Industry Overview - The report focuses on the education sector, specifically primary education in low- and middle-income countries (LMICs), analyzing the relationship between teaching quality and student learning outcomes [8][12] - The study leverages data from the World Bank's Global Education Policy Dashboard (GEPD), which covers 13 education systems across LMICs, including countries like Ethiopia, Pakistan, Peru, and Sierra Leone [33][34] - The report highlights the persistent learning crisis in LMICs, with 57% of children in these countries unable to read and understand a simple text by age 10, and even higher rates in Sub-Saharan Africa (86%) [12][13] Key Findings on Teaching and Learning - Teacher pedagogical skills, as measured by the Teach Primary tool, are positively correlated with student learning outcomes, particularly in literacy [8][21] - Teachers with better content knowledge, especially in mathematics, significantly improve student performance, with a 1-standard-deviation increase in teacher content knowledge leading to a 0.2 standard deviation increase in student learning [24][25] - Teaching practices that foster student engagement, such as play-based and child-centered approaches, are highly predictive of better literacy outcomes [8][62] Teacher Support and Quality - Teachers in LMICs often lack adequate support, with only 33% of teachers having a bachelor's degree and 23% holding a master's degree [39] - Teacher absence rates are high, with students receiving only about half of the scheduled teaching time due to teacher absenteeism, significantly impacting learning outcomes [28] - Effective teacher support systems, such as practical training, mentoring, and feedback, are crucial for improving pedagogical practices and student learning [14][71] Policy Implications - The report emphasizes the importance of structured pedagogy and practical teacher training programs to improve teaching quality and student learning outcomes [21][71] - Instructional leadership, including classroom observations and feedback, is critical for identifying and addressing teaching challenges, yet only 58% of teachers report discussing observation results and 54% receive feedback [73] - Policies should focus on improving teacher recruitment standards, providing in-service training, and ensuring that teachers have access to necessary resources and support [75][76] Data and Methodology - The GEPD uses a combination of school surveys, teacher assessments, and classroom observations to provide a holistic view of the education system [29][30] - The study employs machine learning models, including Conditional Inference Forest (CIF) and Random Forest (RF), to identify key variables predictive of student learning outcomes [85][87] - The PLAY tool, developed to measure student engagement in learning, was applied in three countries (Ethiopia, Peru, and Sierra Leone) to assess the impact of playful learning practices on student outcomes [63][64]

Industry Investment Rating - The report does not explicitly provide an investment rating for the industry [1][2][3] Core Viewpoints - Social registries are fundamental tools for social protection, enabling efficient resource targeting and access to services for vulnerable populations [14] - Over the past two decades, social registries in Latin America and the Caribbean (LAC) have significantly expanded in coverage, interoperability, and usage, with some countries like Chile, Colombia, and Costa Rica achieving over 80% coverage [15] - Social registries play a critical role in the delivery chain of social protection programs, including identifying eligible populations, tracking social investments, and responding to emergencies [16][17] - Despite advancements, LAC social registries face challenges such as strengthening legal frameworks, improving data quality, and enhancing interoperability [18] Summary by Sections Executive Summary - Social registries serve as inclusion systems, allowing citizens to access social programs and consolidating household data for public policy decision-making [14] - The coverage of social registries has grown significantly, with some countries reaching over 80% coverage [15] - Social registries are increasingly used beyond cash transfers, supporting programs in education, health, and economic inclusion [16][17] - Challenges include legal and institutional strengthening, data quality improvement, and enhancing interoperability [18] Introduction - The World Bank has been working to strengthen social registries in LAC, aiming to reduce knowledge gaps and generate recommendations for improving social policies [20] - The technical note draws on previous World Bank publications and surveys conducted with officials from 17 countries [21][22] Role of Social Registries in Social Policy - Social registries are essential for identifying individuals in poverty and vulnerability, enabling their participation in social protection programs [27] - They support the dissemination, admission, and registration of households, facilitating the evaluation