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This paper explores the role of political connections in facilitating access to credit for firms in the Indian corporate sector. This study aims to address gaps in the literature by combining theoretical insights with empirical data. Our model proposes that political connections may reduce risk for firms, thereby enhancing their access to credit. Utilizing a unique dataset of S&P BSE 500 companies from 2001 to 2019, we analyze the extent of these connections and their impact on financial leverage and debt-to-asset ratios. Our findings reveal that politically connected firms, defined by their monetary donations to political parties and the inclusion of Members of Parliament on their boards, exhibit significantly higher financial leverage and debt-to-asset ratios than unconnected firms. This implies a lower perceived borrower's risk and an advantageous position in accessing credit, likely a result of their political ties. The implications of our findings extend to the realms of corporate governance, economic policy, and the broader understanding of emerging market dynamics. • Political connections, as part of non-market strategies of firms, may be crucial in accessing credit. • Our theoretical framework highlights role of risk and donation to political party by a firm in accessing credit. • This study constructs a novel dataset of political connections of Indian companies. • Political connections lead to more favorable borrowing-related outcomes of companies such as, financial leverage and debt-assets ratio. • Political connections specific to a particular political party tend to serve companies more (in terms of the aforementioned outcomes), when that particular party is in power. [ABSTRACT FROM AUTHOR]

We investigate whether fintech development expedites financial inclusion and affects the stability of the financial sector in BRICS economies. We first seek to identify the linkage between Fintech development and financial inclusion in the BRICS economies. We then explore if Fintech poses any threat to financial stability by studying the impact of Fintech on three main factors of financial stability; Country risk, Liquidity, and Price volatility to see any possible threat to financial stability. We apply the robust Global Vector Autoregressive (GVAR) model with Bayesian framework to analyze a monthly dataset ranging from 2015 to 2022. By applying a positive shock to Fintech over financial inclusion and financial stability, we reveal a positive dynamic relationship between fintech development and financial inclusion, with fintech exhibiting a long-term influence on financial inclusion in some BRICS countries than others. However, we found no significant evidence that fintech presents any threat to financial stability; at least not in the short term. We offer several policy implications and future research directions. • This study analyses monthly data of five BRICS economies. • The GVAR model is applied to investigate the impact of fintech on financial inclusion and financial stability. • Fintech significantly promotes financial inclusion in BRICS economies. • Fintech does not threaten financial stability in the BRICS markets. [ABSTRACT FROM AUTHOR]

Azerbaijan is known for its rich oil and natural gas resources and transit location in the Caspian basin. This article explores current political risks for the energy Multinational Corporations (MNC's) in Azerbaijan. In order to identify a political risk, a literature review is conducted, highlighting four categories proposed by Fitzpatrick as the main framework to understand the conditions giving rise to them. The findings focus on oil price fluctuations, COVID-19 pandemic, war with Armenia, climate change and environmental issues, digitalisation and technology and possible developments in Iran as the new political risks for the energy MNC's in Azerbaijan enforcing foreign investors to reconsider their risk analysis in this country. [ABSTRACT FROM AUTHOR]

This paper re-examines the dependence structure between uncertainty in oil prices and sovereign credit risk of oil exporters. To address this issue, we employ a copula approach that allows us to capture asymmetric and nonlinear dependence structures. Empirical analyses involve daily data of the 5-year sovereign credit default swaps spreads and the crude oil implied volatility from January 2010 to May 2019, covering a sample of ten oil-exporting countries. Except for Brazil and Venezuela, our results provide evidence of significant positive and upper tail dependence in the relationship between oil market uncertainty and oil exporters' sovereign risk. Overall, our findings highlight that high uncertainty in oil prices coincides with large-scale increases in the sovereign credit risk of oil-exporting countries, supporting the hypothesis that investors, exposed to economic losses from risk events in oil exporters, are all the more pessimistic that prevails high uncertainty about future oil prices. Our findings have implications for oil exporter' policymakers as well as investors. • We study the relationship between oil price volatility and the sovereign risk of oil exporters. • We use daily data of the sovereign CDS spreads and the crude oil implied volatility. • We provide evidence of positive and upper tail dependence in the relationship. • High uncertainty in oil prices coincides with a surge in the sovereign CDS spreads of oil exporters. [ABSTRACT FROM AUTHOR]

