Search Results (503)

This study examines regional agricultural credit allocation and intensity in Kazakhstan and their relevance to financial inclusion. Data cover 17 harmonised units in 2014–2023. Two-way fixed-effects models use 153 observations for 2015–2023 (T = 9), after lagging output. Outcomes comprise total real credit, credit per agricultural worker, and credit per hectare. Credit remains concentrated: the 2014–2023 Spearman rank correlation is 0.93, and 13 of 17 units remain in the same quartile. The modest decline in the top-three share is not statistically distinguishable from zero. A 1% increase in lagged agricultural output is associated with 0.63% higher current credit. Subsidies are positively associated with credit, with moderate evidence of a stronger association in initially high-credit regions. The interaction has weaker bootstrap support (p = 0.061; 95% CI [−0.01, 0.30]), so the distributional evidence is suggestive rather than definitive. Separate and joint models support a positive branch-density association; ATM-density estimates are imprecise. Regional differences and the main associations persist in the normalised outcomes. These non-causal associations concern geographic financial access and cannot establish borrower-level exclusion. Aggregate credit growth alone does not establish geographically inclusive agricultural finance. Full article

Public administrations increasingly publish programmatic and sectoral data, yet fragmented formats, inconsistent terminology, and uneven documentation limit their joint use. This article presents the design and functional evaluation of the Mexican Agricultural Policy Observatory (MAPO), a digital artifact that integrates agricultural support programs with territorial and production indicators for Mexico’s 32 states. Following a design science research approach, the study constructed a 429-record documentary inventory and retained 407 records with both a recognized state and a validated primary category as the main analytical base. This base was used to generate a 32-by-8 descriptive benchmarking matrix, interactive maps, state profiles, downloadable reports, and a structured-context generative artificial intelligence module. Input acquisition, financing, and technification accounted for 71.01% of the comparable analytical base, while state comparisons revealed marked variation in program counts and thematic diversity. A bounded audit of 50 GenAI outputs showed that prompt constraints did not eliminate causal language, policy prescriptions, or count-to-impact equivalences. MAPO separates deterministic calculations from generative interpretation and requires human review before narrative outputs are used. The study contributes a replicable approach to traceable data integration and design principles for AI-assisted public-sector observatories. MAPO supports exploration, communication, and agenda setting; it does not evaluate program impact, budget adequacy, or beneficiary coverage. Full article

Climate change affects domestic agricultural production, but national food self-sufficiency also depends on institutional and structural conditions that operate over different time horizons. This study examines these relationships using a balanced panel of 101 countries observed annually from 2012 to 2022 (1111 country-year observations). Food self-sufficiency is measured with the Food Self-Sufficiency Ratio (SSR), with SSR > 85% as the primary binary outcome. A pooled logistic regression with a within–between decomposition following the Mundlak approach separates persistent between-country differences from within-country changes, with country-clustered standard errors. The most consistent finding is a positive between-country association between long-run agricultural adaptation-policy status and high self-sufficiency (OR = 6.676, 95% CI: 1.502–29.668), whereas within-country changes in policy status are not statistically significant. This association reflects a persistent cross-country difference and should not be interpreted as a causal short-run effect of policy adoption. Within-country increases in climate-finance scores are negatively associated with the 85% threshold, but this result is sensitive to the outcome definition. Sensitivity analyses using 75%, 80%, and 90% thresholds show that the adaptation-policy association remains positive across all specifications and is the most stable result overall, although it is no longer statistically significant at the 90% threshold. The findings underscore the importance of distinguishing persistent institutional conditions from short-run policy changes when analyzing national food self-sufficiency. Full article

