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Age dependent investment decisions in light of intergenerational altruism
No full textInvestment decisions differ depending on the age of the investor in terms of both the quantity and the composition of the investments. First, this age-dependency of investment decisions is due to changes in risk aversion over the life-cycle, i.e. older investors are normally less willing to bear risks compared to younger investors. Second, older individuals encounter less residual capacity in order to compensate for potential losses, i.e. a potential loss might not be neutralized within the years of residual life expectancy. Simultaneously, both channels lead to less risk taking on the financial market of older investors, and correspondingly, to lower returns on average. This paper shows that intergenerational altruism might neutralize the shift of investment decisions towards less risky assets. In particular, in case the next generation can compensate for potential losses which is internalized and recognized by the investor, the shift in investment decisions might be neutralized or even reversed
Statistical Economic Perspectives on Urban Inequality: A Systematic Review of GIS-Based Methodologies and Applications
No full textUrban inequality, as reflected by uneven spatial allocations of resources, services, and opportunities, has arisen as a major topic for quantitative research and policy intervention. Geographic Information Systems (GIS) provide a solid framework for quantifying, analyzing, and visualizing these disparities; nevertheless, the many statistical approaches used in different studies have not been completely pooled. This analysis looks at 201 peer-reviewed articles published between 1996 and 2024, obtained from the Web of Science and Scopus databases, that use GIS-based approaches to investigate intra-urban differences. Eligibility was limited to English-language, peer-reviewed research that focused on urban settings, with the screening technique following the PRISMA methodology. The review identifies five key theme domains: accessibility, green space, health-related disparity, socioeconomic status, and open space provision. In the literature, statistical and network-based approaches, such as spatial clustering, regression analysis, and bibliometric mapping, are critical for identifying patterns and driving thematic synthesis. Although accessibility remains the core focus, the subject has expanded to include a variety of indicators such as environmental justice and health vulnerability, aided by advances in data sources and spatial analytics. Ongoing methodological issues include spatial concentration in industrialized countries and the limited use of longitudinal or composite measurements. The report concludes by outlining research priorities and practical recommendations for improving statistical rigor, encouraging interdisciplinary collaboration, and assuring policy relevance in GIS-based urban inequality studies
Integrating Machine Learning and Hedonic Regression for Housing Price Prediction: A Systematic International Review of Model Performance and Interpretability
No full textIt is becoming increasingly important to predict property prices to mitigate investment risk, establish policies, and preserve market stability. To determine the practical utility and anticipated efficacy of the sophisticated statistical and machine learning models that have emerged, a comparative analysis is required.
The purpose of this systematic study is to assess the predictive effectiveness and interpretability of hedonic regression and complex machine learning models in the estimation of housing prices in a wide range of foreign scenarios.
In May 2024, a thorough search was conducted in Scopus, Google Scholar, and Web of Science. The search terms included "hedonic pricing models," "machine learning," and "housing price prediction," in addition to others. The inclusion criteria required the utilization of empirical research published after 2000, a comparison of at least two predictive models, and reliable transaction data. Research that utilized non-empirical methodologies or web- scraped prices was excluded. Twenty-three investigations met the eligibility criteria. The evaluation was conducted in accordance with the reporting criteria of PRISMA 2020.
Random Forest was the most frequently employed and consistently high-performing model, being selected in 14 of 23 studies and regarded as exceptional in five. Despite their lack of precision, hedonic regression models provided critical explanatory insights into critical variables, such as proximity to urban centers, property characteristics, and location. The integration of hedonic and machine learning models improved the interpretability and accuracy of the predicted results. Many of the studies included in this review were longitudinal, covered a diverse range of international contexts (specifically, Asia, Europe, America, and Australia), and demonstrated a rise in research output beyond 2020.
