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Anatomie critique de la gestion des sacs plastiques à Madagascar
Get PDFThis article examines the governance of plastic bags in Madagascar, highlighting the disjunction between the ecological ambition of the legal framework and the ineffective reality of its enforcement. Despite the adoption of strict regulations since 2015, the country remains entangled in a regulatory maze where overlapping, poorly coordinated decrees generate confusion rather than impact.
Drawing on field observations and institutional analysis, the paper identifies systemic bottlenecks, institutional contradictions, and the fragility of enforcement mechanisms. The plastic ban thus emerges as a revealing case of environmental governance in crisis, caught between symbolic politics and administrative inertia
La desconfiguración del orden mundial y los aranceles: Efectos sobre la economía de Galicia.
Get PDFOn November 5, 2024, Donald Trump won the U.S. presidential election and, in February 2025, announced new tariffs, defending them as a way to make America "great and rich" again. Tariffs are taxes on imported goods that increase prices, affect consumers and businesses, and cause negative effects such as inflation, reduced investment, and greater uncertainty.
Spain is one of the European economies with the least direct exposure to the United States, although it is not free from risk; in 2024, it exported goods worth €18.379 billion, compared to Germany's €161 billion. In Galicia, the external sector is highly concentrated geographically and by industry. Its exports to the U.S. amounted to €2.093 billion, 4.5% of Spain's total, below Galicia’s overall weight in national foreign trade (6.6%).
The impact of additional tariffs on Galician exports is relatively small. Specifically, if tariffs increased by 20%, Galicia’s economy would see a 0.20% drop in GDP, plus an additional 0.09% due to the effect on supplies to European exporters. The total impact would be a 0.29% decrease in GDP—lower than the expected impact on the Spanish economy (0.31%) and that of the Basque Country (0.66%) and Catalonia (0.36%)
Prehistoric shuttle dispersals in a Malthusian economy
Get PDFEarly humans undertook multiple waves of migration out of Africa and back to the continent. We explore prehistoric human migration in a two-region Malthusian growth model. Whether migration occurs depends on the migration cost, relative population size, relative land supply and relative hunting-gathering productivity between regions. Suppose one region is initially uninhabited. Then, a lower migration cost leads to migration and a larger human population. Back migration occurs when hunting-gathering productivity and supply of natural resources in the foreign region decrease relative to the home region, which provides an economic rationale for the multi-directional "shuttle dispersal model" of prehistoric human migration out of and back to Africa
Ghanaian Inflation and Income Dynamics: Evidence on Volatility and Neutrality
Get PDFThe paper explains how inflation, monetary policy, and fiscal interventions interacted in Ghana from 2005 to 2014. A discrete-time macroeconomic model with money supply, taxation, household consumption, GDP per capita, and price adjustments as variables has been developed. The paper uses FIGARCH and GARCH models to investigate the volatility of inflation to decide if it has long-memory properties. The empirical findings show that the fractional differencing parameter (Hurst exponent ), which means that there is no persistent long-range dependence in inflation volatility. Hence, a standard GARCH(1,1) model is sufficient to describe short-term volatility dynamics, and shocks to conditional variance occur immediately but subside rapidly. Besides that, the research determines a monetary-fiscal neutrality threshold, which highlights the equilibrium where income growth balances the inflationary pressures; this threshold is assessed macroeconomically into general prices and compared to actual general prices to evaluate its validity. The results indicate that inflation in Ghana during this period is mainly of short-memory nature, thus reaffirming the role of short-term monetary and fiscal operations in price stabilization, and confirming the successful validation of the macroeconomic neutrality threshold linking income growth and price stability
Cross Dominance: A Shared-Interest Parallel to Strict Dominance
Get PDFWe describe cross dominance, a bilateral strengthening of weak dominance: switching B->A is never worse for either player. Cross dominance is strictly stronger than weak dominance yet orthogonal to strict dominance; within the Pareto-monotone slice we have SD => CD => WD. This yields a shared-interest ladder (weak -> cross -> strict-cross) that runs in parallel to the classical self-interest ladder (weak -> strict), offering a simple, outcome-agnostic rationale for pruning strategies like B in the motivating 2x2 game
Shortfalls in profitability: Internal Rate of Return re-estimation based on ex-ante indicators and ex-post deviations
Get PDFCost-Benefit Analysis (CBA) is one of the main tools that public administrations have at their disposal to analyze the socio-economic convenience of infrastructure projects. However, the application of this methodology is often problematic due to the uncertainty surrounding the main variables and the optimistic bias of evaluators, which translates into ex-post deviations and the appearance of the so-called “white elephants” (i.e., projects with negative social profitability). Considering the internal rate of return (IRR) as a decision criterion to accept or reject a project, the contribution of this paper to the academic literature is the redefinition of the IRR in order to include an ex-ante indicator and ex-post deviations. The main advantages of this instrument are its simplicity, transparency, and comparability of results when detailed ex-ante data are not available, and applications span from policy to research. Firstly, it facilitates systematic ex-post reviews by administrations, providing a reasonably accurate estimate in a low-cost and transparent manner. Secondly, it enables the empirical testing of profitability in large samples of projects, which could extend our understanding of the overall validity of CBA and best practices for project appraisal
