Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The productivity of schooling is maximized when there is a match between a child's skill level and the complexity of the learning experiences offered at school, with mismatches in either direction being detrimental to learning outcomes [10][75] - The relationship between early childhood skill and the productivity of schooling follows an inverted-U shape, indicating that increasing early childhood skill enhances productivity up to a certain point, after which further increases can reduce productivity due to widening mismatches [10][76] Summary by Sections Introduction - The study emphasizes the importance of matching learning experiences to a child's understanding level to enhance learning outcomes, supported by various learning theories [2] Empirical Evidence - The research utilizes longitudinal data from the Young Lives Study, focusing on children from Peru, India, and Vietnam, to analyze the effects of schooling on child skill [8][12] - The findings indicate that the productivity of schooling is influenced by the difference between a child's existing skill and the complexity of the school curriculum [10][19] Methodology - A value-added specification is employed to account for individual-specific effects and to analyze the relationship between child skill and school complexity [9][41] - The study uses a non-linear dynamic panel model to estimate the effects of schooling, allowing for heterogeneity in productivity based on mismatches [9][50] Results - The main results reveal that a 1% increase in schooling can lead to a 0.55% increase in skill, with the productivity of schooling being highest when there is a match between child skill and school complexity [51][55] - The analysis shows that the effect of early childhood skill on schooling productivity is non-monotonic, with positive effects dominating in lower skill quartiles and negative effects in higher quartiles [56][60] Cross-Country Evidence - The study extends its findings to India and Vietnam, confirming similar patterns of heterogeneous effects of schooling based on the mismatch between child skill and school complexity [61][69] Conclusion - The research underscores the necessity of tailoring educational experiences to align with children's skill levels to optimize learning outcomes, providing external validity to existing educational interventions [75][76]

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The report emphasizes the importance of automation in improving operational efficiency for multifamily property management companies, addressing rising costs, tenant expectations, and employee turnover [3][4][28] - It identifies significant opportunities for improvement in resident-centric operations, back-office operations, and employee retention [6][8] Summary by Sections Key Findings - The use of fully manual processes has decreased compared to the previous year, leading to reduced time and costs associated with administrative tasks for property management companies [5][28] - The report highlights opportunities for improvement in resident-focused operations, back-office operations, and employee retention [6][8] Opportunities to Improve Property Management Operations - The report outlines three main opportunities to enhance resident-facing operations: digitizing resident communication, improving cash flow through flexible payment options, and strengthening retention rates to reduce delinquency [36][48][52] Back-Office Operations - Four key opportunities for improving back-office operations are identified: fully automating rent collection, outsourcing utility billing to recover costs and eliminate workload, and enhancing employee efficiency through outsourcing [60][61][67] Employee Retention - The report discusses two main opportunities to improve employee retention: enhancing leadership and salary to retain staff, and ensuring employees feel valued within larger organizations [96][104]

Public Disclosure Authorized Policy Research Working Paper 11058 Dynamic, High-Resolution Poverty Measurement in Data-Scarce Environments Zhuo Zheng Timothy Wu Richard Lee David Newhouse Talip Kilic Marshall Burke Stefano Ermon David B. Lobell Development Economics Development Data Group February 2025 Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Policy Research Working Paper 11058 Abstract Accurate and comprehensive measurement of household livelihoods is critical f ...

Investment Rating - The report does not explicitly provide an investment rating for the industry analyzed. Core Insights - The labor market impacts of artificial intelligence (AI) are expected to be more limited in low- and middle-income countries (LMICs) compared to high-income countries (HICs), with only 12% of workers in low-income countries and 15% in lower-middle-income countries experiencing high exposure to AI [3][74]. - AI exposure is higher among women, urban workers, and those with higher education levels, indicating a disparity in how different demographic groups are affected by AI advancements [3][12][75]. - The analysis suggests that while AI may enhance productivity and automate certain tasks, it does not necessarily lead to job losses, as it could also augment worker productivity [3][12]. Summary by Sections Introduction - The report highlights the rapid development of AI, particularly generative AI, and its potential to transform jobs and economic structures, similar to historical technological revolutions [8][9]. Measuring AI Exposure and Labor Market Impacts - The study employs the AI Occupational Exposure (AIOE) index to assess the potential impact of AI on various occupations across 25 countries, representing a population of 3.5 billion people [10][30]. - The AIOE index indicates that high-income countries have the highest exposure to AI, with an average score of 62, while low-income countries have an average score of 37 [11][41]. Stylized Facts about AI in Low-, Middle-, and High-Income Countries - The average AIOE across all countries is 47, with significant variations based on income levels. High-income countries show a right-skewed distribution of AI exposure, while low-income countries exhibit a left-skewed distribution [39][41]. - The report categorizes AI exposure into four levels and finds that high-skilled occupations are more exposed to AI than low-skilled ones, with white-collar industries being the most affected [61][64]. Conclusion - The findings emphasize the need for tailored policy responses to manage AI's impact on the workforce, particularly in LMICs, where infrastructure challenges such as lack of electricity may hinder AI adoption [74][76]. - The report concludes that fears of significant labor market disruptions in LMICs due to AI may be overstated, suggesting that the immediate effects may be more about improving access to services rather than widespread job losses [78].

