American Journal of Economics and Sociology最新文献

The proceeding investigates the ineffectiveness of law enforcement placement in specific circumstances from the penological framework of rational choice theory. This work employs game theory modeling to determine an individual's propensity to commit a crime. The succeeding illustrates how it is counterproductive to nudge potential criminals where socially preferable behavior corresponds to a pure strategy Nash equilibrium in a simultaneous two-player game. The result of this analysis demonstrates an addendum to contemporary rational choice theory in criminology. The solutions of these stage games show that increasing the placement of criminal deterrents, like surveillance or fines intended to reduce the number of opportunities to commit deviant behavior, is dysfunctional under particular circumstances. This suggests that law enforcement resources should not be directed to enforcing certain crimes. The implications of this work could help optimize department assets and personnel hours.

This paper examines the impact of exchange rate changes on cultural services trade balances in China, Japan, the United States, United Kingdom, France, and Germany from 2006 to 2015. These six countries represent dominant players whose experiences reflect global impacts. Autoregressive distributed lag (ARDL) models test for J-curve effects. Cultural distance matrices combined with cluster analysis explore how cultural proximity influences trade structures. Results demonstrate a J-curve effect in China contrasting with a reverse J-curve in the United States. China and Japan form one cultural trade cluster distinct from a Western bloc of the United States, United Kingdom, and France. This signifies emerging economies have developed unique cultural trade models. The research enriches empirical evidence on exchange rate impacts for understudied cultural services trade. Introducing cultural distance provides a novel perspective and policy insights for emerging economies.

The rapid digitalization of jobs in the United States and globally provides both an economic opportunity and a challenge for upskilling and reskilling the workforce. Retraining and reintegrating displaced or at-risk workers, particularly in a competitive labor market, brings significant economic benefits to communities, employers, and employees. Individuals in at-risk or declining occupations likely lack requisite digital literacy and associated skills that enable them to transition smoothly into roles that require digital proficiency. Drawing from research indicating the rapid digitalization of the U.S. economy and workforce, this study employs skillshed analysis to examine a sample of vulnerable occupations within coal-related industries. The goal is to evaluate training gaps and wage differentials for individuals shifting from coal-related occupations to roles requiring higher levels of digital literacy. Providing quality reemployment options for coal-economy workers reduces the barriers to transitioning to more sustainable energy provision, yet prior studies have found that coal-economy workers possess lower levels of digital literacy. Our study reaffirms these prior findings that many coal economy workers lack the requisite knowledge, training, and educational attainment to easily transition to occupations requiring high degrees of digitalization. As a result, to be successful in retraining and upskilling those in coal-related occupations and to meet sustainable development goals, it is necessary to assist these workers in their transition into viable occupations.

Labor faces a universal process of increasing exploitation as the following processes converge: Labor is increasingly divorced from a community purpose; the community's economy becomes privatized, which leads to debt bondage and the loss of personal land or availability of land for personal use. This process is repeated from early records of 10,000 BC to the present day. In ancient times, a wise ruler would respond to widespread debt bondage by canceling private debts for the sake of the community. However, there are now no wise rulers on the horizon to cancel debts. This paper may give those who labor, inspiration to continue their struggle for wealth distribution equity.

The recent prevalence of digital currencies has challenged policymakers as they try to control the supply of money and rein in clandestine activities. Corruption and shadow economy are widely prevalent illegal/unobserved activities that have been hard to eliminate worldwide. These longstanding and entrenched activities have possibly found a new avenue to thrive and evade detection/punishment. So disentangling the nexus between corruption, shadow economy, and digital currencies is important. Using recent cross-country data, this paper analyzes the interrelationships between corruption, shadow economy, and cryptocurrencies. We argue that a large underground sector in a nation provides a mechanism through which corrupt government officials use cryptocurrencies to conceal their unauthorized earnings. Employing formal mediation analysis, our results show that the positive nexus between corruption and cryptocurrency adoption is mediated by the shadow sector. Quantitatively speaking, three-fourths of the correlation between corruption and cryptocurrency usage is mediated by the shadow economy. The primary implication of our findings is that effective monitoring of cryptocurrencies should pay attention to policies to control both corruption and the shadow economy.

AI advancements are poised to substantially modify human abilities in the foreseeable future. They include the integration of Brain–Computer Interfaces (BCIs) to augment cognitive functions, the application of gene editing, and the utilization of AI-powered robotic exoskeletons to enhance physical strength. This study employs a comprehensive analytical framework combining factor analysis, clustering, ANOVA, and logistic regression to investigate public attitudes toward these transformative technologies. Our findings reveal three distinct clusters of public opinion reflecting varying optimism and concern toward AI technologies. Cluster 1 (1574 participants) held a positive view with high excitement while Cluster 2 (1334 participants) showed a balanced stance. Cluster 3 (2199 participants) expressed heightened concern despite some excitement. Notably, regional disparities, particularly between urban and rural participants, emerge as a prominent factor influencing these attitudes (ANOVA, F = 15.2, p < 0.001). Furthermore, logistic regression identifies key influencers of public perception, highlighting the significant roles played by religion and regional factors. The implications of these findings extend beyond understanding public sentiment. They underscore the need for informed policies that promote education and awareness about AI technologies, address ethical concerns, and engage the public in decision-making processes. As society navigates this transformative technological landscape, a nuanced understanding of public attitudes becomes paramount, guiding ethical regulation, innovation, and public engagement strategies. This study provides valuable insights into the intricate dynamics surrounding AI acceptance and highlights the importance of adapting measures to evolving perceptions and attitudes among the general public.

The article discusses the political-economy of agribusiness, making use of the category of rent that is considered as a proportion of exchange value diverted from production for the payment to the landowners and, crucially, its class-based allies. Rent is therefore more than just the extraction of value from the use of land, but there is a wider, deeply politicised capture of value from the network of relations that maintain land in production. Agribusiness rent primarily derives from the appropriation of land through the formation of a powerful network involving ‘state-landowners-private agroindustrial sector’, and this network provides the necessary conditions for the extraction of rent and the accumulation of capital.

This research investigates which individuals are aware of and claim the federal adoption tax credit. Using a probit model, I find that the probability that one claims the credit increases with one's income and is lower for Black adoptive parents compared to White ones. These discrepancies in usage stem from different probabilities of knowing about the credit. However, conditional on awareness, I find that the probability of claiming the credit is no different among members of differing income or racial groups, implying that a direct way to increase take-up of the tax credit could simply be increasing awareness of it.

Throughout the recent pandemic, governments used digital video technologies to facilitate social distancing during political meetings. In addition to enabling social distancing, a theoretical advantage of virtual political governance is that it has the potential to mitigate the hierarchical administrative relationship between capitals and regions and the differences in real estate prices and wealth that often follows from such hierarchical structures. However, hardly any governments are currently planning a long-term transition to work-from-home digital governance. On the contrary, several countries are doubling down on the centralization model of government by building new capitals in new locations. This article proposes that in a time of digital alternatives, physically centralized “capitals” could be considered examples of bad equilibrium.