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This IEG evaluation, requested by the World Bank’s Board of Executive Directors, represents the first independent evaluation of the PSIA experience. The evaluation finds that:. • The PSIA approach has appropriately emphasized the importance of assessing the distributional impact of policy actions, understanding institutional and political constraints to development, and building domestic ownership for reforms. • PSIAs have not always explicitly stated their operational objectives (i.e., informing country policies, informing Bank operations, and/or contributing to country capacity). • PSIAs have had limited ownership by Bank staff and managers and have often not been effectively integrated into country assistance programs. • Quality assurance and Monitoring and Evaluation of the overall effectiveness of PSIAs have been weak. The evaluation recommends that the World Bank:. • Ensure that Bank staff understand what the PSIA approach is and when to use it. • Clarify the operational objectives of each PSIA and tailor the approach and timeline to those objectives. • Improve integration of the PSIA into the Bank’s country assistance program by requiring that all earmarked funding for PSIAs be matched by a substantial contribution from the country unit budgets. • Strengthen PSIA effectiveness through enhanced quality assurance.

The Sourcebook introduces a framework for social analysis in Poverty and Social Impact Analysis along with a set of practical tools that address the institutional, political, and social dimensions of policy design and implementation and how these impact poverty and distributional equity. It is designed for country practitioners working in policy analysis in a range of areas, including macroeconomic, sectoral, and public sector policy.

The complexity of ecological-economic systems significantly reduces our ability to investigate their behavior and propose policies aimed at various environmental and/or economic objectives. Following recent suggestions for integrating nonlinear dynamic modeling with input-output (IO) modeling, we develop a fully dynamic ecological-economic model by integrating IO with system dynamics (SD) for better capturing critical attributes of ecological-economic systems. We also develop and evaluate various scenarios using policy impact and policy sensitivity analyses. The model and analysis are applied to the degradation of fish nursery habitats by industrial harbors in the Seine estuary (Haute-Normandie region, France). The modeling technique, dynamization, and scenarios allow us to show trade-offs between economic and ecological outcomes and evaluate the impacts of restoration scenarios and water quality improvement on the fish population.

Background Understanding how policies lead to changes in health systems and in practice helps policymakers and researchers to intervene more successfully. Yet identifying all the possible changes that occur as a result of a new policy is challenging not only methodologically and logistically, as limited resources are available to conduct indefinite evaluations, but also theoretically, as a complete mapping and attribution of post-hoc changes requires a full understanding of the mechanisms underpinning all change. One option is to identify possible changes across a number of policy impact domains. Methods Using a Policy Impact Framework, we brought together data from media, documents and interviews to identify changes to midwifery policy, practice and provision, following the launch of a new global policy initiative, the State of the World’s Midwifery (SoWMy 2014) report published in 2014. We used these identified impacts to develop a map of the mechanisms underpinning these changes. Results SoWMy 2014 contributed to a number of changes at national levels, including increased status of midwifery within national governments, improved curricula and training opportunities for midwives, and improved provision of and access to midwifery-led care. These contributions were attributed to SoWMy 2014 via mechanisms such as stakeholder interaction and acquisition of government support, holding national and international dissemination and training events, and a perceived global momentum around supporting midwifery provision. Policy initiatives of this kind can lead to changes in national and international policy dialogue and practice. We identify factors and mechanisms that are likely to increase the scope and scale of these changes, at contextual, national and global levels. Conclusions Identifying changes following a policy using a policy impact framework can help researchers and policymakers understand why policies have the effect they do. This is important information for those wishing to increase the effectiveness of future policies and interventions.

This study examines the dynamics of Trump's tariff strategy, as well as its long-term impacts on the global economy, trade networks, and inflation trajectories through 2025 and 2030. Using updated statistics and economic models, the analysis shows how protectionist trade policies, which were designed to address trade imbalances, have instead contributed to supply-chain regionalization, a slowdown in global growth, and persistent inflationary pressures. Empirical evidence from 2020 to 2025 shows that the tariff war raised the U.S. trade deficit and delayed the expansion of international commerce. The report offers three forward-looking scenarios - Technological Protectionism, Strategic Recalibration, and Bloc Polarization - in order to assess different policy paths. The results show that while recalibration through selective liberalization could restore modest growth and inflation stability, sustained tariff rises could reduce global GDP growth to 1.7% and trade volume by more than 10% by 2030. Policy proposals emphasize the need to revitalize multilateral trade governance, coordinate monetary and fiscal policies, and promote regional production resilience through sustainable and unique tariff regimes. The research predicts that globalization will eventually shift toward \"managed interdependence\" by fusing strategic autonomy with cooperative frameworks. These findings provide an essential basis for policymakers, economists, and international organizations seeking to develop flexible policies for an increasingly fragmented global trade landscape.

