The empirical literature on the relationship between income inequality and economic growth has produced highly heterogeneous and often conflicting results. This paper investigates the sources of this heterogeneity using a meta-analytic approach that systematically combines and analyzes evidence from relevant studies published between 1994 and 2025. We find an economically small but statistically significant negative average effect of income inequality on subsequent economic growth, together with strong evidence of substantial heterogeneity and selective publication based on statistical significance, but no evidence of systematic directional bias. To explain the observed heterogeneity, we estimate a meta-regression. The results indicate that both real-world characteristics and research design choices shape reported effect sizes. In particular, inequality measured net of taxes and transfers is associated with more negative growth effects, and the adverse impact of inequality is weaker - or even reversed - in high-income economies relative to developing countries. Methodological choices also matter: cross-sectional studies tend to report more negative estimates, while fixed-effects, instrumental-variable, and GMM estimators are associated with more positive estimates in panel settings.
In an emerging pandemic, policymakers need to make important decisions with limited information, for example choosing between a mitigation, suppression or elimination strategy. These strategies may require trade-offs to be made between the health impact of the pandemic and the economic costs of the interventions introduced in response. Mathematical models are a useful tool that can help understand the consequences of alternative policy options on the future dynamics and impact of the epidemic. Most models have focused on direct health impacts, neglecting the economic costs of control measures. Here, we introduce a model framework that captures both health and economic costs. We use this framework to compare the expected aggregate costs of mitigation, suppression and elimination strategies, across a range of different epidemiological and economic parameters. We find that for diseases with low severity, mitigation tends to be the most cost-effective option. For more severe diseases, suppression tends to be most cost effective if the basic reproduction number $R_0$ is relatively low, while elimination tends to be more cost-effective if $R_0$ is high. We use the example of New Zealand's elimination response to the Covid-19 pandemic in 2020 to anchor our framework to a real-world case study. We find that parameter estimates for Covid-19 in New Zealand put it close to or above the threshold at which elimination becomes more cost-effective than mitigation. We conclude that our proposed framework holds promise as a decision-support tool for future pandemic threats, although further work is needed to account for population heterogeneity and other factors relevant to decision-making.
Bitcoin demonstrated the possibility of a financial ledger that operates without the need for a trusted central authority. However, concerns persist regarding its security and considerable energy consumption. We assess the consensus protocols that underpin Bitcoin's functionality, questioning whether they can ensure economically meaningful security while maintaining a permissionless design that allows free entry of operators. We answer this affirmatively by constructing a protocol that guarantees economic security and preserves Bitcoin's permissionless design. This protocol's security does not depend on monetary payments to miners or immense electricity consumption, which our analysis suggests are ineffective. Our framework integrates economic theory with distributed systems theory, and formalizes the role of the protocol's user community.
Meta-analysis employs statistical techniques to synthesize the results of individual studies, providing an estimate of the overall effect size for a specific outcome of interest. The direction and magnitude of this estimate, along with its confidence interval, offer valuable insights into the underlying phenomenon or relationship. As an extension of standard meta-analysis, meta-regression analysis incorporates multiple moderators -- capturing key study characteristics -- into the model to explain heterogeneity in true effect sizes across studies. This study provides a comprehensive overview of meta-analytic procedures tailored to economic research, addressing key challenges such as between-study heterogeneity, publication bias, and effect size dependence. It equips researchers with essential tools and insights to conduct rigorous and informative meta-analyses in economics and related fields.
The role of dogs and cats in the history of the human-animal relationship has been variable. They have served as pets, working animals, useful commensals, subjects of worship and sacrifice, and providers of resources, such as skin and meat. These roles have also been more or less visible in Estonian archaeological material. Here, our focus is on the Middle Ages and Early Modern Period (13th to 18th centuries), which was the time of urbanisation and widening contacts as well as wars and famines. During this time of change, also the roles of dogs and cats as companion and commensal species changed. With over 700 specimens from all over Estonia, we aimed to explore the presence of dogs and cats in archaeological material, their keeping conditions, and their economic use. For dogs, essential questions also involved the different (morpho)types and their possible roles. The study confirmed that new dog types emerged in Estonia from the early 13th century. Furthermore, different site types, specifically castle and urban material, contained dogs with significantly diverse sizes, possibly due to their functionality. There is evidence of the economic value of both cats and dogs in the expression of cut marks that could be related to food waste and fur trading. Stable carbon and nitrogen isotope analysis confirmed the assumption that dogs mainly ate food scraps and leftovers, including freshwater and marine resources. Documented pathologies were rare, leaving the question of caring for or neglecting these animals open.
