Purpose The impact of international agri-food trade on food security and nutrition remains contested, and evidence on its implications for (micro)nutrient intake is still limited. This article explores how Morocco's agri-food production and trade patterns have shaped the nutritional availability over the past 3 decades. Design/methodology/approach Using FAO Food Balance Sheets and national food composition tables to estimate domestic supply, production, imports, and exports of 12 food groups and key nutrients (calories, proteins, fats, carbohydrates, vitamin A, iron and magnesium) from 1991 to 2021. Non-parametric trend tests and a Seemingly Unrelated Regression (SUR) framework, combined with an autoregressive specification, are used to assess structural changes and trade nutrition associations. Nutrient availability is benchmarked against FAO/WHO population-weighted requirements, while food group supply is evaluated relative to EAT–Lancet dietary recommendations. Findings Morocco largely meets national nutritional requirements, consistent with declines in undernourishment, stunting and anaemia. However, calories and fats now exceed recommended levels. Cereal imports have stabilized food supply but increased exposure to global shocks. Despite high vegetable exports, domestic availability remains below dietary recommendations, suggesting a trade-off between export growth and local nutritional adequacy. Research limitations/implications The data used reflect national-level supply and do not capture disparities in access across social groups. While nutrient composition values align with national data, the analysis cannot assess intra-household distribution or affordability. Originality/value The study provides a nutrient-level, country-specific analysis linking trade flows to dietary adequacy in a middle-income context.

Beyond Market Co-movement: A Seemingly Unrelated Regression (SUR) Based Analysis of Hidden Sectoral Connectedness in Indian Equity Indices

This study explores how two alternative norms perform within the Iterative Seemingly Unrelated Regression (ISUR) framework, focusing on their efficiency and accuracy across diverse scenarios -such as varying time spans and country samples.By putting these norms to the test, the research offers hands-on guidance for researchers and practitioners seeking the most effective balance between computational speed and statistical precision.The Euclidean findings reveal which norm delivers the best trade-off, serving as a practical roadmap for optimising ISUR models in real-world applications.Ultimately, this comparison not only sharpens methodological decision-making but also enhances the reliability and efficiency of empirical workflows in econometric analysis.

This study examines the direct and indirect effects of corruption on international trade, with particular emphasis on the mediating role of human capital. Using panel data from selected SAARC countries over the period 1990–2022, the analysis employs a Seemingly Unrelated Regression (SUR) framework within a mediation approach to capture both channels of influence. The empirical findings indicate that corruption adversely affects international trade, while human capital plays a mitigating role by offsetting some of these negative effects. Specifically, higher levels of human capital enhance trade performance and weaken the detrimental impact of corruption. The results highlight the importance of institutional quality and human capital development in promoting trade openness. Based on these findings, the study suggests that policymakers should prioritize anti-corruption measures alongside investments in education and skill development to foster sustainable growth in international trade.

This study extends the seemingly unrelated regression (SUR) model through introducing the ridge (RTSUR) and Liu-Type (LTSUR) estimators as biased estimation techniques to address the problem of multicollinearity in the SUR Tobit (SURT) model. This study theoretically evaluates the superiority of the proposed estimators based on the mean square error (MSE) criterion. The results for the theoretically study showing that, the Liu-Type estimator outperforms other estimators under many conditions. A simulation study was conducted to compare the estimators under various factors. The results of simulation show that, the maximum likelihood (MLE) estimator is the worst estimator at all factors and the LTSUR and RTSUR estimators perform better at high levels of multicollinearity and censoring. The LTSUR still achieved a significant superiority over the RTSUR. In addition, when the number of observations in the equations increases, the performance of the LTSUR and RTSUR estimators improves. Moreover, the simulation mean squared errors (SMSE) values for LTSUR estimator converge as number of observation and censored level increase. To study the behavior of the proposed estimators on real data, we used weather data from Cairo city to examine their influence on pollution levels of carbon monoxide (CO), sulfur dioxide (SO2), and nitrogen dioxide (NO2). The results from the real data were consistent with the findings from the simulation study.

