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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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371013 · Mar 202519922001200920172026
48 results for Political Economy

Study examines how governance, corruption, and R&D affect economic development.

problem The impact of corruption and governance on economic development.
method General equilibrium model with heterogeneous agents and a government, including corruption as a fraction of tax revenues.
result Redistribution and innovation-led strategies can mitigate the negative effects of corruption on economic development.

Venice used 'helicopter money' to subsidize during famine and plague, but it caused instability.

problem Subsidizing inhabitants during containment policies while preventing long-term debt increase.
method Net-worth helicopter money strategy, equivalent to monetary expansion generating losses to the issuer.
result The strategy caused much monetary instability and had to be quickly reversed.

This summarizes the study of the financial and economic crisis in Europe. The starting questions were: 1) Why do we have a crisis? Unde venis? 2) What will be the outcome? Quo vadis? Here is the reasoning which touches many areas, ranging from financial to politics and from psychology and economy.

2013-05-23abs ↗pdf ↗

Since beginning of the 2008 financial crisis almost half a trillion euros have been spent to financially assist EU member states in taxpayer-funded bail-outs. These crisis resolutions are often accompanied by austerity programs causing political and social friction on both domestic and international levels. The questio…

2014-03-06abs ↗pdf ↗

The paper introduces GAER to assess market feasibility under geopolitical and institutional constraints.

problem Feasibility of adaptive market efficiency under heterogeneous institutional and geopolitical conditions.
method Structural framework integrating adaptive market theory, institutional economics, and political economy.
result GAER as a diagnostic indicator for portfolio construction feasibility.

Numerous kinds of uncertainties may affect an economy, e.g. economic, political, and environmental ones. We model the aggregate impact by the uncertainties on an economy and its associated financial market by randomised mixtures of Lévy processes. We assume that market participants observe the randomised mixtures only …

2011-12-09abs ↗pdf ↗

Study examines USD exchange rate dynamics using Kramers-Moyal expansion.

problem Understanding and predicting exchange rate instability.
method Kramers-Moyal expansion and Fokker-Planck formalism applied to log-return data.
result Identifies a stabilizing linear drift and nonlinear diffusion term in exchange rate fluctuations.

A common assumption of political economy is that profit rates across firms or sectors tend to uniformity, and often models are formulated in which this tendency is assumed to have been realised. But in reality this tendency is never realised and the distribution of firm profits is not degenerate but skewed to the right…

2004-07-27abs ↗pdf ↗

Paper finds political networks reduce bond issuance costs in China.

problem The financial value of within-government political networks in China.
method Using municipal leaders' working experience to measure political networks, the study examines the effect on bond issuance yield spreads.
result Political networks reduce bond issuance yield spreads by improving issuer credit ratings, especially in less developed financial markets.

Scores political leanings in Web3 betting markets.

problem Understanding political motivations in decentralized prediction markets.
method Constructing PBLS from Polymarket data, analyzing 15k addresses, 4k events, 8k markets.
result Validated PBLS through internal and external comparisons, revealing political and profit motives.

One important effect of price shocks in the United States has been increased political attention paid to the structure and performance of oil and natural gas markets, along with some governmental support for energy conservation. This paper describes how price changes helped lead the emergence of a political agenda acco…

2015-02-25abs ↗pdf ↗

Study confirms financial bubbles' common patterns in isolated markets.

problem Testing universal dynamics of financial bubbles in isolated markets.
method Log-Periodic Power Law Singularity (LPPLS) model analysis of two major bubble episodes.
result Tehran Stock Exchange shows clear LPPLS hallmarks, supporting bubble universality.

Based mainly on examples of interest in mechanics, we define the notion of a polite group action. One may view this as not only trying to give a more general notion than properness of a group action, but also to more fully understand the role of invariant functions in describing just about everything of interest in red…

2013-05-11abs ↗pdf ↗

Human stablecoin transactions predict political risk in cryptocurrency markets.

problem Predicting political risk in cryptocurrency markets.
method Structural break analysis and surrogate-based robustness tests.
result Human-driven stablecoin transactions shift significantly before major political events.

Model forecasts hourly electricity demand influenced by weather, socio-economic, and political factors.

problem Accurate hourly electricity demand forecasting in the face of multifaceted uncertainties.
method Interpretable probabilistic mid-term forecasting model using Generalized Additive Models (GAMs).
result Highlights vulnerability of countries to extreme weather scenarios under electric heating adoption.

The paper uses Black-Scholes model to analyze political support and coalition agreements.

problem Determining the minimum support level for a minor party in a pre-electoral coalition.
method Modeling political support as a stochastic process with a deterministic growth rate and applying Black-Scholes option pricing theory.
result The minimum support level for a minor party to gain a representative in a pre-electoral coalition.