of socioeconomic conditions [35] - Social registries aim to reduce operational complexity by consolidating data, leading to cost and time savings [36] - Information is the primary input and output of social registries, with data collected through surveys, administrative records, and digital interfaces [37][38] Evolution of Social Registries in LAC - Social registries in LAC have evolved over the past four decades, with significant growth in the last two decades [48][49] - Countries like Colombia have achieved 100% population coverage through innovations in interoperability and data exchange [51] - The use of social registries has expanded beyond cash transfers to include education, health, and subnational government programs [63] Role of Social Registries During the COVID-19 Pandemic - Social registries played a crucial role during the COVID-19 pandemic, enabling rapid responses to citizen needs [68] - Countries implemented innovations such as cross-referencing with new data sources and using machine learning for household classification [72] - Interoperability with administrative data was a key strategy for expanding social registries during the pandemic [73] Social Registries in LAC Today - Social registries are assessed based on five dimensions: institutional arrangements, data collection and updating, socioeconomic classification, information systems, and performance measures [80][81] - Institutional arrangements vary by country, with most registries managed by ministries of social development or planning [86][87] - Data collection methods are evolving towards hybrid models, combining self-declaration with administrative data [96][97] - Interoperability is a key focus, with countries like Chile and Brazil leading in data exchange and integration [162][163] Challenges and Recommendations for LAC Social Registries - Strengthening legal frameworks and institutional support is crucial for the sustainability of social registries [194] - Efficient and sustainable mechanisms for data updating are needed to ensure accurate targeting of social programs [197] - Interoperability with other systems, such as disaster risk management, can enhance the effectiveness of social registries [202][203] - Expanding coverage in high-poverty areas and improving communication with citizens are essential for the future of social registries [205][206] References - The report references various studies and publications from the World Bank and other institutions, providing a comprehensive background on social registries in LAC [211][212]

Industry Investment Rating - The report does not explicitly provide an investment rating for the industry, but it highlights the importance of transitioning to a circular economy (CE) in Türkiye, which presents both challenges and opportunities for industries [18][19][20] Core Report Insights - The transition to a circular economy in Türkiye is driven by both environmental sustainability goals and the need to align with the EU's tightening environmental policies, particularly under the EU-Türkiye Customs Union [19][20] - Türkiye's material demand is expected to increase despite improvements in material intensity, with non-metallic minerals dominating the material mix [35][36] - Circular economy policies can support Türkiye's climate mitigation objectives, potentially reducing CO2 emissions by over 7% in 2030 on top of the Nationally Determined Contribution (NDC) scenario [38][39] - A combination of demand-side and supply-side policies is necessary to achieve circular economy targets, with demand-side measures more effective in reducing non-metallic mineral use and supply-side measures better suited for increasing metal ore recycling [43][44] Macroeconomic Impacts of the CE Transition in Türkiye - Türkiye's economy is projected to see an absolute increase in the use of all material inputs, driven by GDP and population growth, with material intensity declining for all commodities except metal ores [36] - The economic dividend of supporting the CE transition can be reaped by addressing Türkiye's existing skills gap, particularly in high-skilled labor [49] - The costs of implementing CE policies are relatively moderate, with real GDP decreasing by about 1.6% in the combined scenario, but this does not account for co-benefits such as reduced air pollution and improved ecosystem services [47] Positioning Turkish Industry in Circular Global Value Chains - Nearly one-fifth of Turkish firms have adopted resource-efficient production technologies, with higher adoption rates in the garments and textiles sectors compared to fabricated metal products and machinery sectors [55] - Two possible CE futures for Türkiye are outlined: a 'light' transition focusing on material efficiency and recycling, and an 'ambitious' transition involving comprehensive product redesign and higher value-added goods [62] - Factors enabling CE readiness include effective traceability, digital monitoring systems, access to recycled inputs, and technological upgrades [66][67] Prioritizing Industries for Building