Export-based growth strategies have led to increasing economic competition between countries. A country's global competitiveness is shaped by the influence of various factors, and determining these factors is of great importance. This study, which examines the determinants of competitiveness, is based on Porter's (1990) Diamond Model. In addition, three different models were developed in line with Dunning's (1992) contributions to Porter's Diamond Model and an alternative perspective. In this research, which covers Türkiye and 11 European Union member countries, annual data between 1995-2019 were used. In the study, the competitiveness index developed by Balassa was calculated for two different groups of goods that require high technology and are included in the Harmonized System. To explore the relationships among the variables, the Seemingly Unrelated Regression (SUR) method was applied. The empirical findings revealed that determinants such as market demand, resource conditions, industry support structures, competitive strategies, regulatory policies, and productivity levels have statistically significant both positive and negative effects on international competitiveness. In addition, it has been determined that the effects of these variables differ both across the examined commodity groups and countries.

Abstract One of the most robust empirical findings in political science is that in multiparty democracies cabinet ministries are distributed in rough proportion to parties’ legislative seat shares, a pattern known as Gamson’s Law. Yet existing research often overlooks the fact that portfolio and seat shares are compositional—mutually dependent parts of a whole. Standard methods treat them as unconstrained, risking bias, misleading uncertainty estimates, and flawed inference. Unfortunately, the most common strategy for handling compositions—the additive log-ratio (ALR) transformation combined with seemingly unrelated regression (SUR)—fails when the number and identity of compositional elements (like parties) vary across cases. We propose the isometric log-ratio (ILR) transformation—new to political science—as an alternative that both respects compositional geometry and adapts to differing compositional structures. Monte Carlo simulations show that ILR sharply outperforms standard approaches, reducing bias, improving coverage probability, and increasing statistical power. While we apply it to portfolio allocation, ILR provides a general solution for modeling compositional outcomes with other potential uses, including in electoral competition, where ALR+SUR has required strong assumptions or ad hoc adjustments. Using this improved methodology, we find that seat–portfolio proportionality is weaker overall than conventionally reported and varies substantially across governments.

This study aimed to examine the prevalence and temporal trends of SUDs among psychiatric inpatients, investigate the factors predicting involuntary hospitalization, and assess the impact of SUDs and involuntary admission on pharmacological treatment practices. A retrospective cross-sectional analysis was conducted using medical records of all psychiatric inpatients (n = 5,887) admitted to the general psychiatric wards of a regional training and research hospital between 2019 and 2023. Descriptive statistics, logistic regression, linear regression, and seemingly unrelated regression (SUR) analyses were employed to evaluate clinical predictors and treatment trends. The prevalence of SUD was 27.5% (n = 1,619), with mixed substance use being the most common pattern (76.1%). In the logistic regression model, substance use, male sex, and later years of admission were associated with a higher likelihood of involuntary hospitalization, whereas bipolar affective disorder was associated with a lower likelihood. Treatment trends showed an overall increase in atypical antipsychotics, depot antipsychotics, clozapine, and electroconvulsive therapy (ECT); compared with non-users, patients with SUD showed lower use of typical antipsychotics, mood stabilizers, clozapine, and ECT. This large-scale study demonstrates that SUDs are a strong predictor of involuntary psychiatric hospitalization and significantly influence pharmacological treatment patterns. The increasing trend of compulsory admissions, particularly among male patients with SUD, underscores the urgent need for clearer legal and ethical frameworks, as well as the expansion of community-based mental health services in Türkiye.

The purpose of this study is to clarify the structural relationship between teacher collaboration and Inquiry-Based Learning (IBL) networks in the diffusion process of IBL among Japanese teachers (N = 650). Teacher collaboration was measured using three subscales: teacher collaboration among colleagues (CF1), leadership by administrators (CF2), and partnerships with communities and parents (CF3). The analysis revealed high correlations among CF1–CF3 (r = .62-.69) and moderate correlations with the IBL Network (r = .31-.41), indicating the interconnection between intra-school and extra-school collaborative cultures and IBL networks. Furthermore, a Seemingly Unrelated Regression (SUR) model demonstrated a statistically significant reciprocal facilitation relationship between collaboration and the IBL network. These results suggest that the diffusion of IBL is mutually promoted by strong internal interactions (collaboration within schools), external network linkages (diffusion across contexts), and the formation of inquiry-related teacher networks.

