I am most grateful to the editors of the British Journal of Sociology for putting together such an impressive set of review papers about my book. I am very honoured by the very thoughtful essays written by such a distinguished group of scholars coming from sociology, political science, anthropology, history, geography and economics. I warmly thank all participants for their time and attention to my work. I would like to view my book more as work of social science than one of economics or history. It seems to me that we often loose a lot of time in the social sciences because of little disputes about disciplinary boundaries. I could not dream of a better recognition for my work than the stimulating collection of interdisciplinary essays that the British Journal of Sociology is now publishing. I am very fortunate to have so many great readers. There is no way I can do justice to the richness of each review and address the many stimulating points that they raise. I would like however to take this opportunity to briefly clarify a number of issues.
BackgroundCompared to common rice, soft rice is characterized by low amylose content, soft and elastic texture, and low retrogradation of cold rice. However, the differences of quality deteriorate during aging between soft rice and common rice are still unclear.MethodsIn this study, representative soft rice varieties (NJ9108 and NJ46) were chosen as research subjects, and YJ7081 and HD5 were chosen as control. The changes of their components and quality during aging were comprehensively investigated.ResultsDuring aging, the total starch, fat, and protein content of soft rice decrease, while the amylose content increases. The short-range ordered structure of soft rice starch and the secondary structure of proteins gradually degrade with the extension of aging time. In addition, the relative crystallinity of soft rice starch gradually decreases during the aging process. After aging for 24 M, the average taste value of soft rice decreased by 14.86, and the average 2-AP content decreased by 167.82 ng/g. The average taste value of common rice decreased by 12.52, and the average 2-AP content decreased by 140.42 ng/g.ConclusionCompared to common rice, the component contents and the starch short-range ordered structure characteristics of soft rice exhibited more pronounced changes, leading to increased deterioration of cooking, eating, and aroma qualities during aging.
This study investigates the impact of Foreign Direct Investment (FDI) on economic growth in South Asian countries, utilizing annual panel data from five SAARC member states (Bangladesh, India, Nepal, Pakistan, and Sri Lanka) over the period 1980-2017. Data sourced from the World Development Indicators and Penn World Table were analyzed using static panel models, including Ordinary Least Squares, Fixed Effects, Random Effects, and Generalized Least Squares regressions. The empirical findings reveal that FDI exhibits a consistently positive but statistically insignificant correlation with economic growth across all model specifications. In contrast, domestic investment and human capital development emerge as significant and robust positive determinants of growth. Control variables such as government consumption and inflation show expected negative, though generally insignificant, associations with growth. The results imply that for the sampled South Asian economies, enhancing domestic investment and fostering human capital are more critical for driving economic expansion than relying on FDI inflows. Consequently, policymakers should prioritize strategies that strengthen local investment climates and improve educational and skill-building institutions to boost productivity. While FDI's role remains complementary, its insignificant immediate impact suggests the need for further research into the conditional factors such as institutional quality, financial market development, and trade policies that might mediate its effectiveness in fostering long-term growth within the region.
This paper explores the application of Hidden Markov Models (HMM) and Long Short-Term Memory (LSTM) neural networks for economic forecasting, focusing on predicting CPI inflation rates. The study explores a new approach that integrates HMM-derived hidden states and means as additional features for LSTM modeling, aiming to enhance the interpretability and predictive performance of the models. The research begins with data collection and preprocessing, followed by the implementation of the HMM to identify hidden states representing distinct economic conditions. Subsequently, LSTM models are trained using the original and augmented data sets, allowing for comparative analysis and evaluation. The results demonstrate that incorporating HMM-derived data improves the predictive accuracy of LSTM models, particularly in capturing complex temporal patterns and mitigating the impact of volatile economic conditions. Additionally, the paper discusses the implementation of Integrated Gradients for model interpretability and provides insights into the economic dynamics reflected in the forecasting outcomes.
