Laura Padilla-Angulo, Diego Jorrat, José-Ignacio Antón
et al.
This paper evaluates the effect of a short, interactive popularisation talk on upper-secondary students' interest in Economics. This contrasts with previous research, which has primarily examined impersonal interventions to boost interest in Economics. The intervention presents Economics as an empirical social science engaged with real-world social problems. Using a cluster-randomised field experiment conducted during secondary-school campus visits in Spain, we find no statistically significant average effect on stated interest in studying Economics. However, the intervention generates substantial heterogeneity: those with stronger altruistic preferences become significantly more likely to express interest after the talk. These findings suggest that informational outreach may shape who perceives the discipline as aligned with their motivations, even if it does not substantially increase overall interest. More broadly, they indicate that presenting Economics as empirical and socially relevant may broaden the profile of those who consider the field.
The goal of this research is to uncover the channels through which research and development (R&D) impacts economic growth in developing countries. The study employed nine variables from three broader categories in the World Economic Forum database, each covering 32 countries from the lower-middle-income group for the year 2019. The theoretical framework is based on the R&D ecosystem, which includes components such as Institutions, Human capital, Capital market, R&D, and Innovation. Each of these components can contribute to the economic development of the country. Using Structural Equation Modelling (SEM), we build a path diagram to visualize and confirm a potential relationship between the components. R&D features had a positive impact on innovation (regression weight estimate: +0.34, p = 0.001), as did capital market institutions (regression weight estimate: +0.12, p = 0.007), but neither had a significant impact on growth. According to the Schumpeterian institutional interpretation, R&D and innovation efforts may not lead to sustained growth in middle-income countries. We find no significant connection between innovation performance and economic growth. This suggests that while R&D and capital markets may contribute to innovation through entrepreneurship, this contribution is not impactful enough to drive economic growth in developing countries. Our findings provide further evidence of the middle-income trap.
Machine learning algorithms can now outperform classic economic models in predicting quantities ranging from bargaining outcomes, to choice under uncertainty, to an individual's future jobs and wages. Yet this predictive accuracy comes at a cost: most machine learning algorithms function as black boxes, offering little insight into \emph{why} outcomes occur. This article asks whether machine learning can guide the development of new economic theories. Economic models serve an important purpose beyond prediction -- they uncover the general mechanisms behind observed behaviors. A model that identifies the causal pathways of economic development is more valuable than one that merely predicts which countries will escape poverty, because it enables policymakers to encourage that development in countries where it might not have happened otherwise. Similarly, a model that predicts imperfectly across many domains can be more valuable than one that is highly accurate in a specific domain, since the former allows insights and data obtained from one setting to inform decisions and policy in another. Applying machine learning algorithms off-the-shelf is unlikely to yield such models. But recent work shows that, when reconceived with the aims of an economic modeler in mind, machine learning methods can improve both prediction and understanding. These approaches range from adversarially training algorithms to expose the limits of existing models, to imposing economic theory as a constraint on algorithmic search. Advances in large language models complement these strategies and open new research directions.
The Millennium Challenge Corporation (MCC), started in 2004 by the United States Congress, focuses on development initiatives involving good governance, sustainable economic growth, and poverty reduction. Since its inception, it has invested over 13 billion US dollars in 30 countries. Nepal is a recent beneficiary, signing a compact valued at 500 million US dollars in 2017, ratified in 2022. The compact mainly invests in road infrastructure and electricity transmission, including construction of 315 kilometers of high-voltage transmission lines, three substations, and upgrading 100 kilometers of the East-West highway. By supporting commercialization of Nepals 40 gigawatt hydropower potential, the MCC aims to enhance Nepals structural economic prosperity. Beyond economics, the compact influences Nepals foreign policy by diversifying partnerships and reducing overdependence on neighbors China and India. The establishment of the Millennium Challenge Account (MCA)-Nepal fosters host-country ownership, mitigating geopolitical concerns. Building on International Relations scholar Shiping Tangs Institutional Foundations for Economic Development (IFED) framework, this paper shows how the MCC addresses Nepals infrastructure development capacity. Success stories from Ghana and other MCC countries highlight transformative progress toward prosperity, positioning Nepal to leverage both development and diplomatic opportunities. Drawing from multiple sources, this paper argues that the MCC compact provides Nepal with opportunities to overcome infrastructural barriers to growth.
Estimating the effects of climate on economic output is crucial for formulating climate policy, but current empirical findings remain ambiguous. Using annual panel model and panel long-difference model with global subnational data from nearly all countries, we find robust evidence that weather shocks have a transient effect on output. The impact on economic growth is large and significant in the short-run but statistically insignificant in the long-run, except in the coldest and hottest places.