Smart farming (SF) integrates digital technologies, automation, and data analytics to enhance agricultural decision-making and sustainability. However, adoption in emerging economies remains limited due to structural constraints. This study examines the determinants of SF adoption intention in Honduras using an extended Technology–Organization–Environment (TOE) framework that incorporates technological attributes, farm manager characteristics, organizational factors, and business environmental conditions. A cross-sectional survey of 313 agricultural workers, mainly young and female, was analyzed using partial least squares structural equation modeling (PLS-SEM). The model explained 80.8% of the variance in adoption intention. Among the eleven hypothesized predictors, only government support and changes in the digital environment showed significant positive effects. Technological factors, managerial capabilities, organizational conditions, and competitive pressure were not significant. These findings indicate that, in structurally constrained agricultural systems, external enabling conditions—particularly institutional support and digital infrastructure—play a decisive role in shaping adoption intention. The results highlight the need for policies that strengthen rural connectivity, technical training, financing mechanisms, and institutional assistance to facilitate effective implementation of smart farming technologies. The study validates the TOE framework in an emerging economy and underscores the contextual variability of its explanatory dimensions. Full article

This article examines the dual-brokerage regimes governing Vietnamese labour migration to South Korea, situating migration governance within broader debates on Asian capitalism and developmental state transformations. Drawing on the Employment Permit System (EPS) as a paradigmatic case of state-led migration management, we analyse how public brokerage mechanisms—embodied in Vietnam’s Department of Overseas Labour (DOLAB) and licensed sending organisations—intersect with private intermediaries to shape migration pathways. The analysis reveals structural tensions between Korea’s developmental state ambitions to regulate low-skilled labour flows and Vietnam’s export-oriented migration regime, where private brokers extract substantial fees from aspiring migrants. These tensions are amplified in new growth industries—care work, manufacturing, agriculture, and construction—where labour demand intersects with gendered migration patterns and debt-financed mobility. We argue that the Vietnam–Korea migration corridor exemplifies a distinctive form of ‘brokerage capitalism’ within Asian migration governance, where state institutions and private actors co-produce regulatory spaces that simultaneously facilitate and exploit migrant workers. The article contributes to scholarship on Asian capitalism, migration brokerage, and developmental state theory by demonstrating how migration governance reflects broader patterns of variegated capitalism in East and Southeast Asia. Full article

The EU agricultural policy for the period 2023–2027 assumes that improving technical efficiency strengthens the financial sustainability of farms, an assumption rarely tested rigorously at EU country level, or with an explicit distinction between solvency and profitability. Using FADN/FSDN data for 402 country-year observations of arable farms in 28 European countries (2010–2024), technical efficiency is estimated by a fully unrestricted translog stochastic frontier, statistically preferred over the Cobb–Douglas form (χ² = 177.57, df = 10, p < 0.001), and validated by comparison with Data Envelopment Analysis (DEA) and a metafrontier decomposition (EU-15 versus EU-13). The one-year lagged score is entered into panel models of solvency, profitability and regional heterogeneity, estimated with two-way fixed effects (country and year) and robust Driscoll–Kraay standard errors. Lagged technical efficiency shows no robust average effect on solvency or profitability (all p > 0.45), and its marginal effect on solvency does not differ significantly between EU-15 and EU-13 farms after correcting for multiple comparisons (p = 0.352). Farm size, on the other hand, is significantly and negatively associated with solvency, and debt ratio is the most consistent determinant of profitability, identifying capital structure as the more robust channel linking farm operations to financial performance. This divergence between channels shows that farm financial sustainability is not unidimensional: at the one-year horizon tested, efficiency gains do not reliably translate into stronger farm finances, which calls for caution in treating efficiency-oriented support as a general lever for the CAP’s financial sustainability objectives. Full article