Many of today's online services provide personalized recommendations to their users. Such recommendations are typically designed to serve certain user needs, e.g., to quickly find relevant content in situations of information overload. Correspondingly, the academic literature in the field largely focuses on the value of recommender systems for the end user. In this context, one underlying assumption is that the improved service that is achieved through the recommendations will in turn positively impact the organization's goals, e.g., in the form of higher customer retention or loyalty. However, in reality, recommender systems can be used to target organizational economic goals more directly by incorporating monetary considerations such as price awareness and profitability aspects into the underlying recommendation models. In this work, we survey the existing literature on what we call Economic Recommender Systems based on a systematic review approach that helped us identify 133 relevant papers. We first categorize existing works along different dimensions and then review the most important technical approaches from the literature. Furthermore, we discuss common methodologies to evaluate such systems and finally outline the limitations of today's research and future directions.
Mohammed Adil Saleem, Faraz Zaidi, Celine Rozenblat
One perspective to view the economic development of cities is through the presence of multinational firms; how subsidiaries of various organizations are set up throughout the globe and how cities are connected to each other through these networks of multinational firms. Analysis of these networks can reveal interesting economical and spatial trends, as well as help us understand the importance of cities in national and regional economic development. This paper aims to study networks of cities formed due to the linkages of multinational firms over a decade (from 2010 to 2019). More specifically we are interested in analyzing the growth and stability of various cities in terms of the connections they form with other cities over time. Our results can be summarized into two key findings: First, we ascertain the central position of several cities due to their economically stable connections; Second, we successfully identify cities that have evolved over the past decade as the presence of multinational firms has increased in these cities.
Objective: In order to provide a comprehensive and coherent view of social turmoil, the purpose of this study was to design a multilevel model of social turmoil and its effect on the observance of behavioral norms in stadiums.Methodology: The research was applied in terms of purpose and mixed in terms of implementation method (qualitative and quantitative). The statistical population of the research in the first part included existing and available research in valid scientific databases in the field of social turmoil and in the second part was the spectators and managers of football clubs in 1398. Sampling was performed by purposive and available methods. The identification of the desired factors was done by meta-combination method and determining the relationships between them with the help of interpretive structural modeling.Results: The results showed social turmoil at four social levels (global developments and cultural transition, lack of justice in resource distribution, culture industry and lack of agreement on the fundamental values of society), organizational level (base incompatibilities, functional inconsistency of community institutions, non-legislative Necessary and weak (lack of necessary structures), group (ethnicity and sports teams, politicians entering the field of sports, informal groups) and individual level (personal characteristics, family history, lack of self-management, internal and external motivation, economic poverty) was classified. The results also showed that there is a statistically significant inverse relationship between the two variables of feeling social turmoil and the degree of observance of spectator behavioral normsConclusion: Managers of clubs and stadiums should consider legal facilities for sports spectators as good citizens. The People's Police should be formed by the fan club from among the spectators and the necessary preparations should be made for each match by the officials, and they should make careful and appropriate plans before the match in accordance with the rules and standards.Considering the results of the research which showed that the more control and the possibility of punishment for the norm-breakers, the more the development of the principles of fair play increases and the more the beauty of the sport and its enjoyment, so it is suggested that Sports clubs should be organized in a systematic manner and have a serious and effective participation in the development of a moral charter in accordance with the cultural conditions of Iranian society. It is also suggested that spectator rights in sports environments, both before and during competitions, in which the behavioral, verbal and behavioral indicators of officials and police with spectators are precisely defined and to train it through training sessions. Hold public events and workshops. It is suggested that during a systematic and continuous process, good and law-abiding spectators be identified and encouraged through the fan club, and that the managers of clubs and stadiums consider facilities for sports spectators as good citizens according to the law. It is suggested that the People's Police be formed by the fan club from among the spectators and that the necessary preparations be made for each match by the officials, and that they make careful and appropriate plans before the match in accordance with the rules and standards. Win-lose thoughts are not encouraged as much as possible by coaches, managers and players, and the nature of sports participation and enjoyment of the match is promoted.
