Enhancing Investment Ecosystem Readiness: A Game-Theoretic Model of Impact Investment in the MENA Region

Enhancing Investment Ecosystem Readiness: A Game-Theoretic Model of Impact Investment in the MENA Region | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing Investment Ecosystem Readiness: A Game-Theoretic Model of Impact Investment in the MENA Region Metri Mdanat, Andrey Timofeev, Ghazi Samawi, Omar Bwaliez This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7442973/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines investment decision-making in various economic contexts, focusing on the relationship between Investment Ecosystem Readiness, Deal Complexity, and impact investment inflows to address social and economic issues in the MENA region. It aims to understand how regulatory readiness and investment complexity influence impact investors strategic decisions and how these factors interact with government behaviors to shape investment outcomes. A mixed methodology combining both game theoretic modelling and pre-structured investor interviews was used to examine these relationships, offering a systematic framework for understanding the strategic interaction between governments and impact investors, identifying equilibrium conditions that determine investment inflows into 14 MENA countries using data from 2019 to 2024. The study demonstrates that reducing investment complexity while enhancing regulatory readiness significantly improves impact investment inflows. Both investors and governments are likely to benefit from cooperation and transparency, leading to mutually beneficial outcomes and effectively addressing the social and economic challenges of the MENA region suffers from. This study contributes to the existing literature by examining how ecosystem readiness influences impact investment in addressing social and economic challenges and supports sustained economic growth in the MENA region. Policy recommendations include streamlining regulatory frameworks, fostering institutional transparency, and aligning incentives with investor preferences to maximize social and economic impact. Governments should focus on impact investment in their strategies and plans. They need to design policies to improve IER and reduce DC by simplifying regulations and reducing complexity, which can maximize mutual benefits and payoffs for all. Impact investment investment ecosystem readiness game theory Figures Figure 1 Figure 2 1 Introduction 1.1 Investment Ecosystem Investment composition varies across countries, including domestic and foreign, short-term and long-term, as well as direct and indirect investments. The nature of investments depends on their purpose, whether aimed at generating immediate returns or fostering long-term economic growth. Traditional investments have primarily focused on economic growth and employment (Sal & Burlea-Schiopoiu, 2021). However, these investments alone have not effectively addressed all socio-economic and environmental challenges that regions such as MENA seek to achieve (Organisation for Economic Co-operation and Development [OECD], 2021). Consequently, impact investment (I-Inv) has emerged as a strategic approach to mobilize capital for addressing these challenges, integrating financial returns with measurable social and environmental benefits. I-Inv, also known as “sustainable” or “social” investment (Finance Center for South-South Cooperation, 2023 ), aims to foster inclusive economic growth (Mdanat, 2022 ). I-Invs target markets at various growth stages, to generate measurable social and financial returns. According to Kesselring ( 2021 ), I-Inv is targeted at empowering social entrepreneurs to solve societal problems and to respond to market failure. It seeks to enable social-oriented businesses (and community organizations) to generate societally beneficial impacts, while making a profit and exploiting market opportunities (Shuwaikh, Hughes, Brinette, & Khemiri, 2023). However, the limited inflow of I-Inv to the MENA region (hereinafter “the region”) is attributed to the relatively small economies of most regional countries, which are typically characterized by small market sizes and limited purchasing power, aligned with middle-income countries. The OECD (2021) highlights that investors intrinsically seek large markets, suggesting that MENA’s fragmented economies may pose challenges for I-Inv inflows to the region. A critical factor influencing these inflows is the investment ecosystem readiness (IER) of a country. IER refers to the capacity of a country to meet the specific needs and expectations of investors, including stakeholders who participate in or support the investment ecosystem at a country level (Huppé, 2014 ; Ndegwa, 2022 ). IER has been described in terms of traditional indicators like return on investment, long-term commitment (Scottish Marine Environmental Enhancement Fund, 2024 ), and availability of resources (Lustenberger, Malešević, & Spychiger 2021 ), especially in the context of raising external equity finance (Mason & Kwok, 2010 ). While IER pertains mainly to the macroeconomic dimension of I-Inv, deal complexity (DC) refers to the level of difficulty and challenges involved in executing a business transaction, such as a merger, acquisition, partnership, or large-scale contract (International Monetary Fund [IMF], 2021). It encompasses various factors that can complicate negotiations, due diligence, structuring, and finalization of the deal (Levy, 2025 ). Depending on the nature of impact investors who seek to invest in countries, the readiness of the ecosystem can be crucial for I-Invs (Klapper & Love, 2010 ). It pertains to how both ecosystem conditions and deal closure (i.e., DC) in target countries determine the success of I-Invs. IER involves numerous interrelated factors, but the effect of investment ecosystems on I-Invs has received little attention in related studies, despite recent research highlighting the importance of attracting more investment to MENA (Kumar & Dua, 2024 ; Fawaz, 2025 ). This study seeks to contribute to addressing this gap in existing literature. 1.2 Study Context This study aims to explore the relationship between IER, DC, and I-Inv inflows in the MENA region. The key questions that this study tries to answer are: What factors influence impact investors’ decisions in the MENA region? How does IER affect investment attractiveness? How does DC impact the likelihood of attracting I-Inv? What policy measures can governments implement to optimize investment conditions? The primary objective of this study is to analyse how investment readiness and DC influence the strategies of countries and impact investors, adding to a strand of longstanding research on this issue that has yet to explore MENA in detail (Gompers & Lerner, 2001 ; Hoskisson, Eden, Lau, & Wright, 2000 ; Tabash, Farooq, Matar, & Al-Absy, 2024 ). According to Menkhoff and He ( 2013 ), government strategies and DC interact with the investment ecosystem, which moderates the negative effect of complexity on investors and the financial markets. Akin and Akin ( 2025 ) examined the role of government strategies in creating complex investment deals, emphasizing the role of government in shaping an investment-friendly environment. This study contributes to building on the existing literature by bridging the gap between theory and practice through examining how ecosystem readiness influences I-Inv and supports sustained economic growth. To address these issues, this study examines investment decision-making choices in diverse economic contexts by investigating how IER could assist impact investors in the MENA region. While employing pre-structured interviews with main investors and stakeholders in the region, the emphasis is on the systematic use of the game theory modelling of various interrelated factors that determine a country’s IER and performance. Following this introduction, section 2 reviews existing literature on I-Inv and IER. Section 3 presents the theoretical framework. Section 4 describes the methodology, including data sources and game-theoretic modelling. Section 5 presents the results, which are discussed in section 6 and concluded in section 7, noting managerial insights, managerial implications, and contributions arising from this original study. 2 Literature Review Various studies have recognized the impacts of investing at the individual or organizational levels, yet evidence on the nature of the I-Inv under various national ecosystems is still lacking. For instance, Liu ( 2019 ) remarked that research on impact investing in general is still in its infancy. Also, a good part of the research conducted to date on I-Invs focused on the theoretical side of a set of forces that affect impact investors operating in developed countries (Clarkin & Cangioni, 2016 ; Liu, 2019 ). Despite the obvious importance of national investment levels, it is still not clear why impact investors choose to invest in one specific country rather than another, despite countries with varying investment levels sharing common borders and regions, as well as prevailing socio-political and cultural characteristics. According to Ben Letaifa ( 2016 ), regional variation of impact investing is important because it can influence the amount and viability of the regional social entrepreneurship ecosystem. Spigel ( 2017 ) claims that I-Inv is considered a significant feature of a complex system that includes economic, social and cultural forces. On the other hand, I-Inv requirements are similar to the more general requirements of entrepreneurship, as both of them need a healthy environment to operate (Diaz & Dentchev, 2021). Entrepreneurship is the foundation for I-Inv to be implemented and succeed in both developing and developed countries. This indicates that there is a strong relationship between the entrepreneurship ecosystem and the I-Inv ecosystem. According to Roundy ( 2020 ), the availability of entrepreneurs and a support ecosystem is a prerequisite for impact investors to invest in a country. In addition, impact investors can operate in a diverse ecosystem that targets different returns, including environmental, social, and governance (ESG) returns, and corporate social responsibility requirements (Roundy, Holzhauer, & Dai 2018). The similarities between the entrepreneurship ecosystem and I-Inv ecosystem can also be attributed to their ecosystem functions, as well as the complexity of investors’ characteristics and the supporting ecosystem. For both traditional investment and I-Inv there is a need for an ecosystem that spurs and facilitates investors to invest in a country. The ecosystem that incentivizes investors to invest in a country includes many things, for example, the regulatory and legal framework, fiscal system, political environment, economic climate, institutional support, and investor confidence (Jäger, Pfirrmann, Rodriguez, & Topolanek, 2019 ; Spamann, 2021 ). However, the success of the I-Inv in addressing ESG impacts depends on the IER. In this context, IER refers to the overall environment in which investments can thrive. It encompasses the infrastructure, legal framework, financial systems, government policies, and business climate that enable or hinder investment. A highly developed ecosystem typically offers stable financial markets, efficient legal systems, and supportive government policies that facilitate investments. This investment readiness is crucial in determining how attractive a country is to investors (Alexakis, Gogas, Petrella, Polemis, & Salvadè, 2024 ; Menkhoff & He, 2013 ). In practice, I-Invs are determined by a compound of multiple factors that affect the investor’s decision either to invest or not to invest. According to the OECD (2015), governments play a key role in terms of setting conditions for the enabling environment of I-Inv. In addition to the IER, other factors such as the supply, demand, and intermediaries of impact capital, as well as other ecosystem providers, such as research houses and advisory firms, are highly instrumental (Dream Impact, 2021 ). Impact investors require a specific ecosystem in which they can operate. For example, the World Bank (2021) provides insights into how emerging markets’ investment readiness, including financial systems and infrastructure, affects investment flows and economic development, according to various parameters and indicators. This is in line with the general investment environment in developing countries affecting investors’ decisions. They must decide whether to invest or not based on various factors. With regard to IER, the investment environment comprises two main dimensions: (1) whether it is characterized by a high or low level of readiness, and (2) whether the complexity of closing a deal is characterized by a high or low level of complexity. For example, high IER refers to the preparedness of the market to support and facilitate investment deals, which could include infrastructure, regulation, market maturity, and available resources (OECD, 2019; World Bank, 2021). Conversely, high DC refers to the challenges associated with investment transactions, including structure, negotiation, and legal considerations (Fuad & Venugopal 2024 ; Ghauri & Grønhaug, 2010 ; Gompers & Lerner, 2001 ; OECD, 2020). However, high DC may present higher risks, but it can yield higher returns and more significant ESG impacts when managed properly. On the other hand, excessive complexity could inhibit impact by delaying investments or making the investments less profitable, particularly in underdeveloped markets. In general, countries with high IER can attract more investors as long as investor’s needs and expectations are met (Mason & Kwok, 2010 ). 3 Framework Development To understand how IER and DC affect the success of I-Invs, we employ a game-theoretic model to analyse the interaction between governments and impact investors in the MENA region. The model explores how IER and DC influence investment decisions. This model is built based on the interaction between two main players in the ecosystem. The first player is the government, which is seeking to attract investment by making policies and regulations. The second player is the impact investors, who are seeking to invest to maximize returns while creating social/environmental impact. The game also involves strategies for the government to improve IER, reduce DC or maintain the status quo. The combinations of IER and DC analysis using this game allow for four ecosystem cases: • Case , assumed to have high IER (HIER) and low DC (LDC). • Case , assumed to have HIER and high DC (HDC). • Case , assumed to have low IER (LIER) and LDC. • Case , assumed to have LIER and HDC. The government strategy for whether to have LIER and HDC means to have weak IER, bureaucratic barriers, and regulatory uncertainty. Alternatively, the government can choose to have HIER and LDC, which indicates HIER, transparent policies, and streamlined investment processes. On the other hand, the archetypal strategies for impact investors are to (1) invest or (2) avoid investing. The impact investor can choose the strategy to avoid investing due to high risks or poor investment climate, while the converse strategy indicates that investment conditions are perceived to be favourable. Based on the previous strategies for the government and investors, the results can be expressed in a 2×2 strategic game, meaning there are four possible outcomes based on the combination of strategies chosen by both players. It is expected that the benefits and payoffs for governments are an increase in economic growth, job creation and social and environmental impact; for impact investors, the payoffs and benefits are financial returns, and social and environmental impacts. These payoffs for the government and investors are affected by the nature of DC and IER in each country. For example, DC is linked with high corruption, tax evasion and higher compliance costs in MENA countries. Therefore, government payoffs can be described in terms of resource rents measured by non-tax revenue, which averages between 5% and 15% of the GDP in MENA countries (World Bank, 2020 ). According to Transparency International ( 2023 ), corruption reduces net benefits by 1–2% of GDP. In addition, data from OECD (2022) shows that HDC increases compliance costs by 2–3%, indicating that the higher the DC, the higher the compliance costs for investors. Accordingly, the improvement in IER is associated with the fight against tax evasion and increased tax collection. The OECD (2021a) indicates that a 0.1% improvement in IER correlates with a 0.3–0.5% increase in the tax-to-GDP ratio, which is attributable mainly to reduced tax evasion. Therefore, it is assumed that tax collection (i.e., TGR, as defined below) varies with IER in the country. Based on these constructs, the government’s payoffs ( γ ) can be described by Eq. 1: γ = NTR i + TGR i * IER i - RCi (α i i) (1) Where NTR i is non-tax revenue for country i, TGR i is tax to GDP ratio for country i, IER i is the IER for country i, RC i is the rent cost (RC i (HDC) = 2%) and RCi (LDC) = 0%) and α i is the DC (α = 0% for LDC and α = 2% for HDC) for country i. Impact investors are also interested in the IER of the countries they target, and its ability to generate social impact and returns. For example, the Morgan Stanley Capital International index (MSCI, 2023) shows that improving the IER by 0.1% decreases equity risk premiums by 0.5% (specifically, according to MSCI data, a 0.5% equity risk premium reduction per 0.1 IER is scaled to the 0–10 range). Therefore, it is assumed that equity risk premiums vary with IER. According to the Global Impact Investing Network (GIIN, 2023b), I-Invs yield social returns of 3–5%, alongside financial returns. The IMF (2023) indicates that the risk-free rate of a sovereign bond in the MENA region is between 4% and 6%. However, the HDC of investment projects adds a compliance cost of 2–3% for investors (OECD, 2022). According to these rates, the investor’s payoff (β) for investing can be described by Eq. 2: β = RFR i + IERP i - α i + SI i (IER) (2) Where RFR i is the Risk-Free Rate for country i, IERP i is the IER premium for country i, α i is the DC on the investor for country i and SI i is the social impact for country i that varies with IER. If the government strategy is to choose LIER and HDC, and if the investor chooses to invest under this choice, the LIER and weak institutions and transparency limit the investor payoff, the payoff to the investor is (β). HDC reduces the government payoff (γ) by (2%), whereby the government payoff is equal to (γ) due to bureaucratic costs. However, the government could earn a rent equal to (0) under low complexity, if investors are not interested in investing even when there is HIER in the country despite good policies. This means that some countries may choose complexity for short-term rent while other countries might not, even if this discourages investment. Conversely, the government can earn a payoff equal to (γ - LDC), when there are LDC and HIER in the country that attract investors to invest, which boosts tax collection. However, when the government chooses LIER but keeps DC low, and the investor invests in the country, the government payoff is (γ-0), and the LIER will minimize investor payoff, but if the investor avoids the government payoff is (0). In general, under LDC and HIER, the government payoff (γ) from increased taxes could offset the HDC costs. The investor payoff (β) is maximized under HIER compared to LIER as long as (βHIER > βLIER). The government payoff from choosing to have HIER and HDC depends on whether the investor invests or avoids. If the investor decides to invest, the government payoff is (γ), which reflects a 2% of GDP reduction due to HDC. According to the game theory conventions, it is assumed that all players are rational, and aim to maximize their payoffs. Payoffs are influenced by the combination of IER and DC. In addition, it is assumed that the interaction between the government and impact investors is a non-zero-sum game, where collaboration can lead to mutually beneficial outcomes. Therefore, the payoffs that represent the benefits for each player in this game are determined based on their choices. The main definitions used in this strategic game and payoffs for the government and investors are explained in Table 1. 