In the agricultural production cycle, farmers face financial constraints both before planting and before harvesting, which can substantially restrict production decisions and operational efficiency. With the rapid development of agricultural e-commerce and supply chain finance, platform loans and pre-sale financing have become important channels through which farmers can obtain the funds needed for agricultural production. This study develops a two-stage financing portfolio decision model for an agricultural product supply chain and examines the farmer’s optimal financing strategy, planting quantity, and pricing decisions under exogenously given platform loan and pre-sale financing conditions. The results show that the loan interest rate and commission rate significantly influence the farmer’s choice of financing strategy. Specifically, holding other conditions constant, a higher loan interest rate increases the farmer’s incentive to adopt pre-sale financing, whereas a higher commission rate reduces the incentive to adopt it. Numerical simulations further identify the decision boundaries of the two-stage financing portfolio strategies under different parameter conditions. This study provides theoretical insights into farmers’ financing decisions and the selection of multi-stage financing strategies in agricultural product supply chains. Full article

With the steady advancement of industrialization and urbanization, farmers have been increasingly motivated by economic interests to cultivate cash crops with higher returns, leading to the growing prominence of the non-grain conversion of cultivated land. As a major policy instrument for safeguarding returns and mitigating risks, policy-oriented agricultural insurance may alter farmers’ planting decisions and achieve fundamental adjustments in crop planting structures, thereby playing an important role in addressing the challenge of non-grain conversion of cultivated land. Therefore, based on the “risk–return” decision-making framework, this study employs a multi-period difference-in-differences model and provincial panel data from 31 provinces in China during 2013–2023 to investigate the effects and mechanisms of the pilot programs of full-cost insurance and planting income insurance on the non-grain conversion of cultivated land. The results indicate that policy-oriented agricultural insurance significantly inhibits the non-grain conversion of cultivated land and suppresses such conversion through promoting large-scale agricultural land operation and improving the comparative returns to grain production. The heterogeneity analysis reveals that the inhibitory effect of policy-oriented agricultural insurance on non-grain conversion is more pronounced among new agricultural business entities, high-quality cultivated land, and regions with higher levels of natural risks. Accordingly, this study recommends implementing differentiated insurance policies based on cultivated land quality, natural risk levels, and cultivated land transfer entities across regions, and constructing a policy coordination system integrating “fiscal support–insurance–finance” to fully enhance policy effectiveness. Full article

The return migration of agricultural labor has emerged as a notable demographic shift in rural China, yet its association with farmland abandonment has received limited empirical attention. Using household-level microdata from the China Household Finance Survey (CHFS), this study empirically examines the association between agricultural labor return migration on farmland abandonment among rural households and explores the underlying channels. The results indicate a negative association between agricultural labor return migration and the area of farmland abandoned by rural households, and this pattern remains stable across a series of robustness checks. Mechanism analyses suggest that this association is consistent with two channels, namely farmland transfer-out and household investment in farmland. This negative association appears stronger in villages with well-developed specialty agricultural industries, relatively limited non-agricultural employment opportunities, and village cooperatives. These patterns suggest that policy efforts could pay greater attention to the role of labor return migration in improving the efficiency of rural farmland resource utilization. A combination of policy measures is recommended to improve farmland transfer markets, strengthen incentives for agricultural investment, and foster locally adapted specialty rural industries. Full article