The article examines the impact of 16 key parameters of the Georgian economy on economic inequality, using the Perelman model and Ricci flow mathematical methods. The study aims to conduct a deep analysis of the impact of socio-economic challenges and technological progress on the dynamics of the Gini coefficient. The article examines the following parameters: income distribution, productivity (GDP per hour), unemployment rate, investment rate, inflation rate, migration (net negative), education level, social mobility, trade infrastructure, capital flows, innovative activities, access to healthcare, fiscal policy (budget deficit), international trade (turnover relative to GDP), social protection programs, and technological access. The results of the study confirm that technological innovations and social protection programs have a positive impact on reducing inequality. Productivity growth, improving the quality of education, and strengthening R&D investments increase the possibility of inclusive development. Sensitivity analysis shows that social mobility and infrastructure are important factors that affect economic stability. The accuracy of the model is confirmed by high R^2 values (80-90%) and the statistical reliability of the Z-statistic (<0.05). The study uses Ricci flow methods, which allow for a geometric analysis of the transformation of economic parameters in time and space. Recommendations include the strategic introduction of technological progress, the expansion of social protection programs, improving the quality of education, and encouraging international trade, which will contribute to economic sustainability and reduce inequality. The article highlights multifaceted approaches that combine technological innovation and responses to socio-economic challenges to ensure sustainable and inclusive economic development.
Aryan Eftekhari, Doris Folini, Aleksandra Friedl
et al.
We introduce a framework for developing efficient and interpretable climate emulators (CEs) for economic models of climate change. The paper makes two main contributions. First, we propose a general framework for constructing carbon-cycle emulators (CCEs) for macroeconomic models. The framework is implemented as a generalized linear multi-reservoir (box) model that conserves key physical quantities and can be customized for specific applications. We consider three versions of the CCE, which we evaluate within a simple representative agent economic model: (i) a three-box setting comparable to DICE-2016, (ii) a four-box extension, and (iii) a four-box version that explicitly captures land-use change. While the three-box model reproduces benchmark results well and the fourth reservoir adds little, incorporating the impact of land-use change on the carbon storage capacity of the terrestrial biosphere substantially alters atmospheric carbon stocks, temperature trajectories, and the optimal mitigation path. Second, we investigate pattern-scaling techniques that transform global-mean temperature projections from CEs into spatially heterogeneous warming fields. We show how regional baseline climates, non-uniform warming, and the associated uncertainties propagate into economic damages.
This study offers an examination of grassroots innovation actors and their integration within larger economic ecosystems. Through a comparative analysis in Oaxaca, Mexico; La Plata, Argentina; and Araucania, Chile, this research sheds light on the vital role that grassroots innovation plays in broader economic ecosystems. Using Complex Network Analysis and the TE-SER model, the study unveils how these actors interact, collaborate, and influence major economic ecosystems in the context of complex social challenges. The findings highlight that actors from the grassroots innovation ecosystem make up a significant portion of the larger innovation-driven entrepreneurial economic ecosystem, accounting for between 20% and 30% in all three cases and are strategically positioned within the ecosystem's structural network. Additionally, this study emphasizes the potential for greater integration of grassroots innovation actors to leverage resources and foster socio-economic development. The research concludes by advocating for further studies in similar socio-economic contexts to enhance our understanding of integration dynamics and mutual benefits between grassroots innovation ecosystems and other larger economic systems.
Johannes Stangl, András Borsos, Christian Diem
et al.
Urgently needed carbon emissions reductions might lead to strict command-and-control decarbonization strategies with potentially negative economic consequences. Analysing the entire firm-level production network of a European economy, we have explored how the worst outcomes of such approaches can be avoided. We compared the systemic relevance of every firm in Hungary with its annual CO2 emissions to identify optimal emission-reducing strategies with a minimum of additional unemployment and economic losses. Setting specific reduction targets, we studied various decarbonization scenarios and quantified their economic consequences. We determined that for an emissions reduction of 20%, the most effective strategy leads to losses of about 2% of jobs and 2% of economic output. In contrast, a naive scenario targeting the largest emitters first results in 28% job losses and 33% output reduction for the same target. This demonstrates that it is possible to use firm-level production networks to design highly effective decarbonization strategies that practically preserve employment and economic output.
Alessandro Calvia, Fausto Gozzi, Marta Leocata
et al.
We introduce a spatial economic growth model where space is described as a network of interconnected geographic locations and we study a corresponding finite-dimensional optimal control problem on a graph with state constraints. Economic growth models on networks are motivated by the nature of spatial economic data, which naturally possess a graph-like structure: this fact makes these models well-suited for numerical implementation and calibration. The network setting is different from the one adopted in the related literature, where space is modeled as a subset of a Euclidean space, which gives rise to infinite dimensional optimal control problems. After introducing the model and the related control problem, we prove existence and uniqueness of an optimal control and a regularity result for the value function, which sets up the basis for a deeper study of the optimal strategies. Then, we focus on specific cases where it is possible to find, under suitable assumptions, an explicit solution of the control problem. Finally, we discuss the cases of networks of two and three geographic locations.