In a series of papers, Garrett, et al, presents a thermodynamic economic model first laid out in "Are there basic physical constraints on future anthropogenic emissions of carbon dioxide?". This model contains a key conceptual issue that obscures a robust system. This system can link to the Energy Based Cobb-Douglas equation. The key conceptual problem is the belief that $λ$, the symbol for growth in Garrett 2011 would disprove the model if it was not constant. However, $λ$ cannot be a constant in an economic model, because $λ$, with dimension [$\frac{E}{\$ \; GWP}$], represents the aggregate efficiency of all of the more than 359 million firms (and by extension, households) making products globally. To clarify it, I define this aggregate production function distribution as $Λ(t) \equiv \sum {λ_i(t) \cdot \frac{P_i}{GWP}}$, and with light algebra assign a version of the Energy Based Cobb-Douglas (EBDC) function to $λ$. There are various falsified speculations in the body of work that appear to mostly follow from the original issue. The 50 year stable relation of $W$ to $E$ is close, but the trend is not flat. The form and degree to which the "long arm of history" speculation may be true remains to be fully considered, but is falsified in the form presented. The speculation in Garrett 2022 that $\frac{dE}{dt}\rightarrow0$ can cause real GDP to go to zero by inflation is falsified. By generating a dataset going back to -14,000 CE, the speculative $W$ curve appears largely confirmed. The $E$ curve is quite far off prior to 1970 back to 1 CE due to overestimation of pre-industrial energy. By correcting and improving on the foundation issue of Garrett's yeoman effort, improving $E$ and some equation presentation formalism, a robust thermodynamic model of the global economy emerges that is straightforward and practical.
Hausman and McPherson provide an evidential defense of welfare economics, arguing that preferences are not constitutive of welfare but nevertheless provide the best evidence for what promotes welfare. Behavioral economics identifies several ways in which some people's preferences exhibit anomalies that are incoherent or inconsistent with rational choice theory. I argue that the existence of these behavioral anomalies calls into question the evidential defense of welfare economics. The evidential defense does not justify preference purification, or eliminating behavioral anomalies before conducting welfare analysis. But without doing so, the evidential defense yields implausible welfare implications. I discuss how the evidential defense could be modified to accommodate behavioral anomalies.
The article explores the process of creating a large cooperative housing complex in a district of New York. It highlights the unique circumstances that made the cooperative City project possible in the United States. The article also examines the efforts of European countries to foster urban residents’ involvement in urban development. It provides examples of innovative solutions implemented by the population of various European cities. The article delves into the Russian experience of utilizing public initiatives to enhance urban development and improve the quality of life. It emphasizes that the promotion of cooperation in urban life is supported by both governmental authorities and individual citizens and local communities. The article highlights a new phase in this process — changes in urban planning, with the transition from general to master plans becoming part of federal policy.
The world economy has met the challenges of two crises in the current century: the 2007-2008 financial crisis and the 2020-2021 COVID-19 crisis. Crises inflict enormous damage on markets, destroy supply chains, change business activity, cause collapse in important consumer categories, etc. But crises are an accelerator of processes and create many opportunities: new markets and chains of added value, new options for growth, business restructuring, changing the business model, optimizing cash flows, etc. This report presents the results of an empirical study on the impact of the COVID crisis on the economy of public industrial companies. Four quantitative and qualitative economic indicators are used. The performance of different groups of companies during the crisis is compared. Trends have been revealed, conclusions have been drawn and recommendations for using the opportunities have been formed.
This study explores various feature selection techniques applied to macro-economic forecasting, using Iran's World Bank Development Indicators. Employing a comprehensive evaluation framework that includes Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) within a 10-fold cross-validation setup, this research systematically analyzes and ranks different feature selection methodologies. The study distinctly highlights the efficiency of Stepwise Selection, Tree-based methods, Hausdorff distance, Euclidean distance, and Mutual Information (MI) Score, noting their superior performance in reducing predictive errors. In contrast, methods like Recursive Feature Elimination with Cross-Validation (RFECV) and Variance Thresholding showed relatively lower effectiveness. The results underline the robustness of similarity-based approaches, particularly Hausdorff and Euclidean distances, which consistently performed well across various datasets, achieving an average rank of 9.125 out of a range of tested methods. This paper provides crucial insights into the effectiveness of different feature selection methods, offering significant implications for enhancing the predictive accuracy of models used in economic analysis and planning. The findings advocate for the prioritization of stepwise and tree-based methods alongside similarity-based techniques for researchers and practitioners working with complex economic datasets.
Simone Brusatin, Tommaso Padoan, Andrea Coletta
et al.