4 Methodology 4.1 Game Theory Game theory is applied in this study to analyse the interactions between impact investors and the government in order to identify how the ecosystem readiness affects impact investors. We use various proxies to measure the IER and DC in countries under investigation, with a mixed methodology combining both game theoretic modelling and pre-structured investor interviews was used to examine the interaction between two players (“government” and “impact investors”), utilizing the current investment ecosystem in the region to help determine the most likely outcomes. Therefore, the game theory employed is a form of analysis of strategic interactions where the outcome of a participant’s choice of action depends upon the actions of other participants and it can be applied in different contexts. One application could be considering the role of investors in the MENA region. It can be argued that the government’s strategy and policies made it the first mover. Other players (i.e., investors) are obliged to reactively follow this strategy. The Government’s strategy has set many rules and constraints within which the other players choose their actions. All players are assumed to maximize their payoffs. In this study, we model the cooperative spirit and the behaviour of the government and the investors. Even though both players know the best outcome, it is not necessarily achieved, because the players have different immediate interests and priorities (e.g., potential issues of trust) that affect how they interact. This illustrates the difficulty of the two players to stay in cooperation with one another, and to trust each other in the investment relationship between the government and impact investors. 4.2 Payoff Matrix Based on the previous analysis, we construct the payoff matrix for four groups of countries (Groups 1, 2, 3, and 4) based on their readiness and complexity levels. Certain countries exhibit characteristics from multiple groups, combining elements of Group 1 and Group 2 or aligning partially with Group 3 and Group 4. The IER and DC in Fig. 1 represent the payoffs of the 2x2 matrix that illustrates four possible strategic outcomes based on government and investor strategies to invest in the country. The top-left quadrant shows countries operating in an LDC ecosystem and LIER. The top-right quadrant represents countries operating in an HIER and an LDC. The bottom-left quadrant indicates countries operating in LIER and an HDC. While the bottom-right quadrant represents countries operating in an HDC ecosystem and HIER. The players in this game are the government and impact investors. The government wants to attract I-Inv to help solve social and economic challenges. The impact investors seek to make a return and social impact. The combinations of IER and DC yield four cases, as discussed earlier. The government strategies are either to choose (HDC and LIER) or (HDC and HIER). It could choose also (LDC and LIER) or (LDC and HIER) by keeping policies simple and straightforward for investors (Ghemawat, 2001 ). According to the OECD (2019a, 2019b), different levels of DC and IER affect the flow of foreign direct investment across different countries. If the government chooses HDC and LIER by implementing complex policies or regulations, the investor will choose not to invest, the payoff for the government is (0) and for the investor is (0). Conversely, under HDC, the investor may choose to invest and the payoff for the government is ( γ - α ) and for the investor is ( β ). These payoffs represent the benefits or costs to each player based on their choices. Under another alternative, the government may choose LDC and HIER, in this case, the investor may choose not to invest and the payoff for him and the government is (0). If the investor chooses to invest, the payoffs are ( γ - α ) for the government and ( β ) for the investor. The government could choose also LDC and LIER, under this case, the government rent is ( γ ), while the investor payoff is ( β ). Finally, the government payoff from choosing HDC and HIER is ( γ - α ) and the investor payoff is ( β ). Table 2 shows the payoff matrix for the government and impact investors considering all player’s strategies. In general, the level of IER and DC determine the value of government and investor payoff. 4.3 Data The data for 14 Arab countries in the MENA region during the period 2021 to 2024 were used in this study, which are classified according to their rank in the Ease of Doing Business (EoDB) (World Bank, 2020 ) classification and the Global Competitiveness Index (GCI) published by the World Economic Forum ( 2019 ). These countries are: Algeria, Bahrain, Egypt, Jordan, Kuwait, Lebanon, Morocco, Oman, Qatar, Saudi Arabia, Tunisia, United Arab Emirates (UAE), and Yemen. These countries were chosen based on their score of investment readiness and in doing business. Country-specific data was obtained from reports by the OECD (2021), IMF (2021, 2023), Transparency International ( 2023 ) and MSCI (2023). For example, the MSCI (2023) index is considered a key driver of risk and return in equity portfolios that reflect the country’s risk. It is assumed to reflect HDC in frontier markets due to liquidity risk. According to the MSCI index, countries can be classified into two types. “emerging markets” (where α = 0), such as the UAE, Saudi Arabia, Qatar, Kuwait and Egypt; and “frontier markets” (where α = 2), such as Bahrain, Morocco, Oman, Jordan and Tunisia. Other countries were classified as frontier market countries because of their under developed financial markets, smaller market capitalization, lower liquidity and facing challenges and high risks. This comprehensive approach enables an in-depth assessment of how different levels of ecosystem readiness interact with EoDB dimensions, thus offering valuable insights into I-Invs in the region. 5 Results 5.1 Grouping These countries are divided into four groups and aligned based on combining two dimensions, investment DC and IER. To assign countries to groups, the thresholds used to classify countries into groups were derived from scores on key indicators, such as the EoDB, the GCI, and the Corruption Perceptions Index (CPI) (Transparency International, 2022 ), as explained in Table 3. For example, any country that scored 75 or higher on the EoDB 70 or higher on the GCI, and 60 or higher on the CPI was considered to have a high IER. In contrast, any country that scored less than 50 on the EoDB and GCI, and less than 40 on the CPI was considered a low IER. Similarly, in countries that scored 75 or higher on the EoDB, investors spend less than 10 days and cost less than 10% of per capita income in starting a business, and investors spend less than 100 days and cost less than 50% of the value of the warehouse, was considered to have low DC. However, countries that scored less than 50 on the EoDB and investors spend more than 30 days and cost more than 30% of per capita income in starting a business and investors spend more than 200 days and cost more than 100% of the warehouse value, was considered to have HDC. Table 4 shows the DC classification of countries. To numerically illustrate the payoff for the government and investor based on the payoff matrix, we apply the normalized score of EoDB for MENA countries, assuming that the government payoff (γ) and investor return (β) vary with IER and DC. Table 5 shows the investment readiness scored by the EoDB and the DC scored by the MSCI index. Based on the EoDB rank for MENA countries, we can calculate the normalized IER score using Eq. 3: Normalized IER = 1− (Country Rank − 1/ Maximum Rank − 1) (3) In this game, we assume that the government rent is equal to γ which reflects a trade-off between tax revenue gains driven by IER and bureaucratic costs from DC. Higher IER improves tax collection, while HDC (α = 2) reduces net rents by 2% of GDP. Therefore, the government payoff (γ) is rewritten as in Eq. 4: γ = NTR + 0.4* IER- RC(α) (4) On the other hand, the impact investor return is equal to β, which is also assumed to vary with IER and DC. The investor return can be rewritten as in Eq. 5: β = RFR + 5 * IER - α + SI(IER) (5) The coefficients (0.4 and 5) in equations 4 and 5 are derived from OECD and MSCI data to scale logically with real IER country scores. The coefficient of (0.4%) in Eq. 4 is the average of a (0.1) unit improvement in institutional quality (proxied by IER), which correlates with a (0.3–0.5%) increase in tax revenue as a share of GDP (OECD, 2021). Furthermore, the coefficient of (5) in Eq. 5 is the result of a (0.1) unit of IER improvement that reduces equity risk premiums by (0.5%) multiplied by 10 to scale and align with the (0–1) IER score (MSCI, 2023). For example, the government may accept a lower payoff (γ) in the short term to attract long-term investment, while impact investors will seek to invest in HIER for better social and economic returns (β). In general, the government’s payoff depends on whether the investor invests or avoids. Table 6 shows the results of government and investor payoffs using equations 4 and 5. According to the illustrative payoff matrix in Table 6, if the government chooses high DC and the IER is low, the government’s payoff is (γ – α), and the investor’s payoff is (β). Therefore, to reach Nash equilibrium in this game, both players choose their best responses given the other player’s strategy. When both players cooperate, they maximize their payoffs. The government’s best outcome is low DC and high IER in the country, and the investor chooses to invest, whereby the government payoff will be maximized. If the government chooses high DC, it will earn less. Consequently, the government’s best strategy in this case is to create low DC and high IER, as long as the corresponding payoff is greater than in other cases. The Nash equilibrium in these interactions between the government and investors happens when the government chooses to create a low DC and high IER environment. The investor in this case will be able to make a social impact and return. The government will benefit from this investment by reducing unemployment, increasing economic growth, and solving environmental challenges. The government’s payoff represents the economic benefits of I-Inv inflows, including economic growth, employment, and social benefits (OECD, 2021). The interactions between investors and governments within each of the four studied groups are described below. 5.2 Group 1: High Readiness, Low Complexity Countries in this group are characterized by having well-developed investment ecosystems, efficient regulatory environments, strong infrastructure, and streamlined processes for starting and operating businesses. According to the World Bank (2021), these countries are top performers. Countries in this group include the UAE, Saudi Arabia, Bahrain and Oman. In this group, both investors and governments benefit from cooperation and coordination, due to a favourable investment ecosystem and simplified deal structures. The payoff matrix for Group 1 is described in Table 7. The best strategy for the government in these countries is to choose low DC and gain from 10.4–12.3%. For the investor the best strategy would be to increase investment and gain between 10.9–14.2%. In this case, investors always invest as long as their payoff is positive. For instance, the UAE has successfully improved its IER through regulatory reforms, leading to a 15% increase in FDI inflows between 2018 and 2023 (Dhaman, 2024 ). 5.3 Group 2: High Readiness, High Complexity Countries operating in Group 2 have also made significant progress in improving their business environments and strong investment ecosystems, but still face higher complexity in investment deals due to bureaucratic or regulatory challenges. In this group, despite the high readiness of the investment ecosystem, the complexity of investment deals poses challenges for both investors and governments. Countries in this group include Qatar and Kuwait. Table 8 explains the payoff matrix for countries classified in Group 2. The government in Group 2 act in the best way by choosing high complexity, while at the same time they have high IER. In this context, the government gains between 11.2–13.2%, and the investors gain from 8.6–8.9% if they choose to invest in these countries. 5.4 Group 3: Low Readiness, Low Complexity In Group 3, countries have simpler investment deal structures but lack readiness in their investment ecosystems, characterized by weak institutions, poor infrastructure, or unstable regulatory environments (Table 9). Although investment DC is low, the lack of readiness in the investment ecosystem limits the potential benefits for both investors and governments. Countries in this group have the potential to attract I-Inv, but still facing structural and bureaucratic challenges. However, some countries such as Jordan, Morocco, Egypt and Tunisia might be classified in this group if the government implement reform to reduce DC and move from HDC to LDC. In general, the government focus for Group 3 is on how to reduce DC with limited impact on the IER or the government focuses on reforming the IER with limited impact on DC. 5.5 Group 4: Low Readiness, High Complexity These countries face both high complexity in investment deals and low readiness in their investment ecosystems environment, indicating significant challenges for investors due to regulatory and institutional weaknesses (Table 10). This group encompasses countries with major bureaucratic, economic, or political instability concerns, including Algeria, Lebanon, Yemen and Libya. The payoff for countries classified in this group is limited, the government gains range from 1–7.1% and the investor gain is between 5.0–6.4%. 5.6 Regional and Country Level Data Analysis To validate our game-theoretic model, we compare our findings with structured investor interviews conducted by the United Nations Development Programme (UNDP, 2022), Pastorelli, Bala, and Barco Serrano ( 2021 ), and GIIN (2023a) at regional and country levels with main fund managers and businesses operating in emerging markets, including MENA. These pre-structured interviews give us some insight into how both players are choosing actions on the regional ecosystem and country-specific ecosystem levels. At the country level, UNDP (2022) interviews with funds and businesses in Jordan have shown that there is a lack of a unified ecosystem and multi-stakeholder collaboration, legal and regulatory challenges, and insufficient and misaligned funding mechanisms. Other challenges are related to the market size, limited access to finance and talent pool limitations, misunderstanding of I-Inv and its potential, lack of accurate data and effective communication, gender disparities and social challenges, overemphasis on tech and ICT sectors, and neglecting others. In addition, there is a need for a shift in mindset toward long-term impact. Hostile business conditions characterize the main investor perspectives regarding the investment ecosystem, especially in terms of regulatory oversight, a less predictable investment environment, lengthy and unpredictable commercial conflict resolution mechanisms, unclear and changing attitudes towards renewables, and a non-transparent and fast-changing tax system, as articulated by local investors, who also mentioned private companies’ governance and accountability standards, and limited use of public procurement to promote investment (GIIN, 2023a; UNDP, 2022). According to interviewed investors, to enhance the investment ecosystem and increase I-Inv, the government must address these challenges through collaboration, regulatory reforms, innovative financing, and cultural shifts. Key actions include creating a unified platform, updating laws, improving access to capital, standardizing impact reporting, and fostering inclusivity (UNDP, 2022). Although the main engine of growth and employment must move from government to I-Inv. Moreover, the role of government is no longer the conductor of a captive national economy, but becomes a regulator and enabler for investors to compete in global markets. Therefore, to attract more investment to the region the government’s role shifts from offering project-specific arrangements to positioning the country as an attractive investment destination with predictable rule-based conditions and offering competitive investment opportunities (GIIN, 2023a, 2023b). On the regional level, interviews conducted by Pastorelli et al. ( 2021 ), show that MENA is still developing in terms of attracting I-Inv. The majority of countries in the region lack an enabling legal and regulatory environment to attract and retain investors, the lack of regional impact funds and a lack of awareness about I-Inv from both investors and countries. According to respondents, the main obstacle to the development of impact investing in the MENA region is the higher level of multifaceted risk (political instability; economic instability resulting in devaluation risks, credit crunches, geopolitical tensions; etc.). All of these also affect exit strategies for investors, and they occur in a highly underdeveloped ecosystem (e.g. data, scarcity of vehicles and quality investment opportunities, low level of non-financial support services, etc.). Similarly, these findings are confirmed by the OECD (2021), which shows that crises in the region, limited direct trade routes, and high-risk perceptions have had a negative impact. Furthermore, there are no specific incentives for impact investors, and a lack of awareness of investment opportunities and processes. In addition, the low level of I-Inv attracted to the region is widespread in the investment ecosystem, which is not yet developed enough to attract impact investors in terms of the legal and business environment. 