If Economics is understood as the study of the interactions among intentional agents, being rationality the main source of intentional behavior, the mathematical tools that it requires must be extended to capture systemic effects. Here we choose an alternative toolbox based on Category Theory. We examine potential {\em level-agnostic} formalisms, presenting three categories, $\mathcal{PR}$, $\mathcal{G}$ and an encompassing one, $\mathcal{PR-G}$. The latter allows for representing dynamic rearrangements of the interactions among different agents.
Национальные и региональные правительства разрабатывают и внедряют программы поддержки предпринимателей на сельских территориях, однако сами предприниматели оценивают эффективность этих программ недостаточно высоко, что в итоге негативно сказывается на социально-экономическом развитии сельских территорий. Целью работы являются разработка и апробация инструментария исследования воздействия программ поддержки предпринимательства на социально-экономическое развитие сельских территорий. Методология исследования построена на применении герменевтических феноменологических методов исследований в области экономики, дающих возможность исследовать побудительные мотивы всех акторов экономической системы на основании их побудительного опыта как феномена. Компаративный анализ программ поддержки предпринимателей в России и Новой Зеландии был дополнен анализом их восприятия самими предпринимателями, опрошенными методом полуструктурированного интервью, показавшего, что проведение разрозненных проектов, не связанных между собой, снижает их эффективность и их позитивное восприятие предпринимателями; российские предприниматели недостаточно высоко оценивают роль инфраструктуры в успешности проектов; большая часть предпринимательских организаций относится к семейному бизнесу, и это накладывает на их руководителей значительную социальную ответственность, что редко учитывается в предлагаемых государственных программах. Признавая недостаточный рыночный опыт потенциальных предпринимателей, государство, в первую очередь, должно обеспечивать предпринимателей не только и не столько финансовыми ресурсами, сколько информационными, которые позволят организовать устойчивый бизнес. Полученные результаты доказывают, что разработка и реализация мер государственной поддержки сельского предпринимательства требуют вовлечения многих участников: органов государственного управления, местного самоуправления, самих сельских предпринимателей и профессиональных саморегулируемых организаций и, конечно же, сельского населения. Продуктивность совместной деятельности столь разностороннего состава участников требует создания всеобъемлющей системы, что приводит нас к пониманию необходимости формирования такой сельской предпринимательской экосистемы, в рамках которой могут быть достигнуты поставленные ориентиры развития сельского предпринимательства.
With the recent administration change in Mexico, the fluctuations in national energy policy have generated widespread concerns among investors and the public. The debate centers around Mexico's energy dependence on the US and how Mexico's energy development should move forward. The goal of this study is two-fold. We first review the history and background of the recent energy reforms in Mexico. The focus of the study is on quantifying the state-level regional economic impact of the growing US-Mexico natural gas trade in Mexico. We examine both the quantity effect (impact of import volume) and the price effect (impact of natural gas price changes). Our empirical analysis adopts a fixed-effects regression model and the instrumental variables (IV) estimation approach to address spatial heterogeneities and the potential endogeneity associated with natural gas import. The quantity effect analysis suggests a statistically significant positive employment impact of imports in non-mining sectors. The impact in the mining sector, however, is insignificant. The state-level average (non-mining) employment impact is 127 jobs per million MCFs of natural gas imported from the US. The price effect analysis suggests a statistically significant positive employment impact of price increases in the mining sector. A one-percentage increase in natural gas price (1.82 Pesos/GJ, in 2015 Peso) leads to an average state-level mining employment increase of 140 (or 2.38%). We also explored the implications of our findings for Mexico's energy policy, trade policy, and energy security.
This paper aims to present empirical analysis of Iranian economic growth from 1950 to 2018 using data from the World Bank, Madison Data Bank, Statistical Center of Iran, and Central Bank of Iran. The results show that Gross Domestic Product (GDP) per capital increased by 2 percent annually during this time, however this indicator has had a huge fluctuation over time. In addition, the economic growth of Iran and oil revenue have close relationship with each other. In fact, whenever oil crises happen, great fluctuation in growth rate and other indicators happened subsequently. Even though the shares of other sectors like industry and services in GDP have increased over time, the oil sector still plays a key role in the economic growth of Iran. Moreover, growth accounting analysis shows contribution of capital plays a significant role in economic growth of Iran. Furthermore, based on growth accounting framework the steady state of effective capital is 4.27 for Iran's economy.
Stephan Zheng, Alexander Trott, Sunil Srinivasa
et al.