a Competitive Circular Economy in Türkiye - Strong connections between industries are essential for a successful circular economy, with weak links currently observed between high-potential circular industries and their supporting sectors [80][82] - The analysis identifies six priority value chains for Türkiye's CE transition: iron and steel, aluminum, cement, plastics, fertilizers, and chemicals, with 80 core industries and 75 supporting industries identified [84] - Policies for a competitive CE transition include boosting competition in key industries, strengthening primary and manufacturing industries, and fostering collaboration within the tertiary sector [91][93] Next Steps for Türkiye's CE Transition - Türkiye should focus on enhancing the competitiveness of core industries, fostering the growth of upstream and downstream industries, and promoting investments in key industries that support circularity [96][99][100] - Pilot regulations within vital sectors with strong interrelations are recommended, along with broadening the use of network analysis to bolster monitoring, reporting, and verification (MRV) objectives [106]

Industry Overview - São Tomé and Príncipe (STP) is experiencing significant emigration, driven by limited economic and employment prospects, particularly among the younger generation [7] - The country's economy heavily relies on public development aid (APD), making it vulnerable to external funding fluctuations, with GDP growth stagnating in recent years [16] - Poverty remains widespread, with three-quarters of the population at risk of falling or remaining below the poverty line, and significant challenges in human capital, particularly in educational outcomes [16] Migration Trends - Migration from STP is significant and increasing, with Portugal being the primary destination, hosting over half of the diaspora, followed by Angola and Gabon [17] - The introduction of the CPLP mobility agreement in 2022 has facilitated migration to Portugal, reducing legal and administrative barriers for citizens of Portuguese-speaking countries, including STP [17] - Migrants from STP are predominantly young, urban, and moderately more likely to come from higher-income brackets, although vulnerable populations also migrate [17] Economic Impact of Migration - Migration currently brings limited economic benefits to STP due to low and irregular remittances, high transfer costs, inadequate financial infrastructure, and precarious jobs for migrants abroad [7] - Remittances are a crucial income source for STP households, especially for the elderly, poorer households, and female-headed households, but the volume is relatively low compared to the size of the diaspora [22] - The cost of sending remittances to STP through formal channels is higher than the Sub-Saharan African average, and most remittances are sent informally through third parties [27][28] Social Impact of Migration - Migration can disrupt family structures, particularly affecting children who face challenges in care and emotional well-being [7] - Vulnerable families often receive low-value and irregular remittances, as migrants are frequently confined to low-wage jobs abroad, limiting financial support and household stability post-migration [39] - The emigration of an adult, especially a parent, requires critical adjustments in family dynamics, often transferring care responsibilities to other family members, which can negatively impact children's development [41] Policy Recommendations - Improve the employability of youth both domestically and abroad to ensure viable economic prospects for those who choose to stay and productive jobs for those who wish to emigrate [46] - Establish labor mobility agreements with key destination countries to align migrant skills with labor market needs [50] - Strengthen migration management systems to better support migrant workers, engage the diaspora, and generate data for policy-making [52] - Reduce barriers to receiving remittances by promoting the development of a digital financial services ecosystem that enhances financial inclusion [54] - Protect and support family members of migrants who remain in the country, particularly focusing on youth and children, through social assistance programs [55]

Industry Investment Rating - The report highlights significant investment opportunities in clean tech manufacturing across Central and Eastern Europe, particularly in Poland, Bulgaria, Croatia, and Romania, driven by EU policies aimed at onshoring clean tech production [3][10] Core Viewpoints - The EU's Net Zero Industry Act (NZIA) targets sourcing at least 40% of net-zero technologies domestically by 2030, creating opportunities for Central and Eastern European countries to expand production in key clean tech value chains such as electric vehicle batteries, solar photovoltaics, wind turbines, heat pumps, and electrolyzers [3][8] - Poland stands out with the highest export potential and investment requirements in absolute terms, while Bulgaria and Croatia show greater potential relative to