The assessment of climate variability impacts on crop production and price varies by what factors studies consider, including annuals and perennials. Unlike annual crops, climate impacts on perennial crops like coconuts require a multiple-year assessment. Although previous studies have examined climate effects on coconut production, there is a critical gap in understanding multiple-year impacts of climate variability on coconut production and price. Therefore, this paper aims to fill this gap by assessing the extent to which climate variability affects coconut production and prices in Sri Lanka, the fourth largest coconut producer in the world. For this purpose, we analyzed rainfall, temperature, average drought months, coconut production, coconut cultivation area, and coconut retail price from 2010 to 2022. We then created and administered five regression models to illustrate the impact of climate variables for a single year and multiple years on coconut production, yield, and price. The results indicate that rainfall in the previous year is the most critical determinant for production (p = 0.014) and yield (p = 0.032), while drought intensity and temperature shocks show delayed negative effects on production. Lagged temperature shocks and supply shortages significantly increased nominal coconut retail prices. A temperature increase by 1 °C in the previous year raised prices by approximately LKR 36 per nut. After adjusting for inflation, only temperature (p = 0.002) effects was found significant, indicating that climate-induced supply constraints dominate real price changes. Our three-year analysis showed that drought conditions, together with rainfall and temperature variability, reduced production with a delayed effect (p = 0.026). These findings highlight the importance of incorporating multiple-year climate impacts into adaptation and price stabilization policies for coconut and other perennial crops.

This paper develops a medium scale New Keynesian dynamic stochastic general equilibrium (NK-DSGE) model for the Ethiopian economy to examine how financial exclusion affects monetary policy effectiveness. The model features heterogeneous households financially included and financially excluded and distinguishes between monopolistically competitive intermediate-good firms and perfectly competitive final-good firms. Using Bayesian estimation with quarterly data from 2000Q1 to 2022Q4, the model evaluates the transmission of monetary policy, preference, and productivity shocks to consumption and labor supply decisions. The results indicate that the effects of an expansionary monetary policy shock unfold gradually, requiring approximately ten quarters for full transmission following a one-standard-deviation reduction in the policy interest rate. Importantly, monetary policy effectiveness declines as the share of financially excluded households increases. Financial exclusion weakens the interest rate transmission channel and reduces welfare gains from stabilization policy. These findings highlight structural constraints that limit policy effectiveness in economies with underdeveloped financialsystems and underscore the importance of financial inclusion for improving macroeconomic stability and social welfare.

As 2026 begins, young people are coming of age within systems increasingly strained by fragmentation, automation and shrinking access to human‐centered care, according to a new blog published on the Jed Foundation's (JED) website. Rapid technological advances are converging with fewer opportunities for in‐person connection, leaving many youth to develop in environments where social support is mediated — or diminished. These shifts unfold against a backdrop of economic and policy instability, challenging young people's core needs for belonging, stability and guidance.

Introduction While existing research recognizes that policy conditions can influence the link between climate change and agricultural output, a critical question has long been overlooked—even if policy direction is correct, if policies are volatile and unpredictable, they can themselves become a source of risk. How this policy uncertainty alters the relationship between climate change and agricultural production lacks in-depth exploration in academia. This study aims to fill this critical gap by specifically revealing how Climate Policy Uncertainty (CPU) moderates the effects of temperature and precipitation on grain yields. Methods This study employs panel data from 286 prefecture-level cities in China spanning 2001–2020. Based on the C-D production function, it adopts an economic-climate interaction model, incorporates CPU as a moderating variable, and conducts empirical tests using regression method. Results There exists a significant inverse U-shaped relationship between climatic factors and grain yields. However, when CPU increases, this relationship curve becomes significantly steeper, meaning the negative impact of extreme climate on grain yields is amplified. In other words, policy instability may exacerbate the destructive force of climate change. Further regional analysis reveals that this “amplification effect” of CPU is more prominent in non-major grain-producing areas: in the north, it primarily intensifies the precipitation-yield relationship, while in the south, it amplifies the temperature-yield relationship. It is noteworthy that in non-climate adaptation pilot cities, CPU exhibits a more pronounced negative moderating effect. Discussion The core implication of this research is that in the face of climate change, the clarity, coherence, and predictability of policies are themselves a crucial form of adaptive capacity. Ensuring policy stability can effectively stabilize farmers’ production expectations and incentivize long-term investments to combat climate risks. Further, the results also underscore the necessity of driving systemic transformation to convert external risks into endogenous drivers, then CPUs’ responses can be internalized as assets against future extreme weather within a risk framework in the future. Ultimately, anchoring climate-policy regimes in stable, Nature-Based Solutions—especially by advancing them across the Global South—offers a scalable pathway to turn policy uncertainty into ecological and social resilience.

