Proposes new economic accelerators with memory in discrete time.
problem Describing economic processes with power-law memory and periodic sharp splashes.
method Uses capital stock adjustment principle and discrete maps derived from fractional-order differential equations.
result Discrete accelerators with memory accurately describe economic processes.
Interactive tools help teach economics online.
problem Teaching macroeconomic models online.
method Browser-based simulation toolkits.
result Intuitive approach to comparative statics.
This article derives prognostic expressions for the evolution of globally aggregated economic wealth, productivity, inflation, technological change, innovation and growth. The approach is to treat civilization as an open, non-equilibrium thermodynamic system that dissipates energy and diffuses matter in order to sustai…
Forecast predicts US recession in 2017, global economic slowdown, and eventual growth.
problem Short-term economic forecast and potential recession in developed countries.
method Analysis of log-periodic oscillations in DJIA dynamics and historical economic cycles.
result Predicts a recession in the second half of 2017 for developed countries.
Model shows how biased beliefs can lead to economic polarization.
problem Economic polarization due to biased beliefs in interacting markets.
method Evolutionary model of stock market agents with biased beliefs, real economy described by multiplier-accelerator framework.
result Polarized beliefs can lead to multiple steady states of income and price levels, reflecting optimism or pessimism.
Study shows climate change can cause a 'run on fossil fuels' affecting prices and production.
problem Impact of climate change expectations on fossil fuel markets and prices.
method Dynamic, general equilibrium model of climate-change-linked transition risk.
result Climate change expectations can lead to either increased or decreased fossil fuel prices, depending on economic responses.
Study shows ethanol blends and incentives can significantly reduce transportation carbon emissions.
problem Rapid growth in electric vehicles requires complementary strategies to decarbonize transportation.
method Analysis of ethanol blending, regulatory incentives, and economic assessments.
result Ethanol blending, especially E15 and E85, can substantially reduce carbon emissions and provide economic benefits.
For those concerned with the long-term value of their accounts, it can be a challenge to plan in the present for inflation-adjusted economic growth over coming decades. Here, I argue that there exists an economic constant that carries through time, and that this can help us to anticipate the more distant future: global…
AI uses language models to find instrumental variables quickly.
problem Finding valid instrumental variables is a challenging and heuristic process.
method Uses large language models to search for new instrumental variables through narratives and counterfactual reasoning.
result Demonstrates the effectiveness of multi-step and role-playing prompting strategies for LLMs.
This article continues our analysis of the gold price dynamics that was published in December 2010 (abs/1012.4118) and forecasted the possibility of the "burst of the gold bubble" in April - June 2011. Our recent analysis suggests the possibility of one more substantial fluctuation before the final collapse in July 201…
Deep learning speeds up infrastructure reliability analysis.
problem Efficiently evaluate infrastructure system reliability under natural disasters.
method Developed deep neural network surrogates for connectivity determination and system reliability analysis.
result Proposed approach accelerates reliability analysis with high accuracy.
GNN improves financial risk detection in dynamic networks.
problem Complex, changing financial networks make traditional risk identification methods ineffective.
method Graph Neural Networks (GNN) for embedded representation learning of financial data.
result GNN enhances the detection of hidden risks and abnormal behaviors in financial networks.
Deep neural nets classify tool wear in blanking processes.
problem Predicting tool wear in blanking processes to improve quality and reduce downtime.
method Deep Convolutional Neural Networks trained on workpiece images of 16 wear states.
result High accuracy in predicting tool wear states.
The analysis of dollar inflation performed by the authors through the approximation of empirical data for 1913-2012 with a power-law function with an accelerating log-periodic oscillation superimposed over it has made it possible to detect a quasi-singularity point around the 17th of December, 2012. It is demonstrated …
Study maps research streams in biodiversity finance, identifies key areas.
problem Biodiversity loss and need for finance to reverse trends.
method Quantitative bibliometric analysis of 189,456 references.
result Identifies eight primary research streams in biodiversity finance.
We study analytically and numerically Minsky instability as a combination of top-down, bottom-up and peer-to-peer positive feedback loops. The peer-to-peer interactions are represented by the links of a network formed by the connections between firms, contagion leading to avalanches and percolation phase transitions pr…
New mechanism found for power laws including Zipf's law.
problem Understanding the ubiquity of power law distributions.
method Introduced nonlinear self-excited Hawkes processes with fast-accelerating intensities.
result Wide class of nonlinear Hawkes processes have power law intensity PDFs.