The Global Competitiveness Index (GCI) 4.0 provides an annual evaluation of country-level productivity and development in the fourth industrial revolution era. The GCI 4.0 is classified into 12 pillars representing socioeconomic, financial, health, technological, and other factors of production. Country risk, which is an aggregate measure of country-level exposure to financial, political, and economic risks, can influence national development. This study explores the association between country risk and competitiveness by mapping country risk drivers to GCI and GCI pillars to country risk. Two Bayesian Belief Network models, with a minimum prediction accuracy of 81.3 %, are developed using two data-sets representing the GCI and country risk ratings of 107 countries. Sensitivity analysis reveals that low performance in information and communication technology (ICT) adoption (monetary policy) can significantly affect country risk (GCI), whereas innovation capability (financial system risk) and institutions (legal system) can considerably improve country risk (GCI). By delving into how the pillars of competitiveness interact with various risk factors such as political stability, economic volatility, and regulatory environment, decision-makers, investors, and policymakers can gain valuable insights that guide effective resource allocation, risk mitigation strategies, informed policy formulation, and sustainable development efforts. • Probabilistic network models are developed to explore the association between country risk and competitiveness. • Two datasets are used to calibrate and validate the models. • Global competitiveness is explored through the lens of risk science. • A comprehensive sensitivity analysis is performed to assess the relative importance of individual risk drivers. [ABSTRACT FROM AUTHOR]

• Decision makers may emulate policies used in similar countries to reduce political risk of untested policies. • Countries' actual use of these strategies to reduce political risk can vary by policy or country type. • Countries tend to emulate renewable energy policies of countries with similar electric sector conditions. • Countries reduce political risk by emulating policies of politically similar countries for some policies but not others. • Developing countries are more likely to adopt the policies of donors who provide aid for development. The international environmental community and many donor countries have encouraged developing countries to adopt renewable energy (RE) policies that will encourage low-carbon energy development. While the drivers of RE policy adoption have been well-studied in the U.S. and Europe, we know little about the factors that drive RE policy adoption in developing countries. Both theory and anecdotal evidence suggest that policies often spread when one country emulates another's policy, but scholars of policy diffusion have tended to focus on emulation of political and ideological peers, overlooking other factors that may be particularly critical for driving RE policy adoption, including emulation of peers with similar electric sector conditions and emulation that is driven by coercive donor-recipient aid relationships. We use a directed dyadic analysis to assess the factors that prompt a country to emulate another's policies and to determine whether emulation patterns differ across developed and developing countries. We find that both sets of countries tend to emulate the policies of their political peers, and that developing countries tend to emulate the policies of donors. The effect of electric sector similarities varies by policy type. Countries emulate feed-in tariffs of countries with similar electric sector conditions, but they emulate quota policies of countries with dissimilar levels of reliance on renewable energy. Results suggest that different policies may diffuse via different emulation patterns. [ABSTRACT FROM AUTHOR]

Coal is an irreplaceable part of the world energy structure and the condition will not be changed in the near future. Under the Belt and Road initiative, more and more Chinese energy enterprises are planning to invest in coal-fired power plant (CFPP) abroad. However, there are multiple potential risks in investing in CFPP overseas. So, assessing the risk level can help the investors avoid too risky countries and at the same time facilitate the government to take measures to reduce the potential risks to attract more investors. To reasonably assess overseas investment risk of CFPP in countries along the Belt and Road initiative, this paper establishes an evaluation criteria system from eight dimensions which consists of a total of 39 criteria. Then, these criteria weights are determined through a combined analytic network process-Entropy method. Furthermore, considering the psychological characteristics of decision-makers, a TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) approach is used to rank the overall risk level of CFPP investment for 23 nations. The findings indicate that the criterion of economic foundation owns the largest weight. Moreover, among these evaluated nations, Singapore have the lowest risk for China's CFPP investment, followed by New Zealand and Thailand. • Coal-fired power plant investment risk assessment along the "Belt & Road Initiative" is evaluated. • An evaluation criteria system including 39 criteria from eight dimensions is established. • Criteria weights are determined through a combined ANP-Entropy method. • TODIM approach is used to rank the overall risk level for 23 nations. • Singapore New Zealand and Thailand are the ideal investment choices. [ABSTRACT FROM AUTHOR]

