Investment Rating - The report does not explicitly provide an investment rating for the industry under discussion Core Insights - The value-added tax (VAT) is an effective revenue tool for both developed and developing countries, with 175 countries implementing it as of 2024 [7] - VAT exemptions can lead to increased production costs as they deny input tax credits, resulting in VAT being embedded in the prices of goods and services [2][7] - The paper develops a VAT model using data from 29 European countries to analyze the effects of VAT exemptions on final prices and their overall effectiveness [2][7] - Exemptions are often used for pragmatic reasons, such as reducing compliance costs for small businesses and addressing specific policy goals, but they can have negative consequences that undermine their effectiveness [8][21] Summary by Sections Introduction - The VAT's design allows businesses to charge VAT on sales while claiming credits for VAT paid on purchases, ensuring it acts as a tax on final consumption [7] - Exemptions disrupt this process by increasing production costs and embedding VAT in prices, which has not been extensively quantified in previous research [7][8] Methodology - The model is based on input-output tables for 29 European countries, capturing supply and use relationships among 45 commodities [12][24] - The model allows for the introduction and removal of exemptions, capturing the direct, embedded, and cascaded VAT effects [13][14] Simulation Results - The simulation results indicate that effective VAT rates on exempted commodities are always below the baseline VAT rate of 10% but above zero due to embedded VAT [19][64] - The degree of embedded VAT varies significantly across commodities, with some exemptions leading to higher effective tax rates on final consumption than the standard VAT rate [65][66] - The report concludes that exemptions are an inferior policy tool compared to reduced VAT rates and should be limited to addressing specific pragmatic concerns [21][22]

Investment Rating - The report does not explicitly provide an investment rating for the industry. Core Insights - The integration of large language models (LLMs) in evaluation practices can significantly enhance the efficiency and validity of text data analysis, although challenges in ensuring the completeness and relevance of information extraction remain [2][17][19]. Key Considerations for Experimentation - Identifying relevant use cases is crucial, as LLMs should be applied where they can add significant value compared to traditional methods [9][23]. - Detailed workflows for use cases help teams understand how to effectively apply LLMs, allowing for the reuse of successful components [10][28]. - Agreement on resource allocation and expected outcomes is essential for successful experimentation, including clarity on human resources, technology, and definitions of success [11][33]. - A robust sampling strategy is necessary to facilitate effective prompt development and model evaluation [12][67]. - Appropriate metrics must be selected to measure LLM performance, with standard machine learning metrics for discriminative tasks and human assessment criteria for generative tasks [13][36]. Experiments and Results - The report details a series of experiments conducted to evaluate LLM performance in text classification, summarization, synthesis, and information extraction, with satisfactory results achieved in various tasks [19][49]. - For text classification, the model achieved a recall score of 0.75 and a precision score of 0.60, indicating effective performance [53]. - In generative tasks, the model demonstrated high relevance (4.87), coherence (4.97), and faithfulness (0.90) in text summarization, while also performing well in information extraction [58]. Emerging Good Practices - Iterative prompt development and validation are critical for achieving satisfactory results, emphasizing the importance of refining prompts based on model responses [14][60]. - Including representative examples in prompts enhances the model's ability to generate relevant responses [81]. - A request for justification in prompts can aid in understanding the model's reasoning and improve manual verification of responses [80]. Conclusion - The report emphasizes the potential of LLMs to transform evaluation practices through thoughtful integration, continuous learning, and adaptation, while also highlighting the importance of maintaining analytical rigor [18][21].