Investment Rating - The report does not explicitly provide an investment rating for the industry analyzed. Core Insights - The analysis indicates that upward educational mobility is positively associated with GDP per capita in Europe and Central Asia, while relative mobility indicators show no correlation with country income levels [3][13][81] - In Latin America, higher relative mobility correlates with lower income, whereas higher absolute mobility is linked to higher income [13][14][81] - The study introduces a new measure of intergenerational mobility in education, termed the upward mobility gap, which enhances the understanding of educational mobility across different contexts [11][80] Summary by Sections Introduction - The report discusses the importance of social mobility in economic growth, emphasizing that talent allocation improves in socially mobile societies [7][8] Literature Review - Previous studies show significant variations in intergenerational educational mobility across countries, with high persistence in Latin America and greater mobility in Northern Europe [16][18] Measures of Educational Mobility - The report utilizes various measures to capture trends in intergenerational educational mobility, including oriented mobility measures and absolute mobility measures [20][33] Empirical Framework - The empirical analysis employs a framework to assess the relationship between educational mobility and economic development, using data from 68 countries over the period 2000-2020 [37][43] Educational Mobility Across Countries - The report identifies patterns of intergenerational educational mobility, noting that upward absolute mobility has declined in Europe and Central Asia, while South Asia has seen increases in both absolute and relative mobility [12][63] Educational Mobility and Economic Development - The analysis reveals a context-specific relationship between educational mobility and income levels, with upward mobility in higher education showing a positive correlation with GDP per capita across various regions [67][68][81] Conclusions - The findings suggest that the relationship between intergenerational educational mobility and economic development is complex and varies by region, indicating that certain aspects of mobility are more relevant for growth in specific contexts [81][82]

Investment Rating - The report indicates that enhancing data transparency can lead to increased sovereign bond returns, particularly in countries with medium to higher levels of institutional quality [3][10][25]. Core Insights - Improved data transparency can mitigate the negative impact of high debt levels on bond returns, suggesting that even highly indebted countries can attract global investors through enhanced transparency [3][10][25]. - The study identifies a threshold effect, indicating that countries need to achieve a certain level of institutional quality (ICRG score greater than 4.15) for international creditors to benefit from improved data transparency [3][10][25]. - The empirical analysis demonstrates that both creditors and debtors can benefit from increased data transparency, with significant implications for investment decisions in sovereign bonds [34][35]. Summary by Sections Introduction - The report explores the relationship between data transparency and sovereign bond returns, focusing on the benefits for global investors rather than just sovereign borrowers [7][8]. Estimation Technique and Data - The study employs Fixed Effect Instrumental Variables (FE-IV) for panel data analysis to estimate the impact of data transparency on sovereign bond returns, controlling for various macroeconomic and financial factors [12][14][18]. Empirical Analysis - The findings reveal that enhancing data transparency leads to higher bond returns in countries with medium to higher levels of institutional quality, while high levels of public debt generally correlate with lower bond returns [25][26][30]. - The analysis shows that improving data transparency can still attract investors even in highly leveraged countries, thus increasing bond returns [27][30]. Calculating Creditors' Benefits - The report quantifies the potential gains for international creditors from improving data transparency in borrowing countries, estimating significant increases in bond returns across various regions [32][63]. Conclusion - The study concludes that greater data transparency enhances sovereign bond returns, particularly in countries with adequate institutional quality, and highlights the mutual benefits for both creditors and debtors [34][35].

