With the reversal of Roe v. Wade in 2022, many U.S. employers announced they would reimburse employees for abortion-related travel expenses. This action complements increasingly common employer policies subsidizing employee access to assisted reproductive technologies such as in-vitro fertilization and egg freezing. This article reflects on why employers offer these benefits and whether they enhance or undermine reproductive justice. From the employer's perspective, abortion and assisted reproductive technologies help women to plan childbearing around the demands of their jobs. Both are associated with delayed childbirth and reduced fertility, which lower the costs of motherhood to employers. However, firm subsidization of these services does not further reproductive justice because it reifies structures which incentivize women to delay childbirth and reduce fertility, and it reinforces economic and reproductive inequalities. We conclude by questioning whether reproductive justice is possible without transforming the economy so that it prioritizes care over profits.
ABSTRACT This editorial introduces the seven papers included in this issue of Spatial Economic Analysis (SEA). The papers analyse two important topics in spatial economics. The first addresses the spillovers between units in space, specifically the phenomena through which different locations interact and the multiple channels through which these interactions take place. The second topic is related to the obtainment and processing of information at small spatial scales. The topics that are covered in the first theme are hence how distance influences venture capital (VC) investment decisions; the role of various proximities in innovation and regional knowledge production functions; the effects on local labour markets caused by what happens in other markets nearby; the use of different types of proximities and different distances at the same time in estimating spatial autoregressive model with autoregressive disturbances (SARAR) models. On the second topic the issue covers a new two-step technique to estimate small spatial scale synthetic data from microdata and aggregate statistics as an alternative to spatial microsimulation; the use of satellite data to estimate consumer confidence and expectations; and the use of disaggregated general equilibrium modelling based on the partial hypothetical extraction approach in input–output systems to estimate the effects of emergency aid.
Bahram Adrangi, Arjun Chatrath, Saman Hatamerad
et al.
This study investigates the relationship between the market volatility of the iShares Asia 50 ETF (AIA) and economic and market sentiment indicators from the United States, China, and globally during periods of economic uncertainty. Specifically, it examines the association between AIA volatility and key indicators such as the US Economic Uncertainty Index (ECU), the US Economic Policy Uncertainty Index (EPU), China's Economic Policy Uncertainty Index (EPUCH), the Global Economic Policy Uncertainty Index (GEPU), and the Chicago Board Options Exchange's Volatility Index (VIX), spanning the years 2007 to 2023. Employing methodologies such as the two-covariate GARCH-MIDAS model, regime-switching Markov Chain (MSR), and quantile regressions (QR), the study explores the regime-dependent dynamics between AIA volatility and economic/market sentiment, taking into account investors' sensitivity to market uncertainties across different regimes. The findings reveal that the relationship between realized volatility and sentiment varies significantly between high- and low-volatility regimes, reflecting differences in investors' responses to market uncertainties under these conditions. Additionally, a weak association is observed between short-term volatility and economic/market sentiment indicators, suggesting that these indicators may have limited predictive power, especially during high-volatility regimes. The QR results further demonstrate the robustness of MSR estimates across most quantiles. Overall, the study provides valuable insights into the complex interplay between market volatility and economic/market sentiment, offering practical implications for investors and policymakers.
Although empirical literature regarding the Phillips curve is sizeable enough, there is still no wide consensus on its validity and stability. The literature shows that the Phillips relationship is fragile and varies across countries and time periods; a statistical relationship that appears strong during one decade (country) may be weak the next (other). This variability might have some grounds for idiosyncrasy of a country and its economic environment. To address it, this paper scrutinizes the Phillips relationship over 41 countries over the period 1980-2016, paying attention to how inflation dynamics behave during tranquil and recessionary periods. As a result, the paper confirms the variability of the Phillips relationship across countries, as well as time periods. It documents that the relationship holds in the majority of developed countries, while it fails to hold in emerging and frontier economies during tranquil periods. On the other hand, the relationship totally collapses during recessionary periods, even in developed markets. This shows that tranquillity of economic environment is significantly important for the Phillip trade-off to work smoothly. Moreover, both backward- and forward-looking fractions of inflation remarkably increase during recessionary periods as a result of the Phillips coefficient loses its significance within the model. This indicates that markets become more inflation-sensitive during these periods.