6 Discussion 6.1 Overview The results of the game theory used in this study are linked and aligned with pre-structured interviews that have been conducted with key ecosystem players, businesses, investors and fund managers in the region, in terms of I-Inv and IER. The payoff matrices derived for different groups of countries capture the relationship between readiness, complexity, and the preferences of both investors and governments. Moving from one group to another allows us to reflect on the optimal outcome for the government and investors in different investment ecosystem contexts. Applying the game theory to analyse the interactions between investors and governments within each group reveals the following findings. 6.2 Group Findings In Group 1 countries, which are characterized by high IER and low DC, the government’s strategy focuses on optimizing investment allocation strategies to maximize social impact and returns while ensuring compliance with regulations. Both investors and governments are likely to benefit from cooperation and transparency, leading to mutually beneficial outcomes. The social impact of investors in the host country will be reflected in reduced unemployment and poverty, increased economic growth and well-being, and improved socio-economic and environmental conditions. This represents the optimal scenario, where both government and investors achieve the highest payoffs due to reduced complexity and improved investment readiness. The government strategies in Group 2 countries, described as high IER and high DC, would include strategies to navigate complex regulatory landscapes while taking advantage of a strong investment ecosystem. Both negotiation and bargaining tactics may be crucial for impact investors to secure favourable deals, while governments may seek to balance attracting investment with protecting national interests. However, the effects on impact investors in these countries are limited to the socioeconomic and environmental conditions. In Group 3, countries with low IER and low DC, the governments may prioritize policy reforms and capacity-building efforts to improve readiness and attract investment, leading to potential opportunities for collaboration among stakeholders. For investors, the focus is on risk management strategies, considering the challenges posed by weak institutional frameworks despite simpler deal structures. The effects on socio-economic and environmental conditions are negligible. Lastly, for Group 4 countries, categorized by low IER and high DC, the analysis would include assessing the costs and benefits of investing in environments with both complexity and low readiness. Therefore, investors may adopt cautious approaches or demand higher returns to compensate for the uncertainties, while governments face pressures to address institutional deficiencies and reduce barriers to attract investment. In this case, no socio-economic and environmental effects can be materialized in these countries. 6.3 Summary The model used in this study predicts that IER significantly influences investor decisions. This aligns with findings from the OECD (2022), which reported that the vast majority (78%) of surveyed investors stated that transparent regulations were a key factor in investment location choices. This study also shows the importance of creating a sustainable development paradigm in MENA countries that is centred on I-Inv as the engine of growth and employment in the region. Governments can influence their domestic economy, thus their role is to support and enable businesses to attract I-Inv. The primary role of the government is to set a rules-based framework and standardised, predictable conditions, and, as far as possible, to create high IER and reduce DC. In short, their role is to shift their economy from a low to high IER, and to facilitate complex investment deals, so that they can almost qualify as simple. 7 Conclusion Given the findings of this analysis, policy measures to enhance IER and reduce DC can be identified. The main players in this game are the impact investors and the government. Therefore, the payoffs depend on the combination of strategies chosen by all players and are influenced by both ecosystem readiness, which increases payoffs for all players, and DC, which reduces payoffs due to increased risks and costs. In this context, both the government and impact investors achieve the best results when they cooperate. This can happen when the government follows a strategy of low DC and high IER. At the same time, the investor follows a strategy of increasing I-Inv. This means that countries in the region that would like to benefit from I-Inv must move from high DC and low IER (Group 4), from low DC and low IER (Group 3) and from high DC and high IER (Group 2) to low DC and high IER (Group 1), as summarised in Fig. 2. This, of course, would require tremendous changes in their strategies to align with investor’s needs in terms of having low DC and high IER. [Insert Fig. 2 here] Despite the importance of I-Invs and ecosystem readiness, it is clear that I-Invs without high IER will not solve all social, economic, and environmental challenges that the region faces. The fiscal pressure and government needs of many countries in the region required the government to be the first mover in this game. Governments should include I-Inv in their strategies and plans. They need to design policies to improve IER and reduce DC by simplifying regulations and reducing licensing time, which can lead to higher payoffs for all. Therefore, policymakers are advised to hold discussions with key stakeholders to support the investment ecosystem, broaden consensus on reform priorities, and identify specific actions at the national level to be pursued by the ecosystem players. The government should develop a work plan to revise the current approach and engage all players by sharing views and ongoing activities on the investment ecosystem. This could lead to a broad consensus on reform priorities and public support. The government should analyse the potential options for improvement of the current activities on the investment ecosystem to identify additional initiatives to foster the I-Inv ecosystem. Based on the government’s actions and the potential payoffs, investors can choose their strategies, leading to dynamic interactions to achieve mutually beneficial outcomes. Research limitations/implications The main limitations of this study are related to the availability of up-to-date coverage of scores and indices that are used in this study. Furthermore, there are many factors that affect investors’ decisions that need to be included in the analysis, such as geopolitical risks. The results of this study were based on limited factors, thus, future research should include more factors and employ more dynamic models to explain reforms over time. Declarations Data availability The findings of this study are based on data obtained from the World Bank’s Ease of Doing Business Index (2020) and the Global Competitiveness Index of the World Economic Forum ( 2019 ). Country-specific indicators were obtained from the Organization for Economic Cooperation and Development (OECD) (2021), International Monetary Fund ( 2021 , 2023 ), Transparency International ( 2023 ) and Morgan Stanley Capital International (MSCI) (2023) reports. All datasets are accessible through the respective organizations’ official platforms. References Akin I, Akin M (2025) Promoting sustainable practices through green investments in the United Kingdom real estate industry. Sustain Dev 33(1):1526–1544. https://doi.org/10.1002/sd.3194 Alexakis C, Gogas P, Petrella G, Polemis M, Salvadè F (2024) The determinants of investment readiness for SMEs in Europe: An empirical investigation with machine learning techniques. SSRN Article 4906983. http://dx.doi.org/10.2139/ssrn.4906983 Ben Letaifa S (2016) How social entrepreneurship emerges, develops and internationalises during political and economic transitions. Eur J Int Manage 10(4):455–466. https://doi.org/10.1504/EJIM.2016.077424 Clarkin J, Cangioni L, C (2016) Impact Investing: A Primer and Review of the Literature. Entrepreneurship Res J 6(2):135–173. https://doi.org/10.1515/erj-2014-0011 Dhaman (2024) Investment climate in Arab countries 2024. Retrieved from https://www.dhaman.org/climate-reports/Climate%20E%202024.pdf Diaz Gonzalez A, Dentchev NA (2021) Ecosystems in support of social entrepreneurs: a literature review. Social Enterp J 17(3):329–360. https://doi.org/10.1108/SEJ-08-2020-0064 Dream Impact (2021) Ways Forward For a Collaborative Impact Ecosystem: Insights & Conclusions. Retrieved from: https://www.dreamimpacthk.com/collaborative-impact-ecosystem-insights-conclusions/ Fawaz A (2025) Locational advantages and foreign direct investment in MENA: A comprehensive analysis of institutional and economic factors. Transnatl Corporations Rev 17(2):200131. https://doi.org/10.1016/j.tncr.2025.200131 Finance Center for South-South Cooperation (2023) Impact investing. Springer, Singapore. https://doi.org/10.1007/978-981-99-4935-9_1 Fuad M, Venugopal A (2024) Deal completion in mergers and acquisitions: past accomplishment and future direction. Cross Cult Strategic Manage 31(1):1–25. https://doi.org/10.1108/CCSM-02-2022-0034 Ghauri P, Grønhaug K (2010) Research methods in business studies: A practical guide. Financial Times/Prentice Hall, London Ghemawat P (2001) Distance still matters: The hard reality of global expansion. Harvard Business Rev 79(8):137–162 Global Impact Investing Network (2023a) Annual Impact Investor Survey. https://thegiin.org/impact-investor-survey/ Global Impact Investing Network (2023b) Impact investment trends in emerging markets: Survey of 200 institutional investors across Africa, MENA, and Asia. Retrieved from Gompers P, Lerner J (2001) The venture capital cycle. MIT Press, Cambridge, MA Hoskisson RE, Eden L, Lau CM, Wright M (2000) Strategy in emerging economies. Acad Manag J 43(3):249–267. http://dx.doi.org/10.2307/1556394 Huppé GA (2014), July 24 Building impact investment readiness. Stanford Social Innovation Review . https://doi.org/10.48558/67EQ-RM09 International Monetary Fund (2021) Network Determinants of Cross-Border Merger and Acquisition Decisions. Working Papers. WP/19/264 International Monetary Fund (2023) Regional economic outlook: Middle East and Central Asia. Retrieved from https://www.imf.org/en/Publications/REO/MECA/Issues/2023/10/12/regional-economic-outlook-mcd-october-2023 Jäger U, Pfirrmann J, Rodriguez A, Topolanek D (2019) The impact investment ecosystem in Central America. Status quo and opportunities for a regional advisory board within the global movement of impact investment Costa Rica. VIVA Idea, San José Kesselring A (2021) Impact investment – An ecosystem view. Retrieved from https://www.interregeurope.eu/sites/default/files/inline/ASHOKA_-Alexandre_Kesselring.pdf Klapper L, Love I (2010) The impact of the financial crisis on new firm registration. SSRN Article 1641446. http://dx.doi.org/10.2139/ssrn.1641446 Kumar V, Dua P (2024) What explains foreign portfolio investment inflows to BRICS countries? Econ Anal Policy 82:32–46. https://doi.org/10.1016/j.eap.2024.02.033 Levy B (2025) Global M&A industry trends. PricewaterhouseCoopers (PwC). Retrieved from: https://www.pwc.com/gx/en/services/deals/trends.html Liu C (2019) Impact investing: A review of literature and ecosystem. In J. Puaschunder (Ed.), Intergenerational governance and leadership in the corporate world: Emerging research and opportunities (pp. 191–217). Hershey, PA: IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-5225-8003-4.ch010 Lustenberger M, Malešević S, Spychiger F (2021) Ecosystem readiness: Blockchain adoption is driven externally. Front Blockchain 5(4). Article 720454. https://doi.org/10.3389/fbloc.2021.720454 Mason C, Kwok J (2010) Investment readiness programmes and access to finance: A critical review of design issues. Local Econ 25(4):269–292. http://dx.doi.org/10.1080/02690942.2010.504570 Mdanat M (2022) The effects of inclusive business models on development outcomes in developing countries. Int J Dev Confl 11(2):132–152 Menkhoff L, He L (2013) Financial market development and investment ecosystems: A comparative analysis. J Int Bus Stud 44(2):148–164 Morgan Stanley Capital International Index (2023) Country risk premiums report. Retrieved from https://www.msci.com Ndegwa N (2022) Investment readiness for micro small and medium enterprises. Diamond Trust Bank, Nairobi Organisation for Economic Co-operation and Development (2015) Social Impact Investment: Building the Evidence Base. OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264233430-en Organisation for Economic Co-operation and Development (2019a) OECD investment policy perspectives. OECD Publishing, Paris Organisation for Economic Co-operation and Development (2019b) Social impact investment: The impact imperative for sustainable development. Retrieved from https://www.oecd-ilibrary.org/development/social-impact-investment-2019_9789264311299-en Organisation for Economic Co-operation and Development (2020) Investment ecosystems in emerging economies: Challenges and opportunities. OECD Publishing, Paris Organisation for Economic Co-operation and Development (2021a) Middle East and North Africa investment policy perspectives. https://doi.org/10.1787/6d84ee94-en Organisation for Economic Co-operation and Development (2021b) Tax administration 2021. Retrieved from https://www.oecd.org/en/publications/tax-administration-2021_cef472b9-en.html Pastorelli G, Bala A, Barco Serrano S (2021) Study on the opportunities for impact investing to promote the social and green economy in the southern neighbourhood. European Commission Transports & Infrastructures Expertise Group, Brussels Roundy PT (2020) Regional differences in impact investment: A theory of impact investing ecosystems. Social Responsib J 16(4):467–485. http://dx.doi.org/10.1108/SRJ-11-2018-0302 Roundy PT, Holzhauer H, Dai Y (2017) Finance or philanthropy? Understanding the motivations and criteria of impact investors. Social Responsib J 13(3):419–512. http://dx.doi.org/10.1108/SRJ-08-2016-0135 Sall MCA, Burlea-Schiopoiu A (2021) An analysis of the effects of public investment on labor demand through the channel of economic growth with a focus on socio-professional categories and gender. J Risk Financial Manage 14(12). Article 580. https://doi.org/10.3390/jrfm14120580 Scottish Marine Environmental Enhancement Fund (2024) Impact report 2. Retrieved from https://smeef.scot/about/#what-is-smeef Shuwaikh F, Hughes M, Brinette S, Khemiri S (2024) Investment decisions under uncertainty: Corporate venture capital as a real option. Int J Finance Econ 29(2):2452–2471. https://doi.org/10.1002/ijfe.2794 Spamann H (2021), July 1 Indirect investor protection: The investment ecosystem and its legal underpinnings (Law Working Paper No. 594/2021). Harvard University and ECGI. Retrieved from https://www.ecgi.global/publications/working-papers/indirect-investor-protection-the-investment-ecosystem-and-its-legal Spigel B (2017) The Relational Organization of Entrepreneurial Ecosystems. Entrepreneurship Theory Pract 41(1):49–72. https://doi.org/10.1111/etap.12167 Tabash MI, Farooq U, Matar A, Al-Absy MSM (2024) Role of governance in attracting foreign direct investment inflow: Empirical evidence from South Asia region. Cogent Econ Finance 12(1). Article 2358930. https://doi.org/10.1080/23322039.2024.2358930 Transparency International (2022) Corruption Perceptions Index. Retrieved from https://www.transparency.org/en/publications/corruption-perceptions-index-2022 Transparency International (2023) Corruption Perceptions Index. Retrieved from https://www.transparency.org/en/publications/corruption-perceptions-index-2023 Trelstad B (2016) Impact investing: A brief history. Capitalism Soc 11(2):1–14 United Nations Development Programme (2022) Seeds of impact: The impact journey of funds and businesses. UNDP, New York, NY World Bank (2020) Ease of doing business report. Retrieved from https://documents1.worldbank.org/curated/en/688761571934946384/pdf/Doing-Business-2020-Comparing-Business-Regulation-in-190-Economies.pdf World Bank (2023a) Worldwide Bureaucracy Indicators. Retrieved from https://datacatalog.worldbank.org/search/dataset/0038132 World Bank (2023b) Revenue statistics in Middle East and North Africa. Retrieved from https://data.worldbank.org/indicator/GC.TAX.TOTL.GD.ZS World Economic Forum (2019) Global competitiveness report. Retrieved from https://www3.weforum.org/docs/WEF_TheGlobalCompetitivenessReport2019.pdf Tables Table 1: Definition of Main Variables Variable Name Explanation Value / Score IER Investment Ecosystem Readiness. Measures institutional quality, transparency, and ease of doing business. Normalized score (0 – 1), where 1 = highest readiness (HIER), 0 = lowest (LIER). HIER High Investment Ecosystem Readiness. Strong governance, and efficient processes. IER=1 LIER Low Investment Ecosystem Readiness. Bureaucratic hurdles and weak institutions. IER=0 DC Deal Complexity. Compliance costs from bureaucratic complexity. Reflects regulatory burden and compliance costs. α HDC Compliance Cost. High Deal Complexity. Fixed cost for investors under HDC, complex regulations and lengthy approvals. α =2% LDC Compliance Cost. Low Deal Complexity. Fixed cost for investors under LDC streamlined processes and minimal red tape. α =0% γ Government payoff under investment Benefits for the governments derive from non-tax revenue. γ = NTR + 0.4*IER – RC* α NTR Non tax revenue Averaging 5% to 15% of GDP in MENA. TGR(IER) Government payoff varies with IER. Tax to GDP Ratio is improves as IER score increases. 0.1 IER score increase lead to 0.3%–0.5% tax to GDP rise. Average (0.4) β Investor payoff under investment Economic and social returns for investors. β = RFR + 5·IER + α + SI IERP(IER) Investment ecosystem readiness premium varies with IER Additional return from investment. 0.5% reduction in equity risk premium per 0.1 IER increase scaled to (5*IER) SI Social Impact Non-financial returns from impact investments. 3% if LIER, 5% if HIER RC Rent cost Economic losses due to bureaucracy and corruption. 