Investment Rating - The report indicates a positive outlook for gold investment, with central banks and ETF investors expected to drive demand in 2025, while jewellery demand may remain under pressure [11][12][13]. Core Insights - Total gold demand reached a record high of 4,974 tonnes in 2024, with a 1% year-on-year increase in Q4 [1][7]. - Central banks continued to purchase gold at a significant pace, exceeding 1,000 tonnes for the third consecutive year, with Q4 purchases alone amounting to 333 tonnes [1][102]. - Annual investment in gold reached a four-year high of 1,180 tonnes, marking a 25% increase from the previous year [2][62]. - Gold jewellery consumption dropped by 11% to 1,877 tonnes, although the value of jewellery demand increased by 9% to US$144 billion due to rising gold prices [3][32]. - Technology demand for gold grew by 7% to 326 tonnes, driven by advancements in AI and electronics [3][133]. Summary by Sections Demand Overview - Total gold demand rose by 1% year-on-year to 4,974 tonnes, with Q4 demand reaching a new quarterly high [1][7]. - Central banks purchased 1,045 tonnes of gold in 2024, maintaining a strong buying trend [102][112]. - Investment demand surged by 25% to 1,180 tonnes, with significant contributions from gold ETFs and bar and coin investments [2][62]. Supply Overview - Total gold supply increased by 1% year-on-year to 4,974 tonnes, driven by higher mine production and recycling [7][148]. - Mine production reached an estimated 3,661 tonnes, marking a slight increase from the previous year [149][151]. - Recycled gold supply rose by 11% to 1,370 tonnes, reflecting higher gold prices [148][164]. Jewellery Demand - Global jewellery demand fell by 11% to 1,877 tonnes, with significant declines in China and other major markets [32][41]. - Despite the volume drop, the value of jewellery demand increased to US$144 billion due to high gold prices [3][32]. - Indian jewellery demand showed resilience with only a 2% decline, contrasting sharply with China's 24% drop [44][41]. Technology Demand - Technology sector demand for gold increased by 7% to 326 tonnes, with electronics being the largest contributor [133][134]. - The growth in AI applications and recovery in consumer electronics markets were key drivers of this demand [134][135]. Future Outlook - The report anticipates continued strong demand from central banks and ETF investors in 2025, while jewellery demand may face challenges due to high prices [11][12][13]. - Investment in gold is expected to remain robust, supported by macroeconomic factors such as lower interest rates and geopolitical uncertainties [13][14].

Investment Rating - The report emphasizes the hybrid working model as a critical differentiator for companies in attracting and retaining talent, indicating a strong positive outlook for businesses adopting this model [3][21][50]. Core Insights - The hybrid working model is essential for modern companies to thrive, as it leads to happier, more loyal employees and enhances productivity [5][24][30]. - A significant majority of HR leaders (92%) utilize hybrid working as a recruitment tool, with 85% citing it as effective for retention [10][30]. - The demand for local flexible workspaces is increasing, aligning with the concept of '15-minute cities' where daily necessities are accessible within a short distance [39][40]. Summary by Sections Introduction - Hybrid working is a top employee benefit for attracting and retaining talent, with companies lacking this option struggling to recruit quality employees [3][4]. Importance of Hybrid Working - The hybrid model is confirmed as crucial for talent acquisition, with a notable exodus of talent from companies that do not offer flexibility [4][5]. - HR leaders agree that hybrid working improves work-life balance and job satisfaction, driving productivity [5][24]. Recruitment and Retention - 92% of HR leaders use hybrid working to recruit talent, and 75% of candidates have declined roles due to lack of hybrid options [10][12]. - Over 77% of HR leaders believe offering office space close to home aids in talent acquisition [11]. Employee Wellbeing - Hybrid working is linked to improved employee wellbeing, with 86% of hybrid workers feeling less drained and better able to cope with daily life [27][25]. - The model is seen as a major wellness benefit, with 57% citing improved work-life balance as a key advantage [25]. Productivity - 85% of HR leaders believe hybrid working increases productivity, with 56% of hybrid workers reporting higher productivity compared to full-time office work [30][18]. - Academic studies suggest a productivity increase of around 3% to 4% due to hybrid working [30][18]. Equity and Inclusion - The hybrid model supports a more inclusive workforce, allowing individuals with caregiving responsibilities to remain employed [33][34]. - Companies adopting flexible working policies have seen improvements in recruitment and retention, particularly among diverse groups [35]. Learning and Development - 81% of HR leaders state that the hybrid model provides an optimal environment for employee learning and development [44][47]. - The model allows for both in-person mentoring and self-directed learning, appealing particularly to younger generations [45][46]. Conclusion - The hybrid working model is a powerful tool for companies to attract and retain top talent, significantly impacting overall business success [49][50].