AI and reinforcement learning (RL) have improved many areas, but are not yet widely adopted in economic policy design, mechanism design, or economics at large. At the same time, current economic methodology is limited by a lack of counterfactual data, simplistic behavioral models, and limited opportunities to experiment with policies and evaluate behavioral responses. Here we show that machine-learning-based economic simulation is a powerful policy and mechanism design framework to overcome these limitations. The AI Economist is a two-level, deep RL framework that trains both agents and a social planner who co-adapt, providing a tractable solution to the highly unstable and novel two-level RL challenge. From a simple specification of an economy, we learn rational agent behaviors that adapt to learned planner policies and vice versa. We demonstrate the efficacy of the AI Economist on the problem of optimal taxation. In simple one-step economies, the AI Economist recovers the optimal tax policy of economic theory. In complex, dynamic economies, the AI Economist substantially improves both utilitarian social welfare and the trade-off between equality and productivity over baselines. It does so despite emergent tax-gaming strategies, while accounting for agent interactions and behavioral change more accurately than economic theory. These results demonstrate for the first time that two-level, deep RL can be used for understanding and as a complement to theory for economic design, unlocking a new computational learning-based approach to understanding economic policy.
This tidal stream energy industry has to date been comprised of small demonstrator projects made up of one to a four turbines. However, there are currently plans to expand to commercially sized projects with tens of turbines or more. As the industry moves to large-scale arrays for the first time, there has been a push to develop tools to optimise the array design and help bring down the costs. This review investigates different methods of modelling the economic performance of tidal-stream arrays, for use within these optimisation tools. The different cost reduction pathways are discussed from costs falling as the global installed capacity increases, due to greater experience, improved power curves through larger-diameter higher-rated turbines, to economic efficiencies that can be found by moving to large-scale arrays. A literature review is conducted to establish the most appropriate input values for use in economic models. This includes finding a best case, worst case and typical values for costs and other related parameters. The information collated in this review can provide a useful steering for the many optimisation tools that have been developed, especially when cost information is commercially sensitive and a realistic parameter range is difficult to obtain.
The article describes the dynamics of the evolution of political thinking in international relations from binary oppositions to lateral thinking. This evolution is motivated by the new social reality of regional ecosystems that form the basis of globalization processes. Marlene Laruelle and Kazushige Kobayashi initiated an intellectual discussion on the specifics and prospects of transforming the thinking of political and economic elites at the beginning of the 21st century. The article shows that a new platform for the dialogue of non-like-minded people can play a constructive role in the implementation of the glocalization of ecosystems with the possibility of preserving the historically functioning international division of labor. In such a situation, relations between politics and economics are being transformed. The commercial priorities of transactions and the development of transnational digital platforms integrated into the space of the national regulator come to the fore. Groups of economic trans-regional interests can become the fundamental basis for the annihilation of the conflicting intentions of binary political thinking.
The paper deals with the study of global financial transformations impact on the financial sector in Poland. Two types of tendencies of the global financial space development that create new conditions for national financial systems are defined,including: trends that lead to qualitative shifts in countries’ financial systems and do not necessarily imply a negative impact on the national financial systems; threatening challenges that shatter financial markets and restrain their sustainable development. The current positions of Poland’s financial sector in the world and regional financial systems are evaluated. The shifts in the national financial sector in terms of global financial transformations are found out. It is stated that while integrating into the global financial space, Poland will increasingly feel the impact of global transformations that will determine further scenarios for the domestic financial sector development. Exogenous factors that can aggravate challenges threatening the stability of Poland’s financial sector in the near future are identified.
Quite often, the scientific community emphasizes the need to stimulate spatial development and form the most optimal structure of economic space in order to ensure sustainable and integrated development of territories. Despite the development and complexity of the research methodology, existing models and theories of spatial topics do not fully reflect the real picture of the organization of economic space in various countries of the world. However, it is the joint study of the theoretical and methodological foundations of spatial and regional economics and the study of domestic and foreign experiences of spatial organization that makes it possible to implement a full-fledged transformation of the Russian economy in a spatial context. The purpose of this article is to study the spatial organization of the Northern territories of a number of foreign countries and develop proposals on this basis to ensure the spatial development of the Northern and Arctic regions of the Russian Federation. The research used the monographic method, methods of comparative analysis and synthesis of information obtained, as well as graphical and tabular methods of data visualization. The study found that economic space acquires its actual configuration through distribution across economic agents and settlements and through relationships and communication that occur at the stages of production, distribution, exchange, and consumption. The study of the economic space specificity in the Northern territories of foreign countries helped to identify the main factors and conditions for forming the production and settlement frameworks. Based on the results obtained, the authorsdeveloped proposals aimed at improving spatial organization of the Northern and Arctic territories of the Russian Federation. The nclusions contribute to the development of ideas on spatial organization of territories and can be used in the implementation of government policies in the field of spatial and regional development.