Hasil untuk "Home economics"

Sidharth Gat

Many economic theories have been introduced over the course of history to articulate our understanding of the economy. Classical theories by Adam Smith and David Ricardo's Comparative Advantage have been foundational for the last century's work. Improvements have been achieved over time, incorporating insights from many disparate fields of study: contemporary frameworks like Behavioural Economics and Information Economics, which incorporate psychological insights and deviation from rational decision-making and insights from network theory and how the information flow affects the market behaviour, respectively. In this paper, I motivate the necessity of incorporating insights from Physics, and also show that trade as a phenomenon described by the comparative advantage theory cannot exist without the law of conservation of Energy, and incorporating this law leads to axiomatic completeness of the theory. Further, I also argue that while the economy is not a zero-sum game in terms of wealth, it does require at least one associated zero-sum parameter for trade and economy as phenomena to exist.

Marcela Reymond Simoes, Bruna Bombassaro, Milena Monfort-Pires et al.

Julio Cesar dos Reis, Mariana Yumi Takahashi Kamoi, Tarik Marques do Prado Tanure et al.

Diversified sustainable agricultural systems, such as integrated crop-livestock-forest systems (ICLFs), offer substantial potential for enhancing food production to meet the increasing global demand for agricultural goods while, simultaneously, conserving vital natural resources, including soil, water, and forests. However, a critical barrier to the widespread adoption of these sustainable systems in Brazil’s Amazon and Cerrado biomes, its primary agricultural commodity-producing regions, is the lack of comprehensive economic information. This paper presents case studies that evaluate the economic performance of ICLFs compared to traditional agricultural practices in these biomes (extensive livestock and large-scale cropping systems). Additionally, we employ an economic impact analysis using an input–output matrix approach to assess the economic benefits associated with ICLF adoption. The findings indicate that integrated systems exhibit superior economic performance, particularly over the long-term, as evidenced by more favorable viability indicators, such as higher internal rates of return and profitability indexes. In the Cerrado biome, the gross profit per hectare is up to USD 200 higher compared to traditional livestock and USD 26.5 higher than crop farming. While these systems necessitate higher initial investments per hectare, they provide shorter payback periods and increased profitability. Furthermore, it is observed that an ICLF expansion over degraded pasture in Brazil would promote highly positive economic impacts. Approximately 61,000 and 50,000 additional jobs would be generated in the Cerrado and Amazon biomes, respectively. In terms of production value, it would be up to USD 19.7 billion higher in the Cerrado biome and USD 16 billion higher in the Amazon biome compared to traditional livestock farming. These findings reinforce the role of public policies aimed at promoting sustainable agriculture and achieving the targets established in the Brazilian Low-Carbon Agriculture Plan.

Ganapati Kumar Biswas

Financial inclusion is touted one of the principal drivers for economic growth for an economy. The study aims to explore the impact of financial inclusion on economic growth in Bangladesh. In my study, I used the number of loan accounts as the proxy for financial inclusion. Using time series data from spans from 2004-2021, the study revealed that there exists a long-run relationship between GDP, financial inclusion, and other macroeconomic variables in Bangladesh. The study also found that financial inclusion had a positive impact on economic growth of Bangladesh during the study period. Therefore, the policymakers and the central bank of Bangladesh as the apex authority of financial system should promote financial inclusion activities to achieve sustainable economic growth.

Daniel Lu

This paper is an original attempt to understand the foundations of economic reasoning. It endeavors to rigorously define the relationship between subjective interpretations and objective valuations of such interpretations in the context of theoretical economics. This analysis is substantially expanded through a dynamic approach, where the truth of a valuation results in an updated interpretation or changes in the agent's subjective belief regarding the effectiveness of the selected action as well as the objective reality of the effectiveness of all other possible actions (i.e. consequence realization). Complications arise when the economic agent is presented with a set of actions that render ambiguous preference, or when the effectiveness of an action cannot be perceived upon its selection, thereby necessitating a different theory of choice and consequence realization.