Abstract We examine the impact of political risks and financial development on investments in the petroleum industry utilizing a unique dataset of investments in individual oil and gas fields around the world. We find that the expected time to investment is shorter in countries that are politically stable, have solid property rights protection and more developed financial systems. Political risks have the strongest impact on multinational companies, whereas financial development matters only for domestic national oil companies. At the company level we find that expected time to investment is shorter for companies with higher valuation and lower debt. Moreover, companies are more likely to invest in countries where they invested recently and less likely to invest in countries where their competitors invested recently. [ABSTRACT FROM AUTHOR]

Abstract Although the issue of energy security stands high on the scale of the European Union's priorities, there has been no single accepted definition of energy security thus far. In light of the global economic crisis and political instability, the issue of energy security is directly linked to geopolitical and macroeconomic stability. This paper offers a new method of measuring energy security, which unlike the existing indicators of energy stability, in addition to economic and environmental indicators, also includes the political and social aspects within the composite indicator of country risk. The new Energy Security Index (ESI) is defined based on the application of Principal Component Analysis (PCA). Analysis of the values of a new ESI indicator shows that energy security is greatly influenced by GDP per capita, country risk, carbon intensity, energy intensity, final energy consumption per capita and electricity prices, while the least importance rests with the share of renewable sources in energy consumption and energy dependence. The values of the Index by country are stable over the entire observed period, but significant differences are noticeable between countries. The highest index values are reported in Luxembourg, Sweden, Finland and Denmark, and the lowest in Bulgaria, Romania, Estonia and Poland. With the aim of robustness check, the results of EU member states rankings were compared to country rankings based on the Energy Trilemma Index. Compared to country rankings based on the Energy Trilemma Index , three countries recorded the same rank (Denmark, Check Republic and Bulgaria), and the biggest deviation of 9 ranking position was reported by Luxembourg. The results of the research show that there is a statistically important difference in the value of energy security index between the observed groups of countries classified according to the level of macroeconomic stability. Highlights • New approach to energy security quantification, which includes social and political aspects. • Ranking of EU-28, based on new energy security index, is calculated. • Energy security is greatly influenced by GDP per capita and country risk. • Share of renewables in consumption doesn't have high impact on energy security. • Countries with higher macroeconomic stability have higher energy security index. [ABSTRACT FROM AUTHOR]

Abstract This article demonstrates how parties' issue responsiveness depends on the degree of electoral competition that they are facing as well as the salience of the issue on the party system agenda. While a growing literature on issue competition has presented empirical evidence on what parties and when they choose riding the wave strategies, we still lack an encompassing framework of why parties sometimes respond to voters' issue priorities and sometimes not. Taking into account the trade-offs between party supporters' priorities and those of the electorate as a whole this paper presents such a framework. It argues and empirically demonstrates that increasing levels of electoral competition as well as higher salience of issues on the party system agenda make parties more responsive to the priorities of the electorate as a whole at the cost of the priorities of their supporters. [ABSTRACT FROM AUTHOR]

Abstract Country risk is an important factor influencing the international investments and transactions. Forecasting country risks of host countries are crucial for investors to make investment strategies and decisions. Considering the complexity and nonlinearity of country risk, this paper proposes a hybrid forecasting model based on empirical mode decomposition (EMD) and extreme learning machine (ELM). Firstly, the original data is decomposed into several different frequency components using EMD. Then, ELM is used to predict the components of different scales respectively, and finally, final country risk forecasting values are integrated. Taking BRICS countries as sample, empirical results show that the EMD-ELM approach performs better than the single prediction models such as ARIMA, SVR and ELM. [ABSTRACT FROM AUTHOR]

We examine the impact of political risk in the MENA region on the cost at which firms can raise capital. Using the implied cost of equity as a measure of the cost of capital and ICRG's political risk rating as a proxy for political risk, we find that political risk results in a higher cost of capital. Economically, our results suggest that a one standard deviation increase in the political risk index is associated with a 450 basis points increase in the cost of equity capital of MENA firms. Our results are consistent across a battery of robustness checks. Our findings have important policy implications that are relevant to the MENA region and beyond. [ABSTRACT FROM AUTHOR]