their economic size [3][10] - The wind energy value chain offers the most onshoring opportunities, while the electrolyzer value chain presents the fewest [29] Methodology Summary - The analysis uses a five-step framework to identify onshoring potential, including sector filtering, indicator development, composite index creation, export projections, and investment projections [11][12] - Key indicators include demand factors (e.g., EU reliance on non-EU inputs), supply factors (e.g., export competitiveness), and market access ease (e.g., logistics performance) [14][15][16] - A composite Onshoring Attractiveness (OA) index is created using Principal Component Analysis, categorizing opportunities into low, medium, and high attractiveness [23][24] Export and Investment Projections - Under the NZIA scenario, clean tech exports from the 4CEE countries to the EU27 are projected to quintuple by 2030, with Poland capturing 60% of additional exports [43][46] - Investment needs to meet export projections range from $1 billion in Bulgaria, Croatia, and Romania to $5 billion in Poland, with EV battery manufacturing requiring the largest share of investments [55][57] - Clean tech exports are expected to contribute 1.2% to 3.7% of GDP in the 4CEE countries by 2030, with Croatia leading in relative terms [44][57] Policy Implications - Poland is well-positioned to onshore clean tech production, but challenges include labor force upskilling and declining working-age populations [61] - Fiscal constraints in 4CEE countries limit the use of industrial subsidies, necessitating broader policy interventions beyond subsidies to achieve industrial goals [62][63]

Industry Investment Rating - The report does not explicitly provide an investment rating for the industry, but it highlights the challenges and opportunities in China's economic landscape, particularly in the property sector and domestic demand [28][29][32] Core Views - China's GDP growth has moderated to 4.8% in the first three quarters of 2024, driven by subdued domestic demand and a significant drag from the property sector, which saw real estate investment contract by 11.5% y/y in July-November [28] - The government has implemented incremental policy stimulus, including monetary easing and fiscal measures, but the impact has been constrained by weak credit demand and persistent challenges in the property sector [29][32] - The report forecasts GDP growth of 4.9% in 2024 and 4.5% in 2025, with inflation expected to remain low at 0.4% in 2024 before rising to 1.1% in 2025 [30][32] Recent Economic Developments - Domestic demand has weakened, with retail sales growing at 2.8% y/y in July-November, about half of the 2019 growth rate, reflecting weak consumer confidence due to falling property prices and sluggish income growth [28][66] - Manufacturing and infrastructure investment have remained robust, growing by 9.6% and 11.4% y/y respectively in July-November, partially offsetting the contraction in real estate investment [28][66] - Carbon emissions declined by 0.7% y/y in the first three quarters of 2024, driven by reduced output in construction-related industries, despite a 6.6% y/y increase in electricity production [100][101] Outlook, Risks, and Policy Implications - The outlook for China's economy is subject to domestic and external risks, including a persistent downturn in the property sector, tighter local government financing, and global trade uncertainties [33][149] - Policy implications include the need for structural reforms to address vulnerabilities such as high property developer and local government debt, low consumption, and an aging population [34][152] - The report emphasizes the importance of fostering domestic demand, supporting a sustainable property sector recovery, and managing local government financial risks through fiscal reforms [34][157] Special Focus: Economic Mobility and China's Emerging Middle Class - China's secure middle class has expanded significantly, growing from 9.8% of the population in 2010 to 32.1% in 2021, with rural areas seeing a larger absolute reduction in low-income population compared to urban areas [37][165][177] - Education and wage-earning jobs are key pathways to upward mobility, with 62.6% of the secure middle class and 71.2% of the upper-income class belonging to the salaried or wage-earning group [183][184] - Future pathways to upward mobility will likely depend more on higher education, as the economy shifts towards high-value services and innovation-driven industries, with significant gaps in educational attainment between urban and rural areas [191][195]

