Hasil untuk "Regional economics. Space in economics"

Riccardo Ciacci, Alessandro Corvasce

This article introduces a longitudinal, venue-level dataset documenting the spatial and temporal evolution of a specific segment of an informal market in Spain between 2011 and 2023. Using publicly available Google data, we construct a panel of establishments classified within nightlife and adult entertainment categories, commonly referred to in Spanish as clubes de alterne. The primary contribution is methodological: we propose a transparent and replicable framework to track the commercial infrastructure of partially regulated markets that are opaque to standard measurement. The dataset captures the extensive margin of supply the presence and persistence of physical venues and should be interpreted as a conservative, observable lower bound. We document pronounced spatial concentration and heterogeneity across provinces, with establishments clustering in major urban and coastal tourist areas. This dataset provides a new empirical tool to study the interaction between informal markets, regulation and local economic dynamics.

Daniel W. O'Neill, Stefano Vrizzi, Noemi Luna Carmeno et al.

Artificial intelligence (AI) is advancing exponentially and is likely to have profound impacts on human wellbeing, social equity, and environmental sustainability. Here we argue that the "alignment problem" in AI research is also an economic alignment problem, as developing advanced AI inside a growth-based system is likely to increase social, environmental, and existential risks. We show that post-growth research offers concepts and policies that could substantially reduce AI risks, such as by replacing optimisation with satisficing, using the Doughnut of social and planetary boundaries to guide development, and curbing systemic rebound with resource caps. We propose governance and business reforms that treat AI as a commons and prioritise tool-like autonomy-enhancing systems over agentic AI. Finally, we argue that the development of artificial general intelligence (AGI) may require a new economics, for which post-growth scholarship provides a strong foundation.

Anthony Q. Q. Aboagye

Ghana exited her 16th IMF Debt Bailout Programme in April 2019. Unfortunately, in May 2023, she signed on to her 17th IMF Debt Bailout Programme because the country’s debt had once again become unsustainable. The question posed in this paper is, leading to 2021, did the authorities in Ghana undertake a thorough debt sustainability analysis? This study used the IMF-World Bank Debt Sustainability Framework for Low-Income Countries to analyse the dynamics of Ghana’s debt over 2010-2021. Using averages of key variables over 2000-2009, the baseline scenario revealed that, had these averages prevailed, Ghana’s debt ratio would have risen from 35% in 2009 to only 43% in 2021, a far cry from the actual 80.1% that drove her economy into a tailspin in 2022. The baseline scenario was stress tested assuming worsening scenarios of historical values of key variables. The results indicated that looking forward from 2009, moderate stress (worsening of the values of key variables by two standard errors) would be enough to make the year-on-year evolution of the debt ratio unsustainable. The cause of the ballooning debt ratio was traced to a primary balance that remained lower than its debt stabilizing value and Ghana having to borrow regularly to service previous debt.

Camelia Oprean-Stan

The goal of this study is to propose a new concept, Sustainable Economic Value, to define it logically, and to build a simplified model for its evaluation.

Hamidah Oderinwale, Anna Kazlauskas

Despite data's central role in AI production, it remains the least understood input. As AI labs exhaust public data and turn to proprietary sources, with deals reaching hundreds of millions of dollars, research across computer science, economics, law, and policy has fragmented. We establish data economics as a coherent field through three contributions. First, we characterize data's distinctive properties -- nonrivalry, context dependence, and emergent rivalry through contamination -- and trace historical precedents for market formation in commodities such as oil and grain. Second, we present systematic documentation of AI training data deals from 2020 to 2025, revealing persistent market fragmentation, five distinct pricing mechanisms (from per-unit licensing to commissioning), and that most deals exclude original creators from compensation. Third, we propose a formal hierarchy of exchangeable data units (token, record, dataset, corpus, stream) and argue for data's explicit representation in production functions. Building on these foundations, we outline four open research problems foundational to data economics: measuring context-dependent value, balancing governance with privacy, estimating data's contribution to production, and designing mechanisms for heterogeneous, compositional goods.

Minali Grover, Ajay Sharma

This paper explores the influence of inheritance rights on women' empowerment in India. We employ the quasi-natural experiment framework wherein; five states amended the Hindu Succession Act (HSA) from 1976 to 1994 before it was federally amended in 2005. Further, we apply difference-in-difference (DID) strategy and consider triangulation approach to identify women empowerment indicators namely: access to resources, agency, and outcomes to measure varying dimensions of empowerment. Using the India Human Development Survey (IHDS-I), our results indicate a positive impact on marriage choice, intimate partner violence, physical, and civil autonomy. However, negative impact on household autonomy and no significant on economic participation for women exposed to state amendments. Further, exploring the heterogeneities in terms of socio-economic status, location, level of patriarchy in a state, gender of the head of the household. Overall, the study highlights that the impact of inheritance law is not unfirm across different groups.