Work from home and household behavior: Theoretical modelling and results for the United States
Get PDFThis article examines work from home (WFH) from a household perspective, using the collective framework, which accounts for intrahousehold bargaining, allowing decisions to be understood as interdependent between spouses. The analysis uses representative US data from the Panel Study of Income Dynamics for the period 2011-2021, which include detailed information on work hours, WFH, wages, and household demographics. The results reveal that WFH is a coordinated household decision, as spouses’ WFH decisions are positively correlated. Second, WFH is persistent for individuals, with those who had WFH in the past having a higher probability of being WFH in the future. Finally, demographic and economic factors matter little in determining spouses WFH decisions, although wages generally reduce the probability of WFH. These findings suggest that policies should treat the household as the unit of decision and focus on removing structural barriers to initial WFH adoption rather than targeting specific individuals
ESG Drivers of Financial Development: A Multimethod Analysis of Domestic Credit to the Private Sector
Get PDFThis paper investigates the influence of environmental, social, and governance (ESG) factors on financial development, using Domestic Credit to the Private Sector by Banks (DCB) as the core indicator of credit market development. To effectively market the research within the broader literature on finance and ESG issues, the authors employ an approach combining econometric analysis, K-Nearest Neighbors (KNN), cluster analysis, and network analysis. By analyzing the impact through the estimation of the model parameters through the impact of instrumental variable estimation on the model parameters (using Two-Stage Least Squares (IV), Random Effects (IV), and First-Differenced (IV) methods), the study confirms that access to clean fuels and natural resource depletion impact the model margins significantly. However, across all the models used in the analysis, the impact of access to clean energy is positive. By analyzing the significance of the issue using the KNN model throughout the research process on the impact of ESG on credit market dynamics across countries, the research demonstrates that the issue is significant. By performing hierarchical cluster analysis on the significance of the research by considering the significance of the issue in its contribution to the impact on credit market dynamics in countries, in terms of climate stress issues being core in influencing the dynamics of credit in countries, through network analysis mapping performed by carrying out research on the topic
Grassland Restoration Increases Agricultural Yields through Microclimate Regulation
Get PDFEcosystem restoration is often perceived as competing with agricultural production, yet this perception neglects potential synergies emerging from biophysical feedbacks. Here, we demonstrate that large-scale grassland restoration under China’s Grassland Ecological Compensation Policy (GECP) significantly enhances maize yields by regulating local microclimate. Using a staggered difference-in-differences design with county-level panel data, we show that restored grasslands reduced average growing-season temperatures by approximately 0.11℃ and increased precipitation by 11.48mm, thereby suppressing extreme heat and drought during critical reproductive stages. These changes extended the maize reproductive growth period by 0.93 days, elevating yields by 7.76% (0.437t/ha) and reducing crop failure risk by 25.9%.
Economically, the yield gains alone offset over 80% of program costs within five years, and the additional production could alleviate nearly 10% of China's maize import deficit in the Northern Spring Maize Region. Our findings overturn the conventional trade-off narrative between conservation and agri
culture, positioning ecosystem restoration as a scalable strategy for climate resilient food security
A Novel Hybrid Lexicon and Economic Optimized kNN Framework for Sentiment Analysis in Tourism Platforms
Get PDFSentiment analysis in tourism platforms plays a vital role in understanding customer feedback, enhancing service quality, and supporting strategic economic decision-making across tourism markets. Challenges such as imbalanced sentiment classes, domain-specific language, and noisy data reduce the economic efficiency and analytical value of conventional approaches. This paper introduces a novel hybrid framework that combines lexicon-based sentiment and emotion analysis with an economically optimized weighted kNearest Neighbors (kNN) classifier. The framework incorporates advanced data augmentation techniques and comprehensive feature engineering, including n-gram TF-IDF extraction and metric learning—to improve minority sentiment class recognition and increase the economic robustness of predictive analytics. A modified co-optimization layer jointly tunes augmentation
parameters, feature extraction methods, and classifier hyperparameters to maximize minority-class F1-scores while minimizing computational and economic costs. Experimental evaluations on real-world tourism review datasets demonstrate significant improvements in classification performance compared
to baseline models such as SVM, Random Forest, and CNN, highlighting the framework’s economic value in large-scale tourism data processing. Additionally, a real-time business intelligence dashboard is developed for economic monitoring and dynamic visualization of sentiment trends and minorityclass heatmaps, enabling tourism stakeholders to make informed economic
and managerial decisions and strategically respond to customer sentiments. The findings confirm a predominance of positive sentiments across tourism services while identifying economically critical areas requiring improvement. Future work will explore multilingual sentiment analysis and aspect-based models to enhance granularity, scalability, and economic impact. This research contributes an effective, interpretable, and economically oriented solution for advanced sentiment analysis in tourism platforms