Industry Overview - Agriculture accounts for 70% of global freshwater withdrawals, making it a highly water-intensive sector [3] - Climate change is exacerbating the challenges of producing enough food to feed the planet [3] - The 2030 Water Resources Group (WRG) is driving sustainable water use in agriculture and building climate-resilient food systems [3] WRG's Core Initiatives - WRG is a global public-private partnership hosted by the World Bank, aiming to bridge the gap between water supply and demand [4] - Key focus areas include promoting water-efficient agricultural practices, improving farming methods to reduce GHG emissions, and fostering market innovations [5] - WRG enhances agricultural value chain sustainability, improves market access for farmers, and ensures stable food supplies while protecting water resources [5] Key Projects and Achievements India: Climate-Smart Rice Cultivation - In Uttar Pradesh, WRG is helping smallholder farmers adopt water-saving practices and increase yields [9] - Goals include reaching 1 million smallholder farmers, increasing micro-irrigation coverage by 5x, expanding direct-seeded rice area by 10x, and reducing GHG emissions by 60% over five years [9] Bangladesh: Water-Efficient Agriculture - In water-scarce Barind Tract, WRG supports mango, rice, and other crops through farmer hubs offering advanced irrigation technologies [10] - Over five years, the project has trained 19,500 farmers and impacted 58,500 beneficiaries, increasing rice yields by 400 kg/ha and mango yields by 200x [10] Innovative Irrigation Solutions - WRG has developed and implemented pioneering solutions in Africa and Asia to improve yields and water use efficiency [11] - Examples include the world's first and largest community drip irrigation project in Karnataka, India, benefiting 500 smallholders and saving 24 million cubic meters of water [12] - In Kenya, a new financing model for modern irrigation systems has been piloted, contributing to broader farmer-led irrigation development [12] - In South Africa, an automated water management system has reduced water distribution losses by up to 20% and expanded to 21 major irrigation schemes [12] Future Directions - WRG is leveraging its public-private partnership model to pursue bold solutions, such as low-methane rice programs in South and Southeast Asia [6] - These initiatives aim to significantly reduce global methane emissions while enhancing agricultural productivity and water efficiency at scale [6]

Longitudinal Survey Challenges - Longitudinal surveys face challenges in maintaining accuracy over time due to sample attrition, migration, and sample fatigue, which introduce measurement errors[2] - Sample attrition, caused by deaths and relocations, along with the impact of new populations and migration flows, leads to underrepresentation in surveys[2] - Correct panel survey design and implementation require methods to address these issues at different stages: sampling design, data collection, and estimation[7] Proposed Methodology - The study proposes a weighted sharing method-based estimator that provides more accurate individual-level statistics compared to current estimators used in Uganda's national panel survey[2] - The proposed method shows higher stability when changing samples, particularly in cross-sectional estimates based on transition matrices[2] - The methodology focuses on improving survey quality by addressing sampling design, data collection, and estimation stages[8] Empirical Application - The methodology was experimentally evaluated using data from Uganda's national panel survey and the Living Standards Measurement Study (LSMS)[2] - The study applied the proposed methodology to LSMS-ISA data, using Uganda's national panel survey waves from 2009, 2013, and 2015 as a case study[10] - The empirical evaluation demonstrated the effectiveness of the proposed method in improving the quality of survey estimates[10] Data Collection and Tracking - Data collection improvements include flexible methods like phone interviews to reach non-responsive populations and minimal variable data collection for attritors[7] - Tracking rules are defined to balance the cost of tracking migrants with the potential bias introduced by their exclusion from the sample[29] - Proxy interviews and minimal variable sets are used to collect data from non-respondents and migrants, reducing sample attrition bias[53] LSMS-ISA Survey Overview - LSMS-ISA surveys are nationally representative longitudinal household surveys focusing on the relationship between living standards and agriculture[58] - The surveys track households and individuals over time, incorporating new members like immigrants and newborns to maintain representativeness[61] - Tracking methods vary across LSMS-ISA surveys, with some focusing on households and others on individuals, impacting representativeness and cost[63] Uganda National Panel Survey (UNPS) Case Study - The UNPS is a multi-purpose household panel survey in Uganda, providing data on income dynamics, consumption, and agriculture[71] - The study used UNPS data from 2009/10, 2013/14, and 2015/16 waves, with final datasets including 18,313, 17,377, and 15,905 individuals respectively[72] - The empirical evaluation of UNPS data showed that 45% of individuals from the 2009/10 wave were re-interviewed in 2013/14, with 30% of the sample being new individuals[73]