Agricultural residues, municipal organic waste, animal manure, and food-processing residues represent promising resources for sustainable waste-based bioenergy production. In addition to serving as renewable energy sources, these biomass resources can contribute to improved waste management, rural development, and environmental protection. In the context of global efforts to accelerate the transition toward sustainable energy systems, biomass and bioenergy are increasingly being investigated alongside other renewable energy technologies. Jordan faces significant challenges related to its dependence on imported fossil fuels and the associated economic and environmental impacts. Fluctuations in international oil prices, energy security concerns, and the need to reduce greenhouse gas emissions have encouraged Jordan to explore alternative and renewable energy options. Bioenergy offers a potential pathway to diversify the national energy mix while also addressing organic waste management and supporting rural and agricultural sectors. This study assesses the current status of bioenergy in Jordan and reviews the potential of available biomass resources, including agricultural residues, municipal organic waste, animal manure, olive-industry residues, sewage sludge, and food-processing waste. It matches these resources with suitable conversion technologies and provides a qualitative, literature-based discussion of their environmental and socioeconomic implications and the principal conditions affecting implementation. The study also identifies the main technical, logistical, financial, institutional, and regulatory barriers to bioenergy deployment and proposes practical recommendations for policy development, pilot projects, financing mechanisms, and local capacity building. The harmonized results indicate a combined energy potential of approximately 25.3 PJ/year for animal manure and agricultural residues reported on a comparable basis, with animal manure contributing approximately 73% of this total. A screening-level recoverability assessment estimates that approximately 2.55 Mt/year of biomass could potentially be recoverable under the central scenario, compared with 1.94 and 3.17 Mt/year under the low and high scenarios, respectively, excluding sewage sludge. A published theoretical estimate indicates a biogas-derived electricity potential of approximately 960.9 GWh/year, equivalent to about 5.1% of Jordan’s electricity consumption in 2019. The results identify animal manure, source-separated organic municipal waste, sewage sludge, and concentrated food-processing residues as the most relevant near-term resources. These findings can support policymakers, researchers, and industry stakeholders in prioritizing locally appropriate waste-based bioenergy pathways. Full article

Agricultural green total factor productivity is central to reconciling agricultural growth with increasingly binding resource and environmental constraints. Digital inclusive finance may facilitate this transition by relaxing financing constraints and expanding access to productive technologies, yet its contribution to agricultural green productivity remains insufficiently understood. To address this gap, this study develops an analytical framework that identifies technological innovation as a potential mediating transmission channel and agricultural mechanization as the threshold condition in the relationship between digital inclusive finance and agricultural green total factor productivity. Drawing on a balanced panel of 30 Chinese provinces, the empirical analysis employs a two-way fixed-effects model, mediation analysis, and a panel threshold model to test the proposed relationships. The results yield three main findings. First, digital inclusive finance is positively associated with agricultural green total factor productivity, and this relationship remains robust after robustness checks and endogeneity analyses. Second, mediation analysis provides evidence consistent with a positive mediating role of technological innovation in the relationship between digital inclusive finance and agricultural green total factor productivity. Third, the association between digital inclusive finance and agricultural green total factor productivity exhibits significant nonlinear heterogeneity across agricultural mechanization regimes. The regime-specific analysis further indicates that such heterogeneity is more evident in the relationships involving digital inclusive finance, whereas the relationship between technological innovation and agricultural green total factor productivity does not differ significantly across regimes. These findings clarify the heterogeneous relationships among digital inclusive finance, technological innovation, and agricultural green productivity and provide empirical support for coordinating financial policy with agricultural modernization strategies. Full article

Against the backdrop of the “dual carbon” goal and the rural revitalization strategy, green agricultural development is crucial. Using data on China’s listed agricultural enterprises from 2009 to 2024, this article analyzes how corporate ESG performance affects these enterprises’ green total factor productivity. The results show that a better ESG performance significantly improves the green total factor productivity (GTFP), mainly through corporate green technology innovation and eased financing constraints. Environmental regulation strengthens the ESG–GTFP relationship for listed firms. A further analysis shows that ESG has a stronger effect on GTFP growth in small-scale, strong non-agricultural provinces and non-heavy pollution provinces. The sub-dimension test indicates that corporate governance has the largest positive impact, followed by the social dimension, while the environmental dimension needs further improvement. This article offers empirical insights for agricultural enterprises aiming to enhance their green total factor productivity through ESG practices. Full article

