Investment Rating - The report does not explicitly provide an investment rating for the industry but emphasizes the importance of climate policies in attracting green foreign direct investment (FDI) in emerging markets and developing economies (EMDEs) [5][6][17]. Core Insights - The report highlights that achieving COP28 goals necessitates a doubling of clean energy investment globally by 2030, requiring an additional $600 billion in EMDEs excluding China [5][9]. - It identifies that foreign direct investment (FDI) is crucial for EMDEs to bridge the renewable energy investment gap and finance green projects, especially in the context of low fiscal space and constrained domestic investors [5][6]. - The analysis indicates that a greater number of climate policies correlates with higher FDI flows into renewable energy, particularly in countries with solar potential and low fossil fuel dependence [6][17]. - The report notes that while climate policies positively influence green FDI in renewable energy, they do not show a significant relationship with FDI in electric vehicles (EVs) and green hydrogen [6][39]. Summary by Sections Green FDI and Climate Policies - Green FDI has accelerated since 2016, tripling as a share of global GDP from 2014 to 2022, with inflows increasing from approximately $40 billion in 2014 to over $200 billion in 2022 [26][28]. - The report emphasizes that investments in renewable energy have remained stable, while those in EVs and green hydrogen have surged recently [28][29]. Econometric Evidence - The econometric analysis shows that closing the climate policy gap between EMDEs and advanced economies (AEs) could triple the green FDI to GDP ratio in EMDEs and close 40% of the private renewable investment gap [6][17][36]. - The findings suggest that while climate policies are associated with increased green FDI, they do not adversely affect non-green FDI inflows [36][39]. Country-Specific Experiences - Successful countries in attracting green FDI in renewable energy have implemented a diverse set of climate policies and adapted their energy frameworks to technological changes [8][21]. - For EVs, countries with prior automobile manufacturing experience and national sectoral strategies have seen higher FDI inflows [22][23]. - In the case of green hydrogen, comprehensive national strategies and favorable renewable energy production conditions are key drivers of FDI [8][24]. Global Factors - The report discusses how global initiatives, such as the Just Energy Transition Partnership and EU strategies for green hydrogen, have positively impacted green FDI in EMDEs [24][25]. - It also highlights that geopolitical fragmentation may limit the ability of countries to attract green FDI, as investments are less likely between politically distant nations [20][44].

Investment Rating - The report does not explicitly provide an investment rating for the residential property market in Ukraine. Core Insights - The authorities in Ukraine are committed to improving the House Price Index (HPI) to enhance transparency in the real estate market and strengthen systemic risk analysis [5][10] - A technical assistance mission was conducted to develop new processes for compiling the HPI, focusing on data cleaning and capacity building for staff [4][18] - The national HPI for Ukraine shows a price change of approximately 15% over six quarters from Q1 2023 to Q2 2024 [11] Summary by Sections Summary of Mission Outcomes and Priority Recommendations - A technical assistance mission took place from July 15-19, 2024, to assist Ukrainian authorities in developing new methods for HPI compilation [4] - The mission aimed to enhance data processing capabilities and improve the accuracy of property price indices [5][6] Data Sources - The SSSU currently uses data from real estate agents and the OLX platform for compiling the HPI [19] - OLX has agreed to provide data directly to the SSSU on a quarterly basis, which will improve data availability [19] Compilation Methods - The SSSU has implemented improved methods for HPI calculation, including the use of list prices and hedonic methods for quality adjustment [34] - A new stratification of data based on NUTS regional classification has been developed, enhancing the relevance of the data [36] Recommendations - The report outlines several priority recommendations, including upskilling staff in the R statistical package and automating data processing tasks [12][33] - It is recommended to extend data coverage to include houses and gather more detailed location information for properties [32][33]