Group 1: Demand-Side Experiment Findings - The probability of ordering wild meat in the treatment group decreased by 31% compared to the control group (3.1% vs. 4.5%) [63] - 59% of participants in both groups used the provided coupons, indicating no significant difference in coupon usage [64] - The treatment video aimed at reducing wild meat consumption did not show statistically significant effects, potentially due to social desirability bias [63] Group 2: Supply-Side Experiment Insights - A 1% decrease in the price of Moambe Chicken is associated with a 0.91% reduction in total wild meat sales, although this relationship is not statistically significant [3] - The supply-side intervention suggests that making alternative protein sources more affordable could help reduce wild meat consumption [44] - The study involved 68 restaurant days, with 11 days featuring a price reduction for Moambe Chicken, allowing for comparative analysis of sales [46] Group 3: Context and Implications - Kinshasa, the capital of the Democratic Republic of the Congo, has approximately 3,000 wild meat restaurants, selling around 12,540 kg of wild meat annually [12] - The research highlights the need for culturally sensitive interventions that align with local values to effectively reduce wild meat consumption [15] - The findings contribute to understanding how economic incentives and cultural values can be integrated to promote sustainable behaviors in wildlife conservation [15]

Industry Investment Rating - The report does not provide a specific investment rating for the industry [1][2][3] Core Views - The report focuses on estimating poverty levels across 126 districts in Pakistan using a small area estimation (SAE) methodology, which combines data from the Household Income and Expenditure Survey (HIES) 2018-19 and the Pakistan Social and Living Standards Measurement (PSLM) 2019-20 [3][7][8] - The SAE methodology used in this report differs from standard implementations by using a household survey (PSLM) as the target dataset instead of census data, which provides additional information for modeling but introduces additional uncertainty due to sampling [9][10] - The report highlights significant spatial disparities in poverty rates across districts, with the highest poverty rates found in Sindh and Balochistan provinces, while the lowest rates are concentrated in urban areas such as Karachi, Lahore, and Islamabad Capital Territory (ICT) [75][76] Methodology - The SAE methodology employed in the report uses the Census Empirical Best (EB) estimator, which is an advanced version of the ELL method, to estimate poverty rates at the district level [14][15][16] - The methodology involves fitting a linear model to predict welfare (consumption) based on household characteristics and then using this model to estimate consumption in the target dataset (PSLM) [17][18][19] - The report uses a Monte Carlo simulation approach to generate multiple welfare vectors and calculate poverty rates, with adjustments made to account for measurement errors in household size [20][21][22] Data Sources - The primary data sources for the report are the HIES 2018-19 and PSLM 2019-20 surveys, which provide detailed consumption and household characteristic data at the provincial and district levels, respectively [24][27][28] - The HIES 2018-19 survey covers 24,809 households across Pakistan, while the PSLM 2019-20 survey includes 170,246 households, allowing for more precise district-level poverty estimates [27][28] - The report notes that the PSLM 2019-20 survey was conducted using Computer-Assisted Personal Interviewing (CAPI) technology for the first time, which improved data collection efficiency [30] Key Findings - The report identifies significant spatial disparities in poverty rates across Pakistan, with the highest poverty rates in Sindh and Balochistan provinces and the lowest rates in urban areas such as Karachi, Lahore, and ICT [75][76] - The poverty gap analysis shows that in 69 districts, a relatively small increase in welfare could significantly reduce poverty, as the poverty gap (FGT1) is less than 5% [80][81] - The report also highlights the spatial clustering of poverty, with high-poverty clusters in southern KP and northern Balochistan and low-poverty clusters in the fertile plains of Punjab [87][88] Provincial Results - In Khyber Pakhtunkhwa (KP), the poverty map includes former Federally Administered Tribal Areas (FATA) and Frontier Regions (FR) for the first time, with South Waziristan, Mohmand, and Tank districts showing the highest poverty rates [95][96] - Punjab has the lowest poverty rates among the provinces, with the highest poverty rates concentrated in the southwestern districts of Rajanpur, Dera Ghazi Khan, Rahim Yar Khan, and Muzaffargarh [97][98] - Sindh has the highest poverty rates in its southern districts, particularly Tharparkar, which has a poverty rate of 76.9% and a high poverty gap of 19% [99][101] - Balochistan exhibits the highest variability in poverty rates and gaps, with districts like Kech, Zhob, and Sheikh Saedullah (Surab) having both high poverty rates and large poverty gaps [102][103]