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.
Traditional economic growth theories, grounded in deterministic and often linear frameworks, fail to adequately capture the inherent uncertainty, non-commutativity, and complex interdependencies of modern economies. This paper proposes a novel approach by transposing fundamental concepts of quantum mechanics-such as superposition, operator algebra, and path integrals-into the realm of macroeconomic modeling. Within this quantum framework, core economic variables (capital, labor, and technological progress) are redefined as non-commuting operators acting on Hilbert spaces, and the state of the economy is represented as a dynamic wave function governed by a time-dependent Hamiltonian. The evolution of this economic wave function follows a generalized Schr{ö}dinger equation, developed here through Dyson series and Magnus expansions. We also define a quantum production function as the expected value of a composite operator, capturing the probabilistic nature of economic output. By integrating uncertainty relations analogous to Heisenberg's principle, and modeling economic fluctuations via Langevin dynamics, we extend the model to include dissipation, feedback loops, and non-linear interactions between variables. Finally, a Feynman path integral formalism is constructed to provide an alternative trajectory-based interpretation of economic dynamics. This quantum-inspired framework offers a rigorous and flexible methodology to rethink macroeconomic modeling under radical uncertainty, with potential applications in dynamic policy simulations and innovation-driven growth.
I discuss economic and social sources of inequality and elaborate on the role of social networks in inequality, economic immobility, and economic inefficiencies. The lens of social networks clarifies how the entanglement of people's information, opportunities, and behaviors with those of their friends and family leads to persistent differences across communities, resulting in inequality in education, employment, income, health, and wealth. The key role of homophily in separating groups within the network is highlighted. A network perspective's policy implications differ substantially from a narrower economic perspective that ignores social structure. I discuss the importance of ``policy cocktails'' that include aspects that are aimed at both the economic and social forces driving inequality.
Abstract The descriptor ‘servant’ is opaque, capturing nothing of the status of those to whom it was attached. Servants are nonetheless assumed to come from poor backgrounds and to have served in the homes of the wealthy. Taking servants recorded in the church court depositions as a starting point, this chapter explores a constellation of sources and evidence to contextualise their service and situate it within broader life histories. From the depositions, I mine the signatures and marks they left at the bottom of their depositions as a mark of consent, interrogating them as indicators of literacy, status, and identity. I explore their self-assessments of wealth that they gave when testifying, disaggregating the fine gradations of status and wealth they articulated. I trace their lives both inside and outside service, using parish records of baptism, marriage, and death as well as probate material to build a picture of who they served as well as who they went on to marry. By tracing the histories of these women in depositions and other archives, the chapter uncovers the myriad reasons they entered service: to seek training in practical and social skills, to escape poverty, and by compulsion.
In this note, we discuss a poorly known alternative boundary condition to the usual Neumann or `stress-free' boundary condition typically used to weaken boundary layers when diffusion is present but very small. These `diffusion-free' boundary conditions were first developed (as far as the authors know) in 1995 (Sureshkumar & Beris, J. Non-Newtonian Fluid Mech., vol 60, 53-80, 1995) in viscoelastic flow modelling but are worthy of general consideration in other research areas. To illustrate their use, we solve two simple ODE problems and then treat a PDE problem - the inertial wave eigenvalue problem in a rotating cylinder, sphere and spherical shell for small but non-zero Ekman number $E$. Where inviscid inertial waves exist (cylinder and sphere), the viscous flows in the Ekman boundary layer are $O(E^{1/2})$ weaker than for the corresponding stress-free layer and fully $O(E)$ weaker than in a non-slip layer. These diffusion-free boundary conditions can also be used with hyperdiffusion and provide a systematic way to generate as many further boundary conditions as required. The weakening effect of this boundary condition could allow precious numerical resources to focus on other areas of the flow and thereby make smaller, more realistic values of diffusion accessible to simulations.