This study investigated the leadership crisis in Nigeria's education sector and its implications for human capital development and national growth. Against a backdrop of chronic policy failure, institutional decay, and declining educational standards, the research sought to diagnose the multi-level leadership deficits and their consequent impact on the nation's developmental prospects. The study was guided by four specific objectives, four research questions, and three null hypotheses. The study adopted a descriptive survey research design. A sample of 400 respondents, comprising education administrators, lecturers, and policymakers, was selected from public tertiary institutions and relevant government bodies across Nigeria's six geopolitical zones using a multistage sampling technique. Data was collected using a structured, validated questionnaire titled the “Educational Leadership and National Development Questionnaire (ELNDQ),” which demonstrated high reliability with a Cronbach's alpha coefficient of 0.85. Data analysis involved descriptive statistics (mean and standard deviation) to answer the research questions and inferential statistics (simple linear regression) to test the hypotheses at a 0.05 significance level. The findings revealed severe manifestations of policy-level leadership failure, including chronic underfunding, policy instability, and ineffective governance. Regression results confirmed that institutional leadership quality significantly predicts academic disruptions (R² = .622, = .789, p < .001), instructional leadership significantly affects graduate skill quality (R² = .691, = .831, p < .001), and educational outputs significantly correlate with national economic growth indicators (R² = .555, = .745, p < .001). The study concludes that the tripartite leadership crisis in education is a fundamental threat to Nigeria's human capital base and economic stability, necessitating an urgent, systemic overhaul of leadership governance at all levels to reposition the sector as the bedrock of sustainable national development.

This study develops a quantitative indicator for the early diagnosis of commercial instability in business openings and closures and proposes a new analytical framework for assessing the stability of commercial districts. To address the limitations of prior research that relied on static measures such as sales or store counts, two complementary approaches were introduced. First, we propose the Commercial Instability Index (CII), a direction-agnostic metric of turnover instability computed from the standardized relative deviation between openings and closures, where larger values indicate greater instability. Second, entropy-based floating population diversity indicators were applied to capture the distribution of visitors by age, time of day, and day of week, as well as their temporal changes. These indicators were tested on quarterly panel data from 1,650 commercial districts in Seoul between the first quarter of 2019 and the fourth quarter of 2024 using panel regression and spatial panel regression models, specifically the spatial autoregressive (SAR) and spatial error model (SEM). The results showed that higher day-of-week diversity consistently reduced the CII, whereas a greater balance in age diversity provided partial mitigation effects. Moreover, the CII revealed significant spatial dependence, indicating that instability in one district could spread to its neighbors. By focusing on the magnitude of instability rather than its direction, and by integrating floating population diversity with spatial dependence, this study advances beyond static approaches. These findings expand the theoretical scope of commercial district research and offer a practical basis for early warning systems and area-based management strategies, thereby contributing to the development of urban policies for resilience and stability of commercial districts.