Even though hedonic models retain a significant amount of explanatory power, the precision of home price predictions is improved by machine learning, particularly Random Forest and neural networks. The optimal results for researchers, real estate professionals, and policymakers who aim to improve market transparency and enlighten effective policy decisions are achieved through the seamless integration of these techniques
Production Function as a Set of Discrete Options: Neoclassical, Net Zero, and Climate Neutrality
No full textThis study examines the relationship between the neoclassical, net-zero, and climate neutrality perspectives, an area that has received limited attention in formal economic analysis. Adopting the concept of factor substitution, we model the production function as a set of discrete, substitutable options to explore the properties and interactions of these three perspectives. The findings demonstrate that each perspective yields a non-empty subset of solution options. Climate neutrality solutions are situated between neoclassical and net-zero solutions, exhibit discrete convexity, and are influenced by the level of GHG credit costs. Lower GHG credit costs tend to favour neoclassical solutions, while higher costs shift preference toward net-zero solutions. This highlights the importance of GHG credit pricing in guiding the transition to a low-emissions economy. Moreover, the framework enables the categorization of new climate mitigation options based on their effects, whether they are irrelevant, complementary, or disruptive. Overall, the proposed model provides an alternative formal approach that enhances the economic analysis of climate change mitigation strategies
The complementarity of low taxes and pro-social guidelines when polluters have moral preferences
No full textWe present the results of a series of public-bad laboratory experiments in which we assess whether a salient message suggesting pro-social behavior with an implicit moral appeal, and a tax that is insufficient to induce the optimal level of the externality, can complement each other when implemented jointly. Our results suggest that, on average, (a) behavior is consistent with subjects having moral preferences, (b) a salient message suggesting pro-social behavior can be effective, (c) preferences are non-separable from the choice of instrument (i.e, the tax crowds-out part of the subjects´ moral preferences), and crucially, (d) the tax and the informative message do not complement each other. The tax has a greater impact on reducing the externality than the prosocial guideline, even though the tax was only half of that needed to reach the socially optimal level. Nevertheless, when implemented together, the total effect of both instruments is similar to that of the tax alone. This result is stronger for those subjects that are more “nudgeable” by the prosocial guideline. These results challenge the policy recommendation that nudges can effectively complement low taxes while awaiting the political will to raise them
Rational Expectations in Economic Theory
No full textThis paper examines the rational expectations hypothesis, a central concept in modern macroeconomics. It explores the theoretical foundations, methodological implications, applications in macroeconomic models, empirical evidence, criticisms, and relevance for contemporary policy analysis. The analysis highlights both the strengths and limitations of rational expectations, situating it as a benchmark assumption that continues to shape modern economic thought
Combating Money Laundering in the Age of Artificial Intelligence (AI): A Comparative Study between Romania and the Republic of Moldova
No full textThis paper examines the role of artificial intelligence (AI) in combating money laundering (AML), focusing on a comparative study between Romania and the Republic of Moldova. Romania demonstrates advanced AI integration within its financial institutions, employing machine learning and predictive analytics to enhance transaction monitoring, risk assessment, and regulatory compliance. In contrast, Moldova is in the early stages of adopting AI for AML, facing structural, technical, and regulatory challenges that limit the effectiveness of its anti-money laundering efforts. The study highlights how technological adoption, institutional capacity, and regulatory frameworks intersect to shape AML effectiveness. By analyzing similarities, differences, and lessons learned, the paper provides insights into how AI can strengthen financial integrity while addressing the evolving challenges of illicit financial flows in different national contexts
Equilibrium in Keynes: A Note
No full textThis paper investigates the elusive notion of equilibrium in Keynes’s General Theory and its implications for subsequent interpretations of his work. Through a formal setup of the core relationships in the first eighteen chapters of the book, I show that Keynes’s model allows for multiple equilibria that critically depend on fixed nominal wages, expectations and confidence. While this structure resembles the IS-LM model, it diverges in its treatment of price flexibility, speculative motives in money demand, and the central role of expectations and confidence. The paper evaluates four possible interpretations of the General Theory, each arising from a different understanding of the notion of equilibrium in Keynes: (1) the neoclassical synthesis view, which relies on nominal wage rigidity; (2) a Tobinian view, in which macroeconomic equilibrium is unique but potentially unstable; (3) a social-norms view, where real rigidities à la Akerlof prevent wage adjustments and therefore multiple equilibria are possible; and (4) a Minskian interpretation that denies the existence of equilibrium altogether. The first interpretation is incompatible with the view expressed by Keynes in the General Theory. The other three, while clearly distinct from each other, are all compatible with Keynes’s argument—although they appear with varying degrees of clarity in the book
ENTRE LIKES E FAKE NEWS: A LIBERDADE DE EXPRESSÃO EM TEMPOS DE DESINFORMAÇÃO
No full textA liberdade de expressão constitui um dos fundamentos da democracia, mas enfrenta desafios inéditos na era digital. A disseminação de desinformação, a manipulação algorítmica e a concentração de poder nas plataformas digitais comprometem a integridade do espaço público e a confiança nas instituições democráticas. O problema central investigado refere-se ao equilíbrio entre a preservação da liberdade de expressão e a necessidade de combater as fake news, sem violar direitos fundamentais. A pesquisa adota uma abordagem qualitativa, com base em revisão bibliográfica de fontes físicas e digitais, privilegiando análises críticas interdisciplinares sobre direito, comunicação e ciência política. A investigação revelou que o combate à desinformação exige estratégias múltiplas, incluindo regulação responsável das plataformas, promoção da alfabetização digital, educação midiática e incentivo à transparência corporativa. Constatou-se que a regulação deve ser dinâmica, combinando instrumentos estatais, formas de autorregulação e co-regulação, a fim de se adaptar à evolução das práticas de disseminação da desinformação. Conclui-se que soluções isoladas são insuficientes, sendo imprescindível uma abordagem colaborativa entre governos, sociedade civil, empresas e academia para garantir um ambiente digital democrático, plural e seguro
From rubble to recovery: capital, labor, and gender in the “economic miracles” of Germany and Japan
No full textThis paper analyzes the postwar economic growth of Germany and Japan using the Solow Growth Model and its extensions. By examining historical data on savings, investment, capital accumulation, and labor force dynamics, the study identifies the mechanisms behind rapid convergence toward steady-state output. Extending the model to incorporate human capital and labor heterogeneity, it highlights the role of mass education and gender inclusion in sustaining growth. Differences in female labor participation across East and West Germany and Japan are analyzed using the feminization U-hypothesis. The paper also considers political background and cultural factors shaping labor and capital outcomes. It concludes with policy recommendations for modern developing economies, drawn from the postwar experiences of Germany and Japan, emphasizing inclusive labor use, human capital investment, institutional credibility, and capital deepening