An axiomatic approach to macroeconomics based on the mathematical structure of thermodynamics is presented. It deduces relations between aggregate properties of an economy, concerning quantities and flows of goods and money, prices and the value of money, without any recourse to microeconomic foundations about the preferences and actions of individual economic agents. The approach has three important payoffs. 1) it provides a new and solid foundation for aspects of standard macroeconomic theory such as the existence of market prices, the value of money, the meaning of inflation, the symmetry and negative-definiteness of the macro-Slutsky matrix, and the Le Chatelier-Samuelson principle, without relying on implausibly strong rationality assumptions over individual microeconomic agents. 2) the approach generates new results, including implications for money flow and trade when two or more economies are put in contact, in terms of new concepts such as economic entropy, economic temperature, goods' values and money capacity. Some of these are related to standard economic concepts (eg marginal utility of money, market prices). Yet our approach derives them at a purely macroeconomic level and gives them a meaning independent of usual restrictions. Others of the concepts, such as economic entropy and temperature, have no direct counterparts in standard economics, but they have important economic interpretations and implications, as aggregate utility and the inverse marginal aggregate utility of money, respectively. 3) this analysis promises to open up new frontiers in macroeconomics by building a bridge to ideas from non-equilibrium thermodynamics. More broadly, we hope that the economic analogue of entropy (governing the possible transitions between states of economic systems) may prove to be as fruitful for the social sciences as entropy has been in the natural sciences.
Dirk Reinhardt, Akhil S. Anand, Shambhuraj Sawant
et al.
Markov Decision Processes (MDPs) offer a fairly generic and powerful framework to discuss the notion of optimal policies for dynamic systems, in particular when the dynamics are stochastic. However, computing the optimal policy of an MDP can be very difficult due to the curse of dimensionality present in solving the underlying Bellman equations. Model Predictive Control (MPC) is a very popular technique for building control policies for complex dynamic systems. Historically, MPC has focused on constraint satisfaction and steering dynamic systems towards a user-defined reference. More recently, Economic MPC was proposed as a computationally tractable way of building optimal policies for dynamic systems. When stochsaticity is present, economic MPC is close to the MDP framework. In that context, Economic MPC can be construed as attractable heuristic to provide approximate solutions to MDPs. However, there is arguably a knowledge gap in the literature regarding these approximate solutions and the conditions for an MPC scheme to achieve closed-loop optimality. This chapter aims to clarify this approximation pedagogically, to provide the conditions for MPC to deliver optimal policies, and to explore some of their consequences.
Buster P. Mogonong, Jolene T. Fisher, David Furniss
et al.
Rural landscapes in South Africa experience high conversion rates due to intense land use; however, the changes are site specific and depend on the socio-economic and political history of the area. Land cover change (LCC) was assessed in response to socio-economic and political factors in uThukela Municipal District, KwaZulu-Natal, using Landsat imagery from 1984 to 2014, while making comparisons to other studies in South Africa. Socio-economic/political data were used to gain insights into the observed LCC patterns. Land cover was classified using a random forest classifier, and accuracies ranging from 87% to 92% were achieved. Systematic and intensity analysis methods were used to describe patterns, rates, and transitions of LCC in Imbabazane (ILM) and Okhahlamba (OLM) local municipalities. The results showed a reduced rate of change intensity from 3.4% to 0.9% in ILM and from 3.1% to 1.1% in OLM between 1984 and 2014. Grassland was persistent, covering over 70% in both local municipalities between 1984 and 2014. Although persistent, grassland experienced respective losses of 3.7% and 14.3% in both observation periods in ILM and of 10.2% and 13.3% in OLM. During the analysis period, settlements and cropland gained actively in both local municipalities. The changes represent a degree of population, local authority, and people’s perception as influencers of land use and LCC. It is therefore argued that socio-economic and political changes can potentially influence land use and LCC; however, natural ecosystems can persist under those conditions, and this requires more research efforts.
Significance:
This study contributes towards a growing knowledge and understanding of land cover change studies in marginalised landscapes in South Africa. The findings enforce the notion that natural vegetation systems can be altered by human-induced land use such as expansion of settlement and commercial agricultural. We show that in recent times there has been a decline in the overall rate of land cover conversion, and a high persistence of grassland amid global change, although the quality of the vegetation needs further research. We argue that the changes observed in marginalised landscapes are potentially driven by socio-economic and political dynamics.
Israel Barrutia Barreto, Manuel Nicolas Morales Alberto, Carlos Enrique García Soto
et al.