Investment Rating - The fiscal deficit is expected to be 5.5 percent of GDP in FY2024/25, slightly up from 5.4 percent in FY2023/24, indicating a challenging fiscal environment [17][26]. Core Insights - Total revenue is estimated to have declined to 19.9 percent of GDP in FY2023/24 from 21.3 percent a year earlier, projected to rise to 22.2 percent in FY2024/25 [19][34]. - Public debt is expected to remain elevated at about 62 percent of GDP in FY2024/25 [19]. - Spending is budgeted to rise to 27.4 percent of GDP in FY2024/25 from 25.0 percent in FY2023/24, driven by rising costs associated with civil service payroll, MSME development, and higher defense spending [20][47]. - Inflation-adjusted spending on public health is estimated to have declined by 46 percent between FY2019/20 and FY2024/25, significantly impacting healthcare demands [20][68]. - Inflation-adjusted spending on education has declined by 35 percent between FY2019/20 and FY2024/25, reflecting the adverse effects of the pandemic and military coup [21][78]. - Social protection spending has decreased from 0.13 to 0.05 percent of GDP between FY2019/20 and FY2024/25, indicating a shift in government priorities [23][99]. Public Finance Trends - The fiscal deficit is projected to increase slightly to 5.5 percent of GDP in FY2024/25, driven by higher expenditure projections [17][26]. - Non-tax revenue accounted for about two-thirds of total revenue in FY2023/24, with significant contributions from State-owned Economic Enterprises, particularly in oil and gas [18][35]. - Total spending is revised to increase to 27.4 percent of GDP in FY2024/25, largely due to recurrent spending [47]. - The wage bill is expected to yield a 0.1 percentage point increase in the wage bill, up to 1.8 percent of GDP [47]. Sectoral Analysis Health Sector - The Ministry of Health's spending is projected to remain low at around 0.6 percent of GDP in FY2024/25, contributing to a decline in the overall resilience of Myanmar's healthcare system [61][67]. - The real value of Ministry of Health spending has significantly declined, limiting the public health sector's capacity to provide essential services [68]. Education Sector - The Ministry of Education's spending as a percentage of GDP has steadily declined from 2.1 percent in FY2019/20 to around 1.6 percent in FY2024/25 [77][78]. - The budget for the School Improvement Support Program has decreased, reflecting the broader impact of escalating conflict across the country [90]. Social Protection Sector - Social protection spending has declined significantly, with real spending by the Ministry of Social Welfare, Relief, and Resettlement dropping by 66 percent between FY2019/20 and FY2024/25 [107]. - The share of the population receiving any type of cash assistance has reduced from 8.7 percent in 2017 to 5 percent in 2023, indicating a decrease in social support [108].

Investment Rating - The report does not provide a specific investment rating for the industry. Core Insights - The informal sector in low and middle-income countries (LMICs) contributes between 30% to 70% of GDP and employs 20% to 80% of the workforce, indicating a significant portion of economic activity operates outside regulatory frameworks [9][14]. - The study compares two widely used methods for surveying informal enterprises: household surveys and area-based enterprise surveys, revealing significant differences in the estimated number of informal enterprises, with household surveys reporting a notably higher count [4][15]. - Both survey methods yield consistent descriptive statistics regarding informal enterprises and identify key factors influencing their performance, such as bank account ownership, business sector (retail), phone usage, and operating in fixed locations outside the household [4][15]. Summary by Sections Introduction - The informal sector is a prominent feature in LMICs, with substantial contributions to GDP and employment, yet measuring its size poses significant challenges due to methodological issues [9][10]. Methodology - The study employs two main survey methods: household surveys (HS) and area-based enterprise surveys (ISES), each with distinct advantages and disadvantages in estimating the informal sector [20][21]. - The research aims to explore the differences between these methods and provide recommendations for enhancing the measurement of informal enterprises [12][13]. Findings - The analysis indicates that while the two methods differ significantly in estimating the number of informal enterprises, they are largely consistent in generating descriptive statistics about these enterprises and their performance-related factors [15]. - The informal sector in Ghana includes both agricultural and non-agricultural enterprises, with over 65% of employment and nearly 36% of GDP attributed to informal enterprises [14]. Data and Sampling Procedures - Data for the study was collected from two independent surveys conducted in the same geographical areas of Ghana, specifically in Kumasi and Tamale, during similar time frames [30][31]. - The HS-IME survey utilized a two-stage stratified cluster sampling design, while the ISES survey employed an adaptive cluster sampling method, highlighting the methodological differences in capturing informal enterprises [45][46]. Conclusion - The report emphasizes the importance of accurate data collection methods to inform policy decisions regarding the informal sector, which is crucial for understanding economic dynamics and improving labor market conditions in LMICs [14][15].

