - Foreign GDP growth often operates as a push factor (negative coefficient), redirecting capital toward stronger external markets. - Structural and coordinated reform matters: - The composite FDI attractiveness index is significant, while many individual reform indices show limited independent effects, suggesting that coordinated, cross-cutting reforms across markets, institutions, and governance are more likely to attract sustained FDI inflows. - Role of state footprint varies by region: - Globally, a higher (less interventionist) state footprint index is associated with more FDI (positive and significant when included alone). - In the GCC, reducing state dominance is associated with lower FDI, reflecting region-specific dynamics where government-led projects and SWFs play a central role. - Resource-rich economies: - In CCA, resource wealth strongly attracts FDI, supporting resource-seeking FDI hypotheses. - Investor sensitivity to volatility: - CCA economies’ FDI inflows are more sensitive to global volatility than the global sample, indicating weaker investor confidence in the region. *Source: Authors’ calculations.* ### Annex Table 3.2. Drivers of FDI—Global Model Results (continued) ### Annex Table 3.2. Drivers of FDI—Global Model Results (continued) ### Key statistically significant coefficients and estimates - Financial development index: −0.364*** (0.077) - Labor market index: −0.771** (0.358) - State footprint index: 0.251*** (0.086) - Institutional Quality index: 0.302*** (0.087) ### Other reported coefficients (selected) - FDI attractiveness index: −0.0330 (0.079) - Financial development index (other column): −0.021 (0.052) - Labor market index (other column): −0.135 (0.390) - Product market index: 0.2100 (0.381) - Trade index: 0.131 (0.155) - Constant entries: −0.8914.05710.663−0.071−3.385−13.065**4.829065.126*** (2.638)(5.268)(24.513)(4.214)( 7. 2 3 8)(5.560)(10.352)(20.845) ### Model diagnostics and sample - Observations: 8210110010110515110182 - Number of Countries: 5666.00005.0000765 - R2 (Overall): 0.430 0.344 0.347 0.347 0.326 0.303 0.3450.656 - Random-Effect: Ye sYe sYe sYe sYe sYe sYe sYe s *Source: Authors’ calculations. Note: CCA = Caucasus and Central Asia; FDI = foreign direct investment. Standard errors in parentheses. *p < .1, **p < .05, ***p < .01.* --- ### Annex Table 3.4. Drivers of FDI—GCC Model Results ### Key statistically significant coefficients and estimates - Openness: 0.042*** (0.008) in column 1; 0.024** (0.010) in column 2; 0.029** (0.014) in column 4 - Domestic policy rate: 0.243** (0.106) in column 6 - FDI attractiveness index: −0.377** (0.191) (appears in one column) - State footprint index: −0.067* (0.037) and −0.070* (0.036) (appearing in columns with alternative state-footprint measures) ### Other reported coefficients (selected) - Domestic GDP growth: 0.0600 (0.093) … 0.0270 (0.131) across columns - Foreign GDP growth: 0.18500 (0.249) … 0.1970 (0.220) across columns - Foreign policy rate: −0.4860 (0.600) … −0.7900 (0.745) across columns - Volatility index: 0.04900 (0.084) … 0.0410 (0.056) across columns - Global fuel prices: 0.00900 (0.012) … 0.0120 (0.011) across columns - Financial development index: 0.025 (0.068) and −0.092 (0.061) in different columns - Institutional quality index: 0.003 (0.137) and −0.6290 (0.467) in different columns - Trade index: −0.0240 (0.107) and 0.07 (0.188) in different columns - Constant (selected): 21.731* (11.736); −4.749 (8.495); 33.9240 (22.205) in various columns ### Model diagnostics and sample (reported) - Observations: 67889086921149367 - Number of Countries: 56665665 - R2 (Overall): 0.368 0.254 0.261 0.312 0.383 0.263 0.249 0.437 - Random-Effect: Ye sYe sYe sYe sYe sYe sYe sYe s *Source: Authors’ calculations. Note: FDI = foreign direct investment; GCC = Gulf Cooperation Council. Standard errors in parentheses. *p < .1, **p < .05, ***p < .01.