El presente artículo tiene como objetivo brindar una revisión acerca de las criptomonedas y su rol en la economía moderna, centrándose en la inmersión de las criptofinanzas en el sector real de la economía y sus procesos productivos, desde su creación y su tecnología subyacente hasta la concepción y desarrollo a futuro de las monedas digitales de banco central (CBDC). Se evidencia que las criptomonedas, pese a su gran popularidad en ciertos sectores, tiene aún poca relevancia en los procesos productivos. No obstante, y sobre todo con la posibilidad de que las autoridades monetarias emitan su versión de moneda digital, se espera que la relación entre las criptofinanzas y el sector real de la economía sea cada vez mayor.
Economic history and conditions, Economics as a science
Ignacio Martínez Fernández, Miguel Ángel Alonso Neira, Luis Palma Martos
As Bagus and Howden (2010) highlighted, one of the paths to achieve a more fruitful understanding of the business cycle involves examining saving as a heterogeneous analytical category. The aim of this paper is to continue this line of inquiry using the capital-based framework developed by Garrison (2001). This paper contributes to the literature by studying the impact of heterogenous savings on economic growth and business cycles in a capital-based macroeconomics framework. With this aim the implications of disaggregated saving is analysed by means of the differential market signals that are generated by cash-build savings (Pătruți, 2017) and loanable funds accessible through the credit markets.
Mirhan Ürkmez, Carsten Kallesøe, Jan Dimon Bendtsen
et al.
This paper deals with the control of pumps in large-scale water distribution networks with the aim of minimizing economic costs while satisfying operational constraints. Finding a control algorithm in combination with a model that can be applied in real-time is a challenging problem due to the nonlinearities presented by the pipes and the network sizes. We propose a predictive control algorithm with a periodic horizon. The method provides a way for the economic operation of large water networks with a small linear model. Economic Predictive control with a periodic horizon and a terminal state constraint is constructed to keep the state trajectories close to an optimal periodic trajectory. Barrier terms are also included in the cost function to prevent constraint violations. The proposed method is tested on the EPANET implementation of the water network of a medium size Danish town (Randers) and shown to perform as intended under varying conditions.
This paper presents a novel machine learning approach to GDP prediction that incorporates volatility as a model weight. The proposed method is specifically designed to identify and select the most relevant macroeconomic variables for accurate GDP prediction, while taking into account unexpected shocks or events that may impact the economy. The proposed method's effectiveness is tested on real-world data and compared to previous techniques used for GDP forecasting, such as Lasso and Adaptive Lasso. The findings show that the Volatility-weighted Lasso method outperforms other methods in terms of accuracy and robustness, providing policymakers and analysts with a valuable tool for making informed decisions in a rapidly changing economic environment. This study demonstrates how data-driven approaches can help us better understand economic fluctuations and support more effective economic policymaking. Keywords: GDP prediction, Lasso, Volatility, Regularization, Macroeconomics Variable Selection, Machine Learning JEL codes: C22, C53, E37.
This research is devoted to assessing regional economic disparities in Ukraine, where regional economic inequality is a crucial issue the country faces in its medium and long-term development, recently, even in the short term. We analyze the determinants of regional economic growth, mainly industrial and agricultural productions, population, human capital, fertility, migration, and regional government expenditures. Using panel data estimations from 2004 to 2020 for 27 regions of Ukraine, our results show that the gaps between regions in Ukraine have widened last two decades. Natural resource distribution, agricultural and industrial productions, government spending, and migration can explain the disparities. We show that regional government spending is highly concentrated in Kyiv, and the potential of the other regions, especially the Western ones, needs to be used sufficiently. Moreover, despite its historical and economic opportunity, the East region performed little development during the last two decades. The inefficient and inconsistent regional policies played a crucial role in these disparities.
This textbook is an introduction to economic networks, intended for students and researchers in the fields of economics and applied mathematics. The textbook emphasizes quantitative modeling, with the main underlying tools being graph theory, linear algebra, fixed point theory and programming. The text is suitable for a one-semester course, taught either to advanced undergraduate students who are comfortable with linear algebra or to beginning graduate students.