In 2025, fragile and conflict-affected (FCS) included 38 economies that are home to 1 billion people. The recent shocks have intensified fragility-related pressures even in more stable economies. This paper provides a comprehensive discussion of macroeconomic challenges and policies under fragility, expanding on the existing literature and drawing on the implementation of the IMF’s 2022 FCS Strategy. It finds that fragility is associated with slower long-term economic growth amid impaired government functions, including weak public service provision, low tax revenues, and underdeveloped financial sector. In the short term, fragility heightens economies’ vulnerability, with external shocks (such as terms of trade changes) having a stronger and longer-lasting impact. These effects are particularly pronounced in cases when institutional fragility is compounded by conflict or structural characteristics such as fuel export dependence or small country size. The paper argues that strengthening core government functions—macroeconomic stabilization, public service delivery, and market-based resource allocation—is essential to improving macroeconomic performance and addressing fragility, provided institutional and socio-political constraints are accounted for. International financial institutions can support countries’ efforts to mitigate and overcome fragility through tailored policy advice, capacity development, financing, and stronger partnerships with humanitarian, development, and peace organizations.

The Open Unemployment Rate (TPT) in West Java Province is a crucial macroeconomic indicator that requires in-depth analysis considering the demographic and industrial dynamics in the region. This study aims to analyze the simultaneous and partial effects of the Labor Force Participation Rate (TPAK), Population Growth, Average Years of Schooling (RLS), and Provincial Minimum Wage (UMP) on the TPT in West Java during the period 2009–2023. Using a quantitative method with a causality approach and correlational design, secondary time series data were analyzed using Multiple Linear Regression. The results of the simultaneous test (F Test) show that the four independent variables together have a significant effect on the TPT, with a contribution of 51.6% (Adjusted R2 = 0.516). Partially (t Test), it was found that: (1) TPAK does not have a significant effect on the TPT; (2) Population Growth has a significant and negative effect, reflecting its role as a stimulus for Aggregate Demand; (3) RLS has a significant and positive effect, indicating the phenomenon of educated unemployment or skill mismatch; and (4) the UMP has a significant and negative effect, confirming its role as a Keynesian purchasing power stimulus instrument and is the most dominant variable. In conclusion, unemployment in West Java is driven by structural challenges (educational mismatch) which are offset by the effectiveness of the UMP as a purchasing power stabilization policy, but is not significantly influenced by the rate of individual labor force participation. The implication is that policy should focus on reorienting vocational education and maintaining a strategic minimum wage policy.

The paper investigates issues, concerning financial planning at the enterprise. Methods and models of financial forecasting are analyzed and their unification is proposed. The main problems of financial instruments using (such as financial planning) are described. Planning is important element of management, which ensures achievement of strategic priorities. Effective financial planning is essential tool of achieving of the main goals of the enterprise ‒ profit maximization and cost of the enterprise. As market conditions in Ukrainian market of goods and services have its own specificity, which is defined, on the one hand, by means of analysis, formation and allocation of financial resources, and, on the other hand, the sourcesofreserves increasing, in order to implement the operating and investment activities to ensure their sustainable financial development. It should be noted that the formation of these processes has a significant impact on both objective and subjective factors, such as instability of tax policy and regulatory legislation for national currency, the impact of the global economic crisis, reducing the resources and available current assets etc