Agricultural methane, from livestock, manure, and rice cultivation, is the largest human source of the second most important greenhouse gas. Because methane is potent but short-lived, reducing it is one of the fastest available levers on near-term warming. The obstacle, however, is widely understood to be institutional and fiscal rather than technological: these emissions are diffuse and difficult to observe, and governments can reach them only through extension services, monitoring, and regulation, all of which must be paid for. We therefore ask whether a state’s fiscal capacity is associated with lower agricultural methane, using a panel of 27 countries observed from 2014 to 2022 and comparing four governance attributes: trust in government, public employment and representation, control of corruption, and public finance. Only public finance is consistently associated with lower per capita agricultural methane, and the association holds within countries over time as well as across them, so that periods of stronger public finances coincide with lower emissions. No other governance attribute shows such a relationship. Several features of the data are consistent with a fiscal-capacity explanation rather than simple affluence: public finance is essentially uncorrelated with national income in our sample and, unlike control of corruption, bears no relation to consumption-driven emissions such as carbon dioxide and waste. The pattern is also specific to methane rather than to environmental performance in general, and it survives an extensive battery of robustness and reverse-causality checks. The results suggest that money for methane abatement works only through the state’s capacity to spend it well, a consideration that matters for the design of methane finance under the Global Methane Pledge, where funds flow to countries whose fiscal and administrative capacity to deliver agricultural change varies widely. Full article

Improving agricultural labour productivity is essential for enhancing agricultural competitiveness, rural development, and long-term economic sustainability, particularly in transition economies where agriculture continues to play a strategic role. Although previous studies have examined the roles of agricultural finance, government support, and macroeconomic conditions separately, limited evidence exists on their joint long-run and short-run relationships with agricultural labour productivity in Kazakhstan. This study addresses this gap by examining the relationships between government expenditure, agricultural credit, inflation, and agricultural labour productivity using annual data for the period 2004–2025. The autoregressive distributed lag (ARDL) bounds testing approach is employed to distinguish between long-run equilibrium relationships and short-run adjustment dynamics. Prior to estimation, stationarity is examined using augmented Dickey–Fuller and Phillips–Perron unit root tests, while the Bai–Perron multiple structural breakpoint test is used to account for structural change. The robustness of the long-run estimates is further evaluated using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegrating regression (CCR). The findings indicate the existence of a stable long-run relationship among the variables. Government expenditure is positively associated with agricultural labour productivity in both the long run and the short run, whereas agricultural credit exhibits a negative long-run association and no statistically significant short-run relationship. Inflation is not found to be significantly associated with agricultural labour productivity within the estimated model. The robustness estimators produce results that are broadly consistent with the ARDL findings, while diagnostic and stability tests confirm the adequacy of the estimated model. By jointly examining fiscal, financial, and macroeconomic factors, explicitly accounting for structural change, and validating the long-run estimates using alternative cointegration estimators, this study provides updated country-specific evidence on agricultural labour productivity in Kazakhstan and contributes to the broader literature on agricultural productivity in transition economies. Full article

Agricultural cooperatives are widely regarded as engines of rural development, yet their role in advancing the economic, social, and environmental pillars of sustainability within specialized subsectors such as beekeeping remains empirically underexplored, particularly in the Gulf Cooperation Council region. This study examines the social and economic determinants of beekeepers’ membership in agricultural cooperatives in the Al-Baha region of Saudi Arabia, home to roughly 70% of the Kingdom’s beekeeping activity. Data were collected from 200 beekeepers through a structured questionnaire and analyzed using Pearson correlation, multiple linear regression, and the Mann–Whitney U test. Only 21% of respondents were cooperative members. While age, family size, experience, hive holding size, harvest frequency, and marketing-practice adoption were all significantly correlated with membership, regression analysis showed that only years of experience, hive holding size, and adoption of marketing practices remained significant predictors when considered jointly, explaining 30.8% of the variance in membership status (R² = 0.308). Mann–Whitney tests further revealed that members differed significantly from non-members in family labor contribution, access to financing, ownership of a marketing shop, and access to extension services, with shop ownership showing the largest effect size (r = 0.497). These findings indicate that cooperative membership is driven primarily by commercial experience and institutional connectedness rather than demographic characteristics, carrying direct implications for income diversification, rural resilience, and the sustainability agenda under Saudi Vision 2030 and Sustainable Development Goals 2, 5, 8, and 15. Full article