En los artículos Initial and final finance in the monetary circuit and the effective demand theory (2016), y Endogenous money and the theory of long period effective demand (2020), este último escrito con Stefano di Buccianico, el economista Sergio Cesaratto propone un marco interpretativo para integrar algunos de los elementos de la teoría de la demanda agregada y la teoría monetaria heterodoxa en un solo cuerpo teórico coherente. El objetivo de este texto es presentar de la forma más clara y esquemática posible la propuesta teórica de Sergio Cesaratto, teniendo en cuenta la escaza difusión de las teorías pos-keynesianas en español, y la importancia teórica y analítica para la comprensión del funcionamiento del actual sistema económico capitalista.
Economic history and conditions, Economics as a science
Since its emergence around 2010, deep learning has rapidly become the most important technique in Artificial Intelligence (AI), producing an array of scientific firsts in areas as diverse as protein folding, drug discovery, integrated chip design, and weather prediction. As more scientists and engineers adopt deep learning, it is important to consider what effect widespread deployment would have on scientific progress and, ultimately, economic growth. We assess this impact by estimating the idea production function for AI in two computer vision tasks that are considered key test-beds for deep learning and show that AI idea production is notably more capital-intensive than traditional R&D. Because increasing the capital-intensity of R&D accelerates the investments that make scientists and engineers more productive, our work suggests that AI-augmented R&D has the potential to speed up technological change and economic growth.
Since Reform and Opening-up 40 years ago, China has made remarkable achievements in economic fields. And consumption activities, including household consumption, have played an important role in it. Consumer activity is the end of economic activity, because the ultimate aim of other economic activities is to meet consumer demand; consumer activity is the starting point of economic activity, because consumption can drive economic and social development. This paper selects the economic data of more than 40 years since Reform and Opening-up, and establishes the Vector Autoregressive (VAR) model and Vector Error Correction (VEC) model, analyzing the influence of consumption level and total consumption of urban and rural residents on economic growth. The conclusion is that the increase of urban consumption and rural consumption can lead to the increase of GDP, and in the long run, urban consumption can promote economic growth more than rural consumption. According to this conclusion, we analyze the reasons and puts forward some policy suggestions.
Utilization of marginal land for growing dedicated bioenergy crops for second-generation biofuels is appealing to avoid conflicts with food production. This study develops a novel framework to quantify marginal land for the Contiguous United States (CONUS) based on a history of satellite-observed land use change (LUC) over the 2008-2015 period. Frequent LUC between crop and noncrop is assumed to be an indicator of economically marginal land; this land is also likely to have a lower opportunity cost of conversion from food crop to bioenergy crop production. We first present an approach to identify cropland in transition using the time series of Cropland Data Layer (CDL) land cover product and determine the amount of land that can be considered marginal with a high degree of confidence vs with uncertainty across the CONUS. We find that the biophysical characteristics of this land and its productivity and environmental vulnerability vary across the land and lie in between that of permanent cropland and permanent natural vegetation/bare areas; this land also has relatively low intrinsic value and agricultural profit but a high financial burden and economic risk. We find that the total area of marginal land with confidence vs with uncertainty is 10.2 and 58.4 million hectares, respectively, and mainly located along the 100th meridian. Only a portion of this marginal land (1.4-2.2 million hectares with confidence and 14.8-19.4 million hectares with uncertainty) is in the rainfed region and not in crop production and, thus, suitable for producing energy crops without diverting land from food crops in 2016. These estimates are much smaller than the estimates obtained by previous studies, which consider all biophysically low-quality land to be marginal without considering economical marginality. The estimate of marginal land for bioenergy crops obtained in this study is an indicator of the availability of economically marginal land that is suitable for bioenergy crop production; whether this land is actually converted to bioenergy crops will depend on the market conditions. We note the inability to conduct field-level validation of cropland in transition and leave it to future advances in technology to ground-truth land use change and its relationship to economically marginal land.
Abstract Globalisation has lost considerable speed in the last decade. World trade grew more slowly than world production in the 2010s. Protectionist tendencies are slowing down world trade, even if multilateralism has regained support in the post-Trump presidency era. The coronavirus pandemic and supply bottlenecks have also thrown sand into the gears of globalisation. Only international trade in services is still showing robust growth. Germany’s close economic ties with the world also mean that disruptions in supply chains or slumps in demand during pandemics are to be viewed extremely negatively and appropriate strategies for global health security should be pursued.