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The report emphasizes the importance of accurately estimating tax buoyancy for medium-term fiscal sustainability and prudent spending choices [16] - It distinguishes between tax elasticity and tax buoyancy, noting that while both measure tax revenue responses to economic growth, they yield different outcomes [16][20] - The report recommends a methodological approach for estimating tax buoyancy, which is crucial for analyzing a country's tax systems [17] Summary by Sections Introduction - The introduction outlines the significance of revenue mobilization projections and the relationship between tax systems and economic activity [16][17] Theoretical Framework and Empirical Approaches - Tax buoyancy is defined as the total response of tax revenues to both automatic changes in economic growth and discretionary changes in tax policy [20] - Theoretical frameworks for estimating tax buoyancy include autoregressive distributed lag (ARDL) models, which allow for dynamic relationships between tax revenue and GDP [27][28] Empirical Approach for Estimating Tax Buoyancy - The report utilizes annual panel data on total tax revenues and GDP for 171 countries from 1980 to 2021, emphasizing the need for a large number of observations [40] - It recommends using the common correlated effects (CCE) estimator for panel data to account for unobserved heterogeneity and cross-sectional dependence [41] Results - Long-run tax buoyancy estimates are around one for high-, upper-middle-, and lower-middle-income countries, while low-income countries show significantly less than one, indicating a risk of increased indebtedness [46] - Short-run buoyancy estimates across all country-income groups suggest that tax systems are not well equipped to stabilize the economy in the short run [46] - The report presents detailed tax buoyancy estimates by country-income groups and regions, highlighting variations in buoyancy across different classifications [47][49]

Investment Rating - The report indicates a positive outlook for the Vietnamese economy, with a real GDP growth target of 8 percent for 2025, supported by increased domestic consumption and investment [7][30]. Core Insights - Vietnam's GDP growth accelerated to 6.9 percent year-on-year in Q1-2025, up from 5.9 percent in Q1-2024, driven by stronger domestic consumption and investment [2][14]. - Merchandise exports growth slowed to 10.6 percent in Q1-2025 from 16.8 percent in Q1-2024, influenced by high base effects and potential global demand slowdown [3][15]. - FDI new commitments declined by 9.2 percent year-on-year in Q1-2025, while FDI disbursements remained resilient at $4.9 billion, reflecting a 7.1 percent increase year-on-year [3][21]. - Industrial production increased by 8.6 percent year-on-year in March 2025, compared to 4.8 percent in March 2024, with significant contributions from apparel, electronics, and machinery [4][17]. - Retail sales surged by 10.8 percent year-on-year, marking the highest growth in nearly two years, supported by a 9.5 percent increase in average monthly income [4][23]. - Inflation rose to 3.1 percent year-on-year in March 2025, driven by food and housing prices, but remains below the State Bank of Vietnam's target of 5 percent for 2025 [5][25]. Summary by Sections Economic Growth - Real GDP growth reached 6.9 percent year-on-year in Q1-2025, up from 5.9 percent in Q1-2024, with consumption and investment growing by 7.4 percent and 7.2 percent respectively [14]. Trade and Investment - Merchandise exports grew by 10.6 percent in Q1-2025, down from 16.8 percent in Q1-2024, while imports increased by 16.9 percent year-on-year [3][15]. - The trade surplus decreased to $3.2 billion in Q1-2025 from $7.7 billion in Q1-2024 [15]. Industrial Production - Industrial production index rose by 8.6 percent year-on-year in March 2025, with the PMI indicating expansion at 50.5 [4][17]. Domestic Consumption - Retail sales of goods and services increased by 10.8 percent year-on-year, supported by rising average monthly income [4][23]. Inflation and Monetary Policy - Inflation increased to 3.1 percent year-on-year in March 2025, with the SBV raising the inflation target to 5 percent for 2025 [5][25]. Fiscal Performance - Revenue collection for Q1-2025 reached 36.7 percent of the annual plan, driven by increases in VAT and corporate income tax [6][30].