Ting Miao, Pathairat Pastpipatkul, Xinhua Liu et al.

This study employs the stochastic frontier model (SFM) to analyze trade potential and efficiency in wheat and maize among Belt and Road Initiative (BRI) countries from 2002 to 2021, encompassing 45 countries for wheat trade and 55 for maize trade. The empirical findings reveal that economic development level, population growth, government efficiency, political stability, and regulatory quality are critical determinants of trade efficiency. Notably, World Trade Organization (WTO) membership exhibits a negative correlation with trade efficiency, potentially reflecting challenges in rule implementation and opportunity utilization among member states. In the context of maize trade, increased arable land area is inversely associated with efficiency, suggesting potential issues in managing large-scale agricultural regions or optimizing land use. The BRI’s impact on trade efficiency varies across countries, with Turkey and Hungary showing improved wheat trade efficiency, while Ethiopia and Georgia experienced declines. During the COVID-19 pandemic, effective disease management strategies and diversified trade mechanisms significantly influenced trade efficiency. Furthermore, the study reveals that larger economies do not necessarily outperform small and medium-sized economies in terms of trade potential. These findings contribute significantly to the literature on agricultural trade and offer valuable insights for policymakers, emphasizing the importance of enhancing government efficiency, political stability, and regulatory quality in the context of regional economic development initiatives such as the BRI. This research underscores the need for tailored approaches to trade policy and agricultural management, considering the unique characteristics and challenges faced by different economies along BRI.

Mahfujul Alam, Mir Meahadi Hasan, Mrinal Kanti Debnath et al.

Papaya fruits different edible and non-edible portions are valued for the abundance of numerous nutrients and therapeutic benefits. The study was aimed to examine the physico-chemical properties, bioactive compounds (total phenolics and total flavonoids), antioxidant activity and microstructure analysis of the peel, pulp and seed flour of both ripe and unripe papaya. The results demonstrated the different portions of both ripe and unripe papaya fruit flour differed significantly with respect to almost all quality attributes within them. The physico-chemical variations have been evaluated through evaluation of the pH, moisture content, TSS, and ascorbic acid content of the papaya fruits during both ripening stages. Statistically significant variations (p < 0.05) were observed between two distinct stages of ripening. The concentration of ascorbic acid in the fruit revealed a notable increase as it matured, while the pH, moisture, and TSS all exhibited a substantial decrease (p < 0.05) during the immature stage. The unripe peel showed the most significant level of bulk density, tapped density, swelling capacity, crude fiber, and TFC whereas the unripe seed showed the highest value of ash, crude fat, and TPC. For the rest of the value, ripe pulp and seed flour showed a significantly higher value than others. The total phenolic content in seed flour and the total flavonoid content of peel flour were 196.9 ± 0.03 and 164.9 ± 0.08 mgQE/100 g, respectively, at unripe conditions. An immense amount of antioxidant activity was found in ripe (20.48 ± 0.54%) and unripe (16.05 ± 0.32%) peels flour. The flour granules' diverse morphological forms and particle sizes were identified by SEM analysis. The versatility of papaya and its various components provides opportunities for applications in the food, pharmaceutical, cosmetic, and agricultural industries. The papaya fruit flour of different portions have unique functional, nutritional, and morphological characteristics that may contribute to the development of gluten free flour based value added baked products.

Mario Vendrell Calatayud, Mario Vendrell Calatayud, Xueqi Li et al.