Model predicts political ideology using context vectors to mitigate bias and scarcity.

problem Scarcity and selection bias in political ideology prediction.
method Proposes a statistical model decomposing embeddings into context and position vectors, training an end-to-end model for deployment.
result Model can predict ideological labels even with minimal biased data, outperforming state-of-the-art methods.

Study examines Trump's crypto influence on markets, revealing conflicts and vulnerabilities.

problem Presidential power and cryptocurrency markets during Trump's second term.
method Mixed-methods approach combining quantitative and qualitative data.
result Political-linked digital assets became a distinct class with systemic vulnerabilities.

Background. In Italy, in recent years, vaccination coverage for key immunizations as MMR has been declining to worryingly low levels. In 2017, the Italian Gov't expanded the number of mandatory immunizations introducing penalties to unvaccinated children's families. During the 2018 general elections campaign, immunizat…

2019-12-31abs ↗pdf ↗

Study models risks for low-carbon economy in Balkan countries, focusing on shadow economy and populism.

problem Risks and uncertainties in establishing a low-carbon economy in Balkan countries with transition economies.
method Transdisciplinary approach combining economic policy, public opinion, and climate change models.
result Identifies shadow economy and populism as key risk factors for low-carbon economy implementation.

News attention to financial intermediaries and crises predicts excess bond premium and macroeconomic movements.

problem Drivers of the excess bond premium (EBP).
method News attention to 180 topics captures up to 80% of EBP variation and forecasts macroeconomic movements.
result News attention to financial intermediaries and crises drives up the EBP and predicts macroeconomic downturns.

Prediction markets can shape political behavior through persistent signals, not just forecast accuracy.

problem The role of prediction markets beyond forecasting.
method Transaction-level evidence from the 2024 U.S. presidential election, Signal Credibility Index (SCI).
result Price signals in prediction markets are more influential due to persistence, breadth of trader types, and cross-platform consensus.

Anti-ELAB protests affected Hong Kong firms' stock prices, especially those linked to pan-democrats.

problem Impact of anti-ELAB protests on Hong Kong firms' stock prices.
method Daily protesting intensity measured by number of protestors from 2019/6/6 to 2020/1/17; analyzed stock price changes of firms.
result Anti-ELAB protests negatively affected firms linked to pan-democrats, positively affected red chips.

The study shows how trade uncertainty affects stock-bond correlations over time.

problem Impact of trade policy uncertainty on stock-bond correlations.
method Daily data analysis using GARCH-based models (CCC, STCC, DCC) with TPU and political dummy variables.
result Time-varying correlation models better capture the dynamics of stock-bond correlations than constant models.

cMCA uses contrastive learning to identify latent subgroups in political party data.

problem Identifying latent subgroups within political party data.
method Contrastive learning applied to multiple correspondence analysis (MCA).
result cMCA identifies latent subgroups not seen by traditional methods.

Policy shifts between Trump and Biden impact ESG investments, creating volatility.

problem Dramatic policy shifts between Trump and Biden administrations affect ESG investments.
method Analyzes contrasting policies of Trump and Biden administrations and their impacts on ESG investments.
result Policy changes significantly influence ESG investments, leading to volatility and portfolio reassessment.

Machine learning predicts US and EuroZone business cycles with high accuracy.

problem Predicting the business cycle phases in US and EuroZone.
method Three machine learning approaches were compared: Multinomial Logistic Regression (MLR) achieved the best results.
result MLR achieved 65.25% accuracy for EuroZone and 75% for US in predicting business cycle phases.

Analyzes how economic policies affect wealth distribution in Bitcoin token economy.

problem Impact of economic policies on wealth distribution in token economies.
method Eliminated noise in wealth distribution data using macroeconomic and microeconomic time series. Causality analysis between BIPs and wealth distribution data.
result Proposed a structure for economic policy taxonomy in token economies.

Paper connects fair machine learning to political philosophy, highlighting flaws in ideal approaches.

problem Lack of natural formulation for social desiderata in machine learning.
method Proposes metrics and algorithms to satisfy subsets of fairness parities, trading off against utility.
result Misguided fair machine learning algorithms reflect broader flaws in ideal methodological approaches.

We discuss a Pareto macro-economy (a) in a closed system with fixed total wealth and (b) in an open system with average mean wealth and compare our results to a similar analysis in a super-open system (c) with unbounded wealth. Wealth condensation takes place in the social phase for closed and open economies, while it …

2001-01-05abs ↗pdf ↗