This research examines the impact of women’s employment on poverty dynamics and human development in the rural regions of the Philippines. Despite progress in gender equality legislation, women’s participation in the labor force remains constrained by traditional gender roles, cultural expectations, and institutional barriers. Anchored in Social Role Theory and Gender Schema Theory, the study examines how these frameworks influence women’s labor market outcomes and socioeconomic contributions. Using panel data from 16 rural regions between 2018 and 2023, the research employs Pearson Correlation and Seemingly Unrelated Regression (SUR) to examine the relationships among women’s labor force participation rate (WLFPR), number of employed women (NEW), poverty incidence (PVI), and the regional human development index (RHDI). Findings indicate that higher female employment and labor force participation are significantly correlated with reduced poverty incidence and improvements in human development. However, results also highlight the limitations of relying solely on employment indicators, pointing to the need for broader measures of gender equality, such as the gender wage gap, sectoral employment distribution, and legal frameworks as identified in the Philippine Commission on Women’s (PCW) Compendium of Indicators for Gender Equality and Women’s Empowerment (GEWE). The study concludes that empowering women through employment is essential to rural development, but the scope of analysis is limited to 16 regions and PSA census-based data, which requires cautious interpretation. Policy recommendations include childcare support, skills development programs, and reforms aimed at dismantling restrictive gender norms. By addressing both socio-cultural and institutional barriers, this study provides insights for policymakers to promote inclusive and sustainable rural development.

The study examines the effect of environmental tax on environmental quality through the mediating role of energy consumption in developing countries from 2000 to 2020. Employing Seemingly Unrelated Regression (SUR), the effects of environmental taxes on energy consumption patterns and onward environmental upshots are empirically analyzed. The results show that imposition of environmental tax reduces energy consumption and resultantly improves environmental quality. The findings reveal that market-based policy tools strengthen sustainable energy demand and reduce environmental deterioration. The analysis provides insights to formulate effective policy measures to attain the sustainable environment goal.

Purpose This study evaluates the Jockey Club InnoPower Social Welfare Fellowship Program, designed to strengthen adaptive leadership among Hong Kong's social welfare practitioners who face high turnover and organizational instability. Method : A randomized waitlist control trial (23 training, 39 control) was conducted. Quantitative effects on sense of community, leadership, self-efficacy, adaptive capacity, and innovation were analyzed using Bayesian difference-in-differences (DID) and seemingly unrelated regression (SUR). Qualitative data from individual and focus group interviews were thematically analyzed. Results Bayesian DID showed significant improvements in all outcomes, with small-to-large effect sizes (≥95% probability of positive effects). SUR confirmed robust post-training effects ( p < .001). Qualitative findings indicated that the program fostered transformative journeys from individual growth to sector-wide impact and acted as a catalyst for organizational resilience, innovation, and systemic change. Conclusion The study highlights adaptive leadership as a critical approach for strengthening organizational resilience in Hong Kong's social welfare sector.