IntroductionOlive oil is a widely recognized and appreciated food commodity, its quality and health benefits can be compromised when the oil goes through oxidative processes that may occur during production and storage. This study aimed to investigate the effects of the olive genotype on polar phenolic content after seven months of storage.MethodsOil produced from eight different olive cultivars (Leccino, Leccio del Corno, Moraiolo, Frantoio, Bianchera, Pendolino, Maurino, and Caninese) grown in southern Tuscany, Italy, were subjected to chemical analysis such as free fatty acids, peroxide value, K232 and K268, phenolics and UPLC-DAD at the beginning of the trial (Control) and seven months later (Stored).Results and ConclusionsFree fatty acids, peroxide values, K232 and K268, significantly increased, suggesting heightened hydrolysis and oxidation after storage. A cultivar effect was observed, with Leccino, Moraiolo, and Pendolino showing less susceptibility to oxidation (low differences between Control and Stored). In contrast, others (Bianchera and Caninese) are more affected (higher differences between Control and Stored). Phenolics analysis supports this observation, revealing that samples with higher resistance to oxidation exhibit elevated levels of hydroxytyrosol, tyrosol, vanillic acid, caffeic acid, p-coumaric acid, and ferulic acid. Principal Component Analysis highlights that Bianchera and Caninese cultivars correlate with rutin, tyrosol, and pinoresinol. As this research delves into the intricate relationship between genotype diversity, phenolic composition, and oxidative stability, a nuanced understanding emerges, shedding light on how different cultivars may present varying compositions and concentrations of phenols, ultimately influencing the oil’s resistance to the oxidation that occurred during storage.

Ulrike Malmendier

Personal experiences of economic outcomes, from global financial crises to individual-level job losses, can shape individual beliefs, risk attitudes, and choices for years to come. A growing literature on experience effects shows that individuals act as if past outcomes that they experienced were overly likely to occur again, even if they are fully informed about the actual likelihood. This reaction to past experiences is long-lasting though it decays over time as individuals accumulate new experiences. Modern brain science helps understand these processes. Evidence on neural plasticity reveals that personal experiences and learning alter the strength of neural connections and fine-tune the brain structure to those past experiences (“use-dependent brain”). I show that experience effects help understand belief formation and decision-making in a wide range of economic applications, including inflation, home purchases, mortgage choices, and consumption expenditures. I argue that experience-based learning is broadly applicable to economic decision-making and discuss topics for future research in education, health, race, and gender economics.

Eugene Kharitonov, Oksana Zakharchuk, Lin Mei

This study investigates the long-term effects of temperature variations on economic growth using a data-driven approach. Leveraging machine learning techniques, we analyze global land surface temperature data from Berkeley Earth and economic indicators, including GDP and population data, from the World Bank. Our analysis reveals a significant relationship between average temperature and GDP growth, suggesting that climate variations can substantially impact economic performance. This research underscores the importance of incorporating climate factors into economic planning and policymaking, and it demonstrates the utility of machine learning in uncovering complex relationships in climate-economy studies.

Yiting Chen, Tracy Xiao Liu, You Shan et al.

As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT's decisions with utility maximization in classic revealed preference theory. We find that GPT's decisions are largely rational in each domain and demonstrate higher rationality score than those of human subjects in a parallel experiment and in the literature. Moreover, the estimated preference parameters of GPT are slightly different from human subjects and exhibit a lower degree of heterogeneity. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender, but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.

Yuxin Hu

This article presents an analysis of China's economic evolution amidst demographic changes from 1990 to 2050, offering valuable insights for academia and policymakers. It uniquely intertwines various economic theories with empirical data, examining the impact of an aging population, urbanization, and family dynamics on labor, demand, and productivity. The study's novelty lies in its integration of Classical, Neoclassical, and Endogenous Growth theories, alongside models like Barro and Sala-i-Martin, to contextualize China's economic trajectory. It provides a forward-looking perspective, utilizing econometric methods to predict future trends, and suggests practical policy implications. This comprehensive approach sheds light on managing demographic transitions in a global context, making it a significant contribution to the field of demographic economics.

Ishmeet Matharoo

This research paper presents a thorough economic analysis of Bitcoin and its impact. We delve into fundamental principles, and technological evolution into a prominent decentralized digital currency. Analysing Bitcoin's economic dynamics, we explore aspects such as transaction volume, market capitalization, mining activities, and macro trends. Moreover, we investigate Bitcoin's role in economy ecosystem, considering its implications on traditional financial systems, monetary policies, and financial inclusivity. We utilize statistical and analytical tools to assess equilibrium , market behaviour, and economic . Insights from this analysis provide a comprehensive understanding of Bitcoin's economic significance and its transformative potential in shaping the future of global finance. This research contributes to informed decision-making for individuals, institutions, and policymakers navigating the evolving landscape of decentralized finance.