Relevance. Matching is one of the most effective ways to allocate resources in the absence of a pricing mechanism. The article analyzes the pros and cons of matching in comparison with administrative and market methods. The concept of using matching as a tool of regional economic policy is substantiated. The Kursk region is taken as the object of the study. The statistical base is used to understand the complexity of the problem being solved in the information and digital space when using the Gale-Shapley algorithm and its varieties.The purpose is to substantiate the conditions for the use of matching and, in particular, the Gale‒Shapley algorithm for isomorphism of natural resources, physical and human capital at the regional level.Objectives: adaptation of the concept of "matching" to regional economic policy; assessment of the comparative effectiveness of the application of the concept of "matching" to regional economic problems; identification of industries and areas of activity at the level of the Kursk region with a positive expected net benefit from the introduction of matching.Methodology. The article was prepared within the framework of the methodology developed by Nobel laureates in economics Alvin Roth and Lloyd Shapley.Results. The most promising areas of digitalization, informatization and the introduction of matching mechanisms in the Kursk region are the fields of education and healthcare.Conclusions. The Gale-Shapley algorithm in the conditions of digitalization allows stable equilibria in the process of paired interaction of economic agents. Matching leads to a more effective correspondence between the factors of the first (land, natural resources), second (capital, infrastructure) and third (human capital, people) nature. An optimal economic policy should combine matching tools with traditional mechanisms of state regional regulation – administrative and market mechanisms.
This article explores how staff at the UN Regional Economic Commission for Europe (ECE) tried, with mixed success, to incorporate Soviet knowledge and experts into their activities and how these challenging efforts, paradoxically, created a space in which economics could be a shared language of communication across the Cold War divide, both within UN spaces and in adjacent academic networks. This conceptual move allowed economics knowledge to pool between East and West, even though the divide between the blocs was originally expressed in economic terms. In the 1960s, with the global transformations of decolonisation, the ECE’s experts, including those embedded in British academic networks, worked to export their shared knowledge beyond Europe, using the triangulated international space of the UN to promote – and continue gathering – economic information from the Soviet Union.
This article, drawing on the conceptual and methodological foundations and transformative paradigm of regional and spatial economics, presents scientific provisions reflecting the characteristics and specifics of regional economic policy implemented in regions with agro-industrial specialization. It is demonstrated that the transformative potential of regulatory institutions should be focused on three areas: economic specialization sectors, the specific socio-economic lifestyle of the population, and the specific functioning and development of the economic space of agro-industrial regions. In the context of developing a systematized and improved conceptual and methodological framework for the formation and implementation of regional economic policy for the development of agro-industrial entities, the article formulates the directions, principles, and mechanisms for its implementation. It is argued that the potential of territorial marketing and branding, as well as related tools for the development and support of rural (agricultural) and industrial (industrial) tourism, remains untapped in regional economic policy. To implement the territorial component of regional economic policy, it is proposed to use private-municipal partnership projects to exploit agro-industrial potential. This article is useful for researchers studying regional economic issues, as well as specialists working on applied management of regional economic policy implementation.
ABSTRACT Space has always been essential within the economy, yet its importance in economics has been downplayed in several ways. This editorial introduces the seven papers comprising this issue of Spatial Economic Analysis (SEA) and shows that while the classics of economics acknowledged the importance of the location of economic activities, for many years the study of space was left to heterodox economics scholars and geographers. This is despite the established tradition of learned societies, such as Regional Science International and the Regional Studies Association, which are placed at the intersection of these fields. Space finally became mainstream in economics again due, on the one hand, to the introduction of the new economic geography some 30 years ago and, on the other, to the fact that several different economic sub-disciplines have come to understand and consider space as essential for the processes they study. This was facilitated by methodological advancements, such as in spatial econometrics. The seven papers in this issue henceforth illustrate some of the situations and approaches which make space relevant to contemporary economic questions. Essential are, in particular, the interactions between different locations and the interactions between individuals and geographical features.