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - Pakistan's economy has lagged behind regional peers for over a decade, with GDP per capita growth averaging only 1.9% from 2000 to 2022, compared to 4.5% for Bangladesh and 7.5% for China, indicating a need for urgent policy corrections [5][6] - The report highlights macroeconomic distortions and policy-related restrictions, including protectionist interventions and insufficient investment in human capital, as key factors contributing to underperformance [5][8] - Structural reforms are essential for creating fiscal space, building human capital, and enabling private sector growth, with potential growth increases of about 2% over five years from consistent reform implementation [39][58] Summary by Sections Economic Performance and the Road Ahead - Pakistan's living standards have declined, with weak contributions from human and physical capital and shrinking productivity [8] - Economic growth from 2000 to 2020 was primarily driven by physical capital accumulation and increased labor hours, while total factor productivity (TFP) and labor quality contributions were significantly lower [8][19] - The country has struggled with declining export performance and limited trade openness, which hampers development and external viability [8][11] Drivers of Decline in Living Standards - The report identifies persistent resource misallocation and policy-induced distortions as major contributors to the decline in living standards and competitiveness [14][19] - Agriculture, characterized by low productivity and government interventions, exemplifies how policies can trap resources in low-productivity sectors [16][18] - The regulatory environment and public investment management issues have deterred domestic and foreign direct investment, leading to low FDI inflows compared to peers [20][21] Supporting Private Sector Development - To shift Pakistan onto a new economic trajectory, it is crucial to remove protectionist policies and enhance competition, which would spur innovation and resource reallocation [30][39] - The report emphasizes the need for improved public investment efficiency and tax collection to create space for higher investment in physical and human capital [30][53] - Structural reforms could lead to a 7% increase in output and a 6% reduction in the public debt-to-GDP ratio over five years, highlighting the potential for significant macroeconomic gains [57][59]

Investment Rating - The report does not explicitly provide an investment rating for the industry under review. Core Insights - The paper examines the macroeconomic frameworks of IMF-supported programs in low-income countries from 2009 to 2022, focusing on the differences in macroeconomic targets and their achievements between fragile and non-fragile states [3][12][15] - Key findings indicate that program targets for fragile and non-fragile states are similar, with a notable optimism in projections except for inflation, and a weak correlation between targets and actual outcomes [3][15][16] - The study emphasizes the challenges in setting realistic, country-specific targets in IMF-supported programs, highlighting the need for better quantitative tailoring of these programs [3][12][15] Summary by Sections Introduction - The introduction outlines the study's focus on IMF-supported programs in low-income countries, particularly the differences in macroeconomic objectives between fragile and non-fragile states [12][13][18] Main Findings - Limited quantitative tailoring is observed, with no significant differences in program targets between fragile and non-fragile states [15][55] - There is considerable optimism in targets, which are often missed except for inflation [15][16] - Weak correlations exist between targets and outcomes, suggesting that country-independent targets could outperform program projections [16][55] Literature Review - The literature review highlights the scarcity of studies on IMF-supported programs in fragile states, noting that completion rates for lending programs with fragile states are significantly lower than those for non-fragile states [19][20] Methodology - The methodology section details the criteria for program inclusion, focusing on programs with a planned duration of 1.5 years or more, resulting in a sample of 84 programs across 43 countries [27][30] Quantitative Tailoring - The analysis of quantitative tailoring reveals that while absolute ambitiousness of targets is similar for both fragile and non-fragile states, relative ambitiousness may differ based on initial conditions [51][52][59] Optimism - The report assesses the extent of optimism in program targets, finding that targets are generally overly optimistic, particularly regarding growth projections [39][40] Correlation Between Targets and Outcomes - The correlation analysis indicates that for most variables, targets and outcomes are statistically independent, with the implication that better forecasting methods could improve program effectiveness [16][39] Conclusion - The conclusion reiterates the need for more realistic macroeconomic frameworks in IMF-supported programs, particularly for fragile states, to enhance the effectiveness of these programs [12][15][18]

Investment Rating - The report does not explicitly provide an investment rating for the industry under discussion. Core Insights - The productivity growth in Latin America and the Caribbean (LAC) has stagnated since 1980, with income levels showing no convergence with the US, unlike emerging Asia and Europe [8][21] - The sluggish productivity growth is attributed to limited technology diffusion and a large informal sector, which hampers overall economic growth [9][10][19] - Artificial intelligence (AI) has the potential to enhance productivity in the formal sector, reduce informality, and facilitate economic convergence with advanced economies [14][20] Summary by Sections Low Productivity Growth in Latin America and the Caribbean - Labor productivity growth in LAC has been only 0.5 percent annually since 1980, compared to 4.2 percent in East Asia and 1.4 percent in the US [21] - The informal sector remains large, with informal firms being only 15 percent as productive as formal firms, limiting overall productivity growth [25][31] The Important Role of Technology Diffusion in Growth - The limited diffusion of technology is a key reason for low productivity growth in LAC, with IT adoption lagging behind advanced economies [12][11] - Historical patterns show that technology diffusion can account for significant income disparities between countries [41] The Difference AI Can Make - AI is expected to boost labor productivity growth similarly to past IT innovations, with the potential for rapid adoption due to lower capital requirements [13][14] - AI could enable LAC to leapfrog technologies, as seen in Brazil's digital payment system, Pix [14] Labor Market Implications of AI - AI may not necessarily reduce overall employment; instead, it could create new jobs while also leading to job polarization [15][16] - Jobs at high risk of automation are primarily in sectors like call centers, while jobs that benefit from AI are in areas like healthcare [17][18] Adoption of AI in LAC - LAC's exposure to AI is below 40 percent of the labor force, compared to 60 percent in advanced economies, indicating a risk of falling behind in AI adoption [19] - Factors hindering AI adoption include weak competition, regulatory issues, and a large informal sector [19] Policies to Achieve the Full Potential of AI - Policies should focus on enhancing technology diffusion, supporting workforce transitions, and addressing skills gaps through education and training [20] - Investments in digital infrastructure and measures to reduce labor market informality are essential for maximizing AI benefits [20]