Purpose This paper examines how oil supply shocks and monetary policy actions jointly affect wage inequality in the US, with a particular focus on the role of education. The study addresses three key questions: (1) how exogenous oil supply shocks influence wage inequality, (2) how exogenous monetary policy shocks shape income distribution, and (3) whether these effects differ within and between education groups, revealing the role of human capital in amplifying or mitigating inequality. Design/methodology/approach The analysis uses quarterly US data from 2000 to 2021. Wage inequality is measured using the Theil index constructed from CPS/BLS weekly earnings of full-time workers aged 25 and above, allowing additive decomposition into within- and between-education components (high school, bachelor's and advanced degree). Identification relies on exogenous oil supply news shocks and exogenous monetary policy shocks. A vector autoregression (VAR) framework is estimated, and impulse response functions trace the dynamic effects of both shocks on inequality over a 10-quarter horizon. Findings The results show that overall wage inequality increased by about 15% over the sample period, with roughly 75% driven by within-education dispersion rather than differences across education levels. Oil supply shocks significantly raise wage inequality, increasing dispersion within high-school and advanced-degree groups and widening inequality between education groups. In contrast, contractionary monetary policy shocks compress wage inequality, with the strongest effects observed among advanced-degree earners and a reduction in between-education wage gaps. Research limitations/implications This study focuses exclusively on the US due to data availability at a quarterly frequency, which limits the generalizability of the findings to other economies with different labor market institutions and energy dependence. Wage inequality is measured using CPS/BLS data for full-time workers, excluding self-employed and part-time workers, who may experience different distributional effects. The analysis is confined to education-based groupings and does not account for other dimensions of inequality, such as race, gender or industry. Finally, while exogenous shock measures are used, the VAR framework captures average dynamic responses and may not fully reflect nonlinearities or structural changes across different economic regimes. Practical implications The findings show that macroeconomic policies have important distributional effects. Oil supply shocks significantly increase wage inequality, especially within high-school and advanced-degree groups, implying that energy price volatility can worsen income dispersion. Policies that reduce exposure to oil shocks—such as energy diversification and strategic reserves—may therefore also help limit inequality. Monetary policy, while aimed at stabilizing inflation and output, affects income distribution as well: contractionary shocks compress wage inequality, particularly among highly educated workers. Since most inequality arises within education groups, education alone is insufficient; complementary labor market and earnings-stabilization policies are needed to mitigate the unequal effects of macroeconomic shocks. Originality/value This study is among the first to jointly analyze oil supply shocks and monetary policy shocks using exogenous identification while decomposing wage inequality by education. By highlighting heterogeneous distributional responses across education groups, the paper provides new insights into how energy shocks and stabilization policies interact with human capital to shape income inequality.

As a global superpower, the United States plays a dominant role in international political and economic dynamics. The election of Donald Trump in 2017, under the “Make America Great Again” agenda, marked a shift toward protectionist trade policies, including higher import tariffs, in response to China’s rapid economic rise, triggering the U.S.–China trade war. Although U.S. import tariffs were subsequently reduced from 32% to 19%, they continued to pose risks to economic stability in developing countries, including Indonesia. This study employs a mixed-methods approach combining qualitative analysis and quantitative tools—SWOT, Internal–External Factor Evaluation (IFE–EFE), and the Analytic Hierarchy Process (AHP) to examine the impact of the trade war on Indonesia’s economic stability and to formulate a prioritized strategic policy mix. The results indicate that strengthening national economic resilience requires a balanced inward- and outward-looking strategy, including export-oriented industrial downstreaming supported by TKBI policies, export market diversification through RCEP and IEU–CEPA partnerships, enhanced utilization of domestic products (P3DN), and the implementation of Local Currency Settlement (LCS). The findings suggest that enhancing economic resilience in developing countries facing protectionist trade shocks requires a coordinated policy mix integrating trade, industrial, monetary, and financial stability policies, while highlighting the strategic role of financial authorities in mitigating transmission risks from global trade disruptions to the domestic financial system.

Introduction Kazakhstan's pledge to achieve carbon neutrality by 2060 confronts a legacy of coal and oil dependence and the intertwined technical, economic, and social risks of a rapid energy transition. Because implementation will hinge on stakeholder cooperation, understanding how different actors perceive these risks is essential. Methods We conducted a two-round Policy Delphi with stakeholders, including government officials, managers from national companies, financiers/investors, experts, and civil society representatives. Responses were organized using a four-quadrant risk framework that distinguishes implementation from consequential risks and transition risks from physical climate risks. Results All risks raised by participants could be located within this framework, indicating that it captures the main concerns in the Kazakhstani context. Implementation-transition risks dominated, led by regulatory volatility, financing constraints, grid bottlenecks, fossil-fuel lobbying, and skills shortages. These risks were consistently rated as highly important across stakeholder groups, although financiers and civil society actors were less concerned about policy instability than government officials and experts. Discussion By clarifying where stakeholders perceive the greatest implementation risks, the study provides a practical risk map to prioritize reforms in regulation, finance, grid development, and skills, and adds a stakeholder-based perspective to research and policy debates on energy transitions in fossil-fuel-dependent economies such as Kazakhstan.