Martina Gažarová, Petra Lenártová, Lucia Struharňanská

Background. Nutri-score is a useful and comprehensible system of extended nutrition labeling of food, which is intended to provide the consumer with simple guidance in choosing food products, taking into account the consumer’s healthy diet. In several countries, in addition to the mandatory nutritional value of food indicated on the product packaging, the use of the so-called food traffic lights, which, based on a simple graphic display, make it easier for consumers to concentrate on choosing healthier food options. Objective. The aim of the work was to evaluate the nutritional composition of gluten-free food products based on the nutritional data indicated on the packaging of these products in order to find out how useful the use of Front-of-Pack labeling (FOPL) Nutri-score will be in distinguishing the nutritional value of products. Material and Methods. We analyzed 206 randomly selected gluten-free food products obtained from commercial retail chains (semi-finished products, other bakery products, biscuits, flour mixtures, porridges, pasta, muesli, snacks, confectionery, etc.) intended for celiacs. Based on the obtained data, we evaluated the composition of the products using a modified algorithm for calculating the Nutri-score. Results. We found that gluten-free products are a very rich source of energy, especially fats, carbohydrates and sugars, while the proportion of fiber and protein is very low. More than one third of the products had a nutritional score of category A or B, which are healthier variants, but over 40% of the analyzed products already fell into categories D or E. We found the lowest average energy value in the case of products classified in category B, the lowest average fat content and saturated fatty acids were found in products labeled A, the highest sugar content was found in products labeled D and E, the highest average protein content in products labeled A. The highest average salt content was found in products labeled C, fiber in products labeled B and A. Conclusions. Nutritional profiling can significantly contribute to several health-beneficial decisions, especially when choosing and buying healthier food options, including gluten-free foods.

Volha Lazuka

This study provides new evidence on how medical care mitigates the economic consequences of health shocks for individuals and their partners. To identify causal effects, I focus on medical scientific discoveries and exploit longitudinal administrative data for Sweden, using a triple differences design. The results indicate that medical innovation strongly mitigates the negative economic consequences of health shocks for individuals and have spillover effects on their partners. These spillovers are relatively large because medical innovation compensates for partners wage losses in conditions when welfare support for caregiving is insufficient. Overall, the findings indicate that medical innovation not only produces substantial economic gains but also reduces disease-related economic inequalities.

REN Fei, LIU Yu-chun, WANG Chao et al.

Two microbial strains Bacillus subtilis HDJ1 and Bacillus velezensis HDJ2 were screened from soybean paste samples by corn gluten meal medium for high protease activity. Single factor fermentation experiment showed that the optimum conditions of liquid fermentation of corn gluten meal for strain HDJ1 were: fermentation temperature of 40 ℃, fermentation pH 8, inoculum of 6%, substrate concentration of 8%, rotating speed of 200 r/min, liquid-adding volume of 40 mL, fermentation time of 72 h; The optimum conditions for liquid fermentation of corn gluten meal for strain HDJ2 were: fermentation temperature of 40 ℃, fermentation pH 6, inoculum of 9%, substrate concentration of 8%, rotating speed of 150 r/min, liquid-adding volume of 120 mL, fermentation time of 72 h; The optimum conditions for the fermentation of corn gluten meal for equal combination of HDJ1 and HDJ2 were: fermentation temperature of 30 ℃, fermentation pH 8, inoculum amount of 6%, substrate concentration of 8%, rotating speed of 250 r/min, liquid-adding volume of 40 mL, fermentation time of 96 h. The results of Orthogonal test showed that the content of soluble protein of HDJ1, HDJ2, HDJ1 and HDJ2 was the highest when the fermentation temperature was 30 ℃, the fermentation pH was 8, the inoculum amount was 3%, the substrate concentration was 8%, therotation speed was 200 r/min, and the fermentation time was 96 h. The protease activity, soluble protein content and DPPH scavenging rate of the sample significantly increased after freeze-drying of the microbial fermentation, and the fermentation effect of the two combined stains was better than that of single strain.