Christina Hellgren, Johan Hellgren, Behnosh Öhrnell Malekzadeh
Objective Deep neck space infections (DNSI), caused by the spread of an odontogenic infection to the floor of the mouth and neck, are potentially life-threatening but preventable. We explored the total cost of illness (COI) for patients with DNSI of odontogenic origin. Material and methods Cross-sectional, register-based, multi-centre study of the health economics of DNSI treatment. Included were patients aged > 18 years who were treated in hospital for DNSI of odontogenic origin. Subjects were identified from the regional healthcare database VEGA based on the International Classification of Diseases (ICD) codes and surgical procedure codes. The cost per patient (CPP) values for the hospital care, prescription medications and sick leave were extracted. Results In total, 148 patients were included. The average length of the hospital stay was 6 days. Total COI was estimated as 15,400 EUR per patient and 2,280,000 EUR in total. Direct costs accounted for 93% of the COI, and indirect costs were 7%. Conclusion The total COI for patients with DNSI of odontogenic origin was six-fold higher than the average COI for patients in otorhinolaryngology (ORL) care. Preventing DNSI will entail substantial cost savings for the specialised healthcare units and will have a significant impact on the patients.
This paper explores how remote and hybrid work modes are changing the US real estate market in the wake of the pandemic. The research shows that there is a clear segmentation of the market. Specific industries such as technology, finance and professional services requiring high-end office space to support their operations and brand image. Retail, healthcare and manufacturing all have a high demand for physical space due to their specific industry characteristics. This creates regional differences, with high-demand areas able to thrive while others struggle. Futhermore, the paper suggests the implementation of rental subsidies targeted at physical sectors such as retail and dining. This is a benefitial way to increase the demand for real estate and reduce the tax burden on local governments. Additionally, it recommends the repurposing of unused real estate for public services which would drive economic growth. Overall this would increase economic stability and support a more balanced real estate market.
Cities are the frontiers of the Sustainable Development Goals (SDGs) adopted in the United Nations 2030 Agenda. Although quantitative methods have been applied to assess cities’ sustainability progress, knowledge gaps exist in the differences between inland and coastal cities’ performance and their internal variations against common standards. Using the Voronoi-based kaleidoscope diagram embedded in two circular plots, the article visualises the overall sustainability progress of China’s inland and coastal cities in economy, society, biosphere and partnership. By measuring overall progress with circular length and individual scores with kaleidoscope area size, triple inland-coastal gaps and trifold intracoastal inequalities were highlighted, as well as city types characterised by economy-society balance and land–sea relation. References for implementing sustainable development transformations for coastal cities were derived, along with the circular-kaleidoscope diagram’s potential for checking the pulse of cities’ performances in further uses and finishing the circle.
Regional economics. Space in economics, Regional planning
A review of economic approaches showed the lack of a universal method for assessing management decisions in the face of an increasing volume of analyzed data and changing parameters of the external environment. The method of integral indicators is proposed. Integral indicators are one of the modern methods for researching the behavior of an enterprise. It provides an assessment of the impact of the external environment. It shows the ability of the enterprise to adapt to new conditions. The dynamics of the correlation indicator shows the reaction of the enterprise to the impact of external factors. The purpose of the scientific work was achieved: the optimal control of the enterprise was carried out in the conditions of changing the parameters of the external environment For this, the model of the economic object and the method of its analysis are formalized. The structure of an economic object (enterprise) is given. The characteristics of the parameters of the external environment are given. The state of an economic object (enterprise) is modeled taking into account the influence of the external environment. With the help of the software package created by the author, six optimal options for control decisions have been analyzed. The state of an economic object has been modeled depending on the state of the external environment by 5,000 parameters. The research showed significant changes in the values of the correlation of the parameters of the system and the intensity of business processes when the conditions for the functioning of the system change. The optimal control of an economic object (enterprise) is selected according to the integral indicator.