Background: Value Added Tax (VAT) has become a central pillar of domestic revenue mobilisation in Ghana, yet persistent administrative and compliance challenges continue to constrain its full revenue potential. Aims: This study empirically examines the contribution of VAT to total tax revenue and its implications for tax administration efficiency in Ghana over the period 2013 to 2023. Method: Using a mixed methods approach, the study combines time series data on VAT and total tax revenue with primary survey data collected from Ghana Revenue Authority officials in Accra Central and Accra West. Descriptive statistics, trend analysis, correlation, and regression techniques were employed to analyse revenue performance, administrative challenges, and compliance dynamics. Results: The findings reveal a strong and statistically significant positive relationship between VAT revenue and total tax revenue, with a correlation coefficient of 0.93 and an R-squared value of 0.87, indicating that variations in VAT revenue explain a substantial proportion of changes in overall tax revenue. Trend analysis shows that VAT revenue experienced notable fluctuations over the study period, reflecting macroeconomic conditions, policy changes, and administrative efficiency, with particularly strong growth observed between 2021 and 2023. Survey results further indicate that operational inefficiencies, limited automation, inadequate staff training, informal sector non-compliance, policy instability, and weak enforcement of penalties significantly undermine VAT administration. Conclusion: The study showed that while VAT remains a critical driver of revenue mobilisation in Ghana, its effectiveness is heavily dependent on administrative capacity, policy consistency, and taxpayer compliance. Strengthening digital tax systems, expanding the tax net to include informal sector actors, enhancing staff capacity, and promoting taxpayer education are essential to improving VAT performance and sustaining long term revenue growth. The findings contribute to public finance literature by providing empirical evidence on the link between VAT performance and tax administration efficiency in a developing country context.

Hunan Province from 2000 to 2023 is the study area. Based on NOAA precipitation data and county-level rice yield statistics in Hunan Province, the Mann–Kendall test, extreme precipitation indices, and wavelet analysis examine the spatial and temporal evolution characteristics of extreme precipitation and its multi-scale impact on rice yield. The results show that the extreme precipitation in Hunan Province showed a stable pattern of fluctuation, and the main extreme precipitation indexes had no significant change trend. The spatial distribution showed a pattern of “high value in central-northern Hunan and stable in southern Hunan”, and the precipitation was concentrated in June–August. The rice yield showed the characteristics of “stable increase in the core area, intensified fluctuation in the transition area, and continuous shrinkage in the marginal area”, and the Dongting Lake Plain was a high-yield and stable area. Multi-scale analysis shows significant coupling between extreme precipitation and yield: in the 4–8-year cycle, the peak value of precipitation lags behind the response of 1–2 years, and changes synchronously in a short period. The response of rice to extreme precipitation showed a threshold-type nonlinear characteristic. Moderate wetting was beneficial to stable yield, while the yield decreased significantly when the intensity or continuous precipitation exceeded the threshold. Hunan’s rice system has strong climate resilience but requires a multi-scale climate-adaptive agricultural system via engineering, technology, and policy for long-term stability and sustainable grain production.

This white paper examines how equity-centered policy tools can function as guideposts for advancing student belonging when integrated into structured improvement work. Drawing on a qualitative action research study of an Equity in Student Belonging Inquiry Community convened by Catalyst @ Penn GSE, the paper explores how educators interpreted and enacted Pennsylvania’s Culturally Relevant and Sustaining Education (CR-SE) competencies within their local contexts. Framed by critical conceptualizations of belonging as relational, political, and structurally produced, the study situates continuous improvement as a promising yet insufficient approach for equity work unless paired with explicit attention to power, identity, and systemic inequity. Data sources included observations of inquiry community meetings, semi-structured interviews with ten experienced school and district leaders, and artifacts documenting shifts in policy and practice. Findings indicate that participants used the CR-SE competencies to establish shared language, legitimize equity-focused work, and strengthen collective accountability. Educators described how the competencies supported deeper inquiry into belonging, informed professional learning and curriculum decisions, and provided justification for equity-oriented initiatives. At the same time, participants highlighted challenges related to uneven implementation, policy instability, and the risk of superficial compliance when equity tools are not embedded in sustained learning structures. The paper argues that policy alone is insufficient to drive equitable change and that improvement work must be intentionally designed to surface structural inequities and elevate practitioner and student voice. By examining the Catalyst Inquiry Community Model, this study offers insight into how equity-centered improvement communities can support educators in translating policy intent into practice. Implications are offered for educators, leaders, policymakers, and researchers seeking to align equity policy, collaborative inquiry, and systemic efforts to improve student belonging.