ABSTRACT Adoption of pro-nutritional crop varieties such as orange-fleshed sweet potato (OFSP) remains limited among smallholder farmers in Malawi, despite their proven superiority to conventional varieties in improving household nutrition and income. Understanding the behavioural and contextual factors underpinning varietal preferences is critical for designing effective interventions. This study employed a contingent valuation approach to elicit farmers’ differentiated willingness to pay (WTP) for clean planting materials of OFSP and non-OFSP varieties among 721 smallholder households across four districts. Using a Seemingly Unrelated Regression (SUR) model and a Triple-Hurdle framework incorporating a lognormal component and number-line concept, the study innovatively identified the determinants of awareness, preference formation, and the direction of preference thereby capturing both sustained and switching tendencies. Findings revealed that 41% of farmers had adopted OFSP, while the mean WTP for non-OFSP vines (USD 2.64) slightly but significantly exceeded that for OFSP (USD 2.57), confirming the persistence of resistance to biofortified varieties. Sustained preference for OFSP was positively associated with education, household size, off-farm income, and access to vine multipliers, whereas sustained preference for non-OFSP was reinforced by location, higher transaction costs, and mixed extension outcomes. Yield perceptions, market distance, and production purpose influenced potential preference switching. These findings highlight that varietal choices are adaptive responses shaped by perceptions, context, and household needs rather than simple awareness gaps. Policy interventions that integrate targeted nutrition education, strengthen extension messaging, subsidise clean vine access, and improve market linkages are essential to move farmers from indifference towards sustained preference for OFSP.

This study examines the post-privatisation performance of 87 banks in OECD and MENA countries, while identifying the various factors that may influence the privatisation-performance relationship. By using the seemingly unrelated regressions (SUR) model, the results show that in the post-privatisation period, performance slightly decreases in the MENA region. However, over time, privatisation yields significant improvements in the performance of privatised banks in OECD countries. The results also show that the economic and organisational circumstances and the political and institutional environment in which privatised banks operate affect the privatisation-performance relationship. Our results support, therefore, that the factor of private-public ownership must be differentiated from the other factors that also influence the effect of privatisation on the performance of privatised banks.

In the extant literature, it is unclear which welfare parameters financial inclusion can affect to improve welfare at the household level. To fill this knowledge gap, this study employs endogenous switching regression (ESR) and seemingly unrelated regressions (SUR) using data from the Ghana Living Standard Survey Rounds Five and Six to investigate the determinants of financial inclusion and the impact of financial inclusion on household consumption and poverty. The results show that financial inclusion is low in Ghana. Infrastructural variables such as motorable roads, banks, public transport and markets are key determinants of financial inclusion, underscoring the role of information and transaction costs in enabling financial inclusion. We find that financial inclusion robustly promotes welfare by boosting the consumption of various goods and services and reducing poverty. Thus, financial inclusion is a viable policy option for improving household welfare in Ghana.

ABSTRACT This paper revisits the military spending – economic growth nexus by introducing a simple Post-Keynesian model that accounts for both the direct and indirect effects of military expenditure, specifically through the channel of income inequality. A simulation analysis distinguishes between different types of military expenditures, showing that military wages are less harmful – and can even be beneficial – compared to arms purchases, which exacerbate inequality and diminish growth. Decomposition analysis reveals that even when the direct effect of military spending is mildly positive, the inequality-induced indirect effect is strongly negative, resulting in an overall negative impact on growth. Furthermore, using panel data from 150 countries for 1960–2019 and applying Seemingly Unrelated Regression (SUR) methods, we find that military spending negatively impacts economic growth both directly and indirectly by increasing income inequality. Our findings underline the importance of considering the composition of military expenditures and the mediating role of inequality in evaluating defense spending’s macroeconomic consequences.

The current literature rarely addresses the statistical relationship between collision occurrence (objective safety) and reports of perceived unsafety at road sites (subjective safety). This study aims to analyze this relationship using social media data collected and classified from Twitter (now X), applying a Bayesian seemingly unrelated regression (SUR) framework to jointly model both safety dimensions. By analyzing collision data and road-safety-related tweets (RSTs) from Vancouver between 2017 and 2019, macro-level prediction models were developed within the SUR framework and relative risks (RRs) were derived from model parameters to identify the key risk factors. When the RRs for objective safety aligned with those for subjective safety, it indicated that subjective safety could serve as a reliable predictor of objective safety. Five collision types and 9 distinct categories of classified RSTs were employed to develop 45 Bayesian SUR models, where four groups of explanatory variables were used to test different scenarios. While there was a general alignment between subjective and objective safety overall, notable discrepancies were also found when different categories were analyzed. Near-miss observations and safety reports related to active modes were particularly aligned to collision occurrence, especially with property-damage-only collisions. Conversely, design and maintenance-related issues showed minimal alignment with collisions. Overall, the study provided a valuable resource for future risk reduction studies by showing how specific subjective safety observations can or cannot reflect real-world collision risk. This approach suggests the potential for integrating subjective reports into comprehensive safety assessments, offering key insights for policymakers to develop safety strategies more proactively.