Ghazaleh Tarkalam

Iranian architecture has left its mark on world history, with its influence reaching the farthest corners of Europe through the creation of Byzantine architecture. The traditional architecture of Iran, as described by Professor Pirnia, is built upon five principles. These principles highlight the evolution of Iranian civilization over time. Mohsen Foroughi, an exemplary Iranian architect, has skillfully merged the essence of Iranian architecture with contemporary ideals, exemplified by his masterpiece, the "Maison de l’Iran" in Paris, designed in a modern style. In this study, we aimed to explore how Foroughi incorporated these five principles of Iranian architecture into his project in France. Employing a descriptive and analytical method, we assessed the physical and structural components of Iranian architecture, examining how Foroughi's work aligns with the principles and values of Iranian architecture. Our findings demonstrate that Foroughi is in line with traditional Iranian architectural values, contextual materials, and climate-friendly design in his works. Furthermore, Foroughi's expertise in Statics, Material Studies, and Structural techniques sciences enabled him to successfully execute large-scale projects. The Maison de l’Iran exemplifies his understanding of modern styles while honoring the principles of Iranian architecture. His work has been instrumental in shaping modern Iranian architecture, reflecting his artistic creativity and inspiration from Iran's architectural heritage.

Kshama Dwarakanath, Tucker Balch, Svitlana Vyetrenko

We present ABIDES-Economist, an agent-based simulator for economic systems that includes heterogeneous households, firms, a central bank, and a government. Agent behavior can be defined using domain-specific behavioral rules or learned through reinforcement learning by specifying their objectives. We integrate reinforcement learning capabilities for all agents using the OpenAI Gym environment framework for the multi-agent system. To enhance the realism of our model, we base agent parameters and action spaces on economic literature and real U.S. economic data. To tackle the challenges of calibrating heterogeneous agent-based economic models, we conduct a comprehensive survey of stylized facts related to both microeconomic and macroeconomic time series data. We then validate ABIDES-Economist by demonstrating its ability to generate simulated data that aligns with the relevant stylized facts for the economic scenario under consideration, following the learning of all agent behaviors via reinforcement learning. Specifically, we train our economic agents' policies under two broad configurations. The first configuration demonstrates that the learned economic agents produce system data consistent with macroeconomic and microeconomic stylized facts. The second configuration illustrates the utility of the validated simulation platform in designing regulatory policies for the central bank and government. These policies outperform standard rule-based approaches from the literature, which often overlook agent heterogeneity, shocks, and agent adaptability.

Thiago C. Silva, Paulo V. B. Wilhelm, Diego R. Amancio

This study examines the effects of de-globalization trends on international trade networks and their role in improving forecasts for economic growth. Using section-level trade data from nearly 200 countries from 2010 to 2022, we identify significant shifts in the network topology driven by rising trade policy uncertainty. Our analysis highlights key global players through centrality rankings, with the United States, China, and Germany maintaining consistent dominance. Using a horse race of supervised regressors, we find that network topology descriptors evaluated from section-specific trade networks substantially enhance the quality of a country's GDP growth forecast. We also find that non-linear models, such as Random Forest, XGBoost, and LightGBM, outperform traditional linear models used in the economics literature. Using SHAP values to interpret these non-linear model's predictions, we find that about half of most important features originate from the network descriptors, underscoring their vital role in refining forecasts. Moreover, this study emphasizes the significance of recent economic performance, population growth, and the primary sector's influence in shaping economic growth predictions, offering novel insights into the intricacies of economic growth forecasting.

Christian Vedel

In 1825 a storm cut a new channel through Denmark's Limfjord, providing an exogenous shock to first-nature geography. Difference-in-differences estimates show the channel increased trade immediately and, within a generation, lifted population by 26.7 percent - an elasticity of 1.6 relative to the improved market access. Higher fertility and economic growth of new industries, not migration, drove the expansion. A mirror experiment - the waterway's closure circa 1086-1208 - caused symmetric declines in medieval coin and building finds, bolstering external validity. These results offer the first robust causal evidence that first-nature geomorphology shapes the location of economic activity.

Anton Korinek

This paper examines the profound challenges that transformative advances in AI towards Artificial General Intelligence (AGI) will pose for economists and economic policymakers. I examine how the Age of AI will revolutionize the basic structure of our economies by diminishing the role of labor, leading to unprecedented productivity gains but raising concerns about job disruption, income distribution, and the value of education and human capital. I explore what roles may remain for labor post-AGI, and which production factors will grow in importance. The paper then identifies eight key challenges for economic policy in the Age of AI: (1) inequality and income distribution, (2) education and skill development, (3) social and political stability, (4) macroeconomic policy, (5) antitrust and market regulation, (6) intellectual property, (7) environmental implications, and (8) global AI governance. It concludes by emphasizing how economists can contribute to a better understanding of these challenges.