Previously reported effects of institutional quality and political risks on foreign direct investment (FDI) are mixed and, therefore, difficult to interpret. We present empirical evidence suggesting a relatively clear, statistically robust, and intuitive characterization. Institutional factors that affect the likelihood of an abrupt and total loss of foreigners’ capital (i.e., return of capital) dominate factors that affect rates of return conditional on a strictly positive terminal investment value (i.e., return on capital). The evidence is consistent with the hypothesis that expropriation risk is most important among the available measures of different dimensions of institutional quality. A one-standard-deviation reduction in expropriation risk is associated with a 72% increase in FDI, which is substantially larger than the effects of any other dimensions of institutional quality as simultaneously estimated in our empirical models of expected FDI inflows. We show that this evidence is consistent with the predictions of a standard theory of FDI under imperfect contract enforcement and multiple dimensions of political risk. [ABSTRACT FROM AUTHOR]

COVID-19 has disrupted all spheres of life, including country risk regarding the exposure of economies to multi-dimensional risk drivers. However, it remains unexplored how COVID-19 has impacted different drivers of country risk in a probabilistic network setting. This paper uses two datasets on country-level COVID-19 and country risks to explore dependencies among associated drivers using a Bayesian Belief Network model. The drivers of COVID-19 risk, considered in this paper, are hazard and exposure, vulnerability and lack of coping capacity, whereas country risk drivers are economic, financing, political, business environment and commercial risks. The results show that business environment risk is significantly influenced by COVID-19 risk, whereas commercial risk (demand disruptions) is the least important factor driving COVID-19 and country risks. Further, country risk is mainly influenced by financing, political and economic risks. The contribution of this study is to explore the impact of various drivers associated with the country-level COVID-19 and country risks in a unified probabilistic network setting, which can help policy-makers prioritize drivers for managing the two risks. • A probabilistic network model is developed to explore dependencies among various drivers of COVID-19 and country risks. • Two datasets are used to calibrate and validate the model. • Individual risk drivers are assessed for their network-wide impact on COVID-19 and country risks. • A comprehensive sensitivity analysis is performed to assess the relative importance of individual risk drivers. [ABSTRACT FROM AUTHOR]

Nowadays, as an arena of politics, social media ignites political protests, so analyzing topics discussed negatively in the social media has increased in importance for detecting a nation's political risk. In this context, this paper designs and examines an automatic approach to forecast the daily outbreak of political risk from social media at a topic level. It evaluates the forecasting performances of topic features, investigated among the previous works that analyze social media data for politics, hidden Markov model (HMM)-based techniques, widely used for the anomaly detection with time-series data, and detection models, into which the topic features and the detection techniques are combined. When applied to South Korea's Web forum, Daum Agora, statistical comparisons with the constraints of false positive rate of < 0.1 and timeliness of < 0 show that, for accuracy, social network-based feature and, for sensitivity, energy-based feature give the best results but there is no single best detection technique for accuracy and sensitivity. Besides, they demonstrate that the detection model using Markov switching model with jumps (MSJ) with social-network based feature is the best combination for accuracy; there is no single best detection model for sensitivity. This paper helps make a move to prevent the national political risk, and eventually the predictive governance benefits the people. [ABSTRACT FROM AUTHOR]

Abstract: In the application of the Empirical Mode Decomposition (EMD), reconstruction to the intrinsic mode functions (IMFs) which are obtained by EMD is necessary in order to simplify analysis and make reconstruction results of more economic explanatory power. At present, there are two main reconstruction methods; one is based on the changing of data construction, represented by the fine- to-coarse method, the other one takes the correlation of the IMFs into consideration, for example, calculating the correlation between the marginal spectrums of different IMFs. In order to study the internal unity and differences between the two methods, country risk data of the BRICS countries are selected to make the empirical analysis. The results are as follows. Firstly, it is not reasonable that the residue obtained by the EMD is directly regarded as the trend of the original data. Secondly, by fine-to-coarse, all the IMFs can be reconstructed to three time scales, which are denoted as high-frequency mode, low-frequency mode and trend respectively, but explanation of these scales for the real situation is not satisfactory. At last, trend which is extracted based on the correlation of the IMF marginal spectrums can describe the basic behavior of the original data. Contrasted to fine-to-coarse, the results obtained by the second method are more reasonable. [Copyright &y& Elsevier]