Abstract Understanding how men and women perceive multidimensional rural poverty differently is essential for achieving Sustainable Development Goals 1 (No Poverty) and 5 (Gender Equality). A mixed-methods approach was employed to survey 198 male-headed and 186 female-headed households in the Wolaita Zone of southern Ethiopia. Descriptive statistics were employed to assess deprivation in health, education, and living standards, utilizing the Multidimensional Poverty Index (MPI). Inferential statistics were used to evaluate gender differences in perceptions using a seemingly unrelated regression (SUR). The results show statistically significant differences between male and female perceptions across all three dimensions. The SUR model revealed that male-headed MP influenced by education, credit use, market access, and extension services was statistically significant ( p < 0.01) across all three dimensions, while family size influenced the educational dimension ( p < 0.05), and off-farm income significantly empowered the health dimension ( p < 0.01). In contrast, education ( p < 0.01) and credit use ( p < 0.01) were the key variables that influenced women’s perceptions of all the MP dimensions. Extension services enhanced ( p < 0.05) both health and education but reduced the perception of living standards. Family size and market access significantly influenced the MP’s perceptions. This finding demonstrates the importance of gender-based approaches to poverty reduction in realizing SDG 1, 5, 4, 8, and 10. This suggests that it is essential to integrate gender-disaggregated information and local knowledge to develop policies to improve rural development in Ethiopia to be inclusive and sustainable, and policies should be based on gender-based vulnerabilities.

Over the last few decades, socio-spatial disparities in urban Europe have developed in two key ways. On one hand, income inequality has increased worldwide, and this trend has been reflected in growing economic/income residential segregation. Meanwhile, there has been an unprecedented inflow of immigrants to Europe, especially in the last decade. As most existing studies in this field in Europe focus on larger issues, not only is our knowledge of the processes that shape residential segregation patterns limited to a highly specific group of urban areas (generally capital cities), but the available studies also usually focus on one aspect of residential segregation, either economic segregation or immigrant segregation. Consequently, we investigated levels of segregation in the 124 most highly populated cities in Spain, where 47% of the country’s population resided in 2021, measuring dissimilarity indices related to economic status and immigrant status. Using census tract and municipality level data, we explored the main structural determinants of segregation levels, measuring levels of residential segregation using the dissimilarity index (D). Based on three seemingly unrelated regression (SUR) models, we specified the effect of the economic and demographic characteristics of cities on residential segregation. The results of our study reveal that the structural characteristics of urban regions are, in fact, significant predictors of the intensity of income segregation and immigrant segregation in urban areas in Spain. They also show that the recovery from the 2008 crisis in Spain has led to a chronic persistence of income and immigrant segregation.

High and growing household debt is a major economic issue in Asia, contribute to the increasing living costs, personal loans, and housing loans. This study aims to examine the macroeconomic factors contributing to the rise in household debt across seven Southeast Asian countries between 2011 and 2021. Five independent variables were tested: GDP per capita, working population, unemployment rate, inflation rate, and lending interest rate. These variables were analysed using the Panel Data Analysis method, applying a cross-section Seemingly Unrelated Regression (SUR), which included panel specification and diagnostic tests. The estimation results showed that all macroeconomic variables had a negative relationship with household debt, except for the inflation rate. For policy implications, government should develop appropriate strategies related to these macroeconomic variables effectively to manage household debt. While household debt is not harmful, it must be controled at a manageable level. Future research should explore further issues of household debt across multiple countries within specific regions to provide a deeper understanding of their broader impacts.