1% of GDP per unit of DC if LDC, 2% of GDP if HDC. Note. IER, HIER and LIER are Normalized score (0 – 1), where 1 = highest readiness, 0 = lowest obtained from World Bank (2020). Table 2: Government, Investor Payoff Matrix Government LIER HIER Investor LDC β (γ) β (γ) HDC β (γ – α) β (γ – α) Note. Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. β varies with IER, α=0 if LDC, α=2 if HDC. Table 3: IER Classification of Countries Groups Dimension Indicator High Readiness Low Readiness IER Ease of Doing Business Score ≥ 75 < 50 Global Competitiveness Index ≥ 70 < 50 Corruption Perceptions Index ≥ 60 < 40 Source: Ease of Doing Business Report (World Bank, 2020), Global Competitiveness Report (WEF, 2019), and Corruption Perceptions Index (Transparency International, 2022). Table 4: DC Classification of Countries Groups Dimension Indicator Low Complexity High Complexity DC Starting a Business: Time 30 days Starting a Business: Cost 30% of income per capita Dealing with Construction Permits: Time 200 days Dealing with Construction Permits: Cost 100% of warehouse value Ease of Doing Business Score ≥ 75 < 50 Source: Ease of Doing Business Report (World Bank, 2020), Global Competitiveness Report (WEF, 2019), and Corruption Perceptions Index (Transparency International, 2022). Table 5: Ease of Doing Business and MSCI Index Country Ease of Doing Business MSCI Rank IER Score Frontier Markets Emerging Markets UAE 16 0.92 - x Bahrain 43 0.77 x - Morocco 53 0.72 x - Saudi Arabia 62 0.67 - x Oman 68 0.64 x - Jordan 75 0.60 x - Qatar 77 0.59 - x Tunisia 78 0.59 x - Kuwait 83 0.56 - x Egypt 114 0.39 - x Lebanon 143 0.24 - - Algeria 157 0.16 - - Libya 186 0.01 - - Yemen 187 0.00 - - Source: World Bank (2020), MSCI (2023). Table 6: Government, Investor Payoffs (in % of GDP) Country IER MSCI DC RC RFR IERP (5*IER) SI(IER) Investor Payoff NTR TGR (0.4*IER) Government Payoff Rank Score UAE 16 0.92 EM 0.0 1.0% 5.0 4.60 4.6 14.2 10.0 0.37 10.4 Bahrain 43 0.77 EM 0.0 1.0% 5.0 3.85 3.5 12.3 9.5 0.31 9.8 Morocco 53 0.72 FM 2.0 2.0% 6.0 3.60 2.9 10.5 8.0 0.29 6.3 Saudi Arabia 62 0.67 EM 0.0 1.0% 5.0 3.35 3.4 11.7 12.0 0.27 12.3 Oman 68 0.64 FM 0.0 1.0% 5.5 3.20 2.2 10.9 11.0 0.26 11.3 Jordan 75 0.60 FM 2.0 2.0% 6.5 3.00 1.8 9.3 7.5 0.24 5.7 Qatar 77 0.59 EM 2.0 2.0% 5.0 2.95 3.0 8.9 15.0 0.24 13.2 Tunisia 78 0.59 FM 2.0 2.0% 6.5 2.95 1.8 9.2 6.5 0.24 4.7 Kuwait 83 0.56 EM 2.0 2.0% 5.0 2.80 2.8 8.6 13.0 0.22 11.2 Egypt 114 0.39 FM 2.0 2.0% 7.0 1.95 0.4 7.3 7.0 0.16 5.2 Lebanon 143 0.24 - 2.0 2.0% 7.0 1.20 0.2 6.4 4.0 0.10 2.1 Algeria 157 0.16 - 2.0 2.0% 7.0 0.80 4.6 5.9 9.0 0.06 7.1 Libya 186 0.01 - 2.0 2.0% 7.0 0.05 3.5 5.1 5.0 0.00 3.0 Yemen 187 0.00 - 2.0 2.0% 7.0 0.00 2.9 5.0 3.0 0.00 1.0 Sources: World Bank (2023a), IMF (2023), OECD (2021), Transparency International (2023), MSCI (2023), GIIN (2023), and OECD (2023a). Note. EM refers to Emerging Market and FM refers to Frontier Market. DC, α=0 if LDC, α=2 if HDC. Rent cost (RC): 1% if LDC, 2% if HDC. Table 7: Maximum Payoff Matrix for Group 1 (in % of GDP) Government LIER HIER Investor LDC {6.5 – 8.0}, {4.7 – 6.3} {10.9 - 14.2} , {10.4 - 12.3} HDC {5.0 – 6.4}, {1.0 – 7.1} {8.6 – 8.9}, {11.2 -13.2} Note. Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. β varies with IER, α=0 if LDC, α=2 if HDC. Table 8: Maximum Payoff Matrix for Group 2 (in % of GDP) Government LIER HIER Investor LDC {6.5 – 8.0}, {4.7 – 6.3} {10.9 - 14.2} , {10.4 - 12.3} HDC {5.0 – 6.4}, {1.0 – 7.1} {8.6 – 8.9}, {11.2 -13.2} Note. Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. β varies with IER, α=0 if LDC, α=2 if HDC. Table 9: Maximum Payoff Matrix for Group 3 (in % of GDP) Government LIER HIER Investor LDC {6.5 – 8.0}, {4.7 – 6.3} {10.9 - 14.2} , {10.4 - 12.3} HDC {5.0 – 6.4}, {1.0 – 7.1} {8.6 – 8.9}, {11.2 -13.2} Note. Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. β varies with IER, α=0 if LDC, α=2 if HDC. Table 10: Maximum Payoff Matrix for Group 4 (in % of GDP) Government LIER HIER Investor LDC {6.5 – 8.0}, {4.7 – 6.3} {10.9 - 14.2} , {10.4 - 12.3} HDC {5.0 – 6.4}, {1.0 – 7.1} {8.6 – 8.9}, {11.2 -13.2} Note. Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. β varies with IER, α=0 if LDC, α=2 if HDC. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7442973","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":504660049,"identity":"9e709776-4462-4987-bf30-e14857d673d1","order_by":0,"name":"Metri Mdanat","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYBACgwNAIoHhMGMDiPeBgQ0syMDAg1uL5QFmkJbnIC2MjTOI0WIP0sLA8B+spRmq0ACvw8yO9x/78IDhtmz/7Obnj21+8SU2sDdvk2CQscGt5cxh5hkJDLeNZ9w5Ztic28eW2MBzrEyCgScNt5YbycxAv9xObLiRANTSA9QikWMG1HIYpxaD+49BWg4nzr+R/rHZEqRF/g0BLTeYIVo23MgxbGb4AbKFh4CWM8nGDAkGh4033sgpnNnbwGbcxpNWbJGAxy8Gxw8+ZvxRcVh23o30DR9+/Dkm289+eOONjz24QwyqEUozth2DRGZiDwEdCPCnBsr4QbSWUTAKRsEoGP4AALh6XIIxZUrSAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-5577-8627","institution":"German Jordanian University","correspondingAuthor":true,"prefix":"","firstName":"Metri","middleName":"","lastName":"Mdanat","suffix":""},{"id":504660072,"identity":"9b2f98e6-dd35-4ee6-8e5e-25db13297444","order_by":1,"name":"Andrey Timofeev","email":"","orcid":"","institution":"Georgia State University","correspondingAuthor":false,"prefix":"","firstName":"Andrey","middleName":"","lastName":"Timofeev","suffix":""},{"id":504660098,"identity":"be5be4e6-b846-4679-a697-70672bd04389","order_by":2,"name":"Ghazi Samawi","email":"","orcid":"","institution":"German Jordanian University","correspondingAuthor":false,"prefix":"","firstName":"Ghazi","middleName":"","lastName":"Samawi","suffix":""},{"id":504660099,"identity":"82f6cb54-d383-447e-9a3c-ef8ea2feb84f","order_by":3,"name":"Omar Bwaliez","email":"","orcid":"","institution":"German Jordanian University","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Bwaliez","suffix":""}],"badges":[],"createdAt":"2025-08-23 19:22:05","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7442973/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7442973/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89916915,"identity":"aa5a6412-67ed-4ec2-9f72-2d338ee90122","added_by":"auto","created_at":"2025-08-26 12:04:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68874,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7442973/v1/14fb90c22da71a959d0b29e6.png"},{"id":89916916,"identity":"881546eb-9a57-48b6-8df9-53597b74a3a9","added_by":"auto","created_at":"2025-08-26 12:04:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68987,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7442973/v1/ae75ad686dd23b2cf60a2d3c.png"},{"id":89918446,"identity":"d4857175-fc60-4ff8-9375-7a3fdf5b20d4","added_by":"auto","created_at":"2025-08-26 12:20:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1332620,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7442973/v1/8327bdff-2fc7-41bc-a722-599b5f3a6734.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eEnhancing Investment Ecosystem Readiness: A Game-Theoretic Model of Impact Investment in the MENA Region\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 Investment Ecosystem\u003c/h2\u003e\u003cp\u003eInvestment composition varies across countries, including domestic and foreign, short-term and long-term, as well as direct and indirect investments. The nature of investments depends on their purpose, whether aimed at generating immediate returns or fostering long-term economic growth. Traditional investments have primarily focused on economic growth and employment (Sal \u0026amp; Burlea-Schiopoiu, 2021). However, these investments alone have not effectively addressed all socio-economic and environmental challenges that regions such as MENA seek to achieve (Organisation for Economic Co-operation and Development [OECD], 2021). Consequently, impact investment (I-Inv) has emerged as a strategic approach to mobilize capital for addressing these challenges, integrating financial returns with measurable social and environmental benefits.\u003c/p\u003e\u003cp\u003eI-Inv, also known as \u0026ldquo;sustainable\u0026rdquo; or \u0026ldquo;social\u0026rdquo; investment (Finance Center for South-South Cooperation, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), aims to foster inclusive economic growth (Mdanat, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). I-Invs target markets at various growth stages, to generate measurable social and financial returns. According to Kesselring (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), I-Inv is targeted at empowering social entrepreneurs to solve societal problems and to respond to market failure. It seeks to enable social-oriented businesses (and community organizations) to generate societally beneficial impacts, while making a profit and exploiting market opportunities (Shuwaikh, Hughes, Brinette, \u0026amp; Khemiri, 2023).\u003c/p\u003e\u003cp\u003eHowever, the limited inflow of I-Inv to the MENA region (hereinafter \u0026ldquo;the region\u0026rdquo;) is attributed to the relatively small economies of most regional countries, which are typically characterized by small market sizes and limited purchasing power, aligned with middle-income countries. The OECD (2021) highlights that investors intrinsically seek large markets, suggesting that MENA\u0026rsquo;s fragmented economies may pose challenges for I-Inv inflows to the region. A critical factor influencing these inflows is the investment ecosystem readiness (IER) of a country.\u003c/p\u003e\u003cp\u003eIER refers to the capacity of a country to meet the specific needs and expectations of investors, including stakeholders who participate in or support the investment ecosystem at a country level (Hupp\u0026eacute;, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ndegwa, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). IER has been described in terms of traditional indicators like return on investment, long-term commitment (Scottish Marine Environmental Enhancement Fund, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and availability of resources (Lustenberger, Malešević, \u0026amp; Spychiger \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), especially in the context of raising external equity finance (Mason \u0026amp; Kwok, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile IER pertains mainly to the macroeconomic dimension of I-Inv, deal complexity (DC) refers to the level of difficulty and challenges involved in executing a business transaction, such as a merger, acquisition, partnership, or large-scale contract (International Monetary Fund [IMF], 2021). It encompasses various factors that can complicate negotiations, due diligence, structuring, and finalization of the deal (Levy, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDepending on the nature of impact investors who seek to invest in countries, the readiness of the ecosystem can be crucial for I-Invs (Klapper \u0026amp; Love, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). It pertains to how both ecosystem conditions and deal closure (i.e., DC) in target countries determine the success of I-Invs. IER involves numerous interrelated factors, but the effect of investment ecosystems on I-Invs has received little attention in related studies, despite recent research highlighting the importance of attracting more investment to MENA (Kumar \u0026amp; Dua, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Fawaz, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This study seeks to contribute to addressing this gap in existing literature.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Study Context\u003c/h2\u003e\u003cp\u003eThis study aims to explore the relationship between IER, DC, and I-Inv inflows in the MENA region. The key questions that this study tries to answer are:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eWhat factors influence impact investors\u0026rsquo; decisions in the MENA region?\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHow does IER affect investment attractiveness?\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHow does DC impact the likelihood of attracting I-Inv?\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eWhat policy measures can governments implement to optimize investment conditions?\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe primary objective of this study is to analyse how investment readiness and DC influence the strategies of countries and impact investors, adding to a strand of longstanding research on this issue that has yet to explore MENA in detail (Gompers \u0026amp; Lerner, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Hoskisson, Eden, Lau, \u0026amp; Wright, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Tabash, Farooq, Matar, \u0026amp; Al-Absy, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to Menkhoff and He (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), government strategies and DC interact with the investment ecosystem, which moderates the negative effect of complexity on investors and the financial markets. Akin and Akin (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) examined the role of government strategies in creating complex investment deals, emphasizing the role of government in shaping an investment-friendly environment.\u003c/p\u003e\u003cp\u003eThis study contributes to building on the existing literature by bridging the gap between theory and practice through examining how ecosystem readiness influences I-Inv and supports sustained economic growth. To address these issues, this study examines investment decision-making choices in diverse economic contexts by investigating how IER could assist impact investors in the MENA region. While employing pre-structured interviews with main investors and stakeholders in the region, the emphasis is on the systematic use of the game theory modelling of various interrelated factors that determine a country\u0026rsquo;s IER and performance. Following this introduction, section 2 reviews existing literature on I-Inv and IER. Section 3 presents the theoretical framework. Section 4 describes the methodology, including data sources and game-theoretic modelling. Section 5 presents the results, which are discussed in section 6 and concluded in section 7, noting managerial insights, managerial implications, and contributions arising from this original study.\u003c/p\u003e\u003c/div\u003e"},{"header":"2 Literature Review","content":"\u003cp\u003eVarious studies have recognized the impacts of investing at the individual or organizational levels, yet evidence on the nature of the I-Inv under various national ecosystems is still lacking. For instance, Liu (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) remarked that research on impact investing in general is still in its infancy. Also, a good part of the research conducted to date on I-Invs focused on the theoretical side of a set of forces that affect impact investors operating in developed countries (Clarkin \u0026amp; Cangioni, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liu, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Despite the obvious importance of national investment levels, it is still not clear why impact investors choose to invest in one specific country rather than another, despite countries with varying investment levels sharing common borders and regions, as well as prevailing socio-political and cultural characteristics. According to Ben Letaifa (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), regional variation of impact investing is important because it can influence the amount and viability of the regional social entrepreneurship ecosystem.\u003c/p\u003e\u003cp\u003eSpigel (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) claims that I-Inv is considered a significant feature of a complex system that includes economic, social and cultural forces. On the other hand, I-Inv requirements are similar to the more general requirements of entrepreneurship, as both of them need a healthy environment to operate (Diaz \u0026amp; Dentchev, 2021). Entrepreneurship is the foundation for I-Inv to be implemented and succeed in both developing and developed countries. This indicates that there is a strong relationship between the entrepreneurship ecosystem and the I-Inv ecosystem. According to Roundy (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the availability of entrepreneurs and a support ecosystem is a prerequisite for impact investors to invest in a country.\u003c/p\u003e\u003cp\u003eIn addition, impact investors can operate in a diverse ecosystem that targets different returns, including environmental, social, and governance (ESG) returns, and corporate social responsibility requirements (Roundy, Holzhauer, \u0026amp; Dai 2018). The similarities between the entrepreneurship ecosystem and I-Inv ecosystem can also be attributed to their ecosystem functions, as well as the complexity of investors\u0026rsquo; characteristics and the supporting ecosystem.\u003c/p\u003e\u003cp\u003eFor both traditional investment and I-Inv there is a need for an ecosystem that spurs and facilitates investors to invest in a country. The ecosystem that incentivizes investors to invest in a country includes many things, for example, the regulatory and legal framework, fiscal system, political environment, economic climate, institutional support, and investor confidence (J\u0026auml;ger, Pfirrmann, Rodriguez, \u0026amp; Topolanek, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Spamann, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, the success of the I-Inv in addressing ESG impacts depends on the IER. In this context, IER refers to the overall environment in which investments can thrive. It encompasses the infrastructure, legal framework, financial systems, government policies, and business climate that enable or hinder investment. A highly developed ecosystem typically offers stable financial markets, efficient legal systems, and supportive government policies that facilitate investments. This investment readiness is crucial in determining how attractive a country is to investors (Alexakis, Gogas, Petrella, Polemis, \u0026amp; Salvad\u0026egrave;, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Menkhoff \u0026amp; He, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn practice, I-Invs are determined by a compound of multiple factors that affect the investor\u0026rsquo;s decision either to invest or not to invest. According to the OECD (2015), governments play a key role in terms of setting conditions for the enabling environment of I-Inv. In addition to the IER, other factors such as the supply, demand, and intermediaries of impact capital, as well as other ecosystem providers, such as research houses and advisory firms, are highly instrumental (Dream Impact, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Impact investors require a specific ecosystem in which they can operate. For example, the World Bank (2021) provides insights into how emerging markets\u0026rsquo; investment readiness, including financial systems and infrastructure, affects investment flows and economic development, according to various parameters and indicators. This is in line with the general investment environment in developing countries affecting investors\u0026rsquo; decisions. They must decide whether to invest or not based on various factors. With regard to IER, the investment environment comprises two main dimensions: (1) whether it is characterized by a high or low level of readiness, and (2) whether the complexity of closing a deal is characterized by a high or low level of complexity.