کتایون آشاروزنیا, عباسعلی پورآقاجان, سید حسین نسل موسوی

تقلب صورت‌های مالی تبدیل به‌ یک مشکل جدی برای فعالان بازار و سیاست‌گذاران شده است. در واقع، این مسئله قابلیت اطمینان بازارهای سرمایه، رؤسای شرکت‌ها و حتی حرفه حسابرسی را تهدید می‌کند. هدف تحقیق حاضر استفاده از رویکرد مدل‌های پویای میانگین‌گیری جهت پیش‌بینی تقلب در صورت‌های مالی است.تحقیق حاضر از لحاظ روش کاربردی است. بازه زمانی تحقیق 1390 تا 1399 بوده و در برآورد مدل از داده شرکت‌های منتخب در بورس اوراق بهادار تهران بهره گرفته شده است. با استفاده از رویکرد حذف سیستماتیک حجم نمونه تحقیق 125 شرکت انتخاب گردیدند. جهت برآورد مدل از نرم افزار متلب 2021 بهره گرفته شده است. در این تحقیق بر اساس مدل میانگین‌گیری پویا اقدام به پیش‌بینی تقلب و دقت مدل‌های برآوردی نمودیم. بر اساس نتایج متغیرهای بازده دارایی‌ها؛ بازده حقوق صاحبان سهام؛ حاشیه سود عملیاتی؛ نسبت گردش دارایی‌ها و نسبت وجه نقد عملیاتی به فروش بر تقلب تأثیر منفی و سایر متغیرها تأثیر مثبت دارند.

Teresa Graziano, Luca Ruggiero

ABSTRACTThis article provides new insights into the relationship between industrialization and new forms of post-industrial development. Adopting a historical sensibility, it frames the contemporary development of the local economy of the city of Siracusa, in south-east Sicily, in an evolutionary historical perspective. The article focuses on the recent process of touristification of the city and surrounding area, analysing this process in connection with the industrialization and growth-pole strategy implemented in south-east Sicily in the post-war period. Emphasis is placed on the narratives that have been mobilized to justify different forms of development in the area, focusing in particular on the recurrent representation of the area as a periphery. Pointing out the selective use of visions of the past in post-industrial development strategies, the authors highlight how an uncomfortable industrial past has been removed from the main narratives to envision the city of Siracusa as moving towards a new phase of capitalist development. Finally, the article provides novel insights into the critical literature on tourism, showing that tourism, narrated and promoted as a sustainable and eco-compatible alternative to industrialization in Siracusa, can in fact produce highly negative impacts on the local environment and communities.

Marouane Daoui

This article conducts a literature review on the topic of monetary policy in developing countries and focuses on the effectiveness of monetary policy in promoting economic growth and the relationship between monetary policy and economic growth. The literature review finds that the activities of central banks in developing countries are often overlooked by economic models, but recent studies have shown that there are many factors that can affect the effectiveness of monetary policy in these countries. These factors include the profitability of central banks and monetary unions, the independence of central banks in their operations, and lags, rigidities, and disequilibrium analysis. The literature review also finds that studies on the topic have produced mixed results, with some studies finding that monetary policy has a limited or non-existent impact on economic growth and others finding that it plays a crucial role. The article aims to provide a comprehensive understanding of the current state of research in this field and to identify areas for future study.

Christoph F. Strnadl

Ecosystems enjoy increasing attention due to their flexibility and innovative power. It is well known, however, that this type of network-based economic governance structures occupies a potentially unstable position between the two stable (governance) endpoints, namely the firm (i.e., hierarchical governance) and the (open) market (i.e., coordination through the monetary system). This paper develops a formal (mathematical) theory of the economic value of (generic) ecosystem by extending transaction costs economics using certain elements from service-dominant logic. Within a first-best setting of rational actors, we derive analytical solutions for the hub-and-spoke and generic ecosystem configurations under some uniformity assumptions of ecosystem participants. Additionally, we are able to infer a generic condition for the welfare-maximizing and utility-maximizing price of the hub-and-spoke configuration in the familiar form of Lerner indices and elasticities. Relinquishing a first-best rational actors approach, we additionally derive several general propositions on (i) necessary conditions for the economic feasibility of ecosystem-based transactions, (ii) scaling requirements for ecosystem stability, and (iii) a generic feasibility condition for arbitrary provider-consumer ecosystems. Finally, we present an algebraic definition of business ecosystems and relate it to existing informal definition attempts. Thereby we demonstrate that the property of "being an ecosystem" of a network of transacting actors cannot be decided on structural grounds alone.