Economic theory. Demography, Social history and conditions. Social problems. Social reform
In this paper, we assess the drivers of office rental prices in the municipality of Madrid with a sample of 4,721 offices in March, 2020. The estimation was performed using the decision tree approach, which was built with a random forest algorithm. This technique allows us to capture the strong nonlinear component in the relation between price and its drivers, mainly geospatial location. Through a stratified analysis, we find that the willingness to pay high rent in the center of Madrid is a feature of particular relevance to medium-sized offices. For different reasons, we also find some office clusters located far from the city center with high rent for both large and small offices.
Economic growth, development, planning, Economic history and conditions
BackgroundRoad traffic injury is one of the persistent public health challenges in most regions of the world, representing substantial human and economic losses. Annually, about 1.25 million lives are lost, whereas 50 million suffer from road traffic injuries globally. It has been shown that over 60% of the reasons for traffic injuries are a risky driving behavior (RDB). Despite the problem’s pervasiveness, there is a paucity of information about level and factors influencing RDB among professional car drivers in Bahirdar city, northwest Ethiopia.MethodsAn institution-based cross-sectional study was conducted from February to March 2016. A systematic random sampling technique was used to select 376 participants. A self-administered driver behavior questionnaire (DBQ) was used for data collection. We performed a binary logistic regression analysis to investigate the associations of variables. Potential confounders were controlled using a multivariable logistic regression model. We ascertained the significance at < 0.05 p value and evaluated strength of associations using crude odds ratios (COR) and adjusted odds ratios (AOR) with 95% confidence intervals (CI).ResultsA total of 361 drivers participated (response rate, 96%). The mean age was 34 (standard deviations ± 7.97) years. The majority, 98.9% (N = 357), were males. The level of risky driving behavior and road traffic crashes were 79.4% (95% CI 75.92, 83.97) and 16.3% (95% CI 15.91, 24.84), respectively. Average monthly salary [AOR 2.04; 95% CI (1.23, 2.74)], driving experience [AOR 2.72; 95% CI (1.07, 6.89)], distance driven per year [AOR 2.06; 95% CI (1.13, 4.10)], and previous history of involvement in traffic crashes [AOR 2.30; 95% CI (1.15, 7.35)] were significantly associated with risky driving behavior.ConclusionsThe study shows that risky driving behavior is common among professional car drivers in the study setting. Therefore, it is strongly advisable for policy makers and other stake holders to devise strategies that consider working conditions, like monthly salary and driving experiences. The study also suggests that it is often advisable to reduce the distance driven per year and learn from implications of previous history of involvement in traffic crashes.
Resumo Há uma grande controvérsia na literatura econômica brasileira a respeito da hipótese de desindustrialização do Brasil. Os diferentes diagnósticos se devem às distintas definições do processo e aos critérios de análise. O presente estudo irá abordar o tema tanto a partir da definição clássica, utilizada no trabalho seminal de Rowthorn e Wells (1987), como por três conceitos alternativos: i) a desindustrialização prematura; ii) a “visão de Cambridge” e iii) a Mudança Estrutural no interior da indústria de transformação. Os resultados analisados mostram que a desindustrialização brasileira é mais intensa quando analisada pelas abordagens alternativas, pois esse processo ocorre em um nível de produtividade agregado inferior à desindustrialização dos países avançados, a estrutura produtiva da indústria de transformação está se especializando regressivamente, ampliando sua participação em setores de menor produtividade e tem apresentado saldo comercial deficitário a partir de 2008.
Economic history and conditions, Economics as a science
El desarrollo de nuevas tecnologías que permiten distintos niveles de autonomía con respecto al trabajo humano aparenta mostrar una renovación significativa en los últimos años. Aun cuando los procesos de automatización y reestructuración no son una novedad en el capitalismo mundial, las innovaciones digitales y ciberfísicas han signado la dimensión más dinámica e innovadora desde los años ‘80. Esta nueva fase promete ser radicalmente diferente y abarcar un dominio mucho más amplio de problemas. Por medio del análisis de la bibliografía más relevante referida a esta temática, este trabajo se propone contribuir a los debates que giran en torno a cuáles son las aplicaciones (y limitaciones) concretas de estas nuevas tecnologías, sus vínculos con la reestructuración productiva y el impacto sobre el mundo del trabajo
Economic history and conditions, Economics as a science