\u003c/p\u003e\u003cp\u003eFor example, high IER refers to the preparedness of the market to support and facilitate investment deals, which could include infrastructure, regulation, market maturity, and available resources (OECD, 2019; World Bank, 2021). Conversely, high DC refers to the challenges associated with investment transactions, including structure, negotiation, and legal considerations (Fuad \u0026amp; Venugopal \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ghauri \u0026amp; Gr\u0026oslash;nhaug, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gompers \u0026amp; Lerner, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; OECD, 2020). However, high DC may present higher risks, but it can yield higher returns and more significant ESG impacts when managed properly. On the other hand, excessive complexity could inhibit impact by delaying investments or making the investments less profitable, particularly in underdeveloped markets. In general, countries with high IER can attract more investors as long as investor\u0026rsquo;s needs and expectations are met (Mason \u0026amp; Kwok, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e"},{"header":"3 Framework Development","content":"\u003cp\u003eTo understand how IER and DC affect the success of I-Invs, we employ a game-theoretic model to analyse the interaction between governments and impact investors in the MENA region. The model explores how IER and DC influence investment decisions. This model is built based on the interaction between two main players in the ecosystem. The first player is the government, which is seeking to attract investment by making policies and regulations. The second player is the impact investors, who are seeking to invest to maximize returns while creating social/environmental impact. The game also involves strategies for the government to improve IER, reduce DC or maintain the status quo. The combinations of IER and DC analysis using this game allow for four ecosystem cases:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026bull; Case\u003c/strong\u003e, assumed to have high IER (HIER) and low DC (LDC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026bull; Case\u003c/strong\u003e, assumed to have HIER and high DC (HDC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026bull; Case\u003c/strong\u003e, assumed to have low IER (LIER) and LDC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026bull; Case\u003c/strong\u003e, assumed to have LIER and HDC.\u003c/p\u003e\n\u003cp\u003eThe government strategy for whether to have LIER and HDC means to have weak IER, bureaucratic barriers, and regulatory uncertainty. Alternatively, the government can choose to have HIER and LDC, which indicates HIER, transparent policies, and streamlined investment processes.\u003c/p\u003e\n\u003cp\u003eOn the other hand, the archetypal strategies for impact investors are to (1) invest or (2) avoid investing. The impact investor can choose the strategy to avoid investing due to high risks or poor investment climate, while the converse strategy indicates that investment conditions are perceived to be favourable.\u003c/p\u003e\n\u003cp\u003eBased on the previous strategies for the government and investors, the results can be expressed in a 2\u0026times;2 strategic game, meaning there are four possible outcomes based on the combination of strategies chosen by both players. It is expected that the benefits and payoffs for governments are an increase in economic growth, job creation and social and environmental impact; for impact investors, the payoffs and benefits are financial returns, and social and environmental impacts. These payoffs for the government and investors are affected by the nature of DC and IER in each country.\u003c/p\u003e\n\u003cp\u003eFor example, DC is linked with high corruption, tax evasion and higher compliance costs in MENA countries. Therefore, government payoffs can be described in terms of resource rents measured by non-tax revenue, which averages between 5% and 15% of the GDP in MENA countries (World Bank, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to Transparency International (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), corruption reduces net benefits by 1\u0026ndash;2% of GDP. In addition, data from OECD (2022) shows that HDC increases compliance costs by 2\u0026ndash;3%, indicating that the higher the DC, the higher the compliance costs for investors. Accordingly, the improvement in IER is associated with the fight against tax evasion and increased tax collection. The OECD (2021a) indicates that a 0.1% improvement in IER correlates with a 0.3\u0026ndash;0.5% increase in the tax-to-GDP ratio, which is attributable mainly to reduced tax evasion. Therefore, it is assumed that tax collection (i.e., TGR, as defined below) varies with IER in the country. Based on these constructs, the government\u0026rsquo;s payoffs (\u003cstrong\u003e\u0026gamma;\u003c/strong\u003e) can be described by Eq.\u0026nbsp;1:\u003c/p\u003e\n\u003cp\u003e\u0026gamma;\u0026thinsp;=\u0026thinsp;NTR\u003csub\u003ei\u003c/sub\u003e + TGR\u003csub\u003ei\u003c/sub\u003e * IER\u003csub\u003ei\u003c/sub\u003e - RCi (\u0026alpha;\u003csub\u003ei\u003c/sub\u003e i) (1)\u003c/p\u003e\n\u003cp\u003eWhere NTR\u003csub\u003ei\u003c/sub\u003e is non-tax revenue for country i, TGR\u003csub\u003ei\u003c/sub\u003e is tax to GDP ratio for country i, IER\u003csub\u003ei\u003c/sub\u003e is the IER for country i, RC\u003csub\u003ei\u003c/sub\u003e is the rent cost (RC\u003csub\u003ei\u003c/sub\u003e (HDC)\u0026thinsp;=\u0026thinsp;2%) and RCi (LDC)\u0026thinsp;=\u0026thinsp;0%) and \u003cstrong\u003e\u0026alpha;\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ei\u003c/strong\u003e\u003c/sub\u003e is the DC (\u0026alpha;\u0026thinsp;=\u0026thinsp;0% for LDC and \u0026alpha;\u0026thinsp;=\u0026thinsp;2% for HDC) for country i.\u003c/p\u003e\n\u003cp\u003eImpact investors are also interested in the IER of the countries they target, and its ability to generate social impact and returns. For example, the Morgan Stanley Capital International index (MSCI, 2023) shows that improving the IER by 0.1% decreases equity risk premiums by 0.5% (specifically, according to MSCI data, a 0.5% equity risk premium reduction per 0.1 IER is scaled to the 0\u0026ndash;10 range). Therefore, it is assumed that equity risk premiums vary with IER.\u003c/p\u003e\n\u003cp\u003eAccording to the Global Impact Investing Network (GIIN, 2023b), I-Invs yield social returns of 3\u0026ndash;5%, alongside financial returns. The IMF (2023) indicates that the risk-free rate of a sovereign bond in the MENA region is between 4% and 6%. However, the HDC of investment projects adds a compliance cost of 2\u0026ndash;3% for investors (OECD, 2022). According to these rates, the investor\u0026rsquo;s payoff (\u0026beta;) for investing can be described by Eq.\u0026nbsp;2:\u003c/p\u003e\n\u003cp\u003e\u0026beta;\u0026thinsp;=\u0026thinsp;RFR\u003csub\u003ei\u003c/sub\u003e + IERP\u003csub\u003ei\u003c/sub\u003e - \u0026alpha;\u003csub\u003ei\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;SI\u003csub\u003ei\u003c/sub\u003e(IER) (2)\u003c/p\u003e\n\u003cp\u003eWhere RFR\u003csub\u003ei\u003c/sub\u003e is the Risk-Free Rate for country i, IERP\u003csub\u003ei\u003c/sub\u003e is the IER premium for country i, \u003cstrong\u003e\u0026alpha;\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ei\u003c/strong\u003e\u003c/sub\u003e is the DC on the investor for country i and SI\u003csub\u003ei\u003c/sub\u003e is the social impact for country i that varies with IER.\u003c/p\u003e\n\u003cp\u003eIf the government strategy is to choose LIER and HDC, and if the investor chooses to invest under this choice, the LIER and weak institutions and transparency limit the investor payoff, the payoff to the investor is (\u0026beta;).\u003c/p\u003e\n\u003cp\u003eHDC reduces the government payoff (\u0026gamma;) by (2%), whereby the government payoff is equal to (\u0026gamma;) due to bureaucratic costs. However, the government could earn a rent equal to (0) under low complexity, if investors are not interested in investing even when there is HIER in the country despite good policies. This means that some countries may choose complexity for short-term rent while other countries might not, even if this discourages investment.\u003c/p\u003e\n\u003cp\u003eConversely, the government can earn a payoff equal to (\u0026gamma; - LDC), when there are LDC and HIER in the country that attract investors to invest, which boosts tax collection. However, when the government chooses LIER but keeps DC low, and the investor invests in the country, the government payoff is (\u0026gamma;-0), and the LIER will minimize investor payoff, but if the investor avoids the government payoff is (0).\u003c/p\u003e\n\u003cp\u003eIn general, under LDC and HIER, the government payoff (\u0026gamma;) from increased taxes could offset the HDC costs. The investor payoff (\u0026beta;) is maximized under HIER compared to LIER as long as (\u0026beta;HIER\u0026thinsp;\u0026gt;\u0026thinsp;\u0026beta;LIER). The government payoff from choosing to have HIER and HDC depends on whether the investor invests or avoids. If the investor decides to invest, the government payoff is (\u0026gamma;), which reflects a 2% of GDP reduction due to HDC.\u003c/p\u003e\n\u003cp\u003eAccording to the game theory conventions, it is assumed that all players are rational, and aim to maximize their payoffs. Payoffs are influenced by the combination of IER and DC. In addition, it is assumed that the interaction between the government and impact investors is a non-zero-sum game, where collaboration can lead to mutually beneficial outcomes. Therefore, the payoffs that represent the benefits for each player in this game are determined based on their choices.\u003c/p\u003e\n\u003cp\u003eThe main definitions used in this strategic game and payoffs for the government and investors are explained in Table\u0026nbsp;1.\u003c/p\u003e"},{"header":"4 Methodology","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e4.1 Game Theory\u003c/h2\u003e\n\u003cp\u003eGame theory is applied in this study to analyse the interactions between impact investors and the government in order to identify how the ecosystem readiness affects impact investors. We use various proxies to measure the IER and DC in countries under investigation, with a mixed methodology combining both game theoretic modelling and pre-structured investor interviews was used to examine the interaction between two players (\u0026ldquo;government\u0026rdquo; and \u0026ldquo;impact investors\u0026rdquo;), utilizing the current investment ecosystem in the region to help determine the most likely outcomes.\u003c/p\u003e\n\u003cp\u003eTherefore, the game theory employed is a form of analysis of strategic interactions where the outcome of a participant\u0026rsquo;s choice of action depends upon the actions of other participants and it can be applied in different contexts. One application could be considering the role of investors in the MENA region. It can be argued that the government\u0026rsquo;s strategy and policies made it the first mover. Other players (i.e., investors) are obliged to reactively follow this strategy. The Government\u0026rsquo;s strategy has set many rules and constraints within which the other players choose their actions. All players are assumed to maximize their payoffs.\u003c/p\u003e\n\u003cp\u003eIn this study, we model the cooperative spirit and the behaviour of the government and the investors. Even though both players know the best outcome, it is not necessarily achieved, because the players have different immediate interests and priorities (e.g., potential issues of trust) that affect how they interact. This illustrates the difficulty of the two players to stay in cooperation with one another, and to trust each other in the investment relationship between the government and impact investors.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e4.2 Payoff Matrix\u003c/h2\u003e\n\u003cp\u003eBased on the previous analysis, we construct the payoff matrix for four groups of countries (Groups 1, 2, 3, and 4) based on their readiness and complexity levels. Certain countries exhibit characteristics from multiple groups, combining elements of Group 1 and Group 2 or aligning partially with Group 3 and Group 4.\u003c/p\u003e\n\u003cp\u003eThe IER and DC in Fig.\u0026nbsp;1 represent the payoffs of the 2x2 matrix that illustrates four possible strategic outcomes based on government and investor strategies to invest in the country. The top-left quadrant shows countries operating in an LDC ecosystem and LIER. The top-right quadrant represents countries operating in an HIER and an LDC. The bottom-left quadrant indicates countries operating in LIER and an HDC. While the bottom-right quadrant represents countries operating in an HDC ecosystem and HIER.\u003c/p\u003e\n\u003cp\u003eThe players in this game are the government and impact investors. The government wants to attract I-Inv to help solve social and economic challenges. The impact investors seek to make a return and social impact. The combinations of IER and DC yield four cases, as discussed earlier. The government strategies are either to choose (HDC and LIER) or (HDC and HIER). It could choose also (LDC and LIER) or (LDC and HIER) by keeping policies simple and straightforward for investors (Ghemawat, \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e). According to the OECD (2019a, 2019b), different levels of DC and IER affect the flow of foreign direct investment across different countries.\u003c/p\u003e\n\u003cp\u003eIf the government chooses HDC and LIER by implementing complex policies or regulations, the investor will choose not to invest, the payoff for the government is (0) and for the investor is (0). Conversely, under HDC, the investor may choose to invest and the payoff for the government is (\u003cem\u003e\u0026gamma; - \u0026alpha;\u003c/em\u003e) and for the investor is (\u003cem\u003e\u0026beta;\u003c/em\u003e). These payoffs represent the benefits or costs to each player based on their choices.\u003c/p\u003e\n\u003cp\u003eUnder another alternative, the government may choose LDC and HIER, in this case, the investor may choose not to invest and the payoff for him and the government is (0). If the investor chooses to invest, the payoffs are (\u003cem\u003e\u0026gamma; - \u0026alpha;\u003c/em\u003e) for the government and (\u003cem\u003e\u0026beta;\u003c/em\u003e) for the investor. The government could choose also LDC and LIER, under this case, the government rent is (\u003cem\u003e\u0026gamma;\u003c/em\u003e), while the investor payoff is (\u003cem\u003e\u0026beta;\u003c/em\u003e). Finally, the government payoff from choosing HDC and HIER is (\u003cem\u003e\u0026gamma; - \u0026alpha;\u003c/em\u003e) and the investor payoff is (\u003cem\u003e\u0026beta;\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2 shows the payoff matrix for the government and impact investors considering all player\u0026rsquo;s strategies. In general, the level of IER and DC determine the value of government and investor payoff.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e4.3 Data\u003c/h2\u003e\n\u003cp\u003eThe data for 14 Arab countries in the MENA region during the period 2021 to 2024 were used in this study, which are classified according to their rank in the \u003cem\u003eEase of Doing Business\u003c/em\u003e (EoDB) (World Bank, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) classification and the \u003cem\u003eGlobal Competitiveness Index\u003c/em\u003e (GCI) published by the World Economic Forum (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). These countries are: Algeria, Bahrain, Egypt, Jordan, Kuwait, Lebanon, Morocco, Oman, Qatar, Saudi Arabia, Tunisia, United Arab Emirates (UAE), and Yemen. These countries were chosen based on their score of investment readiness and in doing business. Country-specific data was obtained from reports by the OECD (2021), IMF (2021, 2023), Transparency International (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) and MSCI (2023).\u003c/p\u003e\n\u003cp\u003eFor example, the MSCI (2023) index is considered a key driver of risk and return in equity portfolios that reflect the country\u0026rsquo;s risk. It is assumed to reflect HDC in frontier markets due to liquidity risk. According to the MSCI index, countries can be classified into two types. \u0026ldquo;emerging markets\u0026rdquo; (where \u0026alpha;\u0026thinsp;=\u0026thinsp;0), such as the UAE, Saudi Arabia, Qatar, Kuwait and Egypt; and \u0026ldquo;frontier markets\u0026rdquo; (where \u0026alpha;\u0026thinsp;=\u0026thinsp;2), such as Bahrain, Morocco, Oman, Jordan and Tunisia. Other countries were classified as frontier market countries because of their under developed financial markets, smaller market capitalization, lower liquidity and facing challenges and high risks.\u003c/p\u003e\n\u003cp\u003eThis comprehensive approach enables an in-depth assessment of how different levels of ecosystem readiness interact with EoDB dimensions, thus offering valuable insights into I-Invs in the region.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5 Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e5.1 Grouping\u003c/h2\u003e\n\u003cp\u003eThese countries are divided into four groups and aligned based on combining two dimensions, investment DC and IER. To assign countries to groups, the thresholds used to classify countries into groups were derived from scores on key indicators, such as the EoDB, the GCI, and the \u003cem\u003eCorruption Perceptions Index\u003c/em\u003e (CPI) (Transparency International, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), as explained in Table\u0026nbsp;3. For example, any country that scored 75 or higher on the EoDB 70 or higher on the GCI, and 60 or higher on the CPI was considered to have a high IER. In contrast, any country that scored less than 50 on the EoDB and GCI, and less than 40 on the CPI was considered a low IER.