Industry Investment Rating - The report does not explicitly provide an investment rating for the industry, as it focuses on the development of a Global Soft Power Index (GSPI) rather than direct investment recommendations [3][9] Core Viewpoints - The report introduces a new comprehensive Global Soft Power Index (GSPI) composed of six dimensions, which allows for comparisons at both the headline level and sub-indices level, enabling granular analysis of soft power across countries [3][9] - The GSPI is constructed using a three-step approach: normalization of variables, aggregation into sub-indices, and aggregation into the final index, providing a systematic framework for measuring soft power [9][25] - The report highlights the macro-financial relevance of the GSPI, particularly its impact on exchange rate volatility, with the culture and global reach dimensions being the most significant in explaining real exchange rate volatility [10][60][62] Data Overview - The GSPI is based on 29 indicators across six dimensions (commercial, culture, digital, education, global reach, and institutions) for a broad set of countries from 1990 to 2021 [9][15] - Data availability constraints limit the most comprehensive version of the GSPI to a balanced panel of 66 countries from 2007 to 2021 [20] Index Methodology - The GSPI is constructed using a standard three-step approach: normalization of variables, aggregation into sub-indices, and aggregation into the final index [25] - Principal Component Analysis (PCA) is used to determine the weights for each sub-index, ensuring that the highest possible variation in the indicator set is accounted for with the smallest number of factors [27][30] Index Results - There is significant variation in the level of soft power across countries, with the GSPI ranging from -0.59 in the Dominican Republic to 1.68 in South Korea as of 2021 [11][39] - Advanced economies generally have higher levels of soft power, but this is not always the case, as seen in the evolution of soft power in China and the United Kingdom, where China's soft power increased significantly while the UK's declined [11][40] - The GSPI and its sub-indices allow for the classification of countries into four groups based on their soft power levels, with Japan and South Korea forming a distinct group due to their high commercial prowess and lower performance in the culture dimension [43][46] Macro-Financial Application - The GSPI is used to test the impact of soft power on exchange rate volatility, with results showing that low soft-power countries exhibit a different dynamic between soft power and real exchange rate volatility compared to medium and high soft-power countries [10][49] - The culture and global reach dimensions of soft power are particularly relevant in explaining real exchange rate volatility, with global reach being the most significant sub-index [60][62]

Investment Rating - The report does not explicitly provide an investment rating for the electricity production industry regarding decarbonization Core Insights - The electricity production sector is the largest contributor to global emissions, and decarbonizing it involves complex optimization of costs, geographical potential, and technology complementarities [3][7] - Recent energy-economy models indicate a significant shift towards renewable energy, particularly solar and wind, which are projected to dominate the electricity mix by 2050 in scenarios aiming to limit global warming to below 2°C [3][10] - The paper synthesizes various specialized analyses to present a comprehensive overview of decarbonization strategies and the evolving role of different energy sources [8][15] Summary by Sections Introduction - The decarbonization of electricity is a macroeconomic priority due to its significant share in global emissions, necessitating a stable low-carbon electricity system [7][8] The Electricity Mix - Various models project that solar and wind energy will increasingly dominate the electricity mix, with significant regional variations based on local conditions [19][31] - Historical trends show a rapid increase in renewable energy capacity, with countries like Denmark and Lithuania achieving high shares of solar and wind [19][20] Types of Low-Carbon Electricity Production - Solar and wind energy are identified as the most cost-effective options for decarbonization, although they face challenges related to supply variability and land use [51][53] - Other options like hydropower, geothermal energy, carbon capture and storage (CCS), biofuels, and nuclear energy are also discussed, each with unique advantages and limitations [54][56][61] The Role of Cost - The report emphasizes the importance of cost in determining the viability of different energy sources, with solar and wind showing the lowest levelized cost of electricity [4][51] Flexibility Options - Flexibility options such as energy storage, grid extension, and demand flexibility are crucial for integrating variable renewable energy sources into the electricity system [5][46] Conclusion - The findings suggest that while achieving 100% renewable electricity may be challenging, high shares of renewables are feasible, and a diversified energy portfolio can enhance system reliability [40][46]