Investment Rating - The report does not explicitly provide an investment rating for the automotive industry or specific companies within it. Core Insights - The recent US election results are expected to delay the adoption of Battery Electric Vehicles (BEVs) in North America due to a less stringent stance on emissions regulations under the Trump administration [1][4][10] - The delayed adoption of BEVs will have cascading effects on the entire automotive value chain, prolonging profitability challenges for electrification-focused players while extending opportunities for Internal Combustion Engine (ICE)-focused legacy players [2][12] - The regulatory landscape, particularly changes in the US Environmental Protection Agency (EPA) and California Air Resources Board (CARB) standards, is a significant factor influencing electrification forecasts [3][4][19] Summary by Sections Regulatory Impact - The incoming Trump administration is expected to soften EPA emissions and fuel economy standards beyond model year 2027, which will prolong ICE production and hinder EV adoption [11][19] - CARB's Advanced Clean Cars II rule mandates that by 2035, all new cars and light trucks sold must be zero-emission vehicles (ZEVs), but OEMs can only meet 20% of their ZEV requirement with plug-in hybrid electric vehicles (PHEVs) [5][19] Market Scenarios - The report outlines three scenarios for North American light vehicle xEV shares: upside, base, and downside cases, reflecting different regulatory environments and adoption rates [14][20] - In the base case, the repeal of current EPA emissions standards will reduce the need for BEVs, leading OEMs to rely more on hybrids [19] - The downside case assumes a challenge to CARB's ability to set emissions standards, delaying California's 100% ZEV sales target from 2035 to 2040 [20] OEM and Supplier Strategies - Traditional manufacturers must manage a triple powertrain strategy, integrating ICEs, HEVs, and BEVs, while EV-focused OEMs need to compete with hybrids due to anticipated profitability challenges [21][22] - Suppliers are expected to reevaluate their participation in electrification, which may create opportunities, but many sub-scale suppliers may exit the market due to low volumes and profitability issues [23][24]

Investment Rating - The report does not provide a specific investment rating for the industry Core Insights - The report emphasizes the importance of centering health equity in climate action, highlighting that climate change disproportionately affects vulnerable communities and that businesses must prioritize these impacts in their strategies [4][6][11] Summary by Sections Introduction - The Centering Health Equity in Climate Action (CHEC) initiative aims to integrate health and equity into climate action, ensuring that all communities thrive and are not adversely affected by climate change [4][5][7] The Climate/Health Nexus - Climate change is projected to cost $12.5 trillion in economic losses and $1.1 trillion in healthcare costs by 2050, with vulnerable communities facing the greatest health impacts [11][12] - Historical inequities exacerbate the health impacts of climate change, with specific demographic groups, such as Black and Hispanic individuals, being more likely to experience severe consequences [15][17][18] Impacts to Business - Businesses that ignore health equity in their climate strategies risk exacerbating inequities and harming public health, which is essential for their long-term viability [26][30] - The report outlines that integrating health equity can lead to reduced healthcare costs and improved productivity, with a return of $2.30 for every dollar saved on healthcare [39] Recommendations for Businesses - Businesses are encouraged to understand their climate and health equity impacts, starting with the most affected populations in their value chain [44][65] - The report outlines a four-step approach: understanding impacts, prioritizing affected stakeholders, measuring and managing impacts, and embedding equity throughout the organization [46][109][133] Case Studies - Johnson & Johnson's initiative to address heat stress through community clinics demonstrates the importance of partnerships and data-driven approaches to improve health outcomes [50][52] - Kaiser Permanente's community health needs assessment highlights the significance of understanding local environmental impacts on health to inform business strategies [58][60] - Sodexo's development of culturally relevant, plant-based menus in hospitals illustrates how businesses can engage stakeholders to create positive health and climate outcomes [74][78] Next Steps - The report calls for urgent action from businesses to center health within their climate plans and engage with affected stakeholders to create equitable solutions [151]