\u003c/p\u003e\n\u003cp\u003eSimilarly, in countries that scored 75 or higher on the EoDB, investors spend less than 10 days and cost less than 10% of per capita income in starting a business, and investors spend less than 100 days and cost less than 50% of the value of the warehouse, was considered to have low DC. However, countries that scored less than 50 on the EoDB and investors spend more than 30 days and cost more than 30% of per capita income in starting a business and investors spend more than 200 days and cost more than 100% of the warehouse value, was considered to have HDC. Table\u0026nbsp;4 shows the DC classification of countries.\u003c/p\u003e\n\u003cp\u003eTo numerically illustrate the payoff for the government and investor based on the payoff matrix, we apply the normalized score of EoDB for MENA countries, assuming that the government payoff (\u0026gamma;) and investor return (\u0026beta;) vary with IER and DC. Table\u0026nbsp;5 shows the investment readiness scored by the EoDB and the DC scored by the MSCI index. Based on the EoDB rank for MENA countries, we can calculate the normalized IER score using Eq.\u0026nbsp;3:\u003c/p\u003e\n\u003cp\u003eNormalized IER\u0026thinsp;=\u0026thinsp;1\u0026minus; (Country Rank\u0026thinsp;\u0026minus;\u0026thinsp;1/ Maximum Rank\u0026thinsp;\u0026minus;\u0026thinsp;1) (3)\u003c/p\u003e\n\u003cp\u003eIn this game, we assume that the government rent is equal to \u0026gamma; which reflects a trade-off between tax revenue gains driven by IER and bureaucratic costs from DC. Higher IER improves tax collection, while HDC (\u0026alpha;\u0026thinsp;=\u0026thinsp;2) reduces net rents by 2% of GDP. Therefore, the government payoff (\u0026gamma;) is rewritten as in Eq.\u0026nbsp;4:\u003c/p\u003e\n\u003cp\u003e\u0026gamma;\u0026thinsp;=\u0026thinsp;NTR\u0026thinsp;+\u0026thinsp;0.4* IER- RC(\u0026alpha;) (4)\u003c/p\u003e\n\u003cp\u003eOn the other hand, the impact investor return is equal to \u0026beta;, which is also assumed to vary with IER and DC. The investor return can be rewritten as in Eq.\u0026nbsp;5:\u003c/p\u003e\n\u003cp\u003e\u0026beta;\u0026thinsp;=\u0026thinsp;RFR\u0026thinsp;+\u0026thinsp;5 * IER - \u0026alpha;\u0026thinsp;+\u0026thinsp;SI(IER) (5)\u003c/p\u003e\n\u003cp\u003eThe coefficients (0.4 and 5) in equations 4 and 5 are derived from OECD and MSCI data to scale logically with real IER country scores. The coefficient of (0.4%) in Eq.\u0026nbsp;4 is the average of a (0.1) unit improvement in institutional quality (proxied by IER), which correlates with a (0.3\u0026ndash;0.5%) increase in tax revenue as a share of GDP (OECD, 2021). Furthermore, the coefficient of (5) in Eq.\u0026nbsp;5 is the result of a (0.1) unit of IER improvement that reduces equity risk premiums by (0.5%) multiplied by 10 to scale and align with the (0\u0026ndash;1) IER score (MSCI, 2023).\u003c/p\u003e\n\u003cp\u003eFor example, the government may accept a lower payoff (\u0026gamma;) in the short term to attract long-term investment, while impact investors will seek to invest in HIER for better social and economic returns (\u0026beta;). In general, the government\u0026rsquo;s payoff depends on whether the investor invests or avoids. Table\u0026nbsp;6 shows the results of government and investor payoffs using equations 4 and 5.\u003c/p\u003e\n\u003cp\u003eAccording to the illustrative payoff matrix in Table\u0026nbsp;6, if the government chooses high DC and the IER is low, the government\u0026rsquo;s payoff is (\u0026gamma; \u0026ndash; \u0026alpha;), and the investor\u0026rsquo;s payoff is (\u0026beta;). Therefore, to reach Nash equilibrium in this game, both players choose their best responses given the other player\u0026rsquo;s strategy. When both players cooperate, they maximize their payoffs. The government\u0026rsquo;s best outcome is low DC and high IER in the country, and the investor chooses to invest, whereby the government payoff will be maximized. If the government chooses high DC, it will earn less. Consequently, the government\u0026rsquo;s best strategy in this case is to create low DC and high IER, as long as the corresponding payoff is greater than in other cases.\u003c/p\u003e\n\u003cp\u003eThe Nash equilibrium in these interactions between the government and investors happens when the government chooses to create a low DC and high IER environment. The investor in this case will be able to make a social impact and return. The government will benefit from this investment by reducing unemployment, increasing economic growth, and solving environmental challenges. The government\u0026rsquo;s payoff represents the economic benefits of I-Inv inflows, including economic growth, employment, and social benefits (OECD, 2021). The interactions between investors and governments within each of the four studied groups are described below.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e5.2 Group 1: High Readiness, Low Complexity\u003c/h2\u003e\n\u003cp\u003eCountries in this group are characterized by having well-developed investment ecosystems, efficient regulatory environments, strong infrastructure, and streamlined processes for starting and operating businesses. According to the World Bank (2021), these countries are top performers. Countries in this group include the UAE, Saudi Arabia, Bahrain and Oman. In this group, both investors and governments benefit from cooperation and coordination, due to a favourable investment ecosystem and simplified deal structures.\u003c/p\u003e\n\u003cp\u003eThe payoff matrix for Group 1 is described in Table\u0026nbsp;7. The best strategy for the government in these countries is to choose low DC and gain from 10.4\u0026ndash;12.3%. For the investor the best strategy would be to increase investment and gain between 10.9\u0026ndash;14.2%. In this case, investors always invest as long as their payoff is positive. For instance, the UAE has successfully improved its IER through regulatory reforms, leading to a 15% increase in FDI inflows between 2018 and 2023 (Dhaman, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003e5.3 Group 2: High Readiness, High Complexity\u003c/h2\u003e\n\u003cp\u003eCountries operating in Group 2 have also made significant progress in improving their business environments and strong investment ecosystems, but still face higher complexity in investment deals due to bureaucratic or regulatory challenges. In this group, despite the high readiness of the investment ecosystem, the complexity of investment deals poses challenges for both investors and governments. Countries in this group include Qatar and Kuwait.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;8 explains the payoff matrix for countries classified in Group 2. The government in Group 2 act in the best way by choosing high complexity, while at the same time they have high IER. In this context, the government gains between 11.2\u0026ndash;13.2%, and the investors gain from 8.6\u0026ndash;8.9% if they choose to invest in these countries.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003e5.4 Group 3: Low Readiness, Low Complexity\u003c/h2\u003e\n\u003cp\u003eIn Group 3, countries have simpler investment deal structures but lack readiness in their investment ecosystems, characterized by weak institutions, poor infrastructure, or unstable regulatory environments (Table\u0026nbsp;9). Although investment DC is low, the lack of readiness in the investment ecosystem limits the potential benefits for both investors and governments. Countries in this group have the potential to attract I-Inv, but still facing structural and bureaucratic challenges. However, some countries such as Jordan, Morocco, Egypt and Tunisia might be classified in this group if the government implement reform to reduce DC and move from HDC to LDC. In general, the government focus for Group 3 is on how to reduce DC with limited impact on the IER or the government focuses on reforming the IER with limited impact on DC.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003e5.5 Group 4: Low Readiness, High Complexity\u003c/h2\u003e\n\u003cp\u003eThese countries face both high complexity in investment deals and low readiness in their investment ecosystems environment, indicating significant challenges for investors due to regulatory and institutional weaknesses (Table\u0026nbsp;10). This group encompasses countries with major bureaucratic, economic, or political instability concerns, including Algeria, Lebanon, Yemen and Libya. The payoff for countries classified in this group is limited, the government gains range from 1\u0026ndash;7.1% and the investor gain is between 5.0\u0026ndash;6.4%.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003e5.6 Regional and Country Level Data Analysis\u003c/h2\u003e\n\u003cp\u003eTo validate our game-theoretic model, we compare our findings with structured investor interviews conducted by the United Nations Development Programme (UNDP, 2022), Pastorelli, Bala, and Barco Serrano (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), and GIIN (2023a) at regional and country levels with main fund managers and businesses operating in emerging markets, including MENA. These pre-structured interviews give us some insight into how both players are choosing actions on the regional ecosystem and country-specific ecosystem levels.\u003c/p\u003e\n\u003cp\u003eAt the country level, UNDP (2022) interviews with funds and businesses in Jordan have shown that there is a lack of a unified ecosystem and multi-stakeholder collaboration, legal and regulatory challenges, and insufficient and misaligned funding mechanisms. Other challenges are related to the market size, limited access to finance and talent pool limitations, misunderstanding of I-Inv and its potential, lack of accurate data and effective communication, gender disparities and social challenges, overemphasis on tech and ICT sectors, and neglecting others.\u003c/p\u003e\n\u003cp\u003eIn addition, there is a need for a shift in mindset toward long-term impact. Hostile business conditions characterize the main investor perspectives regarding the investment ecosystem, especially in terms of regulatory oversight, a less predictable investment environment, lengthy and unpredictable commercial conflict resolution mechanisms, unclear and changing attitudes towards renewables, and a non-transparent and fast-changing tax system, as articulated by local investors, who also mentioned private companies\u0026rsquo; governance and accountability standards, and limited use of public procurement to promote investment (GIIN, 2023a; UNDP, 2022).\u003c/p\u003e\n\u003cp\u003eAccording to interviewed investors, to enhance the investment ecosystem and increase I-Inv, the government must address these challenges through collaboration, regulatory reforms, innovative financing, and cultural shifts. Key actions include creating a unified platform, updating laws, improving access to capital, standardizing impact reporting, and fostering inclusivity (UNDP, 2022). Although the main engine of growth and employment must move from government to I-Inv. Moreover, the role of government is no longer the conductor of a captive national economy, but becomes a regulator and enabler for investors to compete in global markets. Therefore, to attract more investment to the region the government\u0026rsquo;s role shifts from offering project-specific arrangements to positioning the country as an attractive investment destination with predictable rule-based conditions and offering competitive investment opportunities (GIIN, 2023a, 2023b).\u003c/p\u003e\n\u003cp\u003eOn the regional level, interviews conducted by Pastorelli et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), show that MENA is still developing in terms of attracting I-Inv. The majority of countries in the region lack an enabling legal and regulatory environment to attract and retain investors, the lack of regional impact funds and a lack of awareness about I-Inv from both investors and countries. According to respondents, the main obstacle to the development of impact investing in the MENA region is the higher level of multifaceted risk (political instability; economic instability resulting in devaluation risks, credit crunches, geopolitical tensions; etc.). All of these also affect exit strategies for investors, and they occur in a highly underdeveloped ecosystem (e.g. data, scarcity of vehicles and quality investment opportunities, low level of non-financial support services, etc.). Similarly, these findings are confirmed by the OECD (2021), which shows that crises in the region, limited direct trade routes, and high-risk perceptions have had a negative impact. Furthermore, there are no specific incentives for impact investors, and a lack of awareness of investment opportunities and processes. In addition, the low level of I-Inv attracted to the region is widespread in the investment ecosystem, which is not yet developed enough to attract impact investors in terms of the legal and business environment.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"6 Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e6.1 Overview\u003c/h2\u003e\u003cp\u003eThe results of the game theory used in this study are linked and aligned with pre-structured interviews that have been conducted with key ecosystem players, businesses, investors and fund managers in the region, in terms of I-Inv and IER. The payoff matrices derived for different groups of countries capture the relationship between readiness, complexity, and the preferences of both investors and governments. Moving from one group to another allows us to reflect on the optimal outcome for the government and investors in different investment ecosystem contexts. Applying the game theory to analyse the interactions between investors and governments within each group reveals the following findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e6.2 Group Findings\u003c/h2\u003e\u003cp\u003eIn Group 1 countries, which are characterized by high IER and low DC, the government\u0026rsquo;s strategy focuses on optimizing investment allocation strategies to maximize social impact and returns while ensuring compliance with regulations. Both investors and governments are likely to benefit from cooperation and transparency, leading to mutually beneficial outcomes. The social impact of investors in the host country will be reflected in reduced unemployment and poverty, increased economic growth and well-being, and improved socio-economic and environmental conditions. This represents the optimal scenario, where both government and investors achieve the highest payoffs due to reduced complexity and improved investment readiness.\u003c/p\u003e\u003cp\u003eThe government strategies in Group 2 countries, described as high IER and high DC, would include strategies to navigate complex regulatory landscapes while taking advantage of a strong investment ecosystem. Both negotiation and bargaining tactics may be crucial for impact investors to secure favourable deals, while governments may seek to balance attracting investment with protecting national interests. However, the effects on impact investors in these countries are limited to the socioeconomic and environmental conditions.\u003c/p\u003e\u003cp\u003eIn Group 3, countries with low IER and low DC, the governments may prioritize policy reforms and capacity-building efforts to improve readiness and attract investment, leading to potential opportunities for collaboration among stakeholders. For investors, the focus is on risk management strategies, considering the challenges posed by weak institutional frameworks despite simpler deal structures. The effects on socio-economic and environmental conditions are negligible.\u003c/p\u003e\u003cp\u003eLastly, for Group 4 countries, categorized by low IER and high DC, the analysis would include assessing the costs and benefits of investing in environments with both complexity and low readiness. Therefore, investors may adopt cautious approaches or demand higher returns to compensate for the uncertainties, while governments face pressures to address institutional deficiencies and reduce barriers to attract investment. In this case, no socio-economic and environmental effects can be materialized in these countries.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e6.3 Summary\u003c/h2\u003e\u003cp\u003eThe model used in this study predicts that IER significantly influences investor decisions. This aligns with findings from the OECD (2022), which reported that the vast majority (78%) of surveyed investors stated that transparent regulations were a key factor in investment location choices. This study also shows the importance of creating a sustainable development paradigm in MENA countries that is centred on I-Inv as the engine of growth and employment in the region. Governments can influence their domestic economy, thus their role is to support and enable businesses to attract I-Inv. The primary role of the government is to set a rules-based framework and standardised, predictable conditions, and, as far as possible, to create high IER and reduce DC. In short, their role is to shift their economy from a low to high IER, and to facilitate complex investment deals, so that they can almost qualify as simple.\u003c/p\u003e\u003c/div\u003e"},{"header":"7 Conclusion","content":"\u003cp\u003eGiven the findings of this analysis, policy measures to enhance IER and reduce DC can be identified. The main players in this game are the impact investors and the government. Therefore, the payoffs depend on the combination of strategies chosen by all players and are influenced by both ecosystem readiness, which increases payoffs for all players, and DC, which reduces payoffs due to increased risks and costs. In this context, both the government and impact investors achieve the best results when they cooperate. This can happen when the government follows a strategy of low DC and high IER. At the same time, the investor follows a strategy of increasing I-Inv. This means that countries in the region that would like to benefit from I-Inv must move from high DC and low IER (Group 4), from low DC and low IER (Group 3) and from high DC and high IER (Group 2) to low DC and high IER (Group 1), as summarised in Fig.\u0026nbsp;2. This, of course, would require tremendous changes in their strategies to align with investor\u0026rsquo;s needs in terms of having low DC and high IER.\u003c/p\u003e\u003cp\u003e[Insert Fig.\u0026nbsp;2 here]\u003c/p\u003e\u003cp\u003eDespite the importance of I-Invs and ecosystem readiness, it is clear that I-Invs without high IER will not solve all social, economic, and environmental challenges that the region faces. The fiscal pressure and government needs of many countries in the region required the government to be the first mover in this game. Governments should include I-Inv in their strategies and plans. They need to design policies to improve IER and reduce DC by simplifying regulations and reducing licensing time, which can lead to higher payoffs for all.