Bambang Nurhadi, Valentyn A. Maidannyk, M. Djali et al.

It is difficult to develop instant coconut sugar and honey powders. Agglomeration could be used to increase the instant properties (physical and functional properties). The objective of this study was to determine the physical and functional properties of coconut sugar powder and honey powder agglomerated with rewetting method using polyvinylpyrrolidone (PVP). PVP concentrations used are 1% and 5% compared to nonagglomerated powder as a control. Agglomeration process using PVP decreased the hygroscopic rate, accelerated dissolving time and wettability, decreased bulk, and tapped densities, which led to improvements in flowability and cohesiveness of powder. Color analysis showed an increase in color intensity for brightness (L*) and redness (a*), but a decrease in the yellowness (b*). The use of 5% PVP resulted in better physical and functional properties of powder than 1% PVP, except for the hygroscopic rate, bulk and tapped densities.

Mónica Katz

Las finalidades del comportamiento alimentario son variadas. Más allá de que todas las funciones básicas requieren nutrientes y energía, comer está al servicio de muchas otras funciones: obtener placer, sociabilizar, regular las emociones, disminuir el nivel de estrés, construir identidad. El determinante primario de la ingesta es el entorno construido representado por un sistema social. Luego, otros subsistemas neurales (como el homeostático energético, el hedónico, el emocional y de regulación del estrés y el de funciones ejecutivas) juntos y redundantemente, organizan y determinan el comportamiento alimentario. Dado que vivimos en una cultura obesogénica en la que las barreras a la saciedad deterioran la auto-regulación de la ingesta calórica, la saciedad es el secreto más anhelado para alcanzar una vida y un peso corporal saludable. En este artículo analizaremos la evidencia científica detrás de las diferentes modalidades de saciedad humana (cognitiva, sensorial, hedónica, mecánica y neuroquímica) desde un modelo biopsicosocial.

Amir Mosavi, Pedram Ghamisi, Yaser Faghan et al.

The popularity of deep reinforcement learning (DRL) methods in economics have been exponentially increased. DRL through a wide range of capabilities from reinforcement learning (RL) and deep learning (DL) for handling sophisticated dynamic business environments offers vast opportunities. DRL is characterized by scalability with the potential to be applied to high-dimensional problems in conjunction with noisy and nonlinear patterns of economic data. In this work, we first consider a brief review of DL, RL, and deep RL methods in diverse applications in economics providing an in-depth insight into the state of the art. Furthermore, the architecture of DRL applied to economic applications is investigated in order to highlight the complexity, robustness, accuracy, performance, computational tasks, risk constraints, and profitability. The survey results indicate that DRL can provide better performance and higher accuracy as compared to the traditional algorithms while facing real economic problems at the presence of risk parameters and the ever-increasing uncertainties.

Arthur Charpentier, Romuald Elie, Carl Remlinger

Reinforcement learning algorithms describe how an agent can learn an optimal action policy in a sequential decision process, through repeated experience. In a given environment, the agent policy provides him some running and terminal rewards. As in online learning, the agent learns sequentially. As in multi-armed bandit problems, when an agent picks an action, he can not infer ex-post the rewards induced by other action choices. In reinforcement learning, his actions have consequences: they influence not only rewards, but also future states of the world. The goal of reinforcement learning is to find an optimal policy -- a mapping from the states of the world to the set of actions, in order to maximize cumulative reward, which is a long term strategy. Exploring might be sub-optimal on a short-term horizon but could lead to optimal long-term ones. Many problems of optimal control, popular in economics for more than forty years, can be expressed in the reinforcement learning framework, and recent advances in computational science, provided in particular by deep learning algorithms, can be used by economists in order to solve complex behavioral problems. In this article, we propose a state-of-the-art of reinforcement learning techniques, and present applications in economics, game theory, operation research and finance.