IMF Country Report No. 24/305 KINGDOM OF ESWATINI SELECTED ISSUES September 2024 This paper on Kingdom of Eswatini was prepared by a staff team of the International Monetary Fund as background documentation for the periodic consultation with the member country. It is based on the information available at the time it was completed on September 10, 2024. Copies of this report are available to the public from International Monetary Fund • Publication Services PO Box 92780 • Washington, D.C. 20090 Telephone: (2 ...

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The introduction of Central Bank Digital Currencies (CBDCs) will significantly impact monetary operations, requiring central banks to adapt their frameworks to manage the demand and supply of reserves effectively [14][15][29] - The analysis identifies three scenarios of CBDC substitution: CBDC substituting for cash, bank deposits, and central bank reserves, each with distinct implications for monetary operations [30][31][54] - The design features of CBDCs, such as access, remuneration, and holding limits, will influence the degree of substitution and the resulting effects on monetary policy [31][32] Summary by Sections Introduction - The report discusses the implications of CBDCs on monetary policy transmission and operations, emphasizing the need for central banks to anticipate challenges associated with CBDC implementation [14][15] A Primer on Monetary Operations - Central banks aim for price stability through various monetary policy regimes, including inflation targeting, exchange rate targeting, and monetary targeting [19][20] - Monetary operations involve setting objectives, intermediate targets, operational targets, and using instruments to achieve these targets [20][24] Implications of CBDC for Monetary Operations - CBDC is considered a central bank liability, similar to reserves or cash, and its substitution for other forms of money can affect monetary operations [29] - The report outlines three scenarios of CBDC substitution, each affecting reserve balances and monetary policy differently [30][31] Effects on Short-Term Interest Rates - Scenario 1 (CBDC substituting for cash) is unlikely to significantly affect short-term interest rates but may complicate liquidity forecasting [54] - Scenario 2 (CBDC substituting for bank deposits) is likely to affect short-term interest rates due to changes in reserve balances [55] - Scenario 3 (CBDC substituting for reserves) may not significantly impact short-term interest rates if CBDC is treated equivalently to reserves [61] Adapting Monetary Operations and CBDC Designs - Central banks need to adapt liquidity forecasting methodologies to account for the volatility of CBDC demand [62] - Potential solutions include switching to fixed rate targeting, increasing intra-day liquidity windows, and adjusting operational frameworks to manage interest rate volatility [63][66]

Investment Rating - The report does not explicitly provide an investment rating for the industry under discussion. Core Insights - The report emphasizes the importance of Central Bank Digital Currency (CBDC) in the evolving payments landscape, highlighting its potential to complement existing payment systems like fast payment systems (FPS) and e-money, while addressing issues such as financial inclusion and payment efficiency [12][30][41]. Summary by Sections 1. Introduction - The report discusses the comparative analysis of retail CBDC, FPS, and e-money, emphasizing the need for central banks to consider their specific payment landscapes and objectives when exploring these options [12][14]. 2. Understanding Retail Payment Systems - It outlines the functionalities and features of various payment systems, including e-money, FPS, and CBDC, and describes their core components: instrument, infrastructure, and scheme [16][19]. 3. CBDC's Role in an Evolving Payments Landscape - The report identifies emerging trends in the payments landscape, such as the decline of cash usage and the rise of private digital payment networks, which pose risks to the efficiency and resilience of payment systems [30][31][39]. 4. Implementing a Strategy - It discusses the strategies central banks can adopt to explore CBDC, considering practical constraints such as legal, regulatory, and resource limitations [12][14][41]. 5. Concluding Thoughts - The report concludes that a holistic approach is necessary for central banks to navigate the complexities of the payment landscape, ensuring that CBDC can effectively support their policy objectives [12][14][41].