Agent-based models (ABMs) are simulation models used in economics to overcome some of the limitations of traditional frameworks based on general equilibrium assumptions. However, agents within an ABM follow predetermined 'bounded rational' behavioural rules which can be cumbersome to design and difficult to justify. Here we leverage multi-agent reinforcement learning (RL) to expand the capabilities of ABMs with the introduction of 'fully rational' agents that learn their policy by interacting with the environment and maximising a reward function. Specifically, we propose a 'Rational macro ABM' (R-MABM) framework by extending a paradigmatic macro ABM from the economic literature. We show that gradually substituting ABM firms in the model with RL agents, trained to maximise profits, allows for studying the impact of rationality on the economy. We find that RL agents spontaneously learn three distinct strategies for maximising profits, with the optimal strategy depending on the level of market competition and rationality. We also find that RL agents with independent policies, and without the ability to communicate with each other, spontaneously learn to segregate into different strategic groups, thus increasing market power and overall profits. Finally, we find that a higher number of rational (RL) agents in the economy always improves the macroeconomic environment as measured by total output. Depending on the specific rational policy, this can come at the cost of higher instability. Our R-MABM framework allows for stable multi-agent learning, is available in open source, and represents a principled and robust direction to extend economic simulators.
Kunio Miyake, Sayaka Horiuchi, Ryoji Shinohara
et al.
BackgroundAnimal studies have shown that maternal low-fiber diets during pregnancy may impair brain development and function in offspring, but this has not been validated by epidemiological studies. The aim of this study was to investigate the link between maternal dietary fiber intake during pregnancy and neurodevelopmental delay in offspring using a large birth cohort.MethodsA total of 76,207 mother-infant pairs were analyzed using data from the Japan Environment and Children's Study, a nationwide prospective cohort study. Maternal dietary fiber intake was estimated using the food frequency questionnaire in mid-pregnancy. Maternal dietary fiber intake was adjusted for energy and classified into quintiles. Developmental delay was assessed in five domains using the Japanese version of the Ages and Stages Questionnaire, Third Edition at the age of 3 years. The logistic regression analysis was performed to estimate the odds ratio (OR) and 95% confidence interval (CI) for the link between dietary fiber intake during pregnancy and developmental delay at the age of 3 years.ResultsThe lowest intake group of total dietary fiber had a higher risk of delayed communication [adjusted OR (aOR), 1.51; 95% CI, 1.32–1.74], fine motor (aOR, 1.45; 95% CI, 1.32–1.61), problem-solving (aOR, 1.46; 95% CI, 1.32–1.61), and personal-social skills (aOR, 1.30; 95% CI, 1.12–1.50) than did the highest intake group. An analysis that excluded the effects of insufficient folic acid intake during pregnancy also showed a similar trend.ConclusionThis study showed that maternal dietary fiber deficiency during pregnancy might influence an increased risk of neurodevelopmental delay in offspring.
У статті проаналізовано сучасний стан інвестиційної діяльності в Україні, розглянуто вітчизняний та міжнародний аспекти її ведення, визначено головні проблеми забезпечення високого рівня інвестиційної привабливості національної економіки в контексті реалій сьогодення. Проведено комплексний аналіз факторів формування інвестиційного потенціалу та інвестиційних ризиків на макрорівні, об’єму залучення інвестиційного капіталу в національну економіку, основних перешкод та ризиків низької інвестиційної активності в Україні на сучасному етапі. Визначено динаміку змін показника валового внутрішнього продукту та обсягу капітальних інвестицій в економіку України, запропоновано ключові напрями державної політики щодо активізації процесу залучення інвестицій в національну економіку.
Marco Gortan, Lorenzo Testa, Giorgio Fagiolo
et al.
Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activity is becoming increasingly common in environmental and economic research. We process available information from different climate data sources to provide spatially aggregated data with global coverage for both countries (GADM0 resolution) and regions (GADM1 resolution) and for a variety of climate indicators (average precipitations, average temperatures, average SPEI). We weigh gridded climate data by population density or by night light intensity -- both proxies of economic activity -- before aggregation. Climate variables are measured daily, monthly, and annually, covering (depending on the data source) a time window from 1900 (at the earliest) to 2023. We pipeline all the preprocessing procedures in a unified framework, which we share in the open-access Weighted Climate Data Repository web app. Finally, we validate our data through a systematic comparison with those employed in leading climate impact studies.
Emiliya Bobovnikova, Kirill Vorobev, Danil Zhikharev
et al.
The study examines the targeting of scheduled and surprise inspections of school food services conducted by Rospotrebnadzor. Using reports of cases of mass poisoning from open sources and official inspection data, we look at the association between inspections and mass poisoning incidents in Russian schools. We find that schools are the most audited organizations among all areas of economic activity. Schools bear a significant part of the regulatory burden, contrary to the popular belief that the business actors are the most audited. However, we do not find any changes in the organization of inspections after food poisoning incidents. We also outline the limitations of the risk-based approach in educational institutions.