Introduction. In this article, the authors analyze the specifics of the criminal liability of minors depending on the scene of crime. The authors cite the current statistics of the Information Center of the Main Directorate of the Ministry of Internal Affairs of Russia in the Sverdlovsk region, which demonstrates the prevalence of crimes against public safety by minors in the territory of the city of Ekaterinburg in comparison with other cities of the Sverdlovsk region. The data obtained made it possible to identify the reasons for committing crimes against public safety in the territory of the city of Ekaterinburg, which, in their opinion, should be taken into account when differentiating and individualizing the criminal liability of the minors. According to the authors, the need to follow a differentiated approach to the criminal liability of minors is a relevant issue, which is expressed in the specifics of punishment imposing, procedure for applying compulsory educational measures, exemption from criminal liability, as well as the calculation of the statute of limitations, taking into account the crime scene. At the same time, the issue of no less importance is the one of executing punishment imposed on minors to achieve the criminal liability goals. Materials and methods. As part of the scientific research, a set of general scientific and private scientific methods was used, including a special legal, statistical, comparative methods and hermeneutics. Results. The authors identify and propose to take into account a number of significant factors affecting the efficiency of the criminal legal system in relation to minors (crime scenes). On this basis, recommendations have been developed, including the ones on changing regulatory framework and the application practice. It is revealed that the approach to differentiation corresponds to global practice, so a number of key principles of criminal responsibility of the minors in foreign legislation are given.
Economic theory. Demography, Regional economics. Space in economics
This is a case study on migration management in the United States of America, according to the New Political Economy approach. Attention is paid to how Latin American immigrants are treated, given the change in public policies and their economic perception. There has been a shift from open-door immigration policies to raids and massive deportations, violating the founding principles of the United States and the key to its growth and development, since immigrants are not only a greater productive factor of work, but also bring knowledge, technologies and institutions that improve the competitiveness. Faced with this change in public powers, civil society has reacted, with a revitalization of the Sanctuary Movement. This study uses an explanatory methodology on the evolution of the academic disciplines and approaches dedicated to the research on religion-economics-migration relations, to focus its attention on the case study of the Sanctuary Movement.
Latin America. Spanish America, Regional economics. Space in economics
This study presents a computational simulation exploring the complex interactions between population density and economic factors over a 100-year period. Inspired by the Keller-Segel model, traditionally applied in biological contexts, my model adapts this framework to analyze urban and economic dynamics. The simulation employs two coupled partial differential equations to represent the evolution of population density and money concentration in a hypothetical region. Population density is initially uniform, while money concentration begins with a random distribution. The model integrates diffusion processes for both population and money, coupled with a chemotactic response of the population towards areas of higher economic activity. Over the course of the simulation, we observe the emergence of distinct spatial patterns: population clusters forming around economic hubs and the development of wealth concentration in certain areas. These patterns highlight the mutual reinforcement between population density and economic factors. The study provides insights into the dynamics of urban growth, economic disparities, and resource distribution, offering a simplified yet powerful lens through which to view complex socio-economic systems. My findings have implications for urban planning and policy-making, especially in understanding the long-term evolution of cities and economic centers.