Investment Rating - The report does not explicitly provide an investment rating for the industry or companies involved. Core Insights - The Startup Act in Tunisia aims to promote the creation and growth of innovative enterprises through various incentives, including tax exemptions and simplified procedures, which have shown to improve survival rates and job creation among participating firms [3][10][13]. Summary by Sections Introduction - The report highlights the significant role of startups in job creation and productivity growth, despite their high failure rates. It emphasizes the need for targeted policies to support startups, particularly in developing countries [8]. Impact of the Startup Act - The analysis focuses on the Startup Act's impact on firms that received the startup label, which grants them access to various benefits. The study uses a rigorous methodology to assess the effects on firm survival and performance [9][11][12]. Findings - Participating firms showed an 18 percentage point increase in survival rates compared to the baseline of 53%. Additionally, these firms increased their average employment by 2.0 employees and their wage bill by 69,000 TND (approximately 23,000 USD) [13][14]. Economic Context - Tunisia faced high unemployment rates, particularly among youth, during the analysis period. The Startup Act was implemented in a challenging economic environment, with a contraction in GDP and high inflation [33][35]. Data Sources - The research utilized a comprehensive dataset from various government sources, including tax, employment, and trade data, to evaluate the performance of firms that applied for the startup label [37][38]. Methodology - A difference-in-differences approach was employed to compare the performance of labeled firms with those that were not selected, addressing potential selection bias through a detailed evaluation process [42][44]. Conclusion - The report concludes that the Startup Act has been effective in promoting the survival and growth of innovative startups in Tunisia, providing valuable insights for similar initiatives in developing economies [17][18].

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - Achieving global net-zero carbon emissions requires halting deforestation and leveraging tropical forests as carbon sinks, with market mechanisms from REDD+ projects playing a crucial role [4][10] - Current carbon markets are underdeveloped, with existing mechanisms lacking the quality needed to support expanded demand, although efforts to enhance transparency and regulation are accelerating [4][5] - Innovative financial tools are being explored to mobilize investment in REDD+ frameworks, particularly in tropical countries, with significant potential for future development [5][18] Summary by Sections Section 1: Economic Drivers of Deforestation - Deforestation reflects unsustainable economic models in many developing countries, necessitating a fundamental shift towards sustainable growth that aligns economic development with forest conservation [9][10] - Effective policies combining protection and economic incentives are essential to halt deforestation, particularly in the Amazon [9][10] Section 2: JREDD+ Economics - The average price of REDD+ emission reductions (ERs) has increased significantly, from $3.9 per ton in 2019 to $11.21 per ton in 2023, yet the market remains small and insufficient to incentivize deforestation reduction [11][23] - The estimated cost for economically viable REDD+ supply is between $30 to $50 per ton of CO2, indicating a potential for significant cost savings in the transition to net-zero [12] Section 3: Innovative Financial Tools - The report discusses the potential of forest carbon bonds, call options, and put options to lower investment risks and mobilize private capital for REDD+ projects [18][41] - Forest carbon bonds can provide a mechanism for borrowing against future emission reductions, essential for financing necessary investments to curb deforestation [18][41] - Options contracts can help manage risks associated with carbon price fluctuations, allowing for more stable investment environments [54][56] Section 4: Case Study of Brazil - A numerical example from Brazil illustrates how the proposed financial tools can enhance the capacity for private investment and accelerate JREDD+ initiatives [19][20] - The tools discussed could mobilize substantial investment, creating strong policy incentives to prevent deforestation [19][20] Section 5: Future Outlook - The report emphasizes the need for increased private sector participation in the JREDD+ market, both as buyers of carbon credits and as financiers of emission reduction actions [15][16] - The development of financial solutions tailored to the diverse needs of investors is crucial for attracting private capital to the JREDD+ market [18][32]