Summary: Studies of the impact of local political risk on foreign direct investment inflows overlook that worldwide FDI comes in waves. Using a simple model we show that the impact of political risk on FDI inflows is likely to be weaker, the larger the worldwide amount of FDI, which may question standard estimates and their policy implications. Using a large sample of developing and developed economies, we estimate the sensitivity of the distribution of FDI inflows across countries, to the local political risk. We find that it is a decreasing function of the worldwide amount of FDI. This finding has been upheld after many robustness checks. [Copyright &y& Elsevier]

Abstract: This paper provides a regression analysis of the debt ratio of project-financed LNG infrastructures and gas pipeline projects, by using data relating to projects whose financial close occurred between June 2004 and March 2011. The projects located in risky countries tend to exhibit lower debt ratios, which is consistent with the basic view of risk-averse funds suppliers. However, surprisingly enough, the more concentrated the equity ownership, the lower the debt ratio. [Copyright &y& Elsevier]

Abstract: This interdisciplinary research project focuses on relevant applications of Knowledge Discovery and Artificial Neural Networks in order to identify and analyze levels of country, business and political risk. Its main goal is to help business decision-makers understand the dynamics within the emerging market countries in which they operate. Most of the neural models applied in this study are defined within the framework of unsupervised learning. They are based on Exploratory Projection Pursuit, Topology Preserving Maps and Curvilinear Component Analysis. Two interesting real data sets are analyzed to empirically probe the robustness of these models. The first case study describes information from a significant sample of Spanish multinational enterprises (MNEs). It analyses data pertaining to such aspects as decisions over the location of subsidiary enterprises in various regions across the world, the importance accorded to such decisions and the driving forces behind them. Through a projection-based analysis, this study reveals a range of different reasons underlying the internationalization strategies of Spanish MNEs and the different goals they pursue. It may be concluded that projection connectionist techniques are of immense assistance in the process of identifying the internationalization strategies of Spanish MNEs, their underlying motives and the goals they pursue. The second case study covers several risk categories that include task policy, security, and political stability among others, and it tracks the scores of different countries all over the world. Interesting conclusions are drawn from the application of several business intelligence solutions based on neural projection models, which support data analysis in the context of country and political risk analysis. [Copyright &y& Elsevier]

Abstract: In the perspective of oil-importers, this paper considers an extension of the Value at Risk approach incorporated with time-varying conditional volatility model to trace the actual dynamic risk of regional oil-importing portfolio caused by the country risk volatility. With an application to oil economies in the Former Soviet Union (FSU) region, empirical results show that the country portfolio risk of oil-imports and country risk volatility in the FSU region has more significant influence on China''s oil-importing risk than that on EU''s. [Copyright &y& Elsevier]

Summary: We predict sovereign ratings for developing countries that do not have risk ratings from agencies such as Fitch, Moody’s, and Standard and Poor’s. Ratings are important in determining the volume and cost of capital flows to developing countries through international bond, loan, and equity markets. Sovereign rating also acts as a ceiling for the foreign currency rating of sub-sovereign borrowers and can be important for their access to international debt and equity capital. We generate shadow ratings for several developing countries that have never been rated and find that unrated countries are not always at the bottom of the rating spectrum. Several of them are projected to have a “B” or higher rating, in a similar range to that of the emerging market economies with capital market access. [ABSTRACT FROM AUTHOR]

Abstract: This study provides evidence of the value creation of different equity entry modes in a sample of international investments performed by all Italian medium-sized listed firms in the period 1986–2006. Our research shows a positive and significant market reaction to announcements of internationalization strategies. The results are largely affected by high-equity entry modes carried out in advanced economies. Low-equity entry modes and international operations performed in emerging countries show no significant market reaction. We also find that the relative size of the deal, the firm age, the country risk, and the evolution of information disclosure regulation, matter in explaining the outcomes. [ABSTRACT FROM AUTHOR]

This paper statistically analyzes the effects of climatic natural disasters and political risk on bilateral trade in a large-N sample of countries and years. Our theory suggests that the effects of these forces on trade need to be studied together and that the two forces may interact with one another. In the statistical analysis, the unit of analysis is a pair of countries and the model is based on the trade gravity design. The results show that the direct effects of increases in the incidence of disasters and the political risk level in the importer or the exporter countries are negative, reducing trade. The results for the interaction between the two forces show (1) as the incidence of disasters increases, the marginal effect of political risk on trade becomes more negative, which indicates a greater decline in trade and (2) as political risk declines the marginal effect of disasters becomes less negative, indicating a smaller decline in trade. Additional analyses demonstrate the robustness of these results to changes in model specification, disaster measure, and estimation method. In the bigger picture, our findings suggest that if climate change increases the incidence of climatic disasters as projections of the global science suggest, the growth of economic globalization may decline, ceteris paribus. [Copyright &y& Elsevier]