Keeping a basic tenet of economic theory, rational expectations, we model the nonlinear positive feedback between agents in the stock market as an interplay between nonlinearity and multiplicative noise. The derived hyperbolic stochastic finite-time singularity formula transforms a Gaussian white noise into a rich time…
Traditional models of macroeconomic dynamics are fundamentally incorrect. The reason lies in a misunderstanding of peculiarities of the analysis of infinitesimal quantities. However, even those types of solutions that are envisaged by the above-mentioned models are nonrepresentative in the sense of the reflection of re…
Current economic theories miss most of economic dynamics.
problem Accuracy of economic theories and policies depend on economic variables and processes.
method Identify and analyze overlooked economic variables and processes.
result Many economic variables and processes not accounted for in current theories.
By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii) the mathematical and statistical physics of bifurcations and phase transitions, the log-periodic power law (LPPL) model has been developed as a flexible tool to detec…
Hybrid approach improves crude oil price forecasting using multi-scale data.
problem Forecasting crude oil prices with multi-scale data.
method Hybrid approach combining K-means, KPCA, and KELM.
result Hybrid approach outperforms traditional methods in both level and directional forecasting accuracy.
Paper presents a model to measure economic growth and development.
problem Measuring relative economic growth of different systems.
method S-Shaped model with linear representation to indicate growth, development, or underdevelopment.
result Model accurately measures economic growth and development of regions and macro regions.
Modeling business cycles via collective risk fluctuations in economic agents' risk space.
problem Understanding and predicting business cycles through economic agents' risk dynamics.
method Continuous numerical risk grades for economic agents, modeling collective economic variables and flows as functions of risk coordinates, deriving equations for their evolution.
result Business and credit cycles are explained as fluctuations of collective economic variables and their mean risks in the risk space of economic agents.
Accelerates Riemannian gradient methods with extrapolation.
problem Optimizing functions on manifolds efficiently.
method Extrapolating iterates in Riemannian gradient descent.
result Achieves optimal convergence rate and computational advantage.
Essay combines thermodynamics, economics, and geobiodynamics to model complex systems.
problem Understanding complex evolutionary systems in economics and geobiodynamics.
method Defines Roegenian Economy, links thermodynamics and economics, analyzes phase equilibrium, and discusses economic black holes.
result Roegenian economic systems are described as Carnot groups with phase equilibrium analysis.
'Ergodicity economics' is criticized as pseudoscience.
problem Flawed conceptual basis of mainstream economic theory.
method Claims 'ergodicity economics' is more parsimonious and clearer.
result Peters' approach has not produced falsifiable implications.
Maximal acceleration metrics limit spacetime curvature.
problem Bounding spacetime curvature under maximal acceleration.
method Developed a geometric framework for maximal acceleration metrics and associated connections, proving curvature bounds.
result Uniform bounds on curvature components follow from uniform bounds on maximal acceleration.
Paper introduces economic Carnot cycles in Roegenian economics.
problem Economic efficiency limits in Roegenian systems.
method Uses Carnot cycle principles to model economic systems.
result Validates economic Carnot cycles in Roegenian economics.
Accelerates Q-learning by updating targets more efficiently.
problem Improving convergence speed in Q-learning algorithms.
method Proposes an accelerated target update scheme based on momentum methods.
result The proposed algorithms converge faster than vanilla Q-learning.
Accelerates optimization in asynchronous systems with sparse updates.
problem Optimizing finite-sum objectives in asynchronous lock-free environments.
method New accelerated SVRG variant with sparse updates.
result Achieves optimal incremental gradient complexity.
The paper explores how accelerated methods in optimization can be understood through a continuous-time perspective.
problem Understanding the natural scope of acceleration in optimization methods.
method A variational perspective using a Bregman Lagrangian to study accelerated methods in optimization.
result Accelerated methods can be seen as traveling the same curve in spacetime at different speeds, providing a unified view.