* --- ### Annex Table 3.5. Drivers of FDI—State Footprint Model Results ### Model specification note - State footprint is defined in three alternative ways: (A) size of government and state ownership, (B) size of government and government investment, and (C) state ownership and government investment. ### Key statistically significant coefficients and estimates (selected across columns 1–9) - Domestic GDP growth: - 0.209** (0.082) in column 1 - 0.224*** (0.079) in column 2 - 0.197** (0.079) in column 3 - 0.222*** (0.083) in column 8 - 0.202*** (0.076) in column 9 - Foreign GDP growth: negative and significant across many columns, e.g. - −0.270** (0.133) in column 1 - −0.230** (0.111) in column 2 - −0.291** (0.138) in column 4 - −0.292** (0.139) in column 7 - Openness: consistently positive and highly significant - 0.054*** (0.013) in column 1 - 0.058*** (0.011) in column 2 - 0.056*** (0.013) in column 3 - 0.056*** (0.012) in column 8 - 0.056*** (0.013) in column 9 - FDI attractiveness index: - 0.055 (0.038) in one column; 0.066** (0.029) in other columns - State footprint index: - 0.096*** (0.037) in one column - 0.062* (0.032) and 0.063** (0.027) in other columns - 0.042* (0.023) and 0.065** (0.029) and 0.04 (0.026) in other specifications ### Other reported coefficients (selected) - Natural resource index: −1.026 (0.812) … −0.39 (0.964) across columns - Financial development index: 0.018 (0.020) … 0.015 (0.021) - Labor market index: 0.035 (0.033) … 0.036 (0.033) - Product market index: 0.03 (0.045) … 0.041 (0.047) - Institutional quality index: −0.051 (0.067) … −0.096 (0.068) - Trade index: −0.014 (0.032) … −0.013 (0.032) - Constants (selected): −2.594 (3.106); −7.108** (3.537); −5.018* (2.857); −2.47 (2.842) ### Model diagnostics and sample (reported) - Observations: 1192 1492 1192 1162 1494 1162 1167 1448 1162 - Number of Countries: 73 84 73 71 84 71 71 82 71 - R2 (Overall): 0.306 0.282 0.314 0.307 0.268 0.314 0.308 0.273 0.314 - Random-Effect: Ye sYe sYe sYe sYe sYe sYe sYe s *Source: Authors’ calculations. Note: FDI = foreign direct investment. Standard errors in parentheses. *p < .10, **p < .05, ***p < .01.* --- ### Annex Table 3.6. Drivers of FDI—Resource-Rich Countries Model Results ### Key statistically significant coefficients and estimates (selected) - Domestic GDP growth: strong positive and significant across columns - 0.421*** (0.136) in column 1 - 0.350** (0.137) in column 2 - 0.513*** (0.147) in column 3 - 0.514*** (0.144) in column 4 - 0.379*** (0.103) in column 5 - 0.398*** (0.122) in column 6 - 0.444*** (0.138) in column 7 - 0.339*** (0.078) in column 8 - Foreign policy rate: negative and significant in several columns - −0.654** (0.280) in column 1 - −0.557*** (0.209) in column 3 - −0.628*** (0.220) in column 4 - −0.400* (0.224) in column 7 - −0.855** (0.379) in column 8 - Openness: positive and significant in some specifications - 0.043* (0.025) in column 3 - 0.047* (0.027) in column 4 - 0.095** (0.038) in column 5 - 0.078* (0.041) in column 6 - 0.057* (0.030) in column 7 - 0.067* (0.035) in column 8 - State footprint index: - 0.218** (0.087) in one column - 0.136** (0.061) in another column ### Other reported coefficients (selected) - Foreign GDP growth: −0.269* (0.149) … −0.155 (0.128) across columns - Domestic policy rate: 0.197 (0.133) … 0.12 (0.091) across columns - Volatility index: −0.087 (0.072) … −0.082 (no SE provided in last entry) - Global fuel prices: −0.017 (0.023) … −0.016 (0.018) - FDI attractiveness index: 0.068 (0.065) in one column - Financial development index: 0.007 (0.022) and 0.00 (0.035) - Institutional quality index: −0.175 (0.179) and −0.200 (0.188) - Trade Index: −0.084 (0.076) and −0.078 (0.073) - Constants (selected): −2.161 (4.415); −0.744 (1.964); 2.070 (6.138); −19.401** (7.561); 4.422 (7.686); 2.026 (5.257); −1.868 (7.130) ### Model diagnostics and sample (reported) - Observations: 253315322315387417347253 - Number of Countries: 1721212223242217 - R2 (Overall): 0.1810.1260.148 0.159 0.203 0.1140.1370.255 - Random-Effect: Ye sYe sYe sYe sYe sYe sYe sYe s *Source: Authors’ calculations. Note: FDI = foreign direct investment. Standard errors in parentheses. *p < .1, **p < .05, ***p < .01.* *Source: Authors’ calculations.* --- _Source: https://www.imf.org/-/media/files/publications/dp/2026/english/sgcecea.pdf_