Objective: Sirjan city has increased the economic importance of Kerman province. Sirjan is the main transit point for goods to eastern Iran, as well as Europe and the Persian Gulf and the return route of all commercial goods is from Shahid Rajaei port of Hormozgan to Central Asian countries, Caucasus and Russia. This city has a significant role and position as a special economic hub based on the advantages of docking, in the economic structure of Kerman province and in the future, the importance of this economic position will increase. Also, Golgohar mining region with iron ore rich mines as one of the most important active mining and industrial hubs in the Middle East, has many potentials to become a large and competitive region in Iran and even in the world. Golgohar Mining and Industrial Company, as one of the main players in the region, with a production capacity of 8.5 million tons of concentrate and 5 million tons of pellets, has highlighted its role in the country's steel industry and as a special economic hub based on the advantages of docking, it has a significant role and position in the economic structure of Kerman province. also in the future, the importance of this economic position will increase. Whereas the role of transport in economic development and the creation of incentives to increase investment in this regard is undeniable; The process of selecting different transportation systems and combining them with each other is an important matter in planning the optimal development of Kerman province, because in the absence of the necessary information, transportation decisions regarding the existing demand are made based on experience. Methods: In this study, demand function of carrying minerals in the rail transportation system of Golgohar mine estimated with econometrics technique and panel data model during the period 2011-2017. And while introducing the factors affecting the demand for mineral transportation by rail, using the neural network, the future trend of demand for rail transportation of minerals has been predicted. Findings: The results indicate, value added of the mining sector, tonnage cargo of cargo road transported , cost of freight by train and cargo revenue are the most important variables and they have significant impact and effective on the demand for rail transportation of Golgohar minerals. The inelasticity of the demand for rail transportation of minerals in relation to freight costs by train was also confirmed in this study. Variables not only affect demand for rail transportation, but also a significant impact on the income of producers, industrialists, railroad and eventually to consumer prices. Because minerals as a factor in generating transportation costs has a high share in the cost price. Conclusion: Care should be taken to determine the choice of shipping method according to the time. Therefore, due to the lack of rail facilities and side lines in all areas of demand, at present, only the proposed solutions can be satisfied in the short term.
Economic history and conditions, Economic growth, development, planning
Michelle Escobar Carias, David Johnston, Rachel Knott
et al.
The empirical evidence suggests that key accumulation decisions and risky choices associated with economic development depend, at least in part, on economic preferences such as willingness to take risk and patience. This paper studies whether temperature could be one of the potential channels that influences such economic preferences. Using data from the Indonesia Family Life Survey and NASAs Modern Era Retrospective Analysis for Research and Applications data we exploit quasi exogenous variations in outdoor temperatures caused by the random allocation of survey dates. This approach allows us to estimate the effects of temperature on elicited measures of risk aversion, rational choice violations, and impatience. We then explore three possible mechanisms behind this relationship, cognition, sleep, and mood. Our findings show that higher temperatures lead to significantly increased rational choice violations and impatience, but do not significantly increase risk aversion. These effects are mainly driven by night time temperatures on the day prior to the survey and less so by temperatures on the day of the survey. This impact is quasi linear and increasing when midnight outdoor temperatures are above 22C. The evidence shows that night time temperatures significantly deplete cognitive functioning, mathematical skills in particular. Based on these findings we posit that heat induced night time disturbances cause stress on critical parts of the brain, which then manifest in significantly lower cognitive functions that are critical for individuals to perform economically rational decision making.
The South American tomato pinworm or tomato leaf miner (TLM), Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae), is a serious invasive and destructive insect pest of tomato (Solanum lycopersicum L.) worldwide. The moth can cause 100% damage in tomato crop in both greenhouses and open fields if control measures are not carried out. Due to the high reproduction potential, dispersal ability, and tolerance to environmental conditions, the TLM invaded most tomatoproducing countries in Europe, Africa, and Asia. The tomato leaf miner originated in South America and was first introduced in Spain in 2006 and from where it spread to other part of the world. This chapter consolidates the rich literature on the pest with emphasis on invasion history, economic significance, and possible management options adopted worldwide.
Proof-of-work blockchains need to be carefully designed so as to create the proper incentives for miners to faithfully maintain the network in a sustainable way. This paper describes how the economic engineering of the Conflux Network, a high throughput proof-of-work blockchain, leads to sound economic incentives that support desirable and sustainable mining behavior. In detail, this paper parameterizes the level of income, and thus network security, that Conflux can generate, and it describes how this depends on user behavior and "policy variables'' such as block and interest inflation. It also discusses how the underlying economic engineering design makes the Conflux Network resilient against double spending and selfish mining attacks.