\u003c/p\u003e\u003cp\u003eTherefore, policymakers are advised to hold discussions with key stakeholders to support the investment ecosystem, broaden consensus on reform priorities, and identify specific actions at the national level to be pursued by the ecosystem players. The government should develop a work plan to revise the current approach and engage all players by sharing views and ongoing activities on the investment ecosystem. This could lead to a broad consensus on reform priorities and public support. The government should analyse the potential options for improvement of the current activities on the investment ecosystem to identify additional initiatives to foster the I-Inv ecosystem. Based on the government\u0026rsquo;s actions and the potential payoffs, investors can choose their strategies, leading to dynamic interactions to achieve mutually beneficial outcomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResearch limitations/implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe main limitations of this study are related to the availability of up-to-date coverage of scores and indices that are used in this study. Furthermore, there are many factors that affect investors\u0026rsquo; decisions that need to be included in the analysis, such as geopolitical risks. The results of this study were based on limited factors, thus, future research should include more factors and employ more dynamic models to explain reforms over time.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe findings of this study are based on data obtained from the World Bank\u0026rsquo;s Ease of Doing Business Index (2020) and the Global Competitiveness Index of the World Economic Forum (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Country-specific indicators were obtained from the Organization for Economic Cooperation and Development (OECD) (2021), International Monetary Fund (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Transparency International (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Morgan Stanley Capital International (MSCI) (2023) reports. All datasets are accessible through the respective organizations\u0026rsquo; official platforms.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkin I, Akin M (2025) Promoting sustainable practices through green investments in the United Kingdom real estate industry. Sustain Dev 33(1):1526\u0026ndash;1544. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/sd.3194\u003c/span\u003e\u003cspan address=\"10.1002/sd.3194\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlexakis C, Gogas P, Petrella G, Polemis M, Salvad\u0026egrave; F (2024) The determinants of investment readiness for SMEs in Europe: An empirical investigation with machine learning techniques. SSRN Article 4906983. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.2139/ssrn.4906983\u003c/span\u003e\u003cspan address=\"10.2139/ssrn.4906983\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBen Letaifa S (2016) How social entrepreneurship emerges, develops and internationalises during political and economic transitions. Eur J Int Manage 10(4):455\u0026ndash;466. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1504/EJIM.2016.077424\u003c/span\u003e\u003cspan address=\"10.1504/EJIM.2016.077424\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eClarkin J, Cangioni L, C (2016) Impact Investing: A Primer and Review of the Literature. Entrepreneurship Res J 6(2):135\u0026ndash;173. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1515/erj-2014-0011\u003c/span\u003e\u003cspan address=\"10.1515/erj-2014-0011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDhaman (2024) Investment climate in Arab countries 2024. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dhaman.org/climate-reports/Climate%20E%202024.pdf\u003c/span\u003e\u003cspan address=\"https://www.dhaman.org/climate-reports/Climate%20E%202024.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiaz Gonzalez A, Dentchev NA (2021) Ecosystems in support of social entrepreneurs: a literature review. Social Enterp J 17(3):329\u0026ndash;360. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1108/SEJ-08-2020-0064\u003c/span\u003e\u003cspan address=\"10.1108/SEJ-08-2020-0064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDream Impact (2021) Ways Forward For a Collaborative Impact Ecosystem: Insights \u0026amp; Conclusions. Retrieved from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dreamimpacthk.com/collaborative-impact-ecosystem-insights-conclusions/\u003c/span\u003e\u003cspan address=\"https://www.dreamimpacthk.com/collaborative-impact-ecosystem-insights-conclusions/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFawaz A (2025) Locational advantages and foreign direct investment in MENA: A comprehensive analysis of institutional and economic factors. Transnatl Corporations Rev 17(2):200131. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tncr.2025.200131\u003c/span\u003e\u003cspan address=\"10.1016/j.tncr.2025.200131\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFinance Center for South-South Cooperation (2023) Impact investing. Springer, Singapore. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-981-99-4935-9_1\u003c/span\u003e\u003cspan address=\"10.1007/978-981-99-4935-9_1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFuad M, Venugopal A (2024) Deal completion in mergers and acquisitions: past accomplishment and future direction. Cross Cult Strategic Manage 31(1):1\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1108/CCSM-02-2022-0034\u003c/span\u003e\u003cspan address=\"10.1108/CCSM-02-2022-0034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhauri P, Gr\u0026oslash;nhaug K (2010) Research methods in business studies: A practical guide. Financial Times/Prentice Hall, London\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhemawat P (2001) Distance still matters: The hard reality of global expansion. Harvard Business Rev 79(8):137\u0026ndash;162\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal Impact Investing Network (2023a) Annual Impact Investor Survey. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://thegiin.org/impact-investor-survey/\u003c/span\u003e\u003cspan address=\"https://thegiin.org/impact-investor-survey/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal Impact Investing Network (2023b) Impact investment trends in emerging markets: Survey of 200 institutional investors across Africa, MENA, and Asia. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.giin.org/report\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGompers P, Lerner J (2001) The venture capital cycle. MIT Press, Cambridge, MA\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoskisson RE, Eden L, Lau CM, Wright M (2000) Strategy in emerging economies. Acad Manag J 43(3):249\u0026ndash;267. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.2307/1556394\u003c/span\u003e\u003cspan address=\"10.2307/1556394\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHupp\u0026eacute; GA (2014), July 24 Building impact investment readiness. \u003cem\u003eStanford Social Innovation Review\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.48558/67EQ-RM09\u003c/span\u003e\u003cspan address=\"10.48558/67EQ-RM09\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInternational Monetary Fund (2021) Network Determinants of Cross-Border Merger and Acquisition Decisions. Working Papers. WP/19/264\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInternational Monetary Fund (2023) Regional economic outlook: Middle East and Central Asia. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.imf.org/en/Publications/REO/MECA/Issues/2023/10/12/regional-economic-outlook-mcd-october-2023\u003c/span\u003e\u003cspan address=\"https://www.imf.org/en/Publications/REO/MECA/Issues/2023/10/12/regional-economic-outlook-mcd-october-2023\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJ\u0026auml;ger U, Pfirrmann J, Rodriguez A, Topolanek D (2019) The impact investment ecosystem in Central America. Status quo and opportunities for a regional advisory board within the global movement of impact investment Costa Rica. VIVA Idea, San Jos\u0026eacute;\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKesselring A (2021) Impact investment \u0026ndash; An ecosystem view. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.interregeurope.eu/sites/default/files/inline/ASHOKA_-Alexandre_Kesselring.pdf\u003c/span\u003e\u003cspan address=\"https://www.interregeurope.eu/sites/default/files/inline/ASHOKA_-Alexandre_Kesselring.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlapper L, Love I (2010) The impact of the financial crisis on new firm registration. SSRN Article 1641446. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.2139/ssrn.1641446\u003c/span\u003e\u003cspan address=\"10.2139/ssrn.1641446\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumar V, Dua P (2024) What explains foreign portfolio investment inflows to BRICS countries? Econ Anal Policy 82:32\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eap.2024.02.033\u003c/span\u003e\u003cspan address=\"10.1016/j.eap.2024.02.033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLevy B (2025) Global M\u0026amp;A industry trends. PricewaterhouseCoopers (PwC). Retrieved from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pwc.com/gx/en/services/deals/trends.html\u003c/span\u003e\u003cspan address=\"https://www.pwc.com/gx/en/services/deals/trends.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu C (2019) Impact investing: A review of literature and ecosystem. In J. Puaschunder (Ed.), \u003cem\u003eIntergenerational governance and leadership in the corporate world: Emerging research and opportunities\u003c/em\u003e (pp. 191\u0026ndash;217). Hershey, PA: IGI Global Scientific Publishing. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4018/978-1-5225-8003-4.ch010\u003c/span\u003e\u003cspan address=\"10.4018/978-1-5225-8003-4.ch010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLustenberger M, Malešević S, Spychiger F (2021) Ecosystem readiness: Blockchain adoption is driven externally. Front Blockchain 5(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eArticle 720454. https://doi.org/10.3389/fbloc.2021.720454\u003c/span\u003e\u003cspan address=\"Article 720454. 10.3389/fbloc.2021.720454\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMason C, Kwok J (2010) Investment readiness programmes and access to finance: A critical review of design issues. Local Econ 25(4):269\u0026ndash;292. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1080/02690942.2010.504570\u003c/span\u003e\u003cspan address=\"10.1080/02690942.2010.504570\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMdanat M (2022) The effects of inclusive business models on development outcomes in developing countries. Int J Dev Confl 11(2):132\u0026ndash;152\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMenkhoff L, He L (2013) Financial market development and investment ecosystems: A comparative analysis. J Int Bus Stud 44(2):148\u0026ndash;164\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMorgan Stanley Capital International Index (2023) Country risk premiums report. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.msci.com\u003c/span\u003e\u003cspan address=\"https://www.msci.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNdegwa N (2022) Investment readiness for micro small and medium enterprises. Diamond Trust Bank, Nairobi\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganisation for Economic Co-operation and Development (2015) Social Impact Investment: Building the Evidence Base. OECD Publishing, Paris. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1787/9789264233430-en\u003c/span\u003e\u003cspan address=\"10.1787/9789264233430-en\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganisation for Economic Co-operation and Development (2019a) OECD investment policy perspectives. OECD Publishing, Paris\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganisation for Economic Co-operation and Development (2019b) Social impact investment: The impact imperative for sustainable development. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.oecd-ilibrary.org/development/social-impact-investment-2019_9789264311299-en\u003c/span\u003e\u003cspan address=\"https://www.oecd-ilibrary.org/development/social-impact-investment-2019_9789264311299-en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganisation for Economic Co-operation and Development (2020) Investment ecosystems in emerging economies: Challenges and opportunities. OECD Publishing, Paris\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganisation for Economic Co-operation and Development (2021a) Middle East and North Africa investment policy perspectives. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1787/6d84ee94-en\u003c/span\u003e\u003cspan address=\"10.1787/6d84ee94-en\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganisation for Economic Co-operation and Development (2021b) Tax administration 2021. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.oecd.org/en/publications/tax-administration-2021_cef472b9-en.html\u003c/span\u003e\u003cspan address=\"https://www.oecd.org/en/publications/tax-administration-2021_cef472b9-en.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePastorelli G, Bala A, Barco Serrano S (2021) Study on the opportunities for impact investing to promote the social and green economy in the southern neighbourhood. European Commission Transports \u0026amp; Infrastructures Expertise Group, Brussels\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoundy PT (2020) Regional differences in impact investment: A theory of impact investing ecosystems. Social Responsib J 16(4):467\u0026ndash;485. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1108/SRJ-11-2018-0302\u003c/span\u003e\u003cspan address=\"10.1108/SRJ-11-2018-0302\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoundy PT, Holzhauer H, Dai Y (2017) Finance or philanthropy? Understanding the motivations and criteria of impact investors. Social Responsib J 13(3):419\u0026ndash;512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1108/SRJ-08-2016-0135\u003c/span\u003e\u003cspan address=\"10.1108/SRJ-08-2016-0135\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSall MCA, Burlea-Schiopoiu A (2021) An analysis of the effects of public investment on labor demand through the channel of economic growth with a focus on socio-professional categories and gender. J Risk Financial Manage 14(12). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eArticle 580. https://doi.org/10.3390/jrfm14120580\u003c/span\u003e\u003cspan address=\"Article 580. 10.3390/jrfm14120580\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScottish Marine Environmental Enhancement Fund (2024) Impact report 2. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://smeef.scot/about/#what-is-smeef\u003c/span\u003e\u003cspan address=\"https://smeef.scot/about/#what-is-smeef\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShuwaikh F, Hughes M, Brinette S, Khemiri S (2024) Investment decisions under uncertainty: Corporate venture capital as a real option. Int J Finance Econ 29(2):2452\u0026ndash;2471. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ijfe.2794\u003c/span\u003e\u003cspan address=\"10.1002/ijfe.2794\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSpamann H (2021), July 1 \u003cem\u003eIndirect investor protection: The investment ecosystem and its legal underpinnings\u003c/em\u003e (Law Working Paper No. 594/2021). Harvard University and ECGI. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ecgi.global/publications/working-papers/indirect-investor-protection-the-investment-ecosystem-and-its-legal\u003c/span\u003e\u003cspan address=\"https://www.ecgi.global/publications/working-papers/indirect-investor-protection-the-investment-ecosystem-and-its-legal\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSpigel B (2017) The Relational Organization of Entrepreneurial Ecosystems. Entrepreneurship Theory Pract 41(1):49\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/etap.12167\u003c/span\u003e\u003cspan address=\"10.1111/etap.12167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTabash MI, Farooq U, Matar A, Al-Absy MSM (2024) Role of governance in attracting foreign direct investment inflow: Empirical evidence from South Asia region. Cogent Econ Finance 12(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eArticle 2358930. https://doi.org/10.1080/23322039.2024.2358930\u003c/span\u003e\u003cspan address=\"Article 2358930. 10.1080/23322039.2024.2358930\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTransparency International (2022) Corruption Perceptions Index. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.transparency.org/en/publications/corruption-perceptions-index-2022\u003c/span\u003e\u003cspan address=\"https://www.transparency.org/en/publications/corruption-perceptions-index-2022\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTransparency International (2023) Corruption Perceptions Index. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.transparency.org/en/publications/corruption-perceptions-index-2023\u003c/span\u003e\u003cspan address=\"https://www.transparency.org/en/publications/corruption-perceptions-index-2023\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTrelstad B (2016) Impact investing: A brief history. Capitalism Soc 11(2):1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited Nations Development Programme (2022) Seeds of impact: The impact journey of funds and businesses. UNDP, New York, NY\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Bank (2020) Ease of doing business report. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://documents1.worldbank.org/curated/en/688761571934946384/pdf/Doing-Business-2020-Comparing-Business-Regulation-in-190-Economies.pdf\u003c/span\u003e\u003cspan address=\"https://documents1.worldbank.org/curated/en/688761571934946384/pdf/Doing-Business-2020-Comparing-Business-Regulation-in-190-Economies.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Bank (2023a) Worldwide Bureaucracy Indicators. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://datacatalog.worldbank.org/search/dataset/0038132\u003c/span\u003e\u003cspan address=\"https://datacatalog.worldbank.org/search/dataset/0038132\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Bank (2023b) Revenue statistics in Middle East and North Africa. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.worldbank.org/indicator/GC.TAX.TOTL.GD.ZS\u003c/span\u003e\u003cspan address=\"https://data.worldbank.org/indicator/GC.TAX.TOTL.GD.ZS\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Economic Forum (2019) Global competitiveness report. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www3.weforum.org/docs/WEF_TheGlobalCompetitivenessReport2019.pdf\u003c/span\u003e\u003cspan address=\"https://www3.weforum.org/docs/WEF_TheGlobalCompetitivenessReport2019.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv dir=\"RTL\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 1: Definition of Main Variables\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eExplanation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eValue / Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eInvestment Ecosystem Readiness.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eMeasures institutional quality, transparency, and ease of doing business.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eNormalized score (0 \u0026ndash; 1), where 1 = highest readiness (HIER), 0 = lowest (LIER).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eHIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eHigh Investment Ecosystem Readiness.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eStrong governance, and efficient processes.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIER=1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLow Investment Ecosystem Readiness.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eBureaucratic hurdles and weak institutions.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIER=0\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eDeal Complexity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eCompliance costs from bureaucratic complexity. Reflects regulatory burden and compliance costs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eHDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eCompliance Cost. High Deal Complexity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFixed cost for investors under HDC, complex regulations and lengthy approvals.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026alpha; =2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eCompliance Cost. Low Deal Complexity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFixed cost for investors under LDC streamlined processes and minimal red tape.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026alpha; =0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026gamma;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eGovernment payoff under investment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eBenefits for the governments derive from non-tax revenue.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026gamma; = NTR + 0.4*IER \u0026ndash; RC*\u003cem\u003e\u0026nbsp;\u0026alpha;\u003c/em\u003e\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eNTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eNon tax revenue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eAveraging 5% to 15% of GDP in MENA.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eTGR(IER)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eGovernment payoff varies with IER.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eTax to GDP Ratio is improves as IER score increases.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.1 IER score increase lead to 0.3%\u0026ndash;0.5% tax to GDP rise. Average (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eInvestor payoff under investment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEconomic and social returns for investors.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026beta; = RFR + 5\u0026middot;IER + \u0026alpha; + SI\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIERP(IER)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eInvestment ecosystem readiness premium varies with IER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eAdditional return from investment.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.5% reduction in equity risk premium per 0.1 IER increase scaled to (5*IER)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eSocial Impact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eNon-financial returns from impact investments.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3% if LIER, 5% if HIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eRC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eRent cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEconomic losses due to bureaucracy and corruption.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1% of GDP per unit of DC if LDC, 2% of GDP if HDC.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eNote.\u003c/em\u003e IER, HIER and LIER are Normalized score (0 \u0026ndash; 1), where 1 = highest readiness, 0 = lowest obtained from World Bank (2020).\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 2: Government, Investor Payoff Matrix\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eGovernment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eHIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eInvestor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026beta; (\u0026gamma;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026beta; (\u0026gamma;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eHDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026beta; (\u0026gamma; \u0026ndash; \u0026alpha;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026beta; (\u0026gamma; \u0026ndash; \u0026alpha;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eNote.\u003c/em\u003e Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. \u0026beta; varies with IER, \u0026alpha;=0 if LDC, \u0026alpha;=2 if HDC.\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 3: IER Classification of Countries Groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eIndicator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eHigh Readiness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eLow Readiness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp dir=\"LTR\"\u003eIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eEase of Doing Business Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u0026ge; 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eGlobal Competitiveness Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u0026ge; 70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eCorruption Perceptions Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u0026ge; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp dir=\"LTR\"\u003eSource: \u003cem\u003eEase of Doing Business Report\u003c/em\u003e (World Bank, 2020), \u003cem\u003eGlobal Competitiveness Report\u003c/em\u003e (WEF, 2019), and\u0026nbsp;\u003cem\u003eCorruption Perceptions Index\u003c/em\u003e (Transparency International, 2022).\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 4: DC Classification of Countries Groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eIndicator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eLow Complexity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eHigh Complexity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp dir=\"LTR\"\u003eDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eStarting a Business: Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 10 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026gt; 30 days\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eStarting a Business: Cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 10% of income per capita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026gt; 30% of income per capita\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eDealing with Construction Permits: Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 100 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026gt; 200 days\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eDealing with Construction Permits: Cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 50% of warehouse value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026gt; 100% of warehouse value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEase of Doing Business Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026ge; 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u0026lt; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp dir=\"LTR\"\u003eSource: \u003cem\u003eEase of Doing Business Report\u003c/em\u003e (World Bank, 2020), \u003cem\u003eGlobal Competitiveness Report\u003c/em\u003e (WEF, 2019), and\u0026nbsp;\u003cem\u003eCorruption Perceptions Index\u003c/em\u003e (Transparency International, 2022).\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 5: Ease of Doing Business and MSCI Index\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eEase of Doing Business\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMSCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eRank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIER Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFrontier Markets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEmerging Markets\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eUAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eBahrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eMorocco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eSaudi Arabia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eOman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eJordan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eQatar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eTunisia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eKuwait\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEgypt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLebanon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eAlgeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLibya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eYemen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp dir=\"LTR\"\u003eSource: World Bank (2020), MSCI (2023).\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTable 6: Government, Investor Payoffs (in % of GDP)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eIER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMSCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eRC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eRFR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eIERP (5*IER)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eSI(IER)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eInvestor Payoff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eNTR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTGR (0.4*IER)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eGovernment Payoff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eRank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eScore\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eUAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eBahrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eMorocco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eSaudi Arabia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eOman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eJordan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eQatar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eTunisia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eKuwait\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eEgypt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eFM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eLebanon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eAlgeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eLibya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp dir=\"LTR\"\u003eYemen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eSources:\u003c/em\u003e World Bank (2023a), IMF (2023), OECD (2021), Transparency International (2023), MSCI (2023), GIIN (2023), and OECD (2023a). \u003cem\u003eNote.\u003c/em\u003e EM refers to Emerging Market and FM refers to Frontier Market. DC, \u0026alpha;=0 if LDC, \u0026alpha;=2 if HDC. Rent cost (RC): 1% if LDC, 2% if HDC.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7: Maximum Payoff Matrix for Group 1 (in % of GDP)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.1967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78.2202%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.1967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.5972%;\"\u003e\n \u003cp\u003eLIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvestor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1967%;\"\u003e\n \u003cp\u003eLDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.5972%;\"\u003e\n \u003cp\u003e{6.5 \u0026ndash; 8.0}, {4.7 \u0026ndash; 6.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e{10.9 - 14.2} , {10.4 - 12.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.1967%;\"\u003e\n \u003cp\u003eHDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.5972%;\"\u003e\n \u003cp\u003e{5.0 \u0026ndash; 6.4}, {1.0 \u0026ndash; 7.1}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e{8.6 \u0026ndash; 8.9}, {11.2 -13.2}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. \u0026beta; varies with IER, \u0026alpha;=0 if LDC, \u0026alpha;=2 if HDC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8: Maximum Payoff Matrix for Group 2 (in % of GDP)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvestor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{6.5 \u0026ndash; 8.0}, {4.7 \u0026ndash; 6.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{10.9 - 14.2} , {10.4 - 12.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{5.0 \u0026ndash; 6.4}, {1.0 \u0026ndash; 7.1}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{8.6 \u0026ndash; 8.9}, {11.2 -13.2}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. \u0026beta; varies with IER, \u0026alpha;=0 if LDC, \u0026alpha;=2 if HDC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9: Maximum Payoff Matrix for Group 3 (in % of GDP)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5514%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1776%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5514%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1776%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13.5514%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvestor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.1776%;\"\u003e\n \u003cp\u003eLDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{6.5 \u0026ndash; 8.0}, {4.7 \u0026ndash; 6.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{10.9 - 14.2} , {10.4 - 12.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.1776%;\"\u003e\n \u003cp\u003eHDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{5.0 \u0026ndash; 6.4}, {1.0 \u0026ndash; 7.1}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{8.6 \u0026ndash; 8.9}, {11.2 -13.2}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. \u0026beta; varies with IER, \u0026alpha;=0 if LDC, \u0026alpha;=2 if HDC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 10: Maximum Payoff Matrix for Group 4 (in % of GDP)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLIER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvestor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{6.5 \u0026ndash; 8.0}, {4.7 \u0026ndash; 6.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{10.9 - 14.2} , {10.4 - 12.3}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{5.0 \u0026ndash; 6.4}, {1.0 \u0026ndash; 7.1}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e{8.6 \u0026ndash; 8.9}, {11.2 -13.2}\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e Investor payoffs are the first value in each pair, while Government Payoffs are the second value in each pair. \u0026beta; varies with IER, \u0026alpha;=0 if LDC, \u0026alpha;=2 if HDC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"German Jordanian University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Impact investment, investment ecosystem readiness, game theory","lastPublishedDoi":"10.21203/rs.3.rs-7442973/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7442973/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines investment decision-making in various economic contexts, focusing on the relationship between Investment Ecosystem Readiness, Deal Complexity, and impact investment inflows to address social and economic issues in the MENA region. It aims to understand how regulatory readiness and investment complexity influence impact investors strategic decisions and how these factors interact with government behaviors to shape investment outcomes. A mixed methodology combining both game theoretic modelling and pre-structured investor interviews was used to examine these relationships, offering a systematic framework for understanding the strategic interaction between governments and impact investors, identifying equilibrium conditions that determine investment inflows into 14 MENA countries using data from 2019 to 2024. The study demonstrates that reducing investment complexity while enhancing regulatory readiness significantly improves impact investment inflows. Both investors and governments are likely to benefit from cooperation and transparency, leading to mutually beneficial outcomes and effectively addressing the social and economic challenges of the MENA region suffers from. This study contributes to the existing literature by examining how ecosystem readiness influences impact investment in addressing social and economic challenges and supports sustained economic growth in the MENA region. Policy recommendations include streamlining regulatory frameworks, fostering institutional transparency, and aligning incentives with investor preferences to maximize social and economic impact. Governments should focus on impact investment in their strategies and plans. They need to design policies to improve IER and reduce DC by simplifying regulations and reducing complexity, which can maximize mutual benefits and payoffs for all.\u003c/p\u003e","manuscriptTitle":"Enhancing Investment Ecosystem Readiness: A Game-Theoretic Model of Impact Investment in the MENA Region","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-26 11:56:25","doi":"10.21203/rs.3.rs-7442973/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e82632f0-b7dc-467e-9ca3-d88f60153782","owner":[],"postedDate":"August 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-26T11:56:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-26 11:56:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7442973","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7442973","identity":"rs-7442973","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}