Small Island Tourism Economies (SITEs) are developing sovereign countries that rely on tourism as a source of exports, and need a consistent inflow of foreign investment in order to facilitate economic growth. Access to international capital markets helps SITEs smooth out their consumption over time, while absorbing adverse domestic production shocks. This paper provides a comparison of tourism growth, country risk returns and their associated volatilities (or uncertainty) for 2 SITEs, namely Cyprus and Malta. Monthly data are available for both international tourist arrivals and composite country risk ratings compiled by the International Country Risk Guide (ICRG) for the period May 1986 to May 2002. The time-varying conditional variances of tourism growth and country risk returns for the 2 SITEs are analysed using multivariate models of conditional volatility. Empirical results show that Cyprus and Malta are complementary destinations for international tourists. Changes to tourism patterns in Cyprus lead to changes to tourism patterns in Malta. Hence, tour operators and national tourism promotion authorities in Cyprus and Malta should collaborate closely in marketing and promoting joint tourism products. Moreover, foreign entities interested in investing in the tourism sectors of Cyprus and Malta should consider investment projects that span a long period of time. The performance of the tourism sector and the associated composite risk are independent of each other for the two countries. However, there is a direct relationship between the tourism sectors of Cyprus and Malta and their respective country risk settings. [Copyright &y& Elsevier]

Abstract: The large number of financial crises in emerging markets over the past ten years has left many observers, both from academia and financial institutions, puzzled by an apparent lack of homogenous causal relations between endogenous economic variables and the bursting of large financial shocks. The paper aims at showing that the key difficulty is not the identification of proper endogenous variables, but the ability to combine them in a way that is able to capture the combinatorial aspect of such causal relations. The paper is based on a newly developed non-parametric methodology for country risk signaling: the RiskMonitor CDM-Model. Using a combination of macroeconomic indicators and a composite model of 5 modern non-parametric classification methods, we constructed 9 early warning signals to predict financial crises in emerging markets. These signals are constructed for 3 types of crises (cyclical crises, exchange rate crises and transfer crises) and over 3 horizons (less than 1 year, 1 to 3 years, 3 to 5 years). This complex use of quantitative models is able to provide excellent early warning information, with impressive back-testing results on 50 developing countries over the period 1980 to 2002. [Copyright &y& Elsevier]

Provides a different perspective for elaborating on the role of private infrastructure investments as a medium for attracting foreign capital in developing countries in the 1990s. Reasons for growth in capital flows to infrastructure; Details on an analytical framework for valuation of foreign currency denominated loans to infrastructure projects; Reference to empirical results of an econometric analysis of the credit risk premium relating to foreign loans.

Investment in renewable energy is essential for reaching ambitious climate goals outlined in the Paris Agreement. Unfortunately, a large investment gap prevails, particularly in developing economies with underdeveloped domestic capital markets and weak institutions. Multilateral development banks with softer budget constraints and longer investment horizons can play an important role in filling this gap. Development finance, which traditionally originated in the West, has been increasingly dominated by two Chinese state-owned development banks: the China Development Bank and the China Export-Import Bank. These banks acted as major financiers of the Chinese Belt and Road Initiative and, between 2005 and 2017, provided more than US$220 billion of overseas energy finance - more than any other multilateral development bank. Their investments have been controversial: the Chinese banks were often accused of financing fossil fuels projects located in politically and economically risky countries. This paper uses detailed data on the Chinese energy finance to illustrate the investment pattern of the Chinese banks, and implements Hurdle and simultaneous Probit models to test whether the two banks are in fact tolerant of the country risk: credit, governance and political risk. The analysis shows that projects located in countries that are politically stable but have higher credit risk and corruption levels are more likely to receive Chinese energy finance. Governance risk and autocratic regime type do not affect the decisions of the Chinese banks. This investment pattern indicates missed opportunities for advancing the clean energy transition and creates future risks for the host countries i.e. stranded assets. Image 1 [ABSTRACT FROM AUTHOR]