The relationship between open access and academic impact (usually measured as citations received from academic publications) has been extensively studied but remains a very controversial topic. However, the effect of open access on policy impact (measured as citations received from policy documents) is still unknown. The purpose of this study was to examine the effect of open access on the policy impact, which might initiate a new controversial topic. Research articles in the field of library and information science (LIS) were selected as the data sample ( n  = 48,884). Negative binomial regression models were used to examine the dataset. Furthermore, propensity score matching (PSM) analysis, a causal inference approach, was used to estimate the effect of open access on the policy impact based on a selected LIS journal ( Scientometrics, n  = 4019) that received the most policy citations among the LIS journals. Linear regression models, logit regression models, four other matching methods, open access status provided by different databases, and different sizes of data samples were used to check the robustness of the main results. This study revealed that open access had significant and positive effects on the policy impact.

Despite the negative externalities on the environment and human health, today’s economies still produce excessive carbon dioxide emissions. As a result, governments are trying to shift production and consumption to more sustainable models that reduce the environmental impact of carbon dioxide emissions. The European Union, in particular, has implemented an innovative policy to reduce carbon dioxide emissions by creating a market for emission rights, the emissions trading system. The objective of this paper is to perform a counterfactual analysis to measure the impact of the emissions trading system on the reduction of carbon dioxide emissions. For this purpose, a recently-developed statistical machine learning method called matrix completion with fixed effects estimation is used and compared to traditional econometric techniques. We apply matrix completion with fixed effects estimation to the prediction of missing counterfactual entries of a carbon dioxide emissions matrix whose elements (indexed row-wise by country and column-wise by year) represent emissions without the emissions trading system for country-year pairs. The results obtained, confirmed by robust diagnostic tests, show a significant effect of the emissions trading system on the reduction of carbon dioxide emissions: the majority of European Union countries included in our analysis reduced their total carbon dioxide emissions (associated with selected industries) by about 15.4% during the emissions trading system treatment period 2005–2020, compared to the total carbon dioxide emissions (associated with the same industries) that would have been achieved in the absence of the emissions trading system policy. Finally, several managerial/practical implications of the study are discussed, together with its possible extensions.

Policies designed to contain the COVID-19 pandemic have impacted food systems worldwide. How impacts played out in local food systems, and how these affected the lived experiences of different people is only just coming to light. We conducted a structured analysis of the impacts of COVID-19 containment policies on the food systems of small-scale fishing communities in Kenya, Papua New Guinea, and Saint Lucia, based on interviews with men and women fishers, fish traders, and community leaders. Participants reported that containment policies lead indirectly to reduced volumes of food, lower dietary diversity, increased consumption of traditional foods, and reduced access to fish for food and income. Although the initiating policy and food and nutrition security outcomes often appeared similar, we found that the underlying pathways and feedbacks causing these impacts were different based on local context. Incorporating knowledge of how context-specific factors shape food system outcomes may be key to tailoring strategies to mitigate the ongoing impacts of COVID-19 and designing timely, strategic interventions for future systemic shocks.

The Affordable Care Act (ACA) enabled states to expand Medicaid eligibility, extending coverage to millions, particularly in California. While Medicaid expansion has been linked to earlier diagnoses in several cancers, its impact on thyroid cancer—a slow-growing malignancy lacking formal screening—remains unclear. To assess whether Medicaid expansion influenced thyroid cancer stage at presentation. A retrospective cohort study using SEER data (2009–2020) compared adults aged 18–64 diagnosed with thyroid cancer in California (expansion) and Texas (non-expansion). Difference-in-differences logistic regression evaluated stage changes pre- (2009–2013) and post- (2016–2020) expansion, excluding a 2014–2015 washout period. Among 63,073 patients, no significant difference in stage at diagnosis was observed between states. Estimates for localized, regional, and distant disease changes ranged from −1.3 ​% to 1.1 ​% (all 95 ​% CIs included zero). Medicaid expansion was not associated with a significant shift in thyroid cancer stage at presentation. •Medicaid expansion had limited impact on thyroid cancer stage at diagnosis.•Most thyroid cancers are detected at an early stage.•Medicaid expansion had little effect on when thyroid cancer is diagnosed, likely due to its slow growth and lack of screening guidelines.

Academic expertise is a key pillar of governance processes around the world. A goal of policy and public sector actors is to draw on research to improve decision making, and correspondingly, a goal of public policy and public administration researchers is to provide relevant expertise. It is not clear, however, to what extent these goals are achieved. This study uses the Overton database to analyse the influence of public policy and administration research on policy documents (broadly defined as documents published by policy and public sector organisations). It considers which research is cited by policy documents and which organisations cite research more than others to justify their decisions. The findings show that measuring the influence of academic expertise is not straightforward conceptually or methodologically. However, they emphasise the role of different organisation types for achieving a greater correspondence between research and policy. Specifically, our study shows that think tanks use public policy and administration research more often than government organisations when justifying decisions. The findings provide insight into the utility of new policy databases in illuminating how academic experts can influence the ideas and actions of policy and public sector actors.