Maria Shishanina, Anatoly Sidorov

The article discusses the basic concepts of strategic planning in the Russian Federation, highlights the legal, financial and resource features that act as restrictions in decision making in the field of socio-economic development of municipalities. The analysis concluded that to design an adequate model of socio-economic development of municipalities is a very difficult task, particularly when the traditional approaches are applied. To solve the task, we proposed to use the semantic modeling as well as cognitive maps which are able to point out the set of dependencies that arise between factors having a direct impact on socio-economic development.

Yuliya O. Nichkasova , Eduard Nezhinsky , Halina A. Shmarlouskaya

Kazakhstan’s financial market has always been the focus of the government attention as an important element of country development. Therefore, the main goal is to build a well-developed, competitive and trustworthy financial market that has a dominant influence on the economy and sustainable development. For countries with economies in transition, achievement of a significant level of economic growth is a prerequisite for the formation of a stable capital market and banking system, that will subsequently have a significant positive impact on economic growth. This study investigates the relationship between the local financial market and economic growth for Kazakhstan based on measures of economic growth and its components, as well as empirical indicators of banking development and stock market — size, liquidity and volatility — used as control variables that determine Kazakhstan’s economy. Time series regression analysis and Granger causality test was performed for data from 1994 to 2017 in order to design country-specific measures for financial development. The results showed that world oil prices and total investment are the most powerful factors influencing economic growth. The direction of causation for Kazakhstan comes from economic growth towards the development of the local financial market, contrary to the postulate that the development of a financial intermediary stimulates economic growth. Therefore, at this stage, the financial sector does not stimulate the economic development of Kazakhstan, but rather the economic growth based on oil production and export is a catalyst for the development of the financial sector. It should be recommended to Kazakhstan’s government to shift the focus from financial market to economic development in order to mobilise sufficient domestic and international investments to transform the economy and make a transition to sustainable growth.

Sirovs Toms

As a result of the rapid development of the construction industry, in recent years, research has increasingly used system dynamics (SD) modelling to determine the positive and negative causal feedback in various management processes. Given SD diverse approach to the management of construction companies and projects, it would be necessary to develop a framework for a system dynamics model (SDM) incorporating the main processes of the Baltic States by identifying and providing a systematic understanding of their distribution. Using literature analysis, this study provides the results of 79 selected scientific literature sources from 1991 to 2020. The obtained information is structured according to the annual volume of publications, country of affiliation, the most successful authors and the most popular scientific journals on the topic of the SD. With the assistance of bibliometric analysis and co-occurrence of keywords, system dynamics management processes in construction companies were structured, choosing the following separate elements: (1) project planning, (2) project management, (3) risk management, (4) project performance, (5) project productivity, (6) sustainability. Using a systematic approach, according to the framework of the model, the characteristics of each management process were classified and identified, dividing them into subgroups. The results of the analysis show that the overview of some SD components or processes is mostly provided, which emphasises its aspects and usability in company management, thus indicating the need to identify the framework of the process module. The introduction of the SD process framework in the company would gradually create a competitive advantage in market conditions.

Katarzyna Maciejowska, Bartosz Uniejewski, Rafał Weron

Forecasting electricity prices is a challenging task and an active area of research since the 1990s and the deregulation of the traditionally monopolistic and government-controlled power sectors. Although it aims at predicting both spot and forward prices, the vast majority of research is focused on short-term horizons which exhibit dynamics unlike in any other market. The reason is that power system stability calls for a constant balance between production and consumption, while being weather (both demand and supply) and business activity (demand only) dependent. The recent market innovations do not help in this respect. The rapid expansion of intermittent renewable energy sources is not offset by the costly increase of electricity storage capacities and modernization of the grid infrastructure. On the methodological side, this leads to three visible trends in electricity price forecasting research as of 2022. Firstly, there is a slow, but more noticeable with every year, tendency to consider not only point but also probabilistic (interval, density) or even path (also called ensemble) forecasts. Secondly, there is a clear shift from the relatively parsimonious econometric (or statistical) models towards more complex and harder to comprehend, but more versatile and eventually more accurate statistical/machine learning approaches. Thirdly, statistical error measures are nowadays regarded as only the first evaluation step. Since they may not necessarily reflect the economic value of reducing prediction errors, more and more often, they are complemented by case studies comparing profits from scheduling or trading strategies based on price forecasts obtained from different models.

Luis Felipe Zegarra

This study relies on a linear programming model to estimate welfare ratios in 19th century Lima. By using a linear programming model, the food basket guarantees the intake of basic nutrients at the minimum cost. The subsistence cost includes the cost of food and other basic needs. The estimates show that low-skilled workers in Lima were able to cover their basic needs in 1800-1875. The results also show that living standards of low-skilled workers declined during the Guano Era. Living standards in Lima, however, compared favorably to several cities in Europe.