Conventional economic analysis of stringent climate change mitigation policy generally concludes various levels of economic slowdown as a result of substantial spending on low carbon technology. Equilibrium economics however could not explain or predict the current economic crisis, which is of financial nature. Meanwhi…
We analyze Riemannian accelerated methods using a new framework.
problem Understanding Riemannian accelerated gradient methods.
method Riemannian A-HPE framework, focusing on Euclidean A-HPE insights and metric distortion control.
result Characterization of acceleration for various Riemannian methods.
Paper accelerates SAGA using sampled negative momentum.
problem Directly accelerating SAGA for optimization problems.
method Proposes SSNM for direct acceleration of SAGA.
result Achieves best known oracle complexity for strongly convex problems.
Super-acceleration of gradient descent with momentum improves loss function minimization.
problem Minimizing loss functions in machine learning.
method Extending Nesterov acceleration by using gradients at multiple steps ahead.
result Super-acceleration of the momentum algorithm is beneficial for various loss landscapes and tasks.
Proposes a taxonomy for economic policies.
problem Lack of a standardized list of economic policies.
method Develops a tree taxonomy to categorize economic policies.
result Constructs an exhaustive list of economic policies.
PF-LaCG removes the need for knowing smoothness and strong convexity parameters for locally accelerated CG.
problem Locally accelerated CG requires knowledge of smoothness and strong convexity parameters.
method Parameter-Free Locally Accelerated CG (PF-LaCG) algorithm.
result PF-LaCG achieves local acceleration without requiring knowledge of smoothness and strong convexity parameters.
Study examines how taxes affect wealth inequality in economic models.
problem Reducing economic inequality in models of economic activity.
method Examined Artificial Chemistry models and various tax measures.
result Effective tax measures can reduce economic inequality.
Accelerates coordinate descent methods for machine learning problems.
problem Slowness of coordinate descent methods in machine learning.
method Extrapolation-based accelerated coordinate descent.
result Significant speed-up in practice compared to existing methods.
The study applies Dimensional Analysis to the neoclassical economic growth model.
problem Inconsistency in the neoclassical economic growth model.
method Dimensional Analysis was used to evaluate and adjust the model.
result An adjustment to the neoclassical economic growth model is required to satisfy the principle of dimensional homogeneity.
Continuized Nesterov acceleration accelerates stochastic gradient descent and gossip algorithms.
problem Improving the convergence rate of stochastic gradient descent and gossip algorithms.
method Introducing a continuized variant of Nesterov acceleration, which mixes variables continuously and takes gradient steps at random times.
result The continuized Nesterov acceleration achieves convergence rates similar to Nesterov's original acceleration but with random parameters.
Acceleration in Hilbert spaces reduces computations but not accuracy.
problem Improving learning accuracy with fewer computations.
method Analysis of Nesterov acceleration and heavy-ball methods in Hilbert spaces.
result Acceleration can reduce computations but not improve accuracy with respect to gradient descent.
Accelerated algorithm for density-based clustering outperforms DBSCAN.
problem Density-based clustering with variable density clusters and tuning parameters.
method Accelerated HDBSCAN* algorithm improving upon HDBSCAN*.
result Comparable performance to DBSCAN, eliminates tuning parameter.
Develops accelerated methods for optimization using low-dimensional projected-gradient information.
problem Optimization with low-dimensional projected-gradient information and Nesterov acceleration.
method Randomized-subspace Nesterov accelerated gradient methods for smooth convex and strongly convex optimization.
result Established accelerated oracle-complexity guarantees and unified basis for comparing sketch families.
Phase diagram illustrates key points in Roegenian economics.
problem Understanding the nature of Roegenian economic systems.
method Recalled similarities between Thermodynamics and Roegenian Economics.
result Identified triple and critical points in Roegenian economic system.
Unified Growth Theory contradicted by Asian economic data.
problem Unified Growth Theory fails to explain Asian economic growth.
method Analysis of historical economic growth data in Asia.
result Asian economic growth was hyperbolic, not stagnant.
New RNA scheme accelerates gradient methods online and improves convergence.
problem Improving convergence rates of gradient methods.
method Adapting Regularized Nonlinear Acceleration (RNA) to handle faster multistep algorithms.
result Optimal complexity bounds and asymptotically optimal rates for convex minimization problems.