Pandemics, in addition to affecting the health of populations, can have huge impacts on their social and economic behavior. These factors, on the other hand, have the potential to feed back to and influence the disease spreading. It is important to systematically study these interrelations, to determine which ones have significant effects, and whether the effects are adverse or beneficial. Our recently developed epidemic model with agent-based and geographical elements is used in this study for such a purpose. We perform an extensive parameter space exploration of the socio-economic part of the model, including factors like the attitudes (called values) of the agents towards the disease spreading, health, economic situation, and regulations by government agents. We search for prominent patterns from the resulting simulated data using basic classification tools, namely self-organizing maps and principal component analysis. We seek to isolate the most important value parameters of the population and government agents influencing the disease spreading speed and patterns, and monitor different quantities of the model output, such as infection rates, the propagation speed of the epidemic, economic activity, government regulations, and the compliance of population. Out of these, the ones describing the epidemic spreading were resulting in the most distinctive clustering of the data, and they were selected as the basis of the remaining analysis. We relate the found clusters to three distinct types of disease spreading: wave-like, chaotic, and transitional spreading patterns. The most important value parameter contributing to phase changes between these phases was found to be the compliance of the population agents towards the government regulations. Our thorough mapping of the model parameters confirms our earlier hypotheses. In compliant populations, the infection rates are significantly lower and the infection spreading is slower, while the population agents’ health and economical attitudes show a weaker effect. We have then used a variety of computational classification tools to analyse this vast data: SOM to classify the data, PCA to help visualize the feature vectors used in the SOM classifications, and silhouette numbers to evaluate the quality of the SOM classifications. The feature vectors of our classifications are based on the averages of the four main quantities tracked by the model, which are infection rates, economic activity, government regulations and the popular compliance, and a special β factor we introduced in order to measure the propagation speed of the epidemic. The main motivations of this study is to explore different phases in the behaviour of the model, and transitions between those phases, and to develop computational tools for the future applications of the model to real world situations.
Introduction. The development of the tourist potential of Russian territories is one of the priority state tasks in modern conditions. The purpose of the article is to study the regional specifics of the development of tourism potential in the Russian Federation, a sociological analysis of its key elements in the assessments of municipal leaders.
Materials and Methods. The key research method was a questionnaire survey of heads of local self-government bodies of the Russian Federation (n = 306). At the first stage, questionnaires were sent out by e-mail with representation from all federal districts of the Russian Federation. At the second stage, the analysis of linear distributions and correlation analysis of empirically significant variables (grouping of answers by regions and federal districts of the Russian Federation) were carried out. The use of a set of analytical procedures has made it possible to identify the regional specifics of the development of the tourism potential of the territories. The results were processed using SPSS.
Results. The results of the study have made it possible to identify problems in the development of the tourist potential of Russian territories, both in terms of basic and additional resources. The hypothesis about the predominance of tourist resources aimed at satisfying the “average” consumer demands of the tourist is confirmed. The results of the study have shown a decrease in ratings for economy class catering facilities (average rating 3.02 out of 5), the presence of hostels (1.87 out of 5), as well as the lack of conditions to meet the interests of high-income tourists (in terms of “luxury class restaurants” the average score is 2.21 out of 5). The study revealed an insufficient level of development of additional tourist resources that ensure the realization of the differentiated needs of various social groups.
Discussion and Conclusion. It is concluded that it is expedient to support entrepreneurial initiatives aimed at creating tourism products and services, both in the “economy” and “luxury” segments, the formation of a recognizable image of the territories as part of the promotion of their social resources. The results obtained can be used in the activities of the authorities in the development of strategies for the development of regional tourism.
Economists often estimate models using data from a particular domain, e.g. estimating risk preferences in a particular subject pool or for a specific class of lotteries. Whether a model's predictions extrapolate well across domains depends on whether the estimated model has captured generalizable structure. We provide a tractable formulation for this "out-of-domain" prediction problem and define the transfer error of a model based on how well it performs on data from a new domain. We derive finite-sample forecast intervals that are guaranteed to cover realized transfer errors with a user-selected probability when domains are iid, and use these intervals to compare the transferability of economic models and black box algorithms for predicting certainty equivalents. We find that in this application, the black box algorithms we consider outperform standard economic models when estimated and tested on data from the same domain, but the economic models generalize across domains better than the black-box algorithms do.