Investment Rating - The report does not explicitly provide an investment rating for the industry analyzed. Core Insights - The study estimates the scale of labor market scarring effects in developing countries, particularly focusing on the stigma and human capital loss experienced by unemployed workers due to factory closures. The findings indicate a significant and lasting income reduction, with average hourly wages declining by 7.5% over a nine-year observation period, and a more pronounced decline of 10.8% in the first year following job loss. The analysis reveals that stigma accounts for 30.8% of the average income loss, while lost employer-specific human capital explains the remaining 69.2% [4][59][60]. Summary by Sections Introduction - The introduction discusses the reallocation of labor and the potential for scarring effects in labor markets, particularly in developing countries where informal employment is prevalent. The paper aims to fill the gap in literature regarding labor market scarring effects in these economies [8]. Literature Review - The literature review highlights the scarcity of empirical evidence on labor market scarring effects in developing countries, contrasting with the extensive research available for developed economies. It references various studies that have examined the impact of unemployment on wages and employment probabilities in different contexts [15][18]. Data - The study utilizes data from the National Employment and Unemployment Survey (ENOE) in Mexico, covering a representative sample of approximately 1.67 million workers from 2005 to 2019. The analysis focuses on individuals aged 15 to 65 and examines the effects of job loss due to factory closures [20][22]. Econometric Methods - The econometric strategy involves estimating the average impact of unemployment on labor market outcomes, distinguishing between temporary and permanent effects. The study employs a difference-in-differences (DID) approach to control for unobserved individual characteristics [26][29]. Results - The results indicate that workers displaced by factory closures experience significant and persistent wage declines, with an average reduction of 7.5%. The analysis shows that the probability of formal employment decreases in the short term but recovers over time. The findings also reveal differences in the impact of factory closures based on education levels and gender [39][41][43]. Conclusion - The conclusion summarizes the contributions of the study, emphasizing the importance of understanding labor market scarring effects in developing countries and the relative contributions of stigma and human capital loss to income reductions. The report suggests avenues for future research to further explore these dynamics [58][60].

Investment Rating - The report does not explicitly provide an investment rating for the Maldives industry Core Insights - Economic growth in the Maldives remained robust in 2024, with real GDP growth estimated at 5.5 percent, driven primarily by a strong tourism sector [18][34] - Tourist arrivals reached an all-time high of 2.05 million in 2024, marking an increase of 8.9 percent year-on-year [18][35] - Headline inflation averaged 1.4 percent in 2024, with food inflation rising to 6.6 percent [19][42] - The fiscal deficit widened to MVR 12.7 billion (US$822.4 million) or 11.7 percent of GDP in 2024, driven by increased expenditure [20][52] - The current account deficit (CAD) remained elevated at 20.5 percent of GDP in 2024, with a trade deficit of US$3.3 billion [21][68] - Foreign exchange reserves fell to critically low levels, reaching US$371.2 million in September 2024, before recovering to US$832.1 million by February 2025 [22][69] - Public and publicly guaranteed debt rose to US$9.4 billion, or 134.2 percent of GDP, in 2024 [25][59] - The report emphasizes the need for urgent fiscal consolidation to address rising public debt and external vulnerabilities [30][29] Economic Update - Growth remained robust while inflationary pressures picked up in recent months [34] - Fiscal deficits continued to increase and remain elevated [49] - Public debt and external debt servicing increased in 2024 [59] - Potential austerity measures may impact household welfare if unmitigated [65] - External pressures have severely reduced FX reserves [68] Outlook and Risks - Growth is forecast to moderate, inflation to increase, and fiscal and external deficits to remain elevated [26][27] - Risks to the outlook are heavily tilted to the downside [29] - Implementing a sharp fiscal adjustment remains an urgent priority in the medium term [30]