Temporal Difference Policy for Dynamic Stability of Magnetically Actuated Objects With Uncertain Physical Properties

With the rapid growth of network services, traditional static bandwidth allocation schemes can no longer meet the demands of multi-user, dynamic, and QoS-sensitive applications. Ensuring both efficiency and stability in bandwidth allocation remains a significant challenge, especially under high variability and uncertainty conditions. To address this, we propose a novel algorithm named Uncertainty-Constrained Stability-aware Deep Reinforcement Learning (UCS-DRL) for dynamic bandwidth allocation. UCS-DRL adopts a dual-policy architecture: a task policy that learns optimal bandwidth allocation decisions, and a stability policy guided by uncertainty-aware value estimation to identify and mitigate potential risky or unstable behaviors during deployment. Furthermore, the framework incorporates a curiosity-driven exploration mechanism based on Random Network Distillation, which enhances exploration efficiency by encouraging the agent to visit informative and under-explored states. Experimental results show that UCS-DRL achieves high bandwidth utilization and service quality while reducing policy volatility and risky actions, balancing performance and robustness in dynamic bandwidth allocation.

The hidden cost of uncertainty: How policy instability delays industrial land development in Shanghai, China

This study examines how three monetary policy instruments affect capacity utilization rate (CUR) in Türkiye between 2007 and 2023. We divide the sample into three policy regimes: the global financial crisis (2007-2010), macroprudential (2010-2018), and post-2018 exchange rate-intensive policy regimes. We attribute transmission to the CUR, a high-frequency real activity margin that reflects firms' investment appetite and policy outcomes. The results show that transmission is context-dependent and largely indirect. Across all regimes, the expectations channel, represented by the real sector confidence index, provides the fastest and most persistent effects. The credit/interest-rate channel is powerful only under stress (2007-2010), weak under relative stability and macroprudential control (2010-2018), and contractionary but modest thereafter. After 2018, liquidity (M2) and reserve/exchange-rate dynamics gained salience, indicating that capacity decisions became more sensitive to liquidity availability and FX stabilization policies. Overall, monetary policy alone is unlikely to sustain capacity utilization without reliable communication, exchange rate and reserve management, and macrofinancial underpinnings that stabilize expectations. Policy design should combine transparent guidance with calibrated liquidity and reserve tools and be supported by targeted real sector measures to support sustained improvements in industrial capacity utilization during periods of stress.

The agricultural sector contributes significantly to national GDP, but its fluctuating trends and indications of policy inefficiencies require accurate predictive tools to formulate the right policies to maintain its stability. The purpose of this study is to provide an overview and to estimate the leading indicators of the agricultural sector relative to its real GDP, in both long-term and short-term relationships. This study used secondary data in the form of quarterly data sourced from Statistics Indonesia (BPS), Bank Indonesia (BI), the International Monetary Fund (IMF), and the Financial Services Authority (FSA) from 2004 to 2023. The study used Cross-Spectral Analysis. The results of the study show that there are five leading indicators: agricultural product exports, agricultural product imports, BI-Rate, exchange rate (rupiah/USD), and World Tea Price Index. Based on this result, forecasting was carried out using the Autoregressive Distributed Lag (ARDL) model, and the ARDL (7,3,1,6,7,7) was formed. In the long-term model, significant variables are agricultural product exports, agricultural product imports, and the exchange rate (rupiah/USD). Meanwhile, in the short-term model, the lags of real GDP in the agricultural sector, the BI-Rate, and the World Tea Price Index are significant. These forecasting results indicate that agricultural sector stabilization policies need to account for differences between short- and long-term dynamics. Therefore, strategies for stabilizing Indonesian agriculture are formulated